BibTeX: Morphomics via Next-generation Bioimaging (Aug 2022, updated)

References.bib

@Article{F2006,
author={F., Matias Val{\'e}rio R.
and J., Beveridge Terry},
title={Native Cell Wall Organization Shown by Cryo-Electron Microscopy Confirms the Existence of a Periplasmic Space in Staphylococcus aureus},
journal={Journal of Bacteriology},
year={2006},
month={Feb},
day={01},
publisher={American Society for Microbiology},
volume={188},
number={3},
pages={1011-1021},
doi={10.1128/JB.188.3.1011-1021.2006},
url={https://doi.org/10.1128/JB.188.3.1011-1021.2006}
}

@inproceedings{Kume2021ShortRP,
  doi = {10.48550/ARXIV.2111.13627},
  url = {https://arxiv.org/abs/2111.13627},
  author = {Kume, Satoshi},
  keywords = {Medical Physics (physics.med-ph), Tissues and Organs (q-bio.TO), FOS: Physical sciences, FOS: Physical sciences, FOS: Biological sciences, FOS: Biological sciences},
  title = {Short Review: Pathology of the image big data era using electron microscopy},
  publisher = {arXiv},
  year = {2021},  
  copyright = {Creative Commons Attribution 4.0 International}
}

@Article{Hylton2021,
author={Hylton, Ryan K.
and Swulius, Matthew T.},
title={Challenges and triumphs in cryo-electron tomography},
journal={iScience},
year={2021},
month={Sep},
day={24},
publisher={Elsevier},
volume={24},
number={9},
issn={2589-0042},
doi={10.1016/j.isci.2021.102959},
url={https://doi.org/10.1016/j.isci.2021.102959}
}


@Article{Al-Amoudi2004,
author={Al-Amoudi, Ashraf
and Chang, Jiin-Ju
and Leforestier, Am{\'e}lie
and McDowall, Alasdair
and Salamin, Laur{\'e}e Michel
and Norl{\'e}n, Lars PO
and Richter, Karsten
and Blanc, Nathalie Sartori
and Studer, Daniel
and Dubochet, Jacques},
title={Cryo-electron microscopy of vitreous sections},
journal={The EMBO Journal},
year={2004},
month={Sep},
day={15},
publisher={John Wiley {\&} Sons, Ltd},
volume={23},
number={18},
pages={3583-3588},
keywords={bacterial envelope; desmosome; high-pressure freezing; intermediate filament; vitrification},
abstract={Since the beginning of the 1980s, cryo-electron microscopy of a thin film of vitrified aqueous suspension has made it possible to observe biological particles in their native state, in the absence of the usual artefacts of dehydration and staining. Combined with 3-d reconstruction, it has become an important tool for structural molecular biology. Larger objects such as cells and tissues cannot generally be squeezed in a thin enough film. Cryo-electron microscopy of vitreous sections (CEMOVIS) provides then a solution. It requires vitrification of a sizable piece of biological material and cutting it into ultrathin sections, which are observed in the vitrified state. Each of these operations raises serious difficulties that have now been overcome. In general, the native state seen with CEMOVIS is very different from what has been seen before and it is seen in more detail. CEMOVIS will give its full potential when combined with computerized electron tomography for 3-d reconstruction.},
issn={0261-4189},
doi={10.1038/sj.emboj.7600366},
url={https://doi.org/10.1038/sj.emboj.7600366}
}



@Article{Silvester2021,
author={Silvester, Emma
and Vollmer, Benjamin
and Pra{\v{z}}{\'a}k, Vojt{\v{e}}ch
and Vasishtan, Daven
and Machala, Emily A.
and Whittle, Catheryne
and Black, Susan
and Bath, Jonathan
and Turberfield, Andrew J.
and Gr{\"u}newald, Kay
and Baker, Lindsay A.},
title={DNA origami signposts for identifying proteins on cell membranes by electron cryotomography},
journal={Cell},
year={2021},
month={Feb},
day={18},
volume={184},
number={4},
pages={1110-1121.e16},
keywords={aptamers; cryoEM; cellular electron cryotomography; DNA origami; electron cryomicroscopy; labeling; molecular arrows; protein localisation; signpost origami tags; tagging},
abstract={Summary Electron cryotomography (cryoET), an electron cryomicroscopy (cryoEM) modality, has changed our understanding of biological function by revealing the native molecular details of membranes, viruses, and cells. However, identification of individual molecules within tomograms from cryoET is challenging because of sample crowding and low signal-to-noise ratios. Here, we present a tagging strategy for cryoET that precisely identifies individual protein complexes in tomograms without relying on metal clusters. Our method makes use of DNA origami to produce ``molecular signposts'' that target molecules of interest, here via fluorescent fusion proteins, providing a platform generally applicable to biological surfaces. We demonstrate the specificity of signpost origami tags (SPOTs) in vitro as well as their suitability for cryoET of membrane vesicles, enveloped viruses, and the exterior of intact mammalian cells.},
issn={0092-8674},
url={https://www.sciencedirect.com/science/article/pii/S0092867421000763}
}



@ARTICLE{Atkinson2017,
AUTHOR={Atkinson, Jonathan A. and Wells, Darren M.},   
TITLE={An Updated Protocol for High Throughput Plant Tissue Sectioning},      
JOURNAL={Frontiers in Plant Science},      
VOLUME={8},      
PAGES={1721},     
YEAR={2017},      
URL={https://www.frontiersin.org/article/10.3389/fpls.2017.01721},       
DOI={10.3389/fpls.2017.01721},      
ISSN={1664-462X},   
ABSTRACT={Quantification of the tissue and cellular structure of plant material is essential for the study of a variety of plant sciences applications. Currently, many methods for sectioning plant material are either low throughput or involve free-hand sectioning which requires a significant amount of practice. Here, we present an updated method to provide rapid and high-quality cross sections, primarily of root tissue but which can also be readily applied to other tissues such as leaves or stems. To increase the throughput of traditional agarose embedding and sectioning, custom designed 3D printed molds were utilized to embed 5–15 roots in a block for sectioning in a single cut. A single fluorescent stain in combination with laser scanning confocal microscopy was used to obtain high quality images of thick sections. The provided CAD files allow production of the embedding molds described here from a number of online 3D printing services. Although originally developed for roots, this method provides rapid, high quality cross sections of many plant tissue types, making it suitable for use in forward genetic screens for differences in specific cell structures or developmental changes. To demonstrate the utility of the technique, the two parent lines of the wheat (Triticum aestivum) Chinese Spring × Paragon doubled haploid mapping population were phenotyped for root anatomical differences. Significant differences in adventitious cross section area, stele area, xylem, phloem, metaxylem, and cortical cell file count were found.}
}

@Article{Fermie2021,
author={Fermie, Job
and Zuidema, Wilco
and {\v{S}}ejnoha, Radim
and Wolters, Anouk
and Giepmans, Ben
and Hoogenboom, Jacob
and Kruit, Pieter},
title={High-throughput imaging of biological samples with Delmic's FAST-EM},
journal={Microscopy and Microanalysis},
year={2021},
edition={2021/07/30},
publisher={Cambridge University Press},
volume={27},
number={S1},
pages={558-560},
issn={1431-9276},
doi={10.1017/S1431927621002439},
url={https://www.cambridge.org/core/article/highthroughput-imaging-of-biological-samples-with-delmics-fastem/6F8D10A9864768222313C5BDE5AE9673},
url={https://doi.org/10.1017/S1431927621002439}
}

@Article{Haehn2014,
author={Haehn, D.
and Knowles-Barley, S.
and Roberts, M.
and Beyer, J.
and Kasthuri, N.
and Lichtman, J. W.
and Pfister, H.},
title={Design and Evaluation of Interactive Proofreading Tools for Connectomics},
journal={IEEE Transactions on Visualization and Computer Graphics},
year={2014},
volume={20},
number={12},
pages={2466-2475},
issn={1941-0506},
doi={10.1109/TVCG.2014.2346371},
url={https://doi.org/10.1109/TVCG.2014.2346371}
}



@InProceedings{Zudi2021,
author={Lin, Zudi
and Wei, Donglai
and Petkova, Mariela D.
and Wu, Yuelong
and Ahmed, Zergham
and K, Krishna Swaroop
and Zou, Silin
and Wendt, Nils
and Boulanger-Weill, Jonathan
and Wang, Xueying
and Dhanyasi, Nagaraju
and Arganda-Carreras, Ignacio
and Engert, Florian
and Lichtman, Jeff
and Pfister, Hanspeter},
editor={de Bruijne, Marleen
and Cattin, Philippe C.
and Cotin, St{\'e}phane
and Padoy, Nicolas
and Speidel, Stefanie
and Zheng, Yefeng
and Essert, Caroline},
title={NucMM Dataset: 3D Neuronal Nuclei Instance Segmentation at Sub-Cubic Millimeter Scale},
booktitle={Medical Image Computing and Computer Assisted Intervention -- MICCAI 2021},
year={2021},
publisher={Springer International Publishing},
address={Cham},
pages={164-174},
abstract={Segmenting 3D cell nuclei from microscopy image volumes is critical for biological and clinical analysis, enabling the study of cellular expression patterns and cell lineages. However, current datasets for neuronal nuclei usually contain volumes smaller than 10{\$}{\$}^{\{}-3{\}}{\$}{\$}-3 mm{\$}{\$}^3{\$}{\$}3with fewer than 500 instances per volume, unable to reveal the complexity in large brain regions and restrict the investigation of neuronal structures. In this paper, we have pushed the task forward to the sub-cubic millimeter scale and curated the NucMM dataset with two fully annotated volumes: one 0.1 mm{\$}{\$}^3{\$}{\$}3electron microscopy (EM) volume containing nearly the entire zebrafish brain with around 170,000 nuclei; and one 0.25 mm{\$}{\$}^3{\$}{\$}3micro-CT (uCT) volume containing part of a mouse visual cortex with about 7,000 nuclei. With two imaging modalities and significantly increased volume size and instance numbers, we discover a great diversity of neuronal nuclei in appearance and density, introducing new challenges to the field. We also perform a statistical analysis to illustrate those challenges quantitatively. To tackle the challenges, we propose a novel hybrid-representation learning model that combines the merits of foreground mask, contour map, and signed distance transform to produce high-quality 3D masks. The benchmark comparisons on the NucMM dataset show that our proposed method significantly outperforms state-of-the-art nuclei segmentation approaches. Code and data are available at https://connectomics-bazaar.github.io/proj/nucMM/index.html.},
isbn={978-3-030-87193-2}
}



@InProceedings{Wei2020,
author="Wei, Donglai
and Lin, Zudi
and Franco-Barranco, Daniel
and Wendt, Nils
and Liu, Xingyu
and Yin, Wenjie
and Huang, Xin
and Gupta, Aarush
and Jang, Won-Dong
and Wang, Xueying
and Arganda-Carreras, Ignacio
and Lichtman, Jeff W.
and Pfister, Hanspeter",
editor="Martel, Anne L.
and Abolmaesumi, Purang
and Stoyanov, Danail
and Mateus, Diana
and Zuluaga, Maria A.
and Zhou, S. Kevin
and Racoceanu, Daniel
and Joskowicz, Leo",
title="MitoEM Dataset: Large-Scale 3D Mitochondria Instance Segmentation from EM Images",
booktitle="Medical Image Computing and Computer Assisted Intervention -- MICCAI 2020",
year="2020",
publisher="Springer International Publishing",
address="Cham",
pages="66--76",
abstract="Electron microscopy (EM) allows the identification of intracellular organelles such as mitochondria, providing insights for clinical and scientific studies. However, public mitochondria segmentation datasets only contain hundreds of instances with simple shapes. It is unclear if existing methods achieving human-level accuracy on these small datasets are robust in practice. To this end, we introduce the MitoEM dataset, a 3D mitochondria instance segmentation dataset with two (30 {\$}{\$}{\backslash}upmu {\$}{\$}$\mu$m){\$}{\$}^3{\$}{\$}3volumes from human and rat cortices respectively, 3,600{\$}{\$}{\backslash}times {\$}{\$}{\texttimes}larger than previous benchmarks.  With around 40K instances, we find a great diversity of mitochondria in terms of shape and density. For evaluation, we tailor the implementation of the average precision (AP) metric for 3D data with a 45{\$}{\$}{\backslash}times {\$}{\$}{\texttimes}speedup. On MitoEM, we find existing instance segmentation methods often fail to correctly segment mitochondria with complex shapes or close contacts with other instances. Thus, our MitoEM dataset poses new challenges to the field. We release our code and data: https://donglaiw.github.io/page/mitoEM/index.html.",
isbn="978-3-030-59722-1"
}



@InProceedings{Lu2020,
author="Mi, Lu
and Wang, Hao
and Meirovitch, Yaron
and Schalek, Richard
and Turaga, Srinivas C.
and Lichtman, Jeff W.
and Samuel, Aravinthan D. T.
and Shavit, Nir",
editor="Martel, Anne L.
and Abolmaesumi, Purang
and Stoyanov, Danail
and Mateus, Diana
and Zuluaga, Maria A.
and Zhou, S. Kevin
and Racoceanu, Daniel
and Joskowicz, Leo",
title="Learning Guided Electron Microscopy with Active Acquisition",
booktitle="Medical Image Computing and Computer Assisted Intervention -- MICCAI 2020",
year="2020",
publisher="Springer International Publishing",
address="Cham",
pages="77--87",
abstract="Single-beam scanning electron microscopes (SEM) are widely used to acquire massive datasets for biomedical study, material analysis, and fabrication inspection. Datasets are typically acquired with uniform acquisition: applying the electron beam with the same power and duration to all image pixels, even if there is great variety in the pixels' importance for eventual use. Many SEMs are now able to move the beam to any pixel in the field of view without delay, enabling them, in principle, to invest their time budget more effectively with non-uniform imaging.",
isbn="978-3-030-59722-1"
}



@article {Dorkenwald2019,
	author = {Dorkenwald, Sven and Turner, Nicholas L. and Macrina, Thomas and Lee, Kisuk and Lu, Ran and Wu, Jingpeng and Bodor, Agnes L. and Bleckert, Adam A. and Brittain, Derrick and Kemnitz, Nico and Silversmith, William M. and Ih, Dodam and Zung, Jonathan and Zlateski, Aleksandar and Tartavull, Ignacio and Yu, Szi-Chieh and Popovych, Sergiy and Wong, William and Castro, Manuel and Jordan, Chris S. and Wilson, Alyssa M. and Froudarakis, Emmanouil and Buchanan, JoAnn and Takeno, Marc and Torres, Russel and Mahalingam, Gayathri and Collman, Forrest and Schneider-Mizell, Casey and Bumbarger, Daniel J. and Li, Yang and Becker, Lynne and Suckow, Shelby and Reimer, Jacob and Tolias, Andreas S. and da Costa, Nuno Ma{\c c}arico and Reid, R. Clay and Seung, H. Sebastian},
	title = {Binary and analog variation of synapses between cortical pyramidal neurons},
	elocation-id = {2019.12.29.890319},
	year = {2019},
	doi = {10.1101/2019.12.29.890319},
	publisher = {Cold Spring Harbor Laboratory},
	URL = {https://www.biorxiv.org/content/early/2019/12/31/2019.12.29.890319},
	eprint = {https://www.biorxiv.org/content/early/2019/12/31/2019.12.29.890319.full.pdf},
	journal = {bioRxiv}
}

@InProceedings{Wentao2018,
author="Zhu, Wentao
and Vang, Yeeleng S.
and Huang, Yufang
and Xie, Xiaohui",
editor="Frangi, Alejandro F.
and Schnabel, Julia A.
and Davatzikos, Christos
and Alberola-L{\'o}pez, Carlos
and Fichtinger, Gabor",
title="DeepEM: Deep 3D ConvNets with EM for Weakly Supervised Pulmonary Nodule Detection",
booktitle="Medical Image Computing and Computer Assisted Intervention -- MICCAI 2018",
year="2018",
publisher="Springer International Publishing",
address="Cham",
pages="812--820",
abstract="Recently deep learning has been witnessing widespread adoption in various medical image applications. However, training complex deep neural nets requires large-scale datasets labeled with ground truth, which are often unavailable in many medical image domains. For instance, to train a deep neural net to detect pulmonary nodules in lung computed tomography (CT) images, current practice is to manually label nodule locations and sizes in many CT images to construct a sufficiently large training dataset, which is costly and difficult to scale. On the other hand, electronic medical records (EMR) contain plenty of partial information on the content of each medical image. In this work, we explore how to tap this vast, but currently unexplored data source to improve pulmonary nodule detection. We propose DeepEM, a novel deep 3D ConvNet framework augmented with expectation-maximization (EM), to mine weakly supervised labels in EMRs for pulmonary nodule detection. Experimental results show that DeepEM can lead to 1.5{\%} and 3.9{\%} average improvement in free-response receiver operating characteristic (FROC) scores on LUNA16 and Tianchi datasets, respectively, demonstrating the utility of incomplete information in EMRs for improving deep learning algorithms (https://github.com/uci-cbcl/DeepEM-for-Weakly-Supervised-Detection.git).",
isbn="978-3-030-00934-2"
}

@article {Sheridan2021,
	author = {Sheridan, Arlo and Nguyen, Tri and Deb, Diptodip and Lee, Wei-Chung Allen and Saalfeld, Stephan and Turaga, Srini and Manor, Uri and Funke, Jan},
	title = {Local Shape Descriptors for Neuron Segmentation},
	elocation-id = {2021.01.18.427039},
	year = {2021},
	doi = {10.1101/2021.01.18.427039},
	publisher = {Cold Spring Harbor Laboratory},
	abstract = {We present a simple, yet effective, auxiliary learning task for the problem of neuron segmentation in electron microscopy volumes. The auxiliary task consists of the prediction of Local Shape Descriptors (LSDs), which we combine with conventional voxel-wise direct neighbor affinities for neuron boundary detection. The shape descriptors are designed to capture local statistics about the neuron to be segmented, such as diameter, elongation, and direction. On a large study comparing several existing methods across various specimen, imaging techniques, and resolutions, we find that auxiliary learning of LSDs consistently increases segmentation accuracy of affinity-based methods over a range of metrics. Furthermore, the addition of LSDs promotes affinitybased segmentation methods to be on par with the current state of the art for neuron segmentation (Flood-Filling Networks, FFN), while being two orders of magnitudes more efficient{\textemdash}a critical requirement for the processing of future petabyte-sized datasets. Implementations of the new auxiliary learning task, network architectures, training, prediction, and evaluation code, as well as the datasets used in this study are publicly available as a benchmark for future method contributions.Competing Interest StatementThe authors have declared no competing interest.},
	URL = {https://www.biorxiv.org/content/early/2021/01/18/2021.01.18.427039},
	eprint = {https://www.biorxiv.org/content/early/2021/01/18/2021.01.18.427039.full.pdf},
	journal = {bioRxiv}
}


@Article{Januszewski2018,
author={Januszewski, Micha{\l}
and Kornfeld, J{\"o}rgen
and Li, Peter H.
and Pope, Art
and Blakely, Tim
and Lindsey, Larry
and Maitin-Shepard, Jeremy
and Tyka, Mike
and Denk, Winfried
and Jain, Viren},
title={High-precision automated reconstruction of neurons with flood-filling networks},
journal={Nature Methods},
year={2018},
month={Aug},
day={01},
volume={15},
number={8},
pages={605-610},
abstract={Reconstruction of neural circuits from volume electron microscopy data requires the tracing of cells in their entirety, including all their neurites. Automated approaches have been developed for tracing, but their error rates are too high to generate reliable circuit diagrams without extensive human proofreading. We present flood-filling networks, a method for automated segmentation that, similar to most previous efforts, uses convolutional neural networks, but contains in addition a recurrent pathway that allows the iterative optimization and extension of individual neuronal processes. We used flood-filling networks to trace neurons in a dataset obtained by serial block-face electron microscopy of a zebra finch brain. Using our method, we achieved a mean error-free neurite path length of 1.1{\thinspace}mm, and we observed only four mergers in a test set with a path length of 97{\thinspace}mm. The performance of flood-filling networks was an order of magnitude better than that of previous approaches applied to this dataset, although with substantially increased computational costs.},
issn={1548-7105},
doi={10.1038/s41592-018-0049-4},
url={https://doi.org/10.1038/s41592-018-0049-4}
}

@article{lee2017superhuman,
  author    = {Kisuk Lee and
               Jonathan Zung and
               Peter Li and
               Viren Jain and
               H. Sebastian Seung},
  title     = {Superhuman Accuracy on the {SNEMI3D} Connectomics Challenge},
  journal   = {arXiv preprint arXiv:1706.00120},
  year      = {2017},
}

@Article{Witvliet2021,
author={Witvliet, Daniel
and Mulcahy, Ben
and Mitchell, James K.
and Meirovitch, Yaron
and Berger, Daniel R.
and Wu, Yuelong
and Liu, Yufang
and Koh, Wan Xian
and Parvathala, Rajeev
and Holmyard, Douglas
and Schalek, Richard L.
and Shavit, Nir
and Chisholm, Andrew D.
and Lichtman, Jeff W.
and Samuel, Aravinthan D. T.
and Zhen, Mei},
title={Connectomes across development reveal principles of brain maturation},
journal={Nature},
year={2021},
month={Aug},
day={01},
volume={596},
number={7871},
pages={257-261},
abstract={An animal's nervous system changes as its body grows from birth to adulthood and its behaviours mature1--8. The form and extent of circuit remodelling across the connectome is unknown3,9--15. Here we used serial-section electron microscopy to reconstruct the full brain of eight isogenic Caenorhabditis elegans individuals across postnatal stages to investigate how it changes with age. The overall geometry of the brain is preserved from birth to adulthood, but substantial changes in chemical synaptic connectivity emerge on this consistent scaffold. Comparing connectomes between individuals reveals substantial differences in connectivity that make each brain partly unique. Comparing connectomes across maturation reveals consistent wiring changes between different neurons. These changes alter the strength of existing connections and create new connections. Collective changes in the network alter information processing. During development, the central decision-making circuitry is maintained, whereas sensory and motor pathways substantially remodel. With age, the brain becomes progressively more feedforward and discernibly modular. Thus developmental connectomics reveals principles that underlie brain maturation.},
issn={1476-4687},
doi={10.1038/s41586-021-03778-8},
url={https://doi.org/10.1038/s41586-021-03778-8}
}



@Article{Kuan2020,
author={Kuan, Aaron T.
and Phelps, Jasper S.
and Thomas, Logan A.
and Nguyen, Tri M.
and Han, Julie
and Chen, Chiao-Lin
and Azevedo, Anthony W.
and Tuthill, John C.
and Funke, Jan
and Cloetens, Peter
and Pacureanu, Alexandra
and Lee, Wei-Chung Allen},
title={Dense neuronal reconstruction through X-ray holographic nano-tomography},
journal={Nature Neuroscience},
year={2020},
month={Dec},
day={01},
volume={23},
number={12},
pages={1637-1643},
abstract={Imaging neuronal networks provides a foundation for understanding the nervous system, but resolving dense nanometer-scale structures over large volumes remains challenging for light microscopy (LM) and electron microscopy (EM). Here we show that X-ray holographic nano-tomography (XNH) can image millimeter-scale volumes with sub-100-nm resolution, enabling reconstruction of dense wiring in Drosophila melanogaster and mouse nervous tissue. We performed correlative XNH and EM to reconstruct hundreds of cortical pyramidal cells and show that more superficial cells receive stronger synaptic inhibition on their apical dendrites. By combining multiple XNH scans, we imaged an adult Drosophila leg with sufficient resolution to comprehensively catalog mechanosensory neurons and trace individual motor axons from muscles to the central nervous system. To accelerate neuronal reconstructions, we trained a convolutional neural network to automatically segment neurons from XNH volumes. Thus, XNH bridges a key gap between LM and EM, providing a new avenue for neural circuit discovery.},
issn={1546-1726},
doi={10.1038/s41593-020-0704-9},
url={https://doi.org/10.1038/s41593-020-0704-9}
}



@article{RUECKEL2014,
title = {Spatial resolution characterization of a X-ray microCT system},
journal = {Applied Radiation and Isotopes},
volume = {94},
pages = {230-234},
year = {2014},
issn = {0969-8043},
doi = {https://doi.org/10.1016/j.apradiso.2014.08.014},
url = {https://www.sciencedirect.com/science/article/pii/S0969804314003157},
author = {J. Rueckel and M. Stockmar and F. Pfeiffer and J. Herzen},
keywords = {X-ray imaging, Micro-CT, Spatial resolution, MTF, , General electric},
abstract = {We report on an experimental characterization of the spatial resolution of a commercial X-ray micro-computed tomography scanner. We have measured the full modulation transfer function (MTF) to assess the spatial resolution. The MTF and those spatial frequencies corresponding to a contrast loss of 50% were determined as a function of different applied X-ray tube parameters and magnification-dependent pixel sizes. A significant influence of the focal spot enlargement on the achievable spatial resolution could be shown. Our results allow for the designation of optimal X-ray tube parameters for a specific application requirement.}
}

@Article{Arabi2010,
author={Arabi, H.
and Kamali Asl, A. R.
and Aghamiri, S. M.},
title={The effect of focal spot size on the spatial resolution of variable resolution X-ray CT scanner},
journal={Iranian Journal of Radiation Research (Print)},
year={2010},
address={Iran, Islamic Republic of},
volume={8},
number={1},
pages={37-43},
abstract={A variable resolution X-ray CT scanner provides a great increase In the spatial resolution In variable resolution X-ray CT scanners, the spatial resolution of the system and its field of view can be changed according to the object size One of the main factors that limit the spatial resolution of variable resolution X-ray CT scanner is the effect of the X-ray focal spot Materials and Methods: A theoretical study of the effect of X-ray focal spot on the spatial resolution of variable resolution X-ray CT is presented in this paper In this study, we used the parameters of an actual variable resolution X-ray CT scanner By using the relevant equations, the effects of foal spot sizes of 06 and 01 mm were calculated on spatial resolution of the system at various opening half angles Results: Focal spot size of 06 mm had no significant effect on spatial resolution of the system for opening half angles of above 14degree Even focal spot sizes of larger than 06 mm could not affect the spatial resolution of the system For opening half angles of below 14degree, foal spot size of 06 mm limited the spatial resolution of the system to 57 cycle/mm and caused great spatial resolution non-uniformity along the detector length Conclusion: By focal spot size of 01 mm, the spatial resolution varied as a function of the opening half angle and increased to more than 30 cycle/mm Additionally, focal spot size of 01 mm minimized the spatial resolution non-uniformity along the detector length},
note={INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY},
note={RADIOLOGY AND NUCLEAR MEDICINE},
issn={1728-4554},
url={http://inis.iaea.org/search/search.aspx?orig_q=RN:42044738}
}



@Article{Cengiz2018,
author={Cengiz, Ibrahim Fatih
and Oliveira, Joaquim Miguel
and Reis, Rui L.},
title={Micro-CT -- a digital 3D microstructural voyage into scaffolds: a systematic review of the reported methods and results},
journal={Biomaterials Research},
year={2018},
month={Sep},
day={26},
volume={22},
number={1},
pages={26},
abstract={Cell behavior is the key to tissue regeneration. Given the fact that most of the cells used in tissue engineering are anchorage-dependent, their behavior including adhesion, growth, migration, matrix synthesis, and differentiation is related to the design of the scaffolds. Thus, characterization of the scaffolds is highly required. Micro-computed tomography (micro-CT) provides a powerful platform to analyze, visualize, and explore any portion of interest in the scaffold in a 3D fashion without cutting or destroying it with the benefit of almost no sample preparation need.},
issn={2055-7124},
doi={10.1186/s40824-018-0136-8},
url={https://doi.org/10.1186/s40824-018-0136-8}
}



@article{Banik2020,
title = {An Automatic Nucleus Segmentation and CNN Model based Classification Method of White Blood Cell},
journal = {Expert Systems with Applications},
volume = {149},
pages = {113211},
year = {2020},
issn = {0957-4174},
doi = {https://doi.org/10.1016/j.eswa.2020.113211},
url = {https://www.sciencedirect.com/science/article/pii/S0957417420300373},
author = {Partha Pratim Banik and Rappy Saha and Ki-Doo Kim},
keywords = {White blood cell, Nucleus segmentation, CNN, Convolutional layer, Classification metrics},
abstract = {White blood cells (WBCs) play a remarkable role in the human immune system. To diagnose blood-related diseases, pathologists need to consider the characteristics of WBC. The characteristics of WBC can be defined based on the morphological properties of WBC nucleus. Therefore, nucleus segmentation plays a vital role to classify the WBC image and it is an important part of the medical diagnosis system. In this study, color space conversion and k-means algorithm based new WBC nucleus segmentation method is proposed. Then we localize the WBC based on the location of segmented nucleus to separate them from the entire blood smear image. To classify the localized WBC image, we propose a new convolutional neural network (CNN) model by combining the concept of fusing the features of first and last convolutional layers, and propagating the input image to the convolutional layer. We also use a dropout layer for preventing the model from overfitting problem. We show the effectiveness of our proposed nucleus segmentation method by evaluating with seven quality metrics and comparing with other methods on four public databases. We achieve average accuracy of 98.61% and more than 97% on each public database. We also evaluate our proposed CNN model by using nine classification metrics and achieve an overall accuracy of 96% on BCCD test database. To validate the generalization capability of our proposed CNN model, we show the training and testing accuracy and loss curves for random test set of BCCD database. Further, we compare the performance of our proposed CNN model with four state-of-the-art CNN models (biomedical image classifier) by measuring the value of evaluation metrics.}
}

@article{EMMENLAUER2009,
author = {EMMENLAUER, M. and RONNEBERGER, O. and PONTI, A. and SCHWARB, P. and GRIFFA, A. and FILIPPI, A. and NITSCHKE, R. and DRIEVER, W. and BURKHARDT, H.},
title = {XuvTools: free, fast and reliable stitching of large 3D datasets},
journal = {Journal of Microscopy},
volume = {233},
number = {1},
pages = {42-60},
keywords = {Bleaching, correlation, large scale microscopy, mosaicing, stitching, virtual microscopy, 3D},
doi = {https://doi.org/10.1111/j.1365-2818.2008.03094.x},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-2818.2008.03094.x},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2818.2008.03094.x},
abstract = {Summary Current biomedical research increasingly requires imaging large and thick 3D structures at high resolution. Prominent examples are the tracking of fine filaments over long distances in brain slices, or the localization of gene expression or cell migration in whole animals like Caenorhabditis elegans or zebrafish. To obtain both high resolution and a large field of view (FOV), a combination of multiple recordings (‘tiles’) is one of the options. Although hardware solutions exist for fast and reproducible acquisition of multiple 3D tiles, generic software solutions are missing to assemble (‘stitch’) these tiles quickly and accurately. In this paper, we present a framework that achieves fully automated recombination of tiles recorded at arbitrary positions in 3D space, as long as some small overlap between tiles is provided. A fully automated 3D correlation between all tiles is achieved such that no manual interaction or prior knowledge about tile positions is needed. We use (1) phase-only correlation in a multi-scale approach to estimate the coarse positions, (2) normalized cross-correlation of small patches extracted at salient points to obtain the precise matches, (3) find the globally optimal placement for all tiles by a singular value decomposition and (4) accomplish a nearly seamless stitching by a bleaching correction at the tile borders. If the dataset contains multiple channels, all channels are used to obtain the best matches between tiles. For speedup we employ a heuristic method to prune unneeded correlations, and compute all correlations via the fast Fourier transform (FFT), thereby achieving very good runtime performance. We demonstrate the successful application of the proposed framework to a wide range of different datasets from whole zebrafish embryos and C. elegans, mouse and rat brain slices and fine plant hairs (trichome). Further, we compare our stitching results to those of other commercially and freely available software solutions. The algorithms presented are being made available freely as an open source toolset ‘XuvTools’ at the corresponding author's website (http://lmb.informatik.uni-freiburg.de/people/ronneber), licensed under the GNU General Public License (GPL) v2. Binaries are provided for Linux and Microsoft Windows. The toolset is written in templated C++, such that it can operate on datasets with any bit-depth. Due to the consequent use of 64bit addressing, stacks of arbitrary size (i.e. larger than 4 GB) can be stitched. The runtime on a standard desktop computer is in the range of a few minutes. A user friendly interface for advanced manual interaction and visualization is also available.},
year = {2009}
}



@inproceedings{Zhang2019unet,
author = {Dongqing Zhang and Rueben Banalagay and Jianing Wang and Yiyuan Zhao and Jack H. Noble and Benoit M. Dawant},
title = {{Two-level training of a 3D U-Net for accurate segmentation of the intra-cochlear anatomy in head CTs with limited ground truth training data}},
volume = {10949},
booktitle = {Medical Imaging 2019: Image Processing},
editor = {Elsa D. Angelini and Bennett A. Landman},
organization = {International Society for Optics and Photonics},
publisher = {SPIE},
pages = {45 -- 52},
keywords = {Cochlear implant, medical image segmentation, 3D deep neural networks},
year = {2019},
doi = {10.1117/12.2512529},
URL = {https://doi.org/10.1117/12.2512529}
}


@article{Degenhardt2010,
author = {Karl Degenhardt  and Alexander C. Wright  and Debra Horng  and Arun Padmanabhan  and Jonathan A. Epstein },
title = {Rapid 3D Phenotyping of Cardiovascular Development in Mouse Embryos by Micro-CT With Iodine Staining},
journal = {Circulation: Cardiovascular Imaging},
volume = {3},
number = {3},
pages = {314-322},
year = {2010},
doi = {10.1161/CIRCIMAGING.109.918482},
URL = {https://www.ahajournals.org/doi/abs/10.1161/CIRCIMAGING.109.918482},
eprint = {https://www.ahajournals.org/doi/pdf/10.1161/CIRCIMAGING.109.918482},
    abstract = { Background— Microcomputed tomography (micro-CT) has been used extensively in research to generate high-resolution 3D images of calcified tissues in small animals nondestructively. It has been especially useful for the characterization of skeletal mutations but limited in its utility for the analysis of soft tissue such as the cardiovascular system. Visualization of the cardiovascular system has been largely restricted to structures that can be filled with radiopaque intravascular contrast agents in adult animals. Recent ex vivo studies using osmium tetroxide, iodinated contrast agents, inorganic iodine, and phosphotungstic acid have demonstrated the ability to stain soft tissues differentially, allowing for high intertissue contrast in micro-CT images. In the present study, we demonstrate the application of this technology for visualization of cardiovascular structures in developing mouse embryos using Lugol solution (aqueous potassium iodide plus iodine). Methods and Results— We show the optimization of this method to obtain ex vivo micro-CT images of embryonic and neonatal mice with excellent soft-tissue contrast. We demonstrate the utility of this method to visualize key structures during cardiovascular development at various stages of embryogenesis. Our method benefits from the ease of sample preparation, low toxicity, and low cost. Furthermore, we show how multiple cardiac defects can be demonstrated by micro-CT in a single specimen with a known genetic lesion. Indeed, a previously undescribed cardiac venous abnormality is revealed in a PlexinD1 mutant mouse. Conclusions— Micro-CT of iodine-stained tissue is a valuable technique for the characterization of cardiovascular development and defects in mouse models of congenital heart disease. }
}


@Article{Metscher2009BMC,
author={Metscher, Brian D.},
title={MicroCT for comparative morphology: simple staining methods allow high-contrast 3D imaging of diverse non-mineralized animal tissues},
journal={BMC Physiology},
year={2009},
month={Jun},
day={22},
volume={9},
number={1},
pages={11},
abstract={Comparative, functional, and developmental studies of animal morphology require accurate visualization of three-dimensional structures, but few widely applicable methods exist for non-destructive whole-volume imaging of animal tissues. Quantitative studies in particular require accurately aligned and calibrated volume images of animal structures. X-ray microtomography (microCT) has the potential to produce quantitative 3D images of small biological samples, but its widespread use for non-mineralized tissues has been limited by the low x-ray contrast of soft tissues. Although osmium staining and a few other techniques have been used for contrast enhancement, generally useful methods for microCT imaging for comparative morphology are still lacking.},
issn={1472-6793},
doi={10.1186/1472-6793-9-11},
url={https://doi.org/10.1186/1472-6793-9-11}
}



@article{Metscher2009Developmental,
author = {Metscher, Brian D.},
title = {MicroCT for developmental biology: A versatile tool for high-contrast 3D imaging at histological resolutions},
journal = {Developmental Dynamics},
volume = {238},
number = {3},
pages = {632-640},
keywords = {microCT, X-ray computed tomography, three-dimensional imaging, chick, embryonic development, contrast agents},
doi = {https://doi.org/10.1002/dvdy.21857},
url = {https://anatomypubs.onlinelibrary.wiley.com/doi/abs/10.1002/dvdy.21857},
eprint = {https://anatomypubs.onlinelibrary.wiley.com/doi/pdf/10.1002/dvdy.21857},
abstract = {Abstract Understanding developmental processes requires accurate visualization and parameterization of three-dimensional embryos. Tomographic imaging methods offer automatically aligned and calibrated volumetric images, but the usefulness of X-ray CT imaging for developmental biology has been limited by the low inherent contrast of embryonic tissues. Here, I demonstrate simple staining methods that allow high-contrast imaging of embryonic tissues at histological resolutions using a commercial microCT system. Quantitative comparisons of images of chick embryos treated with different contrast agents show that three very simple methods using inorganic iodine and phosphotungstic acid produce overall contrast and differential tissue contrast for X-ray imaging at least as high as that obtained with osmium. The stains can be used after any common fixation and after storage in aqueous or alcoholic media, and on a wide variety of species. These methods establish microCT imaging as a useful tool for comparative developmental studies, embryo phenotyping, and quantitative modeling of development. Developmental Dynamics 238:632–640, 2009. © 2009 Wiley-Liss, Inc.},
year = {2009}
}



@article{Johnson2020,
    author = {Johnson, Erik C and Wilt, Miller and Rodriguez, Luis M and Norman-Tenazas, Raphael and Rivera, Corban and Drenkow, Nathan and Kleissas, Dean and LaGrow, Theodore J and Cowley, Hannah P and Downs, Joseph and K. Matelsky, Jordan and J. Hughes, Marisa and P. Reilly, Elizabeth and A. Wester, Brock and L. Dyer, Eva and P. Kording, Konrad and R. Gray-Roncal, William},
    title = "{Toward a scalable framework for reproducible processing of volumetric, nanoscale neuroimaging datasets}",
    journal = {GigaScience},
    volume = {9},
    number = {12},
    year = {2020},
    month = {12},
    abstract = "{Emerging neuroimaging datasets (collected with imaging techniques such as electron microscopy, optical microscopy, or X-ray microtomography) describe the location and properties of neurons and their connections at unprecedented scale, promising new ways of understanding the brain. These modern imaging techniques used to interrogate the brain can quickly accumulate gigabytes to petabytes of structural brain imaging data. Unfortunately, many neuroscience laboratories lack the computational resources to work with datasets of this size: computer vision tools are often not portable or scalable, and there is considerable difficulty in reproducing results or extending methods.We developed an ecosystem of neuroimaging data analysis pipelines that use open-source algorithms to create standardized modules and end-to-end optimized approaches. As exemplars we apply our tools to estimate synapse-level connectomes from electron microscopy data and cell distributions from X-ray microtomography data. To facilitate scientific discovery, we propose a generalized processing framework, which connects and extends existing open-source projects to provide large-scale data storage, reproducible algorithms, and workflow execution engines.Our accessible methods and pipelines demonstrate that approaches across multiple neuroimaging experiments can be standardized and applied to diverse datasets. The techniques developed are demonstrated on neuroimaging datasets but may be applied to similar problems in other domains.}",
    issn = {2047-217X},
    doi = {10.1093/gigascience/giaa147},
    url = {https://doi.org/10.1093/gigascience/giaa147},
    note = {giaa147},
    eprint = {https://academic.oup.com/gigascience/article-pdf/9/12/giaa147/35044388/giaa147.pdf},
}





@article {Hider2019,
	author = {Hider, Robert and Kleissas, Dean M. and Pryor, Derek and Gion, Timothy and Rodriguez, Luis and Matelsky, Jordan and Gray-Roncal, William and Wester, Brock},
	title = {The Block Object Storage Service (bossDB): A Cloud-Native Approach for Petascale Neuroscience Discovery},
	elocation-id = {217745},
	year = {2019},
	doi = {10.1101/217745},
	publisher = {Cold Spring Harbor Laboratory},
	abstract = {Large volumetric neuroimaging datasets have grown in size over the past ten years from gigabytes to terabytes, with petascale data becoming available and more common over the next few years. Current approaches to store and analyze these emerging datasets are insufficient in their ability to scale in both cost-effectiveness and performance. Additionally, enabling large-scale processing and annotation is critical as these data grow too large for manual inspection. We provide a new cloud-native managed service for large and multi-modal experiments, with support for data ingest, storage, visualization, and sharing through a RESTful Application Programming Interface (API) and web-based user interface. Our project is open source and can be easily and cost-effectively used for a variety of modalities and applications.},
	URL = {https://www.biorxiv.org/content/early/2019/10/25/217745},
	eprint = {https://www.biorxiv.org/content/early/2019/10/25/217745.full.pdf},
	journal = {bioRxiv}
}

@Article{Vogelstein2018,
author={Vogelstein, Joshua T.
and Perlman, Eric
and Falk, Benjamin
and Baden, Alex
and Gray Roncal, William
and Chandrashekhar, Vikram
and Collman, Forrest
and Seshamani, Sharmishtaa
and Patsolic, Jesse L.
and Lillaney, Kunal
and Kazhdan, Michael
and Hider, Robert
and Pryor, Derek
and Matelsky, Jordan
and Gion, Timothy
and Manavalan, Priya
and Wester, Brock
and Chevillet, Mark
and Trautman, Eric T.
and Khairy, Khaled
and Bridgeford, Eric
and Kleissas, Dean M.
and Tward, Daniel J.
and Crow, Ailey K.
and Hsueh, Brian
and Wright, Matthew A.
and Miller, Michael I.
and Smith, Stephen J.
and Vogelstein, R. Jacob
and Deisseroth, Karl
and Burns, Randal},
title={A community-developed open-source computational ecosystem for big neuro data},
journal={Nature Methods},
year={2018},
month={Nov},
day={01},
volume={15},
number={11},
pages={846-847},
issn={1548-7105},
doi={10.1038/s41592-018-0181-1},
url={https://doi.org/10.1038/s41592-018-0181-1}
}



@Article{Morgan2020,
author={Morgan, Josh L.
and Lichtman, Jeff W.},
title={An Individual Interneuron Participates in Many Kinds of Inhibition and Innervates Much of the Mouse Visual Thalamus},
journal={Neuron},
year={2020},
month={May},
day={06},
publisher={Elsevier},
volume={106},
number={3},
pages={468-481.e2},
issn={0896-6273},
doi={10.1016/j.neuron.2020.02.001},
url={https://doi.org/10.1016/j.neuron.2020.02.001}
}



@incollection{BAENA2019,
title = {Chapter 3 - Serial-section electron microscopy using automated tape-collecting ultramicrotome (ATUM)},
editor = {Thomas Müller-Reichert and Gaia Pigino},
series = {Methods in Cell Biology},
publisher = {Academic Press},
volume = {152},
pages = {41-67},
year = {2019},
booktitle = {Three-Dimensional Electron Microscopy},
issn = {0091-679X},
doi = {https://doi.org/10.1016/bs.mcb.2019.04.004},
url = {https://www.sciencedirect.com/science/article/pii/S0091679X1930055X},
author = {Valentina Baena and Richard Lee Schalek and Jeff William Lichtman and Mark Terasaki},
keywords = {ATUM, Serial section EM, Tape collector, 3D EM, SEM},
abstract = {The Automated Tape-Collecting Ultramicrotome (ATUM) is a tape-reeling device that is placed in a water-filled diamond knife boat to collect serial sections as they are cut by a conventional ultramicrotome. The ATUM can collect thousands of sections of many different shapes and sizes, which are subsequently imaged by a scanning electron microscope. This method has been used for large-scale connectomics projects of mouse brain, and is well suited for other smaller-scale studies of tissues, cells, and organisms. Here, we describe basic procedures for preparing a block for ATUM sectioning, handling of the ATUM, tape preparation, post-treatment of sections, and considerations for mapping, imaging, and aligning the serial sections.}
}

@misc{Kume2021bioc,
  title={BioImageDbs: Bio- and biomedical imaging dataset for machine learning and deep learning (for ExperimentHub)},
  author={Kume, Satoshi and Nishida, Kozo},
  year={2021},
  publisher={Bioconductor},
  note={Experiment Packages},
  howpublished={\url{https://bioconductor.org/packages/release/data/experiment/html/BioImageDbs.html}},
}

@article{Kume2020kenbi,
  title={Large-Area Imaging Technology of Tissue Sections Using SEM and Prospects for Comprehensive Morphological Analysis of Biological Tissues},
  author={Satoshi Kume and Yasuhiro Murakawa},
  journal={KENBIKYO (Japanese)},
  volume={55},
  number={1},
  pages={13-17},
  year={2020},
  doi={10.11410/kenbikyo.55.1_13}
}

@Article{Weigel2021,
author={Weigel, Aubrey V.
and Chang, Chi-Lun
and Shtengel, Gleb
and Xu, C. Shan
and Hoffman, David P.
and Freeman, Melanie
and Iyer, Nirmala
and Aaron, Jesse
and Khuon, Satya
and Bogovic, John
and Qiu, Wei
and Hess, Harald F.
and Lippincott-Schwartz, Jennifer},
title={ER-to-Golgi protein delivery through an interwoven, tubular network extending from ER},
journal={Cell},
year={2021},
month={Apr},
day={29},
publisher={Elsevier},
volume={184},
number={9},
pages={2412-2429.e16},
issn={0092-8674},
doi={10.1016/j.cell.2021.03.035},
url={https://doi.org/10.1016/j.cell.2021.03.035}
}



@article{Thomas2019,
    author = {Delgado, Thomas and Petralia, Ronald S. and Freeman, David W. and Sedlacek, Miloslav and Wang, Ya-Xian and Brenowitz, Stephan D. and Sheu, Shu-Hsien and Gu, Jeffrey W. and Kapogiannis, Dimitrios and Mattson, Mark P. and Yao, Pamela J.},
    title = "{Comparing 3D ultrastructure of presynaptic and postsynaptic mitochondria}",
    journal = {Biology Open},
    volume = {8},
    number = {8},
    year = {2019},
    month = {08},
    abstract = "{Serial-section electron microscopy such as FIB-SEM (focused ion beam scanning electron microscopy) has become an important tool for neuroscientists to trace the trajectories and global architecture of neural circuits in the brain, as well as to visualize the 3D ultrastructure of cellular organelles in neurons. In this study, we examined 3D features of mitochondria in electron microscope images generated from serial sections of four regions of mouse brains: nucleus accumbens (NA), hippocampal CA1, somatosensory cortex and dorsal cochlear nucleus (DCN). We compared mitochondria in the presynaptic terminals to those in the postsynaptic/dendritic compartments, and we focused on the shape and size of mitochondria. A common feature of mitochondria among the four brain regions is that presynaptic mitochondria generally are small and short, and most of them do not extend beyond presynaptic terminals. In contrast, the majority of postsynaptic/dendritic mitochondria are large and many of them spread through significant portions of the dendrites. Comparing among the brain areas, the cerebral cortex and DCN have even larger postsynaptic/dendritic mitochondria than the NA and CA1. Our analysis reveals that mitochondria in neurons are differentially sized and arranged according to their subcellular locations, suggesting a spatial organizing principle of mitochondria at the synapse.}",
    issn = {2046-6390},
    doi = {10.1242/bio.044834},
    url = {https://doi.org/10.1242/bio.044834},
    note = {bio044834},
    eprint = {https://journals.biologists.com/bio/article-pdf/8/8/bio044834/1835764/bio044834.pdf},
}





@article{Lopez2019,
    author = {Turegano-Lopez, M and Santuy, A and DeFelipe, J and Merchan-Perez, A},
    title = "{Size, Shape, and Distribution of Multivesicular Bodies in the Juvenile Rat Somatosensory Cortex: A 3D Electron Microscopy Study}",
    journal = {Cerebral Cortex},
    volume = {30},
    number = {3},
    pages = {1887-1901},
    year = {2019},
    month = {10},
    abstract = "{Multivesicular bodies (MVBs) are membrane-bound organelles that belong to the endosomal pathway. They participate in the transport, sorting, storage, recycling, degradation, and release of multiple substances. They interchange cargo with other organelles and participate in their renovation and degradation. We have used focused ion beam milling and scanning electron microscopy (FIB-SEM) to obtain stacks of serial sections from the neuropil of the somatosensory cortex of the juvenile rat. Using dedicated software, we have 3D-reconstructed 1618 MVBs. The mean density of MVBs was 0.21 per cubic micron. They were unequally distributed between dendrites (39.14\\%), axons (18.16\\%), and nonsynaptic cell processes (42.70\\%). About one out of five MVBs (18.16\\%) were docked on mitochondria, representing the process by which the endosomal pathway participates in mitochondrial maintenance. Other features of MVBs, such as the presence of tubular protrusions (6.66\\%) or clathrin coats (19.74\\%) can also be interpreted in functional terms, since both are typical of early endosomes. The sizes of MVBs follow a lognormal distribution, with differences across cortical layers and cellular compartments. The mean volume of dendritic MVBs is more than twice as large as the volume of axonic MVBs. In layer I, they are smaller, on average, than in the other layers.}",
    issn = {1047-3211},
    doi = {10.1093/cercor/bhz211},
    url = {https://doi.org/10.1093/cercor/bhz211},
    eprint = {https://academic.oup.com/cercor/article-pdf/30/3/1887/33011196/bhz211.pdf},
}





@ARTICLE{Tate2021,
AUTHOR={Knothe Tate, Melissa L. and Srikantha, Abhilash and Wojek, Christian and Zeidler, Dirk},   
TITLE={Connectomics of Bone to Brain—Probing Physical Renderings of Cellular Experience},      
JOURNAL={Frontiers in Physiology},      
VOLUME={12},      
PAGES={1018},     
YEAR={2021},      
URL={https://www.frontiersin.org/article/10.3389/fphys.2021.647603},       
DOI={10.3389/fphys.2021.647603},      
ISSN={1664-042X},   
ABSTRACT={“Brainless” cells, the living constituents inhabiting all biological materials, exhibit remarkably smart, i.e., stimuli-responsive and adaptive, behavior. The emergent spatial and temporal patterns of adaptation, observed as changes in cellular connectivity and tissue remodeling by cells, underpin neuroplasticity, muscle memory, immunological imprinting, and sentience itself, in diverse physiological systems from brain to bone. Connectomics addresses the direct connectivity of cells and cells’ adaptation to dynamic environments through manufacture of extracellular matrix, forming tissues and architectures comprising interacting organs and systems of organisms. There is imperative to understand the physical renderings of cellular experience throughout life, from the time of emergence, to growth, adaptation and aging-associated degeneration of tissues. Here we address this need through development of technological approaches that incorporate cross length scale (nm to m) structural data, acquired via multibeam scanning electron microscopy, with machine learning and information transfer using network modeling approaches. This pilot case study uses cutting edge imaging methods for nano- to meso-scale study of cellular inhabitants within human hip tissue resected during the normal course of hip replacement surgery. We discuss the technical approach and workflow and identify the resulting opportunities as well as pitfalls to avoid, delineating a path for cellular connectomics studies in diverse tissue/organ environments and their interactions within organisms and across species. Finally, we discuss the implications of the outlined approach for neuromechanics and the control of physical behavior and neuromuscular training.}
}

@article {Rae2021,
article_type = {journal},
title = {A robust method for particulate detection of a genetic tag for 3D electron microscopy},
author = {Rae, James and Ferguson, Charles and Ariotti, Nicholas and Webb, Richard I and Cheng, Han-Hao and Mead, James L and Riches, James D and Hunter, Dominic JB and Martel, Nick and Baltos, Joanne and Christopoulos, Arthur and Bryce, Nicole S and Cagigas, Maria Lastra and Fonseka, Sachini and Sayre, Marcel E and Hardeman, Edna C and Gunning, Peter W and Gambin, Yann and Hall, Thomas E and Parton, Robert G},
editor = {Frost, Adam and Akhmanova, Anna and Schwab, Yannick and Verkade, Paul},
volume = 10,
year = 2021,
month = {apr},
pub_date = {2021-04-27},
pages = {e64630},
citation = {eLife 2021;10:e64630},
doi = {10.7554/eLife.64630},
url = {https://doi.org/10.7554/eLife.64630},
abstract = {Genetic tags allow rapid localization of tagged proteins in cells and tissues. APEX, an ascorbate peroxidase, has proven to be one of the most versatile and robust genetic tags for ultrastructural localization by electron microscopy (EM). Here, we describe a simple method, APEX-Gold, which converts the diffuse oxidized diaminobenzidine reaction product of APEX into a silver/gold particle akin to that used for immunogold labelling. The method increases the signal-to-noise ratio for EM detection, providing unambiguous detection of the tagged protein, and creates a readily quantifiable particulate signal. We demonstrate the wide applicability of this method for detection of membrane proteins, cytoplasmic proteins, and cytoskeletal proteins. The method can be combined with different EM techniques including fast freezing and freeze substitution, focussed ion beam scanning EM, and electron tomography. Quantitation of expressed APEX-fusion proteins is achievable using membrane vesicles generated by a cell-free expression system. These membrane vesicles possess a defined quantum of signal, which can act as an internal standard for determination of the absolute density of expressed APEX-fusion proteins. Detection of fusion proteins expressed at low levels in cells from CRISPR-edited mice demonstrates the high sensitivity of the APEX-Gold method.},
keywords = {APEX, electron microscopy, particulate marker, 3D-electron microscopy, genetically encoded},
journal = {eLife},
issn = {2050-084X},
publisher = {eLife Sciences Publications, Ltd},
}


@Article{Polilov2021,
author={Polilov, Alexey A.
and Makarova, Anastasia A.
and Pang, Song
and Shan Xu, C.
and Hess, Harald},
title={Protocol for preparation of heterogeneous biological samples for 3D electron microscopy: a case study for insects},
journal={Scientific Reports},
year={2021},
month={Feb},
day={25},
volume={11},
number={1},
pages={4717},
abstract={Modern morphological and structural studies are coming to a new level by incorporating the latest methods of three-dimensional electron microscopy (3D-EM). One of the key problems for the wide usage of these methods is posed by difficulties with sample preparation, since the methods work poorly with heterogeneous (consisting of tissues different in structure and in chemical composition) samples and require expensive equipment and usually much time. We have developed a simple protocol allows preparing heterogeneous biological samples suitable for 3D-EM in a laboratory that has a standard supply of equipment and reagents for electron microscopy. This protocol, combined with focused ion-beam scanning electron microscopy, makes it possible to study 3D ultrastructure of complex biological samples, e.g., whole insect heads, over their entire volume at the cellular and subcellular levels. The protocol provides new opportunities for many areas of study, including connectomics.},
issn={2045-2322},
doi={10.1038/s41598-021-83936-0},
url={https://doi.org/10.1038/s41598-021-83936-0}
}



@ARTICLE{Shibata2019,
AUTHOR={Shibata, Shinsuke and Iseda, Taro and Mitsuhashi, Takayuki and Oka, Atsushi and Shindo, Tomoko and Moritoki, Nobuko and Nagai, Toshihiro and Otsubo, Shinya and Inoue, Takashi and Sasaki, Erika and Akazawa, Chihiro and Takahashi, Takao and Schalek, Richard and Lichtman, Jeff W. and Okano, Hideyuki},   
TITLE={Large-Area Fluorescence and Electron Microscopic Correlative Imaging With Multibeam Scanning Electron Microscopy},      
JOURNAL={Frontiers in Neural Circuits},      
VOLUME={13},      
PAGES={29},     
YEAR={2019},      
URL={https://www.frontiersin.org/article/10.3389/fncir.2019.00029},       
DOI={10.3389/fncir.2019.00029},      
ISSN={1662-5110},   
ABSTRACT={Recent improvements in correlative light and electron microscopy (CLEM) technology have led to dramatic improvements in the ability to observe tissues and cells. Fluorescence labeling has been used to visualize the localization of molecules of interest through immunostaining or genetic modification strategies for the identification of the molecular signatures of biological specimens. Newer technologies such as tissue clearing have expanded the field of observation available for fluorescence labeling; however, the area of correlative observation available for electron microscopy (EM) remains restricted. In this study, we developed a large-area CLEM imaging procedure to show specific molecular localization in large-scale EM sections of mouse and marmoset brain. Target molecules were labeled with antibodies and sequentially visualized in cryostat sections using fluorescence and gold particles. Fluorescence images were obtained by light microscopy immediately after antibody staining. Immunostained sections were postfixed for EM, and silver-enhanced sections were dehydrated in a graded ethanol series and embedded in resin. Ultrathin sections for EM were prepared from fully polymerized resin blocks, collected on silicon wafers, and observed by multibeam scanning electron microscopy (SEM). Multibeam SEM has made rapid, large-area observation at high resolution possible, paving the way for the analysis of detailed structures using the CLEM approach. Here, we describe detailed methods for large-area CLEM in various tissues of both rodents and primates.}
}

@article{PLUK2009,
author = {PLUK, H. and STOKES, D.J. and LICH, B. and WIERINGA, B. and FRANSEN, J.},
title = {Advantages of indium–tin oxide-coated glass slides in correlative scanning electron microscopy applications of uncoated cultured cells},
journal = {Journal of Microscopy},
volume = {233},
number = {3},
pages = {353-363},
keywords = {Backscattered electron imaging, conductive glass slides, correlative microscopy, fluorescence light microscopy, indium–tin oxide, mouse embryonic fibroblasts, scanning electron microscopy},
doi = {https://doi.org/10.1111/j.1365-2818.2009.03140.x},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-2818.2009.03140.x},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2818.2009.03140.x},
abstract = {Summary A method of direct visualization by correlative scanning electron microscopy (SEM) and fluorescence light microscopy of cell structures of tissue cultured cells grown on conductive glass slides is described. We show that by growing cells on indium–tin oxide (ITO)-coated glass slides, secondary electron (SE) and backscatter electron (BSE) images of uncoated cells can be obtained in high-vacuum SEM without charging artefacts. Interestingly, we observed that BSE imaging is influenced by both accelerating voltage and ITO coating thickness. By combining SE and BSE imaging with fluorescence light microscopy imaging, we were able to reveal detailed features of actin cytoskeletal and mitochondrial structures in mouse embryonic fibroblasts. We propose that the application of ITO glass as a substrate for cell culture can easily be extended and offers new opportunities for correlative light and electron microscopy studies of adherently growing cells.},
year = {2009}
}



@Article{Sawaguchi2018,
author={Sawaguchi, Akira
and Kamimura, Takeshi
and Yamashita, Atsushi
and Takahashi, Nobuyasu
and Ichikawa, Kaori
and Aoyama, Fumiyo
and Asada, Yujiro},
title={Informative three-dimensional survey of cell/tissue architectures in thick paraffin sections by simple low-vacuum scanning electron microscopy},
journal={Scientific Reports},
year={2018},
month={May},
day={10},
volume={8},
number={1},
pages={7479},
abstract={Recent advances in bio-medical research, such as the production of regenerative organs from stem cells, require three-dimensional analysis of cell/tissue architectures. High-resolution imaging by electron microscopy is the best way to elucidate complex cell/tissue architectures, but the conventional method requires a skillful and time-consuming preparation. The present study developed a three-dimensional survey method for assessing cell/tissue architectures in 30-{\textmu}m-thick paraffin sections by taking advantage of backscattered electron imaging in a low-vacuum scanning electron microscope. As a result, in the kidney, the podocytes and their processes were clearly observed to cover the glomerulus. The 30{\thinspace}{\textmu}m thickness facilitated an investigation on face-side (instead of sectioned) images of the epithelium and endothelium, which are rarely seen within conventional thin sections. In the testis, differentiated spermatozoa were three-dimensionally assembled in the middle of the seminiferous tubule. Further application to vascular-injury thrombus formation revealed the distinctive networks of fibrin fibres and platelets, capturing the erythrocytes into the thrombus. The four-segmented BSE detector provided topographic bird's-eye images that allowed a three-dimensional understanding of the cell/tissue architectures at the electron-microscopic level. Here, we describe the precise procedures of this imaging method and provide representative electron micrographs of normal rat organs, experimental thrombus formation, and three-dimensionally cultured tumour cells.},
issn={2045-2322},
doi={10.1038/s41598-018-25840-8},
url={https://doi.org/10.1038/s41598-018-25840-8}
}




@article{YOUNG1993,
author = {YOUNG, R. J. and DINGLE, T. and ROBINSON, K. and PUGH, P. J. A.},
title = {An application of scanned focused ion beam milling to studies on the internal morphology of small arthropods},
journal = {Journal of Microscopy},
volume = {172},
number = {1},
pages = {81-88},
keywords = {Arthropods, morphology, ion beam milling, focused ion beam milling, scanning electron microscopy},
doi = {https://doi.org/10.1111/j.1365-2818.1993.tb03396.x},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-2818.1993.tb03396.x},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2818.1993.tb03396.x},
abstract = {Summary For the first time a scanned focused ion beam of approximately 50 nm diameter has been used to prepare biological material. Small defined areas of the surface were removed by ion etching to allow examination of the underlying structures with a scanning electron microscope. Different milling procedures were carried out on two anatomical features in mites of the genus Halarachne (Halarachnidae: Mesostigmata). In the first, square holes were milled into the surface of the peritrematal plate to reveal the structure of the underlying respiratory peritrematal groove. In the second, transverse cuts were made across the shafts of the sensory sensilli which make up the sensory Haller's organ on tarsus I. This latter procedure revealed detail both within the core and walls of sensilli. Details of specimen preparation and milling procedures, as well as suitability and interpretation of results, are presented.},
year = {1993}
}

@Article{Helmstaedter2013,
author={Helmstaedter, Moritz
and Briggman, Kevin L.
and Turaga, Srinivas C.
and Jain, Viren
and Seung, H. Sebastian
and Denk, Winfried},
title={Connectomic reconstruction of the inner plexiform layer in the mouse retina},
journal={Nature},
year={2013},
month={Aug},
day={01},
volume={500},
number={7461},
pages={168-174},
abstract={Comprehensive high-resolution structural maps are central to functional exploration and understanding in biology. For the nervous system, in which high resolution and large spatial extent are both needed, such maps are scarce as they challenge data acquisition and analysis capabilities. Here we present for the mouse inner plexiform layer---the main computational neuropil region in the mammalian retina---the dense reconstruction of 950 neurons and their mutual contacts. This was achieved by applying a combination of crowd-sourced manual annotation and machine-learning-based volume segmentation to serial block-face electron microscopy data. We characterize a new type of retinal bipolar interneuron and show that we can subdivide a known type based on connectivity. Circuit motifs that emerge from our data indicate a functional mechanism for a known cellular response in a ganglion cell that detects localized motion, and predict that another ganglion cell is motion sensitive.},
issn={1476-4687},
doi={10.1038/nature12346},
url={https://doi.org/10.1038/nature12346}
}



@Article{Bankhead2017,
author={Bankhead, Peter
and Loughrey, Maurice B.
and Fern{\'a}ndez, Jos{\'e} A.
and Dombrowski, Yvonne
and McArt, Darragh G.
and Dunne, Philip D.
and McQuaid, Stephen
and Gray, Ronan T.
and Murray, Liam J.
and Coleman, Helen G.
and James, Jacqueline A.
and Salto-Tellez, Manuel
and Hamilton, Peter W.},
title={QuPath: Open source software for digital pathology image analysis},
journal={Scientific Reports},
year={2017},
month={Dec},
day={04},
volume={7},
number={1},
pages={16878},
abstract={QuPath is new bioimage analysis software designed to meet the growing need for a user-friendly, extensible, open-source solution for digital pathology and whole slide image analysis. In addition to offering a comprehensive panel of tumor identification and high-throughput biomarker evaluation tools, QuPath provides researchers with powerful batch-processing and scripting functionality, and an extensible platform with which to develop and share new algorithms to analyze complex tissue images. Furthermore, QuPath's flexible design makes it suitable for a wide range of additional image analysis applications across biomedical research.},
issn={2045-2322},
doi={10.1038/s41598-017-17204-5},
url={https://doi.org/10.1038/s41598-017-17204-5}
}



@Article{Tustison2021,
author={Tustison, Nicholas J.
and Cook, Philip A.
and Holbrook, Andrew J.
and Johnson, Hans J.
and Muschelli, John
and Devenyi, Gabriel A.
and Duda, Jeffrey T.
and Das, Sandhitsu R.
and Cullen, Nicholas C.
and Gillen, Daniel L.
and Yassa, Michael A.
and Stone, James R.
and Gee, James C.
and Avants, Brian B.},
title={The ANTsX ecosystem for quantitative biological and medical imaging},
journal={Scientific Reports},
year={2021},
month={Apr},
day={27},
volume={11},
number={1},
pages={9068},
abstract={The Advanced Normalizations Tools ecosystem, known as ANTsX, consists of multiple open-source software libraries which house top-performing algorithms used worldwide by scientific and research communities for processing and analyzing biological and medical imaging data. The base software library, ANTs, is built upon, and contributes to, the NIH-sponsored Insight Toolkit. Founded in 2008 with the highly regarded Symmetric Normalization image registration framework, the ANTs library has since grown to include additional functionality. Recent enhancements include statistical, visualization, and deep learning capabilities through interfacing with both the R statistical project (ANTsR) and Python (ANTsPy). Additionally, the corresponding deep learning extensions ANTsRNet and ANTsPyNet (built on the popular TensorFlow/Keras libraries) contain several popular network architectures and trained models for specific applications. One such comprehensive application is a deep learning analog for generating cortical thickness data from structural T1-weighted brain MRI, both cross-sectionally and longitudinally. These pipelines significantly improve computational efficiency and provide comparable-to-superior accuracy over multiple criteria relative to the existing ANTs workflows and simultaneously illustrate the importance of the comprehensive ANTsX approach as a framework for medical image analysis.},
issn={2045-2322},
doi={10.1038/s41598-021-87564-6},
url={https://doi.org/10.1038/s41598-021-87564-6}
}



@Article{Haberl2018,
author={Haberl, Matthias G.
and Churas, Christopher
and Tindall, Lucas
and Boassa, Daniela
and Phan, S{\'e}bastien
and Bushong, Eric A.
and Madany, Matthew
and Akay, Raffi
and Deerinck, Thomas J.
and Peltier, Steven T.
and Ellisman, Mark H.},
title={CDeep3M---Plug-and-Play cloud-based deep learning for image segmentation},
journal={Nature Methods},
year={2018},
month={Sep},
day={01},
volume={15},
number={9},
pages={677-680},
abstract={As biomedical imaging datasets expand, deep neural networks are considered vital for image processing, yet community access is still limited by setting up complex computational environments and availability of high-performance computing resources. We address these bottlenecks with CDeep3M, a ready-to-use image segmentation solution employing a cloud-based deep convolutional neural network. We benchmark CDeep3M on large and complex two-dimensional and three-dimensional imaging datasets from light, X-ray, and electron microscopy.},
issn={1548-7105},
doi={10.1038/s41592-018-0106-z},
url={https://doi.org/10.1038/s41592-018-0106-z}
}



@article{Yang2020,
    doi = {10.1371/journal.pcbi.1008193},
    author = {Yang, Linfeng and Ghosh, Rajarshi P. and Franklin, J. Matthew and Chen, Simon and You, Chenyu and Narayan, Raja R. and Melcher, Marc L. and Liphardt, Jan T.},
    journal = {PLOS Computational Biology},
    publisher = {Public Library of Science},
    title = {NuSeT: A deep learning tool for reliably separating and analyzing crowded cells},
    year = {2020},
    month = {09},
    volume = {16},
    url = {https://doi.org/10.1371/journal.pcbi.1008193},
    pages = {1-20},
    abstract = {Segmenting cell nuclei within microscopy images is a ubiquitous task in biological research and clinical applications. Unfortunately, segmenting low-contrast overlapping objects that may be tightly packed is a major bottleneck in standard deep learning-based models. We report a Nuclear Segmentation Tool (NuSeT) based on deep learning that accurately segments nuclei across multiple types of fluorescence imaging data. Using a hybrid network consisting of U-Net and Region Proposal Networks (RPN), followed by a watershed step, we have achieved superior performance in detecting and delineating nuclear boundaries in 2D and 3D images of varying complexities. By using foreground normalization and additional training on synthetic images containing non-cellular artifacts, NuSeT improves nuclear detection and reduces false positives. NuSeT addresses common challenges in nuclear segmentation such as variability in nuclear signal and shape, limited training sample size, and sample preparation artifacts. Compared to other segmentation models, NuSeT consistently fares better in generating accurate segmentation masks and assigning boundaries for touching nuclei.},
    number = {9},

}


@article{Belevich2021,
    doi = {10.1371/journal.pcbi.1008374},
    author = {Belevich, Ilya and Jokitalo, Eija},
    journal = {PLOS Computational Biology},
    publisher = {Public Library of Science},
    title = {DeepMIB: User-friendly and open-source software for training of deep learning network for biological image segmentation},
    year = {2021},
    month = {03},
    volume = {17},
    url = {https://doi.org/10.1371/journal.pcbi.1008374},
    pages = {1-9},
    abstract = {We present DeepMIB, a new software package that is capable of training convolutional neural networks for segmentation of multidimensional microscopy datasets on any workstation. We demonstrate its successful application for segmentation of 2D and 3D electron and multicolor light microscopy datasets with isotropic and anisotropic voxels. We distribute DeepMIB as both an open-source multi-platform Matlab code and as compiled standalone application for Windows, MacOS and Linux. It comes in a single package that is simple to install and use as it does not require knowledge of programming. DeepMIB is suitable for everyone interested of bringing a power of deep learning into own image segmentation workflows.},
    number = {3},

}


@article{Belevich2016,
    doi = {10.1371/journal.pbio.1002340},
    author = {Belevich, Ilya and Joensuu, Merja and Kumar, Darshan and Vihinen, Helena and Jokitalo, Eija},
    journal = {PLOS Biology},
    publisher = {Public Library of Science},
    title = {Microscopy Image Browser: A Platform for Segmentation and Analysis of Multidimensional Datasets},
    year = {2016},
    month = {01},
    volume = {14},
    url = {https://doi.org/10.1371/journal.pbio.1002340},
    pages = {1-13},
    abstract = {Understanding the structure–function relationship of cells and organelles in their natural context requires multidimensional imaging. As techniques for multimodal 3-D imaging have become more accessible, effective processing, visualization, and analysis of large datasets are posing a bottleneck for the workflow. Here, we present a new software package for high-performance segmentation and image processing of multidimensional datasets that improves and facilitates the full utilization and quantitative analysis of acquired data, which is freely available from a dedicated website. The open-source environment enables modification and insertion of new plug-ins to customize the program for specific needs. We provide practical examples of program features used for processing, segmentation and analysis of light and electron microscopy datasets, and detailed tutorials to enable users to rapidly and thoroughly learn how to use the program.},
    number = {1},

}


@Article{deHaan2021,
author={de Haan, Kevin
and Zhang, Yijie
and Zuckerman, Jonathan E.
and Liu, Tairan
and Sisk, Anthony E.
and Diaz, Miguel F. P.
and Jen, Kuang-Yu
and Nobori, Alexander
and Liou, Sofia
and Zhang, Sarah
and Riahi, Rana
and Rivenson, Yair
and Wallace, W. Dean
and Ozcan, Aydogan},
title={Deep learning-based transformation of H{\&}E stained tissues into special stains},
journal={Nature Communications},
year={2021},
month={Aug},
day={12},
volume={12},
number={1},
pages={4884},
abstract={Pathology is practiced by visual inspection of histochemically stained tissue slides. While the hematoxylin and eosin (H{\&}E) stain is most commonly used, special stains can provide additional contrast to different tissue components. Here, we demonstrate the utility of supervised learning-based computational stain transformation from H{\&}E to special stains (Masson's Trichrome, periodic acid-Schiff and Jones silver stain) using kidney needle core biopsy tissue sections. Based on the evaluation by three renal pathologists, followed by adjudication by a fourth pathologist, we show that the generation of virtual special stains from existing H{\&}E images improves the diagnosis of several non-neoplastic kidney diseases, sampled from 58 unique subjects (P = 0.0095). A second study found that the quality of the computationally generated special stains was statistically equivalent to those which were histochemically stained. This stain-to-stain transformation framework can improve preliminary diagnoses when additional special stains are needed, also providing significant savings in time and cost.},
issn={2041-1723},
doi={10.1038/s41467-021-25221-2},
url={https://doi.org/10.1038/s41467-021-25221-2}
}



@article{Rana2020,
    author = {Rana, Aman and Lowe, Alarice and Lithgow, Marie and Horback, Katharine and Janovitz, Tyler and Da Silva, Annacarolina and Tsai, Harrison and Shanmugam, Vignesh and Bayat, Akram and Shah, Pratik},
    title = "{Use of Deep Learning to Develop and Analyze Computational Hematoxylin and Eosin Staining of Prostate Core Biopsy Images for Tumor Diagnosis}",
    journal = {JAMA Network Open},
    volume = {3},
    number = {5},
    pages = {e205111-e205111},
    year = {2020},
    month = {05},
    abstract = "{Histopathological diagnoses of tumors from tissue biopsy after hematoxylin and eosin (H\\&E) dye staining is the criterion standard for oncological care, but H\\&E staining requires trained operators, dyes and reagents, and precious tissue samples that cannot be reused.To use deep learning algorithms to develop models that perform accurate computational H\\&E staining of native nonstained prostate core biopsy images and to develop methods for interpretation of H\\&E staining deep learning models and analysis of computationally stained images by computer vision and clinical approaches.This cross-sectional study used hundreds of thousands of native nonstained RGB (red, green, and blue channel) whole slide image (WSI) patches of prostate core tissue biopsies obtained from excess tissue material from prostate core biopsies performed in the course of routine clinical care between January 7, 2014, and January 7, 2017, at Brigham and Women’s Hospital, Boston, Massachusetts. Biopsies were registered with their H\\&E-stained versions. Conditional generative adversarial neural networks (cGANs) that automate conversion of native nonstained RGB WSI to computational H\\&E-stained images were then trained. Deidentified whole slide images of prostate core biopsy and medical record data were transferred to Massachusetts Institute of Technology, Cambridge, for computational research. Results were shared with physicians for clinical evaluations. Data were analyzed from July 2018 to February 2019.Methods for detailed computer vision image analytics, visualization of trained cGAN model outputs, and clinical evaluation of virtually stained images were developed. The main outcome was interpretable deep learning models and computational H\\&E-stained images that achieved high performance in these metrics.Among 38 patients who provided samples, single core biopsy images were extracted from each whole slide, resulting in 102 individual nonstained and H\\&E dye–stained image pairs that were compared with matched computationally stained and unstained images. Calculations showed high similarities between computationally and H\\&E dye–stained images, with a mean (SD) structural similarity index (SSIM) of 0.902 (0.026), Pearson correlation coefficient (PCC) of 0.962 (0.096), and peak signal to noise ratio (PSNR) of 22.821 (1.232) dB. A second cGAN performed accurate computational destaining of H\\&E-stained images back to their native nonstained form, with a mean (SD) SSIM of 0.900 (0.030), PCC of 0.963 (0.011), and PSNR of 25.646 (1.943) dB compared with native nonstained images. A single blind prospective study computed approximately 95\\% pixel-by-pixel overlap among prostate tumor annotations provided by 5 board certified pathologists on computationally stained images, compared with those on H\\&E dye–stained images. This study also used the first visualization and explanation of neural network kernel activation maps during H\\&E staining and destaining of RGB images by cGANs. High similarities between kernel activation maps of computationally and H\\&E-stained images (mean-squared errors \\<0.0005) provide additional mathematical and mechanistic validation of the staining system.These findings suggest that computational H\\&E staining of native unlabeled RGB images of prostate core biopsy could reproduce Gleason grade tumor signatures that were easily assessed and validated by clinicians. Methods for benchmarking, visualization, and clinical validation of deep learning models and virtually H\\&E-stained images communicated in this study have wide applications in clinical informatics and oncology research. Clinical researchers may use these systems for early indications of possible abnormalities in native nonstained tissue biopsies prior to histopathological workflows.}",
    issn = {2574-3805},
    doi = {10.1001/jamanetworkopen.2020.5111},
    url = {https://doi.org/10.1001/jamanetworkopen.2020.5111},
    eprint = {https://jamanetwork.com/journals/jamanetworkopen/articlepdf/2766071/rana\_2020\_oi\_200241.pdf},
}





@INPROCEEDINGS{Tsuda2019, 
 author={Tsuda, Hiroki and Hotta, Kazuhiro},  booktitle={2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops (CVPRW)},   title={Cell Image Segmentation by Integrating Pix2pixs for Each Class},   year={2019},  volume={},  number={},  pages={1065-1073},  doi={10.1109/CVPRW.2019.00139}}

@article{Thomas2021,
title = {Residual cyclegan for robust domain transformation of histopathological tissue slides},
journal = {Medical Image Analysis},
volume = {70},
pages = {102004},
year = {2021},
issn = {1361-8415},
doi = {https://doi.org/10.1016/j.media.2021.102004},
url = {https://www.sciencedirect.com/science/article/pii/S1361841521000505},
author = {Thomas {de Bel} and John-Melle Bokhorst and Jeroen {van der Laak} and Geert Litjens},
keywords = {Histopathology, Adversarial networks, Stain normalization, Structure segmentation},
abstract = {Variation between stains in histopathology is commonplace across different medical centers. This can have a significant effect on the reliability of machine learning algorithms. In this paper, we propose to reduce performance variability by using -consistent generative adversarial (CycleGAN) networks to remove staining variation. We improve upon the regular CycleGAN by incorporating residual learning. We comprehensively evaluate the performance of our stain transformation method and compare its usefulness in addition to extensive data augmentation to enhance the robustness of tissue segmentation algorithms. Our steps are as follows: first, we train a model to perform segmentation on tissue slides from a single source center, while heavily applying augmentations to increase robustness to unseen data. Second, we evaluate and compare the segmentation performance on data from other centers, both with and without applying our CycleGAN stain transformation. We compare segmentation performances in a colon tissue segmentation and kidney tissue segmentation task, covering data from 6 different centers. We show that our transformation method improves the overall Dice coefficient by 9% over the non-normalized target data and by 4% over traditional stain transformation in our colon tissue segmentation task. For kidney segmentation, our residual CycleGAN increases performance by 10% over no transformation and around 2% compared to the non-residual CycleGAN.}
}


@Article{Zhang2020,
author={Zhang, Yijie
and de Haan, Kevin
and Rivenson, Yair
and Li, Jingxi
and Delis, Apostolos
and Ozcan, Aydogan},
title={Digital synthesis of histological stains using micro-structured and multiplexed virtual staining of label-free tissue},
journal={Light: Science {\&} Applications},
year={2020},
month={May},
day={06},
volume={9},
number={1},
pages={78},
abstract={Histological staining is a vital step in diagnosing various diseases and has been used for more than a century to provide contrast in tissue sections, rendering the tissue constituents visible for microscopic analysis by medical experts. However, this process is time consuming, labour intensive, expensive and destructive to the specimen. Recently, the ability to virtually stain unlabelled tissue sections, entirely avoiding the histochemical staining step, has been demonstrated using tissue-stain-specific deep neural networks. Here, we present a new deep-learning-based framework that generates virtually stained images using label-free tissue images, in which different stains are merged following a micro-structure map defined by the user. This approach uses a single deep neural network that receives two different sources of information as its input: (1) autofluorescence images of the label-free tissue sample and (2) a ``digital staining matrix'', which represents the desired microscopic map of the different stains to be virtually generated in the same tissue section. This digital staining matrix is also used to virtually blend existing stains, digitally synthesizing new histological stains. We trained and blindly tested this virtual-staining network using unlabelled kidney tissue sections to generate micro-structured combinations of haematoxylin and eosin (H{\&}E), Jones' silver stain, and Masson's trichrome stain. Using a single network, this approach multiplexes the virtual staining of label-free tissue images with multiple types of stains and paves the way for synthesizing new digital histological stains that can be created in the same tissue cross section, which is currently not feasible with standard histochemical staining methods.},
issn={2047-7538},
doi={10.1038/s41377-020-0315-y},
url={https://doi.org/10.1038/s41377-020-0315-y}
}



@ARTICLE{Xu2020,
AUTHOR={Xu, Zidui and Li, Xi and Zhu, Xihan and Chen, Luyang and He, Yonghong and Chen, Yupeng},   
TITLE={Effective Immunohistochemistry Pathology Microscopy Image Generation Using CycleGAN},      
JOURNAL={Frontiers in Molecular Biosciences},      
VOLUME={7},      
PAGES={243},     
YEAR={2020},      
URL={https://www.frontiersin.org/article/10.3389/fmolb.2020.571180},       
DOI={10.3389/fmolb.2020.571180},      
ISSN={2296-889X},   
ABSTRACT={Immunohistochemistry detection technology is able to detect more difficult tumors than regular pathology detection technology only with hematoxylin-eosin stained pathology microscopy images, – for example, neuroendocrine tumor detection. However, making immunohistochemistry pathology microscopy images costs much time and money. In this paper, we propose an effective immunohistochemistry pathology microscopic image-generation method that can generate synthetic immunohistochemistry pathology microscopic images from hematoxylin-eosin stained pathology microscopy images without any annotation. CycleGAN is adopted as the basic architecture for the unpaired and unannotated dataset. Moreover, multiple instances learning algorithms and the idea behind conditional GAN are considered to improve performance. To our knowledge, this is the first attempt to generate immunohistochemistry pathology microscopic images, and our method can achieve good performance, which will be very useful for pathologists and patients when applied in clinical practice.}
}


@Article{Hagita2018,
author={Hagita, Katsumi
and Higuchi, Takeshi
and Jinnai, Hiroshi},
title={Super-resolution for asymmetric resolution of FIB-SEM 3D imaging using AI with deep learning},
journal={Scientific Reports},
year={2018},
month={Apr},
day={12},
volume={8},
number={1},
pages={5877},
abstract={Scanning electron microscopy equipped with a focused ion beam (FIB-SEM) is a promising three-dimensional (3D) imaging technique for nano- and meso-scale morphologies. In FIB-SEM, the specimen surface is stripped by an ion beam and imaged by an SEM installed orthogonally to the FIB. The lateral resolution is governed by the SEM, while the depth resolution, i.e., the FIB milling direction, is determined by the thickness of the stripped thin layer. In most cases, the lateral resolution is superior to the depth resolution; hence, asymmetric resolution is generated in the 3D image. Here, we propose a new approach based on an image-processing or deep-learning-based method for super-resolution of 3D images with such asymmetric resolution, so as to restore the depth resolution to achieve symmetric resolution. The deep-learning-based method learns from high-resolution sub-images obtained via SEM and recovers low-resolution sub-images parallel to the FIB milling direction. The 3D morphologies of polymeric nano-composites are used as test images, which are subjected to the deep-learning-based method as well as conventional methods. We find that the former yields superior restoration, particularly as the asymmetric resolution is increased. Our super-resolution approach for images having asymmetric resolution enables observation time reduction.},
issn={2045-2322},
doi={10.1038/s41598-018-24330-1},
url={https://doi.org/10.1038/s41598-018-24330-1}
}



@article {Januszewski2019,
	author = {Januszewski, Micha{\l} and Jain, Viren},
	title = {Segmentation-Enhanced CycleGAN},
	elocation-id = {548081},
	year = {2019},
	doi = {10.1101/548081},
	publisher = {Cold Spring Harbor Laboratory},
	abstract = {Algorithmic reconstruction of neurons from volume electron microscopy data traditionally requires training machine learning models on dataset-specific ground truth annotations that are expensive and tedious to acquire. We enhanced the training procedure of an unsupervised image-to-image translation method with additional components derived from an automated neuron segmentation approach. We show that this method, Segmentation-Enhanced CycleGAN (SECGAN), enables near perfect reconstruction accuracy on a benchmark connectomics segmentation dataset despite operating in a {\textquotedblleft}zero-shot{\textquotedblright} setting in which the segmentation model was trained using only volumetric labels from a different dataset and imaging method. By reducing or eliminating the need for novel ground truth annotations, SECGANs alleviate one of the main practical burdens involved in pursuing automated reconstruction of volume electron microscopy data.},
	URL = {https://www.biorxiv.org/content/early/2019/02/13/548081},
	eprint = {https://www.biorxiv.org/content/early/2019/02/13/548081.full.pdf},
	journal = {bioRxiv}
}



@Article{deHaan2019,
author={de Haan, Kevin
and Ballard, Zachary S.
and Rivenson, Yair
and Wu, Yichen
and Ozcan, Aydogan},
title={Resolution enhancement in scanning electron microscopy using deep learning},
journal={Scientific Reports},
year={2019},
month={Aug},
day={19},
volume={9},
number={1},
pages={12050},
abstract={We report resolution enhancement in scanning electron microscopy (SEM) images using a generative adversarial network. We demonstrate the veracity of this deep learning-based super-resolution technique by inferring unresolved features in low-resolution SEM images and comparing them with the accurately co-registered high-resolution SEM images of the same samples. Through spatial frequency analysis, we also report that our method generates images with frequency spectra matching higher resolution SEM images of the same fields-of-view. By using this technique, higher resolution SEM images can be taken faster, while also reducing both electron charging and damage to the samples.},
issn={2045-2322},
doi={10.1038/s41598-019-48444-2},
url={https://doi.org/10.1038/s41598-019-48444-2}
}



@Article{Fang2021,
author={Fang, Linjing
and Monroe, Fred
and Novak, Sammy Weiser
and Kirk, Lyndsey
and Schiavon, Cara R.
and Yu, Seungyoon B.
and Zhang, Tong
and Wu, Melissa
and Kastner, Kyle
and Latif, Alaa Abdel
and Lin, Zijun
and Shaw, Andrew
and Kubota, Yoshiyuki
and Mendenhall, John
and Zhang, Zhao
and Pekkurnaz, Gulcin
and Harris, Kristen
and Howard, Jeremy
and Manor, Uri},
title={Deep learning-based point-scanning super-resolution imaging},
journal={Nature Methods},
year={2021},
month={Apr},
day={01},
volume={18},
number={4},
pages={406-416},
abstract={Point-scanning imaging systems are among the most widely used tools for high-resolution cellular and tissue imaging, benefiting from arbitrarily defined pixel sizes. The resolution, speed, sample preservation and signal-to-noise ratio (SNR) of point-scanning systems are difficult to optimize simultaneously. We show these limitations can be mitigated via the use of deep learning-based supersampling of undersampled images acquired on a point-scanning system, which we term point-scanning super-resolution (PSSR) imaging. We designed a `crappifier' that computationally degrades high SNR, high-pixel resolution ground truth images to simulate low SNR, low-resolution counterparts for training PSSR models that can restore real-world undersampled images. For high spatiotemporal resolution fluorescence time-lapse data, we developed a `multi-frame' PSSR approach that uses information in adjacent frames to improve model predictions. PSSR facilitates point-scanning image acquisition with otherwise unattainable resolution, speed and sensitivity. All the training data, models and code for PSSR are publicly available at 3DEM.org.},
issn={1548-7105},
doi={10.1038/s41592-021-01080-z},
url={https://doi.org/10.1038/s41592-021-01080-z}
}



@article {Minnen2021,
	author = {Minnen, David and Januszewski, Micha{\l} and Shapson-Coe, Alexander and Schalek, Richard L. and Ball{\'e}, Johannes and Lichtman, Jeff W. and Jain, Viren},
	title = {Denoising-based Image Compression for Connectomics},
	elocation-id = {2021.05.29.445828},
	year = {2021},
	doi = {10.1101/2021.05.29.445828},
	publisher = {Cold Spring Harbor Laboratory},
	abstract = {Connectomic reconstruction of neural circuits relies on nanometer resolution microscopy which produces on the order of a petabyte of imagery for each cubic millimeter of brain tissue. The cost of storing such data is a significant barrier to broadening the use of connectomic approaches and scaling to even larger volumes. We present an image compression approach that uses machine learning-based denoising and standard image codecs to compress raw electron microscopy imagery of neuropil up to 17-fold with negligible loss of reconstruction accuracy.Competing Interest StatementThe authors have declared no competing interest.},
	URL = {https://www.biorxiv.org/content/early/2021/05/30/2021.05.29.445828},
	eprint = {https://www.biorxiv.org/content/early/2021/05/30/2021.05.29.445828.full.pdf},
	journal = {bioRxiv}
}



@article{Mohan2020,
  title={Deep Denoising For Scientific Discovery: A Case Study In Electron Microscopy},
  author={Sreyas Mohan and Ram{\'o}n Manzorro and Joshua L. Vincent and Binh Tang and D. Y. Sheth and Eero P. Simoncelli and David S. Matteson and Peter A. Crozier and Carlos Fernandez-Granda},
  journal={ArXiv},
  year={2020},
  volume={abs/2010.12970}
}


@Article{Wang2020,
author={Wang, Feng
and Henninen, Trond R.
and Keller, Debora
and Erni, Rolf},
title={Noise2Atom: unsupervised denoising for scanning transmission electron microscopy images},
journal={Applied Microscopy},
year={2020},
month={Oct},
day={20},
volume={50},
number={1},
pages={23},
abstract={We propose an effective deep learning model to denoise scanning transmission electron microscopy (STEM) image series, named Noise2Atom, to map images from a source domain {\$}{\backslash}mathcal {\{}S{\}}{\$}to a target domain {\$}{\backslash}mathcal {\{}C{\}}{\$}, where {\$}{\backslash}mathcal {\{}S{\}}{\$}is for our noisy experimental dataset, and {\$}{\backslash}mathcal {\{}C{\}}{\$}is for the desired clear atomic images. Noise2Atom uses two external networks to apply additional constraints from the domain knowledge. This model requires no signal prior, no noise model estimation, and no paired training images. The only assumption is that the inputs are acquired with identical experimental configurations. To evaluate the restoration performance of our model, as it is impossible to obtain ground truth for our experimental dataset, we propose consecutive structural similarity (CSS) for image quality assessment, based on the fact that the structures remain much the same as the previous frame(s) within small scan intervals. We demonstrate the superiority of our model by providing evaluation in terms of CSS and visual quality on different experimental datasets.},
issn={2287-4445},
doi={10.1186/s42649-020-00041-8},
url={https://doi.org/10.1186/s42649-020-00041-8}
}



@INPROCEEDINGS{Quan2019,  
author={Quan, Tran Minh and Hildebrand, David Grant Colburn and Lee, Kanggeun and Thomas, Logan A. and Kuan, Aaron T. and Lee, Wei-Chung Allen and Jeong, Won-Ki},  booktitle={2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)},   title={Removing Imaging Artifacts in Electron Microscopy using an Asymmetrically Cyclic Adversarial Network without Paired Training Data},   year={2019},  volume={},  number={},  pages={3804-3813},  doi={10.1109/ICCVW.2019.00473}}

@ARTICLE{Creswell2018, 
 author={Creswell, Antonia and White, Tom and Dumoulin, Vincent and Arulkumaran, Kai and Sengupta, Biswa and Bharath, Anil A.},  journal={IEEE Signal Processing Magazine},   title={Generative Adversarial Networks: An Overview},   year={2018},  volume={35},  number={1},  pages={53-65},  doi={10.1109/MSP.2017.2765202}}

@INPROCEEDINGS{Zhu2017, 
 author={Zhu, Jun-Yan and Park, Taesung and Isola, Phillip and Efros, Alexei A.},  booktitle={2017 IEEE International Conference on Computer Vision (ICCV)},   title={Unpaired Image-to-Image Translation Using Cycle-Consistent Adversarial Networks},   year={2017},  volume={},  number={},  pages={2242-2251},  doi={10.1109/ICCV.2017.244}}

@article{Wang2016DeepLF,
  title={Deep Learning for Identifying Metastatic Breast Cancer},
  author={Dayong Wang and Aditya Khosla and Rishab Gargeya and Humayun Irshad and Andrew H. Beck},
  journal={ArXiv},
  year={2016},
  volume={abs/1606.05718}
}

@Article{Howard2021,
author={Howard, Frederick M.
and Dolezal, James
and Kochanny, Sara
and Schulte, Jefree
and Chen, Heather
and Heij, Lara
and Huo, Dezheng
and Nanda, Rita
and Olopade, Olufunmilayo I.
and Kather, Jakob N.
and Cipriani, Nicole
and Grossman, Robert L.
and Pearson, Alexander T.},
title={The impact of site-specific digital histology signatures on deep learning model accuracy and bias},
journal={Nature Communications},
year={2021},
month={Jul},
day={20},
volume={12},
number={1},
pages={4423},
abstract={The Cancer Genome Atlas (TCGA) is one of the largest biorepositories of digital histology. Deep learning (DL) models have been trained on TCGA to predict numerous features directly from histology, including survival, gene expression patterns, and driver mutations. However, we demonstrate that these features vary substantially across tissue submitting sites in TCGA for over 3,000 patients with six cancer subtypes. Additionally, we show that histologic image differences between submitting sites can easily be identified with DL. Site detection remains possible despite commonly used color normalization and augmentation methods, and we quantify the image characteristics constituting this site-specific digital histology signature. We demonstrate that these site-specific signatures lead to biased accuracy for prediction of features including survival, genomic mutations, and tumor stage. Furthermore, ethnicity can also be inferred from site-specific signatures, which must be accounted for to ensure equitable application of DL. These site-specific signatures can lead to overoptimistic estimates of model performance, and we propose a quadratic programming method that abrogates this bias by ensuring models are not trained and validated on samples from the same site.},
issn={2041-1723},
doi={10.1038/s41467-021-24698-1},
url={https://doi.org/10.1038/s41467-021-24698-1}
}



@Article{Jurgenson2020,
author={Levy-Jurgenson, Alona
and Tekpli, Xavier
and Kristensen, Vessela N.
and Yakhini, Zohar},
title={Spatial transcriptomics inferred from pathology whole-slide images links tumor heterogeneity to survival in breast and lung cancer},
journal={Scientific Reports},
year={2020},
month={Nov},
day={02},
volume={10},
number={1},
pages={18802},
abstract={Digital analysis of pathology whole-slide images is fast becoming a game changer in cancer diagnosis and treatment. Specifically, deep learning methods have shown great potential to support pathology analysis, with recent studies identifying molecular traits that were not previously recognized in pathology H{\&}E whole-slide images. Simultaneous to these developments, it is becoming increasingly evident that tumor heterogeneity is an important determinant of cancer prognosis and susceptibility to treatment, and should therefore play a role in the evolving practices of matching treatment protocols to patients. State of the art diagnostic procedures, however, do not provide automated methods for characterizing and/or quantifying tumor heterogeneity, certainly not in a spatial context. Further, existing methods for analyzing pathology whole-slide images from bulk measurements require many training samples and complex pipelines. Our work addresses these two challenges. First, we train deep learning models to spatially resolve bulk mRNA and miRNA expression levels on pathology whole-slide images (WSIs). Our models reach up to 0.95 AUC on held-out test sets from two cancer cohorts using a simple training pipeline and a small number of training samples. Using the inferred gene expression levels, we further develop a method to spatially characterize tumor heterogeneity. Specifically, we produce tumor molecular cartographies and heterogeneity maps of WSIs and formulate a heterogeneity index (HTI) that quantifies the level of heterogeneity within these maps. Applying our methods to breast and lung cancer slides, we show a significant statistical link between heterogeneity and survival. Our methods potentially open a new and accessible approach to investigating tumor heterogeneity and other spatial molecular properties and their link to clinical characteristics, including treatment susceptibility and survival.},
issn={2045-2322},
doi={10.1038/s41598-020-75708-z},
url={https://doi.org/10.1038/s41598-020-75708-z}
}



@Article{Greener2021,
author={Greener, Joe G.
and Kandathil, Shaun M.
and Moffat, Lewis
and Jones, David T.},
title={A guide to machine learning for biologists},
journal={Nature Reviews Molecular Cell Biology},
year={2021},
month={Sep},
day={13},
abstract={The expanding scale and inherent complexity of biological data have encouraged a growing use of machine learning in biology to build informative and predictive models of the underlying biological processes. All machine learning techniques fit models to data; however, the specific methods are quite varied and can at first glance seem bewildering. In this Review, we aim to provide readers with a gentle introduction to a few key machine learning techniques, including the most recently developed and widely used techniques involving deep neural networks. We describe how different techniques may be suited to specific types of biological data, and also discuss some best practices and points to consider when one is embarking on experiments involving machine learning. Some emerging directions in machine learning methodology are also discussed.},
issn={1471-0080},
doi={10.1038/s41580-021-00407-0},
url={https://doi.org/10.1038/s41580-021-00407-0}
}



@Article{Schmauch2020,
author={Schmauch, Beno{\^i}t
and Romagnoni, Alberto
and Pronier, Elodie
and Saillard, Charlie
and Maill{\'e}, Pascale
and Calderaro, Julien
and Kamoun, Aur{\'e}lie
and Sefta, Meriem
and Toldo, Sylvain
and Zaslavskiy, Mikhail
and Clozel, Thomas
and Moarii, Matahi
and Courtiol, Pierre
and Wainrib, Gilles},
title={A deep learning model to predict RNA-Seq expression of tumours from whole slide images},
journal={Nature Communications},
year={2020},
month={Aug},
day={03},
volume={11},
number={1},
pages={3877},
abstract={Deep learning methods for digital pathology analysis are an effective way to address multiple clinical questions, from diagnosis to prediction of treatment outcomes. These methods have also been used to predict gene mutations from pathology images, but no comprehensive evaluation of their potential for extracting molecular features from histology slides has yet been performed. We show that HE2RNA, a model based on the integration of multiple data modes, can be trained to systematically predict RNA-Seq profiles from whole-slide images alone, without expert annotation. Through its interpretable design, HE2RNA provides virtual spatialization of gene expression, as validated by CD3- and CD20-staining on an independent dataset. The transcriptomic representation learned by HE2RNA can also be transferred on other datasets, even of small size, to increase prediction performance for specific molecular phenotypes. We illustrate the use of this approach in clinical diagnosis purposes such as the identification of tumors with microsatellite instability.},
issn={2041-1723},
doi={10.1038/s41467-020-17678-4},
url={https://doi.org/10.1038/s41467-020-17678-4}
}



@Article{Tavolara2021,
author={Tavolara, Thomas E.
and Niazi, M. K. K.
and Gower, Adam C.
and Ginese, Melanie
and Beamer, Gillian
and Gurcan, Metin N.},
title={Deep learning predicts gene expression as an intermediate data modality to identify susceptibility patterns in <em>Mycobacterium tuberculosis</em> infected Diversity Outbred mice},
journal={EBioMedicine},
year={2021},
month={May},
day={01},
publisher={Elsevier},
volume={67},
issn={2352-3964},
doi={10.1016/j.ebiom.2021.103388},
url={https://doi.org/10.1016/j.ebiom.2021.103388}
}



@Article{Ash2021,
author={Ash, Jordan T.
and Darnell, Gregory
and Munro, Daniel
and Engelhardt, Barbara E.},
title={Joint analysis of expression levels and histological images identifies genes associated with tissue morphology},
journal={Nature Communications},
year={2021},
month={Mar},
day={11},
volume={12},
number={1},
pages={1609},
abstract={Histopathological images are used to characterize complex phenotypes such as tumor stage. Our goal is to associate features of stained tissue images with high-dimensional genomic markers. We use convolutional autoencoders and sparse canonical correlation analysis (CCA) on paired histological images and bulk gene expression to identify subsets of genes whose expression levels in a tissue sample correlate with subsets of morphological features from the corresponding sample image. We apply our approach, ImageCCA, to two TCGA data sets, and find gene sets associated with the structure of the extracellular matrix and cell wall infrastructure, implicating uncharacterized genes in extracellular processes. We find sets of genes associated with specific cell types, including neuronal cells and cells of the immune system. We apply ImageCCA to the GTEx v6 data, and find image features that capture population variation in thyroid and in colon tissues associated with genetic variants (image morphology QTLs, or imQTLs), suggesting that genetic variation regulates population variation in tissue morphological traits.},
issn={2041-1723},
doi={10.1038/s41467-021-21727-x},
url={https://doi.org/10.1038/s41467-021-21727-x}
}



@InProceedings{Stepec2021,
    author    = {Stepec, Dejan and Skocaj, Danijel},
    title     = {Unsupervised Detection of Cancerous Regions in Histology Imagery Using Image-to-Image Translation},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops},
    month     = {June},
    year      = {2021},
    pages     = {3785-3792}
}

@ARTICLE{Wang2021,
AUTHOR={Wang, Xiaoxiao and Zou, Chong and Zhang, Yi and Li, Xiuqing and Wang, Chenxi and Ke, Fei and Chen, Jie and Wang, Wei and Wang, Dian and Xu, Xinyu and Xie, Ling and Zhang, Yifen},   
TITLE={Prediction of BRCA Gene Mutation in Breast Cancer Based on Deep Learning and Histopathology Images},      
JOURNAL={Frontiers in Genetics},      
VOLUME={12},      
PAGES={1147},     
YEAR={2021},      
URL={https://www.frontiersin.org/article/10.3389/fgene.2021.661109},       
DOI={10.3389/fgene.2021.661109},      
ISSN={1664-8021},  
ABSTRACT={<sec>BackgroundBreast cancer is one of the most common cancers and the leading cause of death from cancer among women worldwide. The genetic predisposition to breast cancer may be associated with a mutation in particular genes such as gene BRCA1/2. Patients who carry a germline pathogenic mutation in BRCA1/2 genes have a significantly increased risk of developing breast cancer and might benefit from targeted therapy. However, genetic testing is time consuming and costly. This study aims to predict the risk of gBRCA mutation by using the whole-slide pathology features of breast cancer H&E stains and the patients’ gBRCA mutation status.</sec><sec>MethodsIn this study, we trained a deep convolutional neural network (CNN) of ResNet on whole-slide images (WSIs) to predict the gBRCA mutation in breast cancer. Since the dimensions are too large for slide-based training, we divided WSI into smaller tiles with the original resolution. The tile-based classification was then combined by adding the positive classification result to generate the combined slide-based accuracy. Models were trained based on the annotated tumor location and gBRCA mutation status labeled by a designated breast cancer pathologist. Four models were trained on tiles cropped at 5×, 10×, 20×, and 40× magnification, assuming that low magnification and high magnification may provide different levels of information for classification.</sec><sec>ResultsA trained model was validated through an external dataset that contains 17 mutants and 47 wilds. In the external validation dataset, AUCs (95% CI) of DL models that used 40×, 20×, 10×, and 5× magnification tiles among all cases were 0.766 (0.763–0.769), 0.763 (0.758–0.769), 0.750 (0.738–0.761), and 0.551 (0.526–0.575), respectively, while the corresponding magnification slides among all cases were 0.774 (0.642–0.905), 0.804 (0.676–0.931), 0.828 (0.691–0.966), and 0.635 (0.471–0.798), respectively. The study also identified the influence of histological grade to the accuracy of the prediction.</sec><sec>ConclusionIn this paper, the combination of pathology and molecular omics was used to establish the gBRCA mutation risk prediction model, revealing the correlation between the whole-slide histopathological images and gRCA mutation risk. The results indicated that the prediction accuracy is likely to improve as the training data expand. The findings demonstrated that deep CNNs could be used to assist pathologists in the detection of gene mutation in breast cancer.</sec>}
}


@Article{Murchan2021,
AUTHOR = {Murchan, Pierre and Ó’Brien, Cathal and O’Connell, Shane and McNevin, Ciara S. and Baird, Anne-Marie and Sheils, Orla and Ó Broin, Pilib and Finn, Stephen P.},
TITLE = {Deep Learning of Histopathological Features for the Prediction of Tumour Molecular Genetics},
JOURNAL = {Diagnostics},
VOLUME = {11},
YEAR = {2021},
NUMBER = {8},
ARTICLE-NUMBER = {1406},
URL = {https://www.mdpi.com/2075-4418/11/8/1406},
PubMedID = {34441338},
ISSN = {2075-4418},
ABSTRACT = {Advanced diagnostics are enabling cancer treatments to become increasingly tailored to the individual through developments in immunotherapies and targeted therapies. However, long turnaround times and high costs of molecular testing hinder the widespread implementation of targeted cancer treatments. Meanwhile, gold-standard histopathological assessment carried out by a trained pathologist is widely regarded as routine and mandatory in most cancers. Recently, methods have been developed to mine hidden information from histopathological slides using deep learning applied to scanned and digitized slides; deep learning comprises a collection of computational methods which learn patterns in data in order to make predictions. Such methods have been reported to be successful in a variety of cancers for predicting the presence of biomarkers such as driver mutations, tumour mutational burden, and microsatellite instability. This information could prove valuable to pathologists and oncologists in clinical decision making for cancer treatment and triage for in-depth sequencing. In addition to identifying molecular features, deep learning has been applied to predict prognosis and treatment response in certain cancers. Despite reported successes, many challenges remain before the clinical implementation of such diagnostic strategies in the clinical setting is possible. This review aims to outline recent developments in the field of deep learning for predicting molecular genetics from histopathological slides, as well as to highlight limitations and pitfalls of working with histopathology slides in deep learning.},
DOI = {10.3390/diagnostics11081406}
}






@Article{Hecht2020,
AUTHOR = {Hecht, Helge and Sarhan, Mhd Hasan and Popovici, Vlad},
TITLE = {Disentangled Autoencoder for Cross-Stain Feature Extraction in Pathology Image Analysis},
JOURNAL = {Applied Sciences},
VOLUME = {10},
YEAR = {2020},
NUMBER = {18},
ARTICLE-NUMBER = {6427},
URL = {https://www.mdpi.com/2076-3417/10/18/6427},
ISSN = {2076-3417},
ABSTRACT = {A novel deep autoencoder architecture is proposed for the analysis of histopathology images. Its purpose is to produce a disentangled latent representation in which the structure and colour information are confined to different subspaces so that stain-independent models may be learned. For this, we introduce two constraints on the representation which are implemented as a classifier and an adversarial discriminator. We show how they can be used for learning a latent representation across haematoxylin-eosin and a number of immune stains. Finally, we demonstrate the utility of the proposed representation in the context of matching image patches for registration applications and for learning a bag of visual words for whole slide image summarization.},
DOI = {10.3390/app10186427}
}





@article {Bruck2021,
	author = {Br{\"u}ck, Oscar E. and Lallukka-Br{\"u}ck, Susanna E. and Hohtari, Helena R. and Ianevski, Aleksandr and Ebeling, Freja T. and Kovanen, Panu E. and Kyt{\"o}l{\"a}, Soili I. and Aittokallio, Tero A. and Ramos, Pedro M. and Porkka, Kimmo V. and Mustjoki, Satu M.},
	title = {Machine Learning of Bone Marrow Histopathology Identifies Genetic and Clinical Determinants in Patients with MDS},
	volume = {2},
	number = {3},
	pages = {238--249},
	year = {2021},
	doi = {10.1158/2643-3230.BCD-20-0162},
	publisher = {American Association for Cancer Research Journals},
	abstract = {In myelodysplastic syndrome (MDS) and myeloproliferative neoplasm (MPN), bone marrow (BM) histopathology is assessed to identify dysplastic cellular morphology, cellularity, and blast excess. Yet, other morphologic findings may elude the human eye. We used convolutional neural networks to extract morphologic features from 236 MDS, 87 MDS/MPN, and 11 control BM biopsies. These features predicted genetic and cytogenetic aberrations, prognosis, age, and gender in multivariate regression models. Highest prediction accuracy was found for TET2 [area under the receiver operating curve (AUROC) = 0.94] and spliceosome mutations (0.89) and chromosome 7 monosomy (0.89). Mutation prediction probability correlated with variant allele frequency and number of affected genes per pathway, demonstrating the algorithms{\textquoteright} ability to identify relevant morphologic patterns. By converting regression models to texture and cellular composition, we reproduced the classical del(5q) MDS morphology consisting of hypolobulated megakaryocytes. In summary, this study highlights the potential of linking deep BM histopathology with genetics and clinical variables.Significance: Histopathology is elementary in the diagnostics of patients with MDS, but its high-dimensional data are underused. By elucidating the association of morphologic features with clinical variables and molecular genetics, this study highlights the vast potential of convolutional neural networks in understanding MDS pathology and how genetics is reflected in BM morphology.See related commentary by Elemento, p. 195.},
	issn = {2643-3230},
	URL = {https://bloodcancerdiscov.aacrjournals.org/content/2/3/238},
	eprint = {https://bloodcancerdiscov.aacrjournals.org/content/2/3/238.full.pdf},
	journal = {Blood Cancer Discovery}
}



@Article{Echle2021,
author={Echle, Amelie
and Rindtorff, Niklas Timon
and Brinker, Titus Josef
and Luedde, Tom
and Pearson, Alexander Thomas
and Kather, Jakob Nikolas},
title={Deep learning in cancer pathology: a new generation of clinical biomarkers},
journal={British Journal of Cancer},
year={2021},
month={Feb},
day={01},
volume={124},
number={4},
pages={686-696},
abstract={Clinical workflows in oncology rely on predictive and prognostic molecular biomarkers. However, the growing number of these complex biomarkers tends to increase the cost and time for decision-making in routine daily oncology practice; furthermore, biomarkers often require tumour tissue on top of routine diagnostic material. Nevertheless, routinely available tumour tissue contains an abundance of clinically relevant information that is currently not fully exploited. Advances in deep learning (DL), an artificial intelligence (AI) technology, have enabled the extraction of previously hidden information directly from routine histology images of cancer, providing potentially clinically useful information. Here, we outline emerging concepts of how DL can extract biomarkers directly from histology images and summarise studies of basic and advanced image analysis for cancer histology. Basic image analysis tasks include detection, grading and subtyping of tumour tissue in histology images; they are aimed at automating pathology workflows and consequently do not immediately translate into clinical decisions. Exceeding such basic approaches, DL has also been used for advanced image analysis tasks, which have the potential of directly affecting clinical decision-making processes. These advanced approaches include inference of molecular features, prediction of survival and end-to-end prediction of therapy response. Predictions made by such DL systems could simplify and enrich clinical decision-making, but require rigorous external validation in clinical settings.},
issn={1532-1827},
doi={10.1038/s41416-020-01122-x},
url={https://doi.org/10.1038/s41416-020-01122-x}
}



@Article{Jayapandian2021,
author={Jayapandian, Catherine P.
and Chen, Yijiang
and Janowczyk, Andrew R.
and Palmer, Matthew B.
and Cassol, Clarissa A.
and Sekulic, Miroslav
and Hodgin, Jeffrey B.
and Zee, Jarcy
and Hewitt, Stephen M.
and O'Toole, John
and Toro, Paula
and Sedor, John R.
and Barisoni, Laura
and Madabhushi, Anant
and Sedor, J.
and Dell, K.
and Schachere, M.
and Negrey, J.
and Lemley, K.
and Lim, E.
and Srivastava, T.
and Garrett, A.
and Sethna, C.
and Laurent, K.
and Appel, G.
and Toledo, M.
and Barisoni, L.
and Greenbaum, L.
and Wang, C.
and Kang, C.
and Adler, S.
and Nast, C.
and LaPage, J.
and Stroger Jr., John H.,
and Athavale, A.
and Itteera, M.
and Neu, A.
and Boynton, S.
and Fervenza, F.
and Hogan, M.
and Lieske, J.
and Chernitskiy, V.
and Kaskel, F.
and Kumar, N.
and Flynn, P.
and Kopp, J.
and Blake, J.
and Trachtman, H.
and Zhdanova, O.
and Modersitzki, F.
and Vento, S.
and Lafayette, R.
and Mehta, K.
and Gadegbeku, C.
and Johnstone, D.
and Quinn-Boyle, S.
and Cattran, D.
and Hladunewich, M.
and Reich, H.
and Ling, P.
and Romano, M.
and Fornoni, A.
and Bidot, C.
and Kretzler, M.
and Gipson, D.
and Williams, A.
and LaVigne, J.
and Derebail, V.
and Gibson, K.
and Froment, A.
and Grubbs, S.
and Holzman, L.
and Meyers, K.
and Kallem, K.
and Lalli, J.
and Sambandam, K.
and Wang, Z.
and Rogers, M.
and Jefferson, A.
and Hingorani, S.
and Tuttle, K.
and Bray, M.
and Kelton, M.
and Cooper, A.
and Freedman, B.
and Lin, J. J.},
title={Development and evaluation of deep learning{\&}{\#}x2013;based segmentation of histologic structures in the kidney cortex with multiple histologic stains},
journal={Kidney International},
year={2021},
month={Jan},
day={01},
publisher={Elsevier},
volume={99},
number={1},
pages={86-101},
issn={0085-2538},
doi={10.1016/j.kint.2020.07.044},
url={https://doi.org/10.1016/j.kint.2020.07.044}
}



@article {Bouteldja2021,
	author = {Bouteldja, Nassim and Klinkhammer, Barbara M. and B{\"u}low, Roman D. and Droste, Patrick and Otten, Simon W. and Freifrau von Stillfried, Saskia and Moellmann, Julia and Sheehan, Susan M. and Korstanje, Ron and Menzel, Sylvia and Bankhead, Peter and Mietsch, Matthias and Drummer, Charis and Lehrke, Michael and Kramann, Rafael and Floege, J{\"u}rgen and Boor, Peter and Merhof, Dorit},
	title = {Deep Learning{\textendash}Based Segmentation and Quantification in Experimental Kidney Histopathology},
	volume = {32},
	number = {1},
	pages = {52--68},
	year = {2021},
	doi = {10.1681/ASN.2020050597},
	publisher = {American Society of Nephrology},
	abstract = {Nephropathologic analyses provide important outcomes-related data in the animal model studies that are essential to understanding kidney disease pathophysiology. In this work, the authors used a deep learning technique, the convolutional neural network, as a multiclass histology segmentation tool to evaluate kidney disease in animal models. This enabled a rapid, automated, high-performance segmentation of digital whole-slide images of periodic acid{\textendash}Schiff{\textendash}stained kidney tissues, allowing high-throughput quantitative and comparative analyses in multiple murine disease models and other species. The convolutional neural network also performed well in evaluating patient samples, providing a translational bridge between preclinical and clinical research. Extracted quantitative morphologic features closely correlated with standard morphometric measurements. Deep learning{\textendash}based segmentation in experimental renal pathology is a promising step toward reproducible, unbiased, and high-throughput quantitative digital nephropathology.Background Nephropathologic analyses provide important outcomes-related data in experiments with the animal models that are essential for understanding kidney disease pathophysiology. Precision medicine increases the demand for quantitative, unbiased, reproducible, and efficient histopathologic analyses, which will require novel high-throughput tools. A deep learning technique, the convolutional neural network, is increasingly applied in pathology because of its high performance in tasks like histology segmentation.Methods We investigated use of a convolutional neural network architecture for accurate segmentation of periodic acid{\textendash}Schiff-stained kidney tissue from healthy mice and five murine disease models and from other species used in preclinical research. We trained the convolutional neural network to segment six major renal structures: glomerular tuft, glomerulus including Bowman{\textquoteright}s capsule, tubules, arteries, arterial lumina, and veins. To achieve high accuracy, we performed a large number of expert-based annotations, 72,722 in total.Results Multiclass segmentation performance was very high in all disease models. The convolutional neural network allowed high-throughput and large-scale, quantitative and comparative analyses of various models. In disease models, computational feature extraction revealed interstitial expansion, tubular dilation and atrophy, and glomerular size variability. Validation showed a high correlation of findings with current standard morphometric analysis. The convolutional neural network also showed high performance in other species used in research{\textemdash}including rats, pigs, bears, and marmosets{\textemdash}as well as in humans, providing a translational bridge between preclinical and clinical studies.Conclusions We developed a deep learning algorithm for accurate multiclass segmentation of digital whole-slide images of periodic acid{\textendash}Schiff-stained kidneys from various species and renal disease models. This enables reproducible quantitative histopathologic analyses in preclinical models that also might be applicable to clinical studies.},
	issn = {1046-6673},
	URL = {https://jasn.asnjournals.org/content/32/1/52},
	eprint = {https://jasn.asnjournals.org/content/32/1/52.full.pdf},
	journal = {Journal of the American Society of Nephrology}
}



@article {Hermsen2019,
	author = {Hermsen, Meyke and de Bel, Thomas and den Boer, Marjolijn and Steenbergen, Eric J. and Kers, Jesper and Florquin, Sandrine and Roelofs, Joris J. T. H. and Stegall, Mark D. and Alexander, Mariam P. and Smith, Byron H. and Smeets, Bart and Hilbrands, Luuk B. and van der Laak, Jeroen A. W. M.},
	title = {Deep Learning{\textendash}Based Histopathologic Assessment of Kidney Tissue},
	volume = {30},
	number = {10},
	pages = {1968--1979},
	year = {2019},
	doi = {10.1681/ASN.2019020144},
	publisher = {American Society of Nephrology},
	abstract = {Histopathologic assessment of kidney tissue currently relies on manual scoring or traditional image-processing techniques to quantify and classify tissue features, time-consuming approaches that have limited reproducibility. The authors present an alternative approach, featuring a convolutional neural network for multiclass segmentation of kidney tissue in sections stained by periodic acid{\textendash}Schiff. Their findings demonstrate applicability of convolutional neural networks for tissue from multiple centers, for biopsies and nephrectomy samples, and for the analysis of both healthy and pathologic tissues. In addition, they validated the network{\textquoteright}s results with components from the Banff classification system. Their convolutional neural network may have utility for quantitative studies involving kidney histopathology across centers and potential for application in routine diagnostics.Background The development of deep neural networks is facilitating more advanced digital analysis of histopathologic images. We trained a convolutional neural network for multiclass segmentation of digitized kidney tissue sections stained with periodic acid{\textendash}Schiff (PAS).Methods We trained the network using multiclass annotations from 40 whole-slide images of stained kidney transplant biopsies and applied it to four independent data sets. We assessed multiclass segmentation performance by calculating Dice coefficients for ten tissue classes on ten transplant biopsies from the Radboud University Medical Center in Nijmegen, The Netherlands, and on ten transplant biopsies from an external center for validation. We also fully segmented 15 nephrectomy samples and calculated the network{\textquoteright}s glomerular detection rates and compared network-based measures with visually scored histologic components (Banff classification) in 82 kidney transplant biopsies.Results The weighted mean Dice coefficients of all classes were 0.80 and 0.84 in ten kidney transplant biopsies from the Radboud center and the external center, respectively. The best segmented class was {\textquotedblleft}glomeruli{\textquotedblright} in both data sets (Dice coefficients, 0.95 and 0.94, respectively), followed by {\textquotedblleft}tubuli combined{\textquotedblright} and {\textquotedblleft}interstitium.{\textquotedblright} The network detected 92.7\% of all glomeruli in nephrectomy samples, with 10.4\% false positives. In whole transplant biopsies, the mean intraclass correlation coefficient for glomerular counting performed by pathologists versus the network was 0.94. We found significant correlations between visually scored histologic components and network-based measures.Conclusions This study presents the first convolutional neural network for multiclass segmentation of PAS-stained nephrectomy samples and transplant biopsies. Our network may have utility for quantitative studies involving kidney histopathology across centers and provide opportunities for deep learning applications in routine diagnostics.},
	issn = {1046-6673},
	URL = {https://jasn.asnjournals.org/content/30/10/1968},
	eprint = {https://jasn.asnjournals.org/content/30/10/1968.full.pdf},
	journal = {Journal of the American Society of Nephrology}
}



@article{Kolachalama2018,
title = {Association of Pathological Fibrosis With Renal Survival Using Deep Neural Networks},
journal = {Kidney International Reports},
volume = {3},
number = {2},
pages = {464-475},
year = {2018},
issn = {2468-0249},
doi = {https://doi.org/10.1016/j.ekir.2017.11.002},
url = {https://www.sciencedirect.com/science/article/pii/S2468024917304370},
author = {Vijaya B. Kolachalama and Priyamvada Singh and Christopher Q. Lin and Dan Mun and Mostafa E. Belghasem and Joel M. Henderson and Jean M. Francis and David J. Salant and Vipul C. Chitalia},
keywords = {histology, machine learning, renal fibrosis, renal survival},
abstract = {Introduction
Chronic kidney damage is routinely assessed semiquantitatively by scoring the amount of fibrosis and tubular atrophy in a renal biopsy sample. Although image digitization and morphometric techniques can better quantify the extent of histologic damage, we need more widely applicable ways to stratify kidney disease severity.
Methods
We leveraged a deep learning architecture to better associate patient-specific histologic images with clinical phenotypes (training classes) including chronic kidney disease (CKD) stage, serum creatinine, and nephrotic-range proteinuria at the time of biopsy, and 1-, 3-, and 5-year renal survival. Trichrome-stained images processed from renal biopsy samples were collected on 171 patients treated at the Boston Medical Center from 2009 to 2012. Six convolutional neural network (CNN) models were trained using these images as inputs and the training classes as outputs, respectively. For comparison, we also trained separate classifiers using the pathologist-estimated fibrosis score (PEFS) as input and the training classes as outputs, respectively.
Results
CNN models outperformed PEFS across the classification tasks. Specifically, the CNN model predicted the CKD stage more accurately than the PEFS model (κ = 0.519 vs. 0.051). For creatinine models, the area under curve (AUC) was 0.912 (CNN) versus 0.840 (PEFS). For proteinuria models, AUC was 0.867 (CNN) versus 0.702 (PEFS). AUC values for the CNN models for 1-, 3-, and 5-year renal survival were 0.878, 0.875, and 0.904, respectively, whereas the AUC values for PEFS model were 0.811, 0.800, and 0.786, respectively.
Conclusion
The study demonstrates a proof of principle that deep learning can be applied to routine renal biopsy images.}
}


@Article{Esteva2017,
author={Esteva, Andre
and Kuprel, Brett
and Novoa, Roberto A.
and Ko, Justin
and Swetter, Susan M.
and Blau, Helen M.
and Thrun, Sebastian},
title={Dermatologist-level classification of skin cancer with deep neural networks},
journal={Nature},
year={2017},
month={Feb},
day={01},
volume={542},
number={7639},
pages={115-118},
abstract={An artificial intelligence trained to classify images of skin lesions as benign lesions or malignant skin cancers achieves the accuracy of board-certified dermatologists.},
issn={1476-4687},
doi={10.1038/nature21056},
url={https://doi.org/10.1038/nature21056}
}



@Article{Coudray2018,
author={Coudray, Nicolas
and Ocampo, Paolo Santiago
and Sakellaropoulos, Theodore
and Narula, Navneet
and Snuderl, Matija
and Feny{\"o}, David
and Moreira, Andre L.
and Razavian, Narges
and Tsirigos, Aristotelis},
title={Classification and mutation prediction from non--small cell lung cancer histopathology images using deep learning},
journal={Nature Medicine},
year={2018},
month={Oct},
day={01},
volume={24},
number={10},
pages={1559-1567},
abstract={Visual inspection of histopathology slides is one of the main methods used by pathologists to assess the stage, type and subtype of lung tumors. Adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC) are the most prevalent subtypes of lung cancer, and their distinction requires visual inspection by an experienced pathologist. In this study, we trained a deep convolutional neural network (inception v3) on whole-slide images obtained from The Cancer Genome Atlas to accurately and automatically classify them into LUAD, LUSC or normal lung tissue. The performance of our method is comparable to that of pathologists, with an average area under the curve (AUC) of 0.97. Our model was validated on independent datasets of frozen tissues, formalin-fixed paraffin-embedded tissues and biopsies. Furthermore, we trained the network to predict the ten most commonly mutated genes in LUAD. We found that six of them---STK11, EGFR, FAT1, SETBP1, KRAS and TP53---can be predicted from pathology images, with AUCs from 0.733 to 0.856 as measured on a held-out population. These findings suggest that deep-learning models can assist pathologists in the detection of cancer subtype or gene mutations. Our approach can be applied to any cancer type, and the code is available at https://github.com/ncoudray/DeepPATH.},
issn={1546-170X},
doi={10.1038/s41591-018-0177-5},
url={https://doi.org/10.1038/s41591-018-0177-5}
}



@Article{Campanella2019,
author={Campanella, Gabriele
and Hanna, Matthew G.
and Geneslaw, Luke
and Miraflor, Allen
and Werneck Krauss Silva, Vitor
and Busam, Klaus J.
and Brogi, Edi
and Reuter, Victor E.
and Klimstra, David S.
and Fuchs, Thomas J.},
title={Clinical-grade computational pathology using weakly supervised deep learning on whole slide images},
journal={Nature Medicine},
year={2019},
month={Aug},
day={01},
volume={25},
number={8},
pages={1301-1309},
abstract={The development of decision support systems for pathology and their deployment in clinical practice have been hindered by the need for large manually annotated datasets. To overcome this problem, we present a multiple instance learning-based deep learning system that uses only the reported diagnoses as labels for training, thereby avoiding expensive and time-consuming pixel-wise manual annotations. We evaluated this framework at scale on a dataset of 44,732 whole slide images from 15,187 patients without any form of data curation. Tests on prostate cancer, basal cell carcinoma and breast cancer metastases to axillary lymph nodes resulted in areas under the curve above 0.98 for all cancer types. Its clinical application would allow pathologists to exclude 65--75{\%} of slides while retaining 100{\%} sensitivity. Our results show that this system has the ability to train accurate classification models at unprecedented scale, laying the foundation for the deployment of computational decision support systems in clinical practice.},
issn={1546-170X},
doi={10.1038/s41591-019-0508-1},
url={https://doi.org/10.1038/s41591-019-0508-1}
}



@Article{Kather2019,
author={Kather, Jakob Nikolas
and Pearson, Alexander T.
and Halama, Niels
and J{\"a}ger, Dirk
and Krause, Jeremias
and Loosen, Sven H.
and Marx, Alexander
and Boor, Peter
and Tacke, Frank
and Neumann, Ulf Peter
and Grabsch, Heike I.
and Yoshikawa, Takaki
and Brenner, Hermann
and Chang-Claude, Jenny
and Hoffmeister, Michael
and Trautwein, Christian
and Luedde, Tom},
title={Deep learning can predict microsatellite instability directly from histology in gastrointestinal cancer},
journal={Nature Medicine},
year={2019},
month={Jul},
day={01},
volume={25},
number={7},
pages={1054-1056},
abstract={Microsatellite instability determines whether patients with gastrointestinal cancer respond exceptionally well to immunotherapy. However, in clinical practice, not every patient is tested for MSI, because this requires additional genetic or immunohistochemical tests. Here we show that deep residual learning can predict MSI directly from H{\&}E histology, which is ubiquitously available. This approach has the potential to provide immunotherapy to a much broader subset of patients with gastrointestinal cancer.},
issn={1546-170X},
doi={10.1038/s41591-019-0462-y},
url={https://doi.org/10.1038/s41591-019-0462-y}
}



@Article{Zhang2019,
author={Zhang, Zizhao
and Chen, Pingjun
and McGough, Mason
and Xing, Fuyong
and Wang, Chunbao
and Bui, Marilyn
and Xie, Yuanpu
and Sapkota, Manish
and Cui, Lei
and Dhillon, Jasreman
and Ahmad, Nazeel
and Khalil, Farah K.
and Dickinson, Shohreh I.
and Shi, Xiaoshuang
and Liu, Fujun
and Su, Hai
and Cai, Jinzheng
and Yang, Lin},
title={Pathologist-level interpretable whole-slide cancer diagnosis with deep learning},
journal={Nature Machine Intelligence},
year={2019},
month={May},
day={01},
volume={1},
number={5},
pages={236-245},
abstract={Diagnostic pathology is the foundation and gold standard for identifying carcinomas. However, high inter-observer variability substantially affects productivity in routine pathology and is especially ubiquitous in diagnostician-deficient medical centres. Despite rapid growth in computer-aided diagnosis (CAD), the application of whole-slide pathology diagnosis remains impractical. Here, we present a novel pathology whole-slide diagnosis method, powered by artificial intelligence, to address the lack of interpretable diagnosis. The proposed method masters the ability to automate the human-like diagnostic reasoning process and translate gigapixels directly to a series of interpretable predictions, providing second opinions and thereby encouraging consensus in clinics. Moreover, using 913 collected examples of whole-slide data representing patients with bladder cancer, we show that our method matches the performance of 17 pathologists in the diagnosis of urothelial carcinoma. We believe that our method provides an innovative and reliable means for making diagnostic suggestions and can be deployed at low cost as next-generation, artificial intelligence-enhanced CAD technology for use in diagnostic pathology.},
issn={2522-5839},
doi={10.1038/s42256-019-0052-1},
url={https://doi.org/10.1038/s42256-019-0052-1}
}



@Article{Tabibu2019,
author={Tabibu, Sairam
and Vinod, P. K.
and Jawahar, C. V.},
title={Pan-Renal Cell Carcinoma classification and survival prediction from histopathology images using deep learning},
journal={Scientific Reports},
year={2019},
month={Jul},
day={19},
volume={9},
number={1},
pages={10509},
abstract={Histopathological images contain morphological markers of disease progression that have diagnostic and predictive values. In this study, we demonstrate how deep learning framework can be used for an automatic classification of Renal Cell Carcinoma (RCC) subtypes, and for identification of features that predict survival outcome from digital histopathological images. Convolutional neural networks (CNN's) trained on whole-slide images distinguish clear cell and chromophobe RCC from normal tissue with a classification accuracy of 93.39{\%} and 87.34{\%}, respectively. Further, a CNN trained to distinguish clear cell, chromophobe and papillary RCC achieves a classification accuracy of 94.07{\%}. Here, we introduced a novel support vector machine-based method that helped to break the multi-class classification task into multiple binary classification tasks which not only improved the performance of the model but also helped to deal with data imbalance. Finally, we extracted the morphological features from high probability tumor regions identified by the CNN to predict patient survival outcome of most common clear cell RCC. The generated risk index based on both tumor shape and nuclei features are significantly associated with patient survival outcome. These results highlight that deep learning can play a role in both cancer diagnosis and prognosis.},
issn={2045-2322},
doi={10.1038/s41598-019-46718-3},
url={https://doi.org/10.1038/s41598-019-46718-3}
}



@article{Ehteshami2017,
    author = {Ehteshami Bejnordi, Babak and Veta, Mitko and Johannes van Diest, Paul and van Ginneken, Bram and Karssemeijer, Nico and Litjens, Geert and van der Laak, Jeroen A. W. M. and and the CAMELYON16 Consortium},
    title = "{Diagnostic Assessment of Deep Learning Algorithms for Detection of Lymph Node Metastases in Women With Breast Cancer}",
    journal = {JAMA},
    volume = {318},
    number = {22},
    pages = {2199-2210},
    year = {2017},
    month = {12},
    abstract = "{Application of deep learning algorithms to whole-slide pathology images can potentially improve diagnostic accuracy and efficiency.Assess the performance of automated deep learning algorithms at detecting metastases in hematoxylin and eosin–stained tissue sections of lymph nodes of women with breast cancer and compare it with pathologists’ diagnoses in a diagnostic setting.Researcher challenge competition (CAMELYON16) to develop automated solutions for detecting lymph node metastases (November 2015-November 2016). A training data set of whole-slide images from 2 centers in the Netherlands with (n = 110) and without (n = 160) nodal metastases verified by immunohistochemical staining were provided to challenge participants to build algorithms. Algorithm performance was evaluated in an independent test set of 129 whole-slide images (49 with and 80 without metastases). The same test set of corresponding glass slides was also evaluated by a panel of 11 pathologists with time constraint (WTC) from the Netherlands to ascertain likelihood of nodal metastases for each slide in a flexible 2-hour session, simulating routine pathology workflow, and by 1 pathologist without time constraint (WOTC).Deep learning algorithms submitted as part of a challenge competition or pathologist interpretation.The presence of specific metastatic foci and the absence vs presence of lymph node metastasis in a slide or image using receiver operating characteristic curve analysis. The 11 pathologists participating in the simulation exercise rated their diagnostic confidence as definitely normal, probably normal, equivocal, probably tumor, or definitely tumor.The area under the receiver operating characteristic curve (AUC) for the algorithms ranged from 0.556 to 0.994. The top-performing algorithm achieved a lesion-level, true-positive fraction comparable with that of the pathologist WOTC (72.4\\% [95\\% CI, 64.3\\%-80.4\\%]) at a mean of 0.0125 false-positives per normal whole-slide image. For the whole-slide image classification task, the best algorithm (AUC, 0.994 [95\\% CI, 0.983-0.999]) performed significantly better than the pathologists WTC in a diagnostic simulation (mean AUC, 0.810 [range, 0.738-0.884]; P \\&lt; .001). The top 5 algorithms had a mean AUC that was comparable with the pathologist interpreting the slides in the absence of time constraints (mean AUC, 0.960 [range, 0.923-0.994] for the top 5 algorithms vs 0.966 [95\\% CI, 0.927-0.998] for the pathologist WOTC).In the setting of a challenge competition, some deep learning algorithms achieved better diagnostic performance than a panel of 11 pathologists participating in a simulation exercise designed to mimic routine pathology workflow; algorithm performance was comparable with an expert pathologist interpreting whole-slide images without time constraints. Whether this approach has clinical utility will require evaluation in a clinical setting.}",
    issn = {0098-7484},
    doi = {10.1001/jama.2017.14585},
    url = {https://doi.org/10.1001/jama.2017.14585},
    eprint = {https://jamanetwork.com/journals/jama/articlepdf/2665774/jama\_ehteshami\_bejnordi\_2017\_oi\_170113.pdf},
}





@Article{Bera2019,
author={Bera, Kaustav
and Schalper, Kurt A.
and Rimm, David L.
and Velcheti, Vamsidhar
and Madabhushi, Anant},
title={Artificial intelligence in digital pathology --- new tools for diagnosis and precision oncology},
journal={Nature Reviews Clinical Oncology},
year={2019},
month={Nov},
day={01},
volume={16},
number={11},
pages={703-715},
abstract={In the past decade, advances in precision oncology have resulted in an increased demand for predictive assays that enable the selection and stratification of patients for treatment. The enormous divergence of signalling and transcriptional networks mediating the crosstalk between cancer, stromal and immune cells complicates the development of functionally relevant biomarkers based on a single gene or protein. However, the result of these complex processes can be uniquely captured in the morphometric features of stained tissue specimens. The possibility of digitizing whole-slide images of tissue has led to the advent of artificial intelligence (AI) and machine learning tools in digital pathology, which enable mining of subvisual morphometric phenotypes and might, ultimately, improve patient management. In this Perspective, we critically evaluate various AI-based computational approaches for digital pathology, focusing on deep neural networks and `hand-crafted' feature-based methodologies. We aim to provide a broad framework for incorporating AI and machine learning tools into clinical oncology, with an emphasis on biomarker development. We discuss some of the challenges relating to the use of AI, including the need for well-curated validation datasets, regulatory approval and fair reimbursement strategies. Finally, we present potential future opportunities for precision oncology.},
issn={1759-4782},
doi={10.1038/s41571-019-0252-y},
url={https://doi.org/10.1038/s41571-019-0252-y}
}



@Article{Yamamoto2019,
author={Yamamoto, Yoichiro
and Tsuzuki, Toyonori
and Akatsuka, Jun
and Ueki, Masao
and Morikawa, Hiromu
and Numata, Yasushi
and Takahara, Taishi
and Tsuyuki, Takuji
and Tsutsumi, Kotaro
and Nakazawa, Ryuto
and Shimizu, Akira
and Maeda, Ichiro
and Tsuchiya, Shinichi
and Kanno, Hiroyuki
and Kondo, Yukihiro
and Fukumoto, Manabu
and Tamiya, Gen
and Ueda, Naonori
and Kimura, Go},
title={Automated acquisition of explainable knowledge from unannotated histopathology images},
journal={Nature Communications},
year={2019},
month={Dec},
day={18},
volume={10},
number={1},
pages={5642},
abstract={Deep learning algorithms have been successfully used in medical image classification. In the next stage, the technology of acquiring explainable knowledge from medical images is highly desired. Here we show that deep learning algorithm enables automated acquisition of explainable features from diagnostic annotation-free histopathology images. We compare the prediction accuracy of prostate cancer recurrence using our algorithm-generated features with that of diagnosis by expert pathologists using established criteria on 13,188 whole-mount pathology images consisting of over 86 billion image patches. Our method not only reveals findings established by humans but also features that have not been recognized, showing higher accuracy than human in prognostic prediction. Combining both our algorithm-generated features and human-established criteria predicts the recurrence more accurately than using either method alone. We confirm robustness of our method using external validation datasets including 2276 pathology images. This study opens up fields of machine learning analysis for discovering uncharted knowledge.},
issn={2041-1723},
doi={10.1038/s41467-019-13647-8},
url={https://doi.org/10.1038/s41467-019-13647-8}
}



@article {Tsang2018,
article_type = {journal},
title = {High-quality ultrastructural preservation using cryofixation for 3D electron microscopy of genetically labeled tissues},
author = {Tsang, Tin Ki and Bushong, Eric A and Boassa, Daniela and Hu, Junru and Romoli, Benedetto and Phan, Sebastien and Dulcis, Davide and Su, Chih-Ying and Ellisman, Mark H},
editor = {Helmstaedter, Moritz},
volume = 7,
year = 2018,
month = {may},
pub_date = {2018-05-11},
pages = {e35524},
citation = {eLife 2018;7:e35524},
doi = {10.7554/eLife.35524},
url = {https://doi.org/10.7554/eLife.35524},
abstract = {Electron microscopy (EM) offers unparalleled power to study cell substructures at the nanoscale. Cryofixation by high-pressure freezing offers optimal morphological preservation, as it captures cellular structures instantaneously in their near-native state. However, the applicability of cryofixation is limited by its incompatibility with diaminobenzidine labeling using genetic EM tags and the high-contrast \textit{en bloc} staining required for serial block-face scanning electron microscopy (SBEM). In addition, it is challenging to perform correlated light and electron microscopy (CLEM) with cryofixed samples. Consequently, these powerful methods cannot be applied to address questions requiring optimal morphological preservation. Here, we developed an approach that overcomes these limitations; it enables genetically labeled, cryofixed samples to be characterized with SBEM and 3D CLEM. Our approach is broadly applicable, as demonstrated in cultured cells, \textit{Drosophila} olfactory organ and mouse brain. This optimization exploits the potential of cryofixation, allowing for quality ultrastructural preservation for diverse EM applications.},
keywords = {cryofixation by high pressure freezing, APEX2, CryoChem, genetic labeling, correlated light and electron microscopy, serial block-face scanning electron microscopy},
journal = {eLife},
issn = {2050-084X},
publisher = {eLife Sciences Publications, Ltd},
}



@Article{Diao2021,
author={Diao, James A.
and Wang, Jason K.
and Chui, Wan Fung
and Mountain, Victoria
and Gullapally, Sai Chowdary
and Srinivasan, Ramprakash
and Mitchell, Richard N.
and Glass, Benjamin
and Hoffman, Sara
and Rao, Sudha K.
and Maheshwari, Chirag
and Lahiri, Abhik
and Prakash, Aaditya
and McLoughlin, Ryan
and Kerner, Jennifer K.
and Resnick, Murray B.
and Montalto, Michael C.
and Khosla, Aditya
and Wapinski, Ilan N.
and Beck, Andrew H.
and Elliott, Hunter L.
and Taylor-Weiner, Amaro},
title={Human-interpretable image features derived from densely mapped cancer pathology slides predict diverse molecular phenotypes},
journal={Nature Communications},
year={2021},
month={Mar},
day={12},
volume={12},
number={1},
pages={1613},
abstract={Computational methods have made substantial progress in improving the accuracy and throughput of pathology workflows for diagnostic, prognostic, and genomic prediction. Still, lack of interpretability remains a significant barrier to clinical integration. We present an approach for predicting clinically-relevant molecular phenotypes from whole-slide histopathology images using human-interpretable image features (HIFs). Our method leverages >1.6 million annotations from board-certified pathologists across >5700 samples to train deep learning models for cell and tissue classification that can exhaustively map whole-slide images at two and four micron-resolution. Cell- and tissue-type model outputs are combined into 607 HIFs that quantify specific and biologically-relevant characteristics across five cancer types. We demonstrate that these HIFs correlate with well-known markers of the tumor microenvironment and can predict diverse molecular signatures (AUROC 0.601--0.864), including expression of four immune checkpoint proteins and homologous recombination deficiency, with performance comparable to `black-box' methods. Our HIF-based approach provides a comprehensive, quantitative, and interpretable window into the composition and spatial architecture of the tumor microenvironment.},
issn={2041-1723},
doi={10.1038/s41467-021-21896-9},
url={https://doi.org/10.1038/s41467-021-21896-9}
}



@article{Srinidhi2021,
title = {Deep neural network models for computational histopathology: A survey},
journal = {Medical Image Analysis},
volume = {67},
pages = {101813},
year = {2021},
issn = {1361-8415},
doi = {https://doi.org/10.1016/j.media.2020.101813},
url = {https://www.sciencedirect.com/science/article/pii/S1361841520301778},
author = {Chetan L. Srinidhi and Ozan Ciga and Anne L. Martel},
keywords = {Deep learning, Convolutional neural networks, Computational histopathology, Digital pathology, Histology image analysis, Survey, Review},
abstract = {Histopathological images contain rich phenotypic information that can be used to monitor underlying mechanisms contributing to disease progression and patient survival outcomes. Recently, deep learning has become the mainstream methodological choice for analyzing and interpreting histology images. In this paper, we present a comprehensive review of state-of-the-art deep learning approaches that have been used in the context of histopathological image analysis. From the survey of over 130 papers, we review the field’s progress based on the methodological aspect of different machine learning strategies such as supervised, weakly supervised, unsupervised, transfer learning and various other sub-variants of these methods. We also provide an overview of deep learning based survival models that are applicable for disease-specific prognosis tasks. Finally, we summarize several existing open datasets and highlight critical challenges and limitations with current deep learning approaches, along with possible avenues for future research.}
}


@article{WANG2019,
title = {Pathology Image Analysis Using Segmentation Deep Learning Algorithms},
journal = {The American Journal of Pathology},
volume = {189},
number = {9},
pages = {1686-1698},
year = {2019},
issn = {0002-9440},
doi = {https://doi.org/10.1016/j.ajpath.2019.05.007},
url = {https://www.sciencedirect.com/science/article/pii/S0002944018311210},
author = {Shidan Wang and Donghan M. Yang and Ruichen Rong and Xiaowei Zhan and Guanghua Xiao},
abstract = {With the rapid development of image scanning techniques and visualization software, whole slide imaging (WSI) is becoming a routine diagnostic method. Accelerating clinical diagnosis from pathology images and automating image analysis efficiently and accurately remain significant challenges. Recently, deep learning algorithms have shown great promise in pathology image analysis, such as in tumor region identification, metastasis detection, and patient prognosis. Many machine learning algorithms, including convolutional neural networks, have been proposed to automatically segment pathology images. Among these algorithms, segmentation deep learning algorithms such as fully convolutional networks stand out for their accuracy, computational efficiency, and generalizability. Thus, deep learning–based pathology image segmentation has become an important tool in WSI analysis. In this review, the pathology image segmentation process using deep learning algorithms is described in detail. The goals are to provide quick guidance for implementing deep learning into pathology image analysis and to provide some potential ways of further improving segmentation performance. Although there have been previous reviews on using machine learning methods in digital pathology image analysis, this is the first in-depth review of the applications of deep learning algorithms for segmentation in WSI analysis.}
}


@Article{vanderLaak2021,
author={van der Laak, Jeroen
and Litjens, Geert
and Ciompi, Francesco},
title={Deep learning in histopathology: the path to the clinic},
journal={Nature Medicine},
year={2021},
month={May},
day={01},
volume={27},
number={5},
pages={775-784},
abstract={Machine learning techniques have great potential to improve medical diagnostics, offering ways to improve accuracy, reproducibility and speed, and to ease workloads for clinicians. In the field of histopathology, deep learning algorithms have been developed that perform similarly to trained pathologists for tasks such as tumor detection and grading. However, despite these promising results, very few algorithms have reached clinical implementation, challenging the balance between hope and hype for these new techniques. This Review provides an overview of the current state of the field, as well as describing the challenges that still need to be addressed before artificial intelligence in histopathology can achieve clinical value.},
issn={1546-170X},
doi={10.1038/s41591-021-01343-4},
url={https://doi.org/10.1038/s41591-021-01343-4}
}



@Article{vonChamier2021,
author={von Chamier, Lucas
and Laine, Romain F.
and Jukkala, Johanna
and Spahn, Christoph
and Krentzel, Daniel
and Nehme, Elias
and Lerche, Martina
and Hern{\'a}ndez-P{\'e}rez, Sara
and Mattila, Pieta K.
and Karinou, Eleni
and Holden, S{\'e}amus
and Solak, Ahmet Can
and Krull, Alexander
and Buchholz, Tim-Oliver
and Jones, Martin L.
and Royer, Lo{\"i}c A.
and Leterrier, Christophe
and Shechtman, Yoav
and Jug, Florian
and Heilemann, Mike
and Jacquemet, Guillaume
and Henriques, Ricardo},
title={Democratising deep learning for microscopy with ZeroCostDL4Mic},
journal={Nature Communications},
year={2021},
month={Apr},
day={15},
volume={12},
number={1},
pages={2276},
abstract={Deep Learning (DL) methods are powerful analytical tools for microscopy and can outperform conventional image processing pipelines. Despite the enthusiasm and innovations fuelled by DL technology, the need to access powerful and compatible resources to train DL networks leads to an accessibility barrier that novice users often find difficult to overcome. Here, we present ZeroCostDL4Mic, an entry-level platform simplifying DL access by leveraging the free, cloud-based computational resources of Google Colab. ZeroCostDL4Mic allows researchers with no coding expertise to train and apply key DL networks to perform tasks including segmentation (using U-Net and StarDist), object detection (using YOLOv2), denoising (using CARE and Noise2Void), super-resolution microscopy (using Deep-STORM), and image-to-image translation (using Label-free prediction - fnet, pix2pix and CycleGAN). Importantly, we provide suitable quantitative tools for each network to evaluate model performance, allowing model optimisation. We demonstrate the application of the platform to study multiple biological processes.},
issn={2041-1723},
doi={10.1038/s41467-021-22518-0},
url={https://doi.org/10.1038/s41467-021-22518-0}
}



@Article{Huo2021,
author={Huo, Yuankai
and Deng, Ruining
and Liu, Quan
and Fogo, Agnes B.
and Yang, Haichun},
title={AI applications in renal pathology},
journal={Kidney International},
year={2021},
month={Jun},
day={01},
publisher={Elsevier},
volume={99},
number={6},
pages={1309-1320},
issn={0085-2538},
doi={10.1016/j.kint.2021.01.015},
url={https://doi.org/10.1016/j.kint.2021.01.015}
}



@InProceedings{Ronneberger2015,
author="Ronneberger, Olaf
and Fischer, Philipp
and Brox, Thomas",
editor="Navab, Nassir
and Hornegger, Joachim
and Wells, William M.
and Frangi, Alejandro F.",
title="U-Net: Convolutional Networks for Biomedical Image Segmentation",
booktitle="Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2015",
year="2015",
publisher="Springer International Publishing",
address="Cham",
pages="234--241",
abstract="There is large consent that successful training of deep networks requires many thousand annotated training samples. In this paper, we present a network and training strategy that relies on the strong use of data augmentation to use the available annotated samples more efficiently. The architecture consists of a contracting path to capture context and a symmetric expanding path that enables precise localization. We show that such a network can be trained end-to-end from very few images and outperforms the prior best method (a sliding-window convolutional network) on the ISBI challenge for segmentation of neuronal structures in electron microscopic stacks. Using the same network trained on transmitted light microscopy images (phase contrast and DIC) we won the ISBI cell tracking challenge 2015 in these categories by a large margin. Moreover, the network is fast. Segmentation of a 512x512 image takes less than a second on a recent GPU. The full implementation (based on Caffe) and the trained networks are available at http://lmb.informatik.uni-freiburg.de/people/ronneber/u-net.",
isbn="978-3-319-24574-4"
}



@article{KOGA2017,
  title={<b>Integrative method for three-dimensional imaging of the entire Golgi apparatus by combining thiamine pyrophosphatase cytochemistry and array tomography using backscattered electron-mode scanning electron micr</b><b>oscopy </b>},
  author={Daisuke KOGA and Satoshi KUSUMI and Tatsuo USHIKI and Tsuyoshi WATANABE},
  journal={Biomedical Research},
  volume={38},
  number={5},
  pages={285-296},
  year={2017},
  doi={10.2220/biomedres.38.285}
}


@article{Mayhew2015,
title = {Morphomics: An integral part of systems biology of the human placenta},
journal = {Placenta},
volume = {36},
number = {4},
pages = {329-340},
year = {2015},
issn = {0143-4004},
doi = {https://doi.org/10.1016/j.placenta.2015.01.001},
url = {https://www.sciencedirect.com/science/article/pii/S014340041500003X},
author = {T.M. Mayhew},
keywords = {Placenta, Systems biology, Morphomics, Nanomorphomics, Quantification},
abstract = {Introduction
The placenta is a transient organ the functioning of which has health consequences far beyond the embryo/fetus. Understanding the biology of any system (organ, organism, single cell, etc) requires a comprehensive and inclusive approach which embraces all the biomedical disciplines and ‘omic’ technologies and then integrates information obtained from all of them. Among the latest ‘omics’ is morphomics. The terms morphome and morphomics have been applied incoherently in biology and biomedicine but, recently, they have been given clear and widescale definitions.
Methods
Morphomics is placed in the context of other ‘omics’ and its pertinent technologies and tools for sampling and quantitation are reviewed. Emphasis is accorded to the importance of random sampling principles in systems biology and the value of combining 3D quantification with alternative imaging techniques to advance knowledge and understanding of the human placental morphome.
Results and conclusions
By analogy to other ‘omes’, the morphome is the totality of morphological features within a system and morphomics is the systematic study of those structures. Information about structure is required at multiple levels of resolution in order to understand better the processes by which a given system alters with time, experimental treatment or environmental insult. Therefore, morphomics research includes all imaging techniques at all levels of achievable resolution from gross anatomy and medical imaging, via optical and electron microscopy, to molecular characterisation. Quantification is an important element of all ‘omics’ studies and, because biological systems exist and operate in 3-dimensional (3D) space, precise descriptions of form, content and spatial relationships require the quantification of structure in 3D. These considerations are relevant to future study contributions to the Human Placenta Project.}
}


@InProceedings{Cire2013,
author="Cire{\c{s}}an, Dan C.
and Giusti, Alessandro
and Gambardella, Luca M.
and Schmidhuber, J{\"u}rgen",
editor="Mori, Kensaku
and Sakuma, Ichiro
and Sato, Yoshinobu
and Barillot, Christian
and Navab, Nassir",
title="Mitosis Detection in Breast Cancer Histology Images with Deep Neural Networks",
booktitle="Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2013",
year="2013",
publisher="Springer Berlin Heidelberg",
address="Berlin, Heidelberg",
pages="411--418",
abstract="We use deep max-pooling convolutional neural networks to detect mitosis in breast histology images. The networks are trained to classify each pixel in the images, using as context a patch centered on the pixel. Simple postprocessing is then applied to the network output. Our approach won the ICPR 2012 mitosis detection competition, outperforming other contestants by a significant margin.",
isbn="978-3-642-40763-5"
}



@Article{vanderLaak2021,
author={van der Laak, Jeroen
and Litjens, Geert
and Ciompi, Francesco},
title={Deep learning in histopathology: the path to the clinic},
journal={Nature Medicine},
year={2021},
month={May},
day={01},
volume={27},
number={5},
pages={775-784},
abstract={Machine learning techniques have great potential to improve medical diagnostics, offering ways to improve accuracy, reproducibility and speed, and to ease workloads for clinicians. In the field of histopathology, deep learning algorithms have been developed that perform similarly to trained pathologists for tasks such as tumor detection and grading. However, despite these promising results, very few algorithms have reached clinical implementation, challenging the balance between hope and hype for these new techniques. This Review provides an overview of the current state of the field, as well as describing the challenges that still need to be addressed before artificial intelligence in histopathology can achieve clinical value.},
issn={1546-170X},
doi={10.1038/s41591-021-01343-4},
url={https://doi.org/10.1038/s41591-021-01343-4}
}



@Article{Zhang2019,
author={Zhang, Zizhao
and Chen, Pingjun
and McGough, Mason
and Xing, Fuyong
and Wang, Chunbao
and Bui, Marilyn
and Xie, Yuanpu
and Sapkota, Manish
and Cui, Lei
and Dhillon, Jasreman
and Ahmad, Nazeel
and Khalil, Farah K.
and Dickinson, Shohreh I.
and Shi, Xiaoshuang
and Liu, Fujun
and Su, Hai
and Cai, Jinzheng
and Yang, Lin},
title={Pathologist-level interpretable whole-slide cancer diagnosis with deep learning},
journal={Nature Machine Intelligence},
year={2019},
month={May},
day={01},
volume={1},
number={5},
pages={236-245},
abstract={Diagnostic pathology is the foundation and gold standard for identifying carcinomas. However, high inter-observer variability substantially affects productivity in routine pathology and is especially ubiquitous in diagnostician-deficient medical centres. Despite rapid growth in computer-aided diagnosis (CAD), the application of whole-slide pathology diagnosis remains impractical. Here, we present a novel pathology whole-slide diagnosis method, powered by artificial intelligence, to address the lack of interpretable diagnosis. The proposed method masters the ability to automate the human-like diagnostic reasoning process and translate gigapixels directly to a series of interpretable predictions, providing second opinions and thereby encouraging consensus in clinics. Moreover, using 913 collected examples of whole-slide data representing patients with bladder cancer, we show that our method matches the performance of 17 pathologists in the diagnosis of urothelial carcinoma. We believe that our method provides an innovative and reliable means for making diagnostic suggestions and can be deployed at low cost as next-generation, artificial intelligence-enhanced CAD technology for use in diagnostic pathology.},
issn={2522-5839},
doi={10.1038/s42256-019-0052-1},
url={https://doi.org/10.1038/s42256-019-0052-1}
}



@Article{Karabag2021,
AUTHOR = {Karabağ, Cefa and Jones, Martin L. and Reyes-Aldasoro, Constantino Carlos},
TITLE = {Volumetric Semantic Instance Segmentation of the Plasma Membrane of HeLa Cells},
JOURNAL = {Journal of Imaging},
VOLUME = {7},
YEAR = {2021},
NUMBER = {6},
ARTICLE-NUMBER = {93},
URL = {https://www.mdpi.com/2313-433X/7/6/93},
ISSN = {2313-433X},
ABSTRACT = {In this work, an unsupervised volumetric semantic instance segmentation of the plasma membrane of HeLa cells as observed with serial block face scanning electron microscopy is described. The resin background of the images was segmented at different slices of a 3D stack of 518 slices with 8192 × 8192 pixels each. The background was used to create a distance map, which helped identify and rank the cells by their size at each slice. The centroids of the cells detected at different slices were linked to identify them as a single cell that spanned a number of slices. A subset of these cells, i.e., the largest ones and those not close to the edges were selected for further processing. The selected cells were then automatically cropped to smaller regions of interest of 2000 × 2000 × 300 voxels that were treated as cell instances. Then, for each of these volumes, the nucleus was segmented, and the cell was separated from any neighbouring cells through a series of traditional image processing steps that followed the plasma membrane. The segmentation process was repeated for all the regions of interest previously selected. For one cell for which the ground truth was available, the algorithm provided excellent results in Accuracy (AC) and the Jaccard similarity Index (JI): nucleus: JI =0.9665, AC =0.9975, cell including nucleus JI =0.8711, AC =0.9655, cell excluding nucleus JI =0.8094, AC =0.9629. A limitation of the algorithm for the plasma membrane segmentation was the presence of background. In samples with tightly packed cells, this may not be available. When tested for these conditions, the segmentation of the nuclear envelope was still possible. All the code and data were released openly through GitHub, Zenodo and EMPIAR.},
DOI = {10.3390/jimaging7060093}
}





@article{Horstmann2012,
    doi = {10.1371/journal.pone.0035172},
    author = {Horstmann, Heinz and Körber, Christoph and Sätzler, Kurt and Aydin, Daniel and Kuner, Thomas},
    journal = {PLOS ONE},
    publisher = {Public Library of Science},
    title = {Serial Section Scanning Electron Microscopy (S3EM) on Silicon Wafers for Ultra-Structural Volume Imaging of Cells and Tissues},
    year = {2012},
    month = {04},
    volume = {7},
    url = {https://doi.org/10.1371/journal.pone.0035172},
    pages = {1-8},
    abstract = {High resolution, three-dimensional (3D) representations of cellular ultrastructure are essential for structure function studies in all areas of cell biology. While limited subcellular volumes have been routinely examined using serial section transmission electron microscopy (ssTEM), complete ultrastructural reconstructions of large volumes, entire cells or even tissue are difficult to achieve using ssTEM. Here, we introduce a novel approach combining serial sectioning of tissue with scanning electron microscopy (SEM) using a conductive silicon wafer as a support. Ribbons containing hundreds of 35 nm thick sections can be generated and imaged on the wafer at a lateral pixel resolution of 3.7 nm by recording the backscattered electrons with the in-lens detector of the SEM. The resulting electron micrographs are qualitatively comparable to those obtained by conventional TEM. S3EM images of the same region of interest in consecutive sections can be used for 3D reconstructions of large structures. We demonstrate the potential of this approach by reconstructing a 31.7 µm3 volume of a calyx of Held presynaptic terminal. The approach introduced here, Serial Section SEM (S3EM), for the first time provides the possibility to obtain 3D ultrastructure of large volumes with high resolution and to selectively and repetitively home in on structures of interest. S3EM accelerates process duration, is amenable to full automation and can be implemented with standard instrumentation.},
    number = {4}
}


@article{Tun2021,
author = {Tun, W. M.  and Poologasundarampillai, G.  and Bischof, H.  and Nye, G.  and King, O. N. F.  and Basham, M.  and Tokudome, Y.  and Lewis, R. M.  and Johnstone, E. D.  and Brownbill, P.  and Darrow, M.  and Chernyavsky, I. L. },
title = {A massively multi-scale approach to characterizing tissue architecture by synchrotron micro-CT applied to the human placenta},
journal = {Journal of The Royal Society Interface},
volume = {18},
number = {179},
pages = {20210140},
year = {2021},
doi = {10.1098/rsif.2021.0140},
URL = {https://royalsocietypublishing.org/doi/abs/10.1098/rsif.2021.0140},
eprint = {https://royalsocietypublishing.org/doi/pdf/10.1098/rsif.2021.0140},
    abstract = { Multi-scale structural assessment of biological soft tissue is challenging but essential to gain insight into structure–function relationships of tissue/organ. Using the human placenta as an example, this study brings together sophisticated sample preparation protocols, advanced imaging and robust, validated machine-learning segmentation techniques to provide the first massively multi-scale and multi-domain information that enables detailed morphological and functional analyses of both maternal and fetal placental domains. Finally, we quantify the scale-dependent error in morphological metrics of heterogeneous placental tissue, estimating the minimal tissue scale needed in extracting meaningful biological data. The developed protocol is beneficial for high-throughput investigation of structure–function relationships in both normal and diseased placentas, allowing us to optimize therapeutic approaches for pathological pregnancies. In addition, the methodology presented is applicable in the characterization of tissue architecture and physiological behaviours of other complex organs with similarity to the placenta, where an exchange barrier possesses circulating vascular and avascular fluid spaces. }
}



@Article{Sakdinawat2010,
author={Sakdinawat, Anne
and Attwood, David},
title={Nanoscale X-ray imaging},
journal={Nature Photonics},
year={2010},
month={Dec},
day={01},
volume={4},
number={12},
pages={840-848},
abstract={Recent years have seen significant progress in the field of soft- and hard-X-ray microscopy, both technically, through developments in source, optics and imaging methodologies, and also scientifically, through a wide range of applications. While an ever-growing community is pursuing the extensive applications of today's available X-ray tools, other groups are investigating improvements in techniques, including new optics, higher spatial resolutions, brighter compact sources and shorter-duration X-ray pulses. This Review covers recent work in the development of direct image-forming X-ray microscopy techniques and the relevant applications, including three-dimensional biological tomography, dynamical processes in magnetic nanostructures, chemical speciation studies, industrial applications related to solar cells and batteries, and studies of archaeological materials and historical works of art.},
issn={1749-4893},
doi={10.1038/nphoton.2010.267},
url={https://doi.org/10.1038/nphoton.2010.267}
}

@article{Weinhardt2020,
    doi = {10.1371/journal.pone.0227601},
    author = {Weinhardt, Venera and Chen, Jian-Hua and Ekman, Axel A. and Guo, Jessica and Remesh, Soumya G. and Hammel, Michal and McDermott, Gerry and Chao, Weilun and Oh, Sharon and Le Gros, Mark A. and Larabell, Carolyn A.},
    journal = {PLOS ONE},
    publisher = {Public Library of Science},
    title = {Switchable resolution in soft x-ray tomography of single cells},
    year = {2020},
    month = {01},
    volume = {15},
    url = {https://doi.org/10.1371/journal.pone.0227601},
    pages = {1-14},
    abstract = {The diversity of living cells, in both size and internal complexity, calls for imaging methods with adaptable spatial resolution. Soft x-ray tomography (SXT) is a three-dimensional imaging technique ideally suited to visualizing and quantifying the internal organization of single cells of varying sizes in a near-native state. The achievable resolution of the soft x-ray microscope is largely determined by the objective lens, but switching between objectives is extremely time-consuming and typically undertaken only during microscope maintenance procedures. Since the resolution of the optic is inversely proportional to the depth of focus, an optic capable of imaging the thickest cells is routinely selected. This unnecessarily limits the achievable resolution in smaller cells and eliminates the ability to obtain high-resolution images of regions of interest in larger cells. Here, we describe developments to overcome this shortfall and allow selection of microscope optics best suited to the specimen characteristics and data requirements. We demonstrate that switchable objective capability advances the flexibility of SXT to enable imaging cells ranging in size from bacteria to yeast and mammalian cells without physically modifying the microscope, and we demonstrate the use of this technology to image the same specimen with both optics.},
number = {1}
}


@article {Dyer2017,
	author = {Dyer, Eva L. and Gray Roncal, William and Prasad, Judy A. and Fernandes, Hugo L. and G{\"u}rsoy, Doga and De Andrade, Vincent and Fezzaa, Kamel and Xiao, Xianghui and Vogelstein, Joshua T. and Jacobsen, Chris and K{\"o}rding, Konrad P. and Kasthuri, Narayanan},
	title = {Quantifying Mesoscale Neuroanatomy Using X-Ray Microtomography},
	volume = {4},
	number = {5},
	elocation-id = {ENEURO.0195-17.2017},
	year = {2017},
	doi = {10.1523/ENEURO.0195-17.2017},
	publisher = {Society for Neuroscience},
	abstract = {Methods for resolving the three-dimensional (3D) microstructure of the brain typically start by thinly slicing and staining the brain, followed by imaging numerous individual sections with visible light photons or electrons. In contrast, X-rays can be used to image thick samples, providing a rapid approach for producing large 3D brain maps without sectioning. Here we demonstrate the use of synchrotron X-ray microtomography ({\textmu}CT) for producing mesoscale (\~{}1 {\textmu}m 3 resolution) brain maps from millimeter-scale volumes of mouse brain. We introduce a pipeline for {\textmu}CT-based brain mapping that develops and integrates methods for sample preparation, imaging, and automated segmentation of cells, blood vessels, and myelinated axons, in addition to statistical analyses of these brain structures. Our results demonstrate that X-ray tomography achieves rapid quantification of large brain volumes, complementing other brain mapping and connectomics efforts.},
	URL = {https://www.eneuro.org/content/4/5/ENEURO.0195-17.2017},
	eprint = {https://www.eneuro.org/content/4/5/ENEURO.0195-17.2017.full.pdf},
	journal = {eNeuro}
}



@article {Topperwien2018,
	author = {T{\"o}pperwien, Mareike and van der Meer, Franziska and Stadelmann, Christine and Salditt, Tim},
	title = {Three-dimensional virtual histology of human cerebellum by X-ray phase-contrast tomography},
	volume = {115},
	number = {27},
	pages = {6940--6945},
	year = {2018},
	doi = {10.1073/pnas.1801678115},
	publisher = {National Academy of Sciences},
	abstract = {The complex cytoarchitecture of human brain tissue is traditionally studied by histology, providing structural information in 2D planes. This can be partly extended to 3D by inspecting many parallel slices, however, at nonisotropic resolution. This work shows that propagation-based X-ray phase-contrast tomography, both at the synchrotron and even at a compact laboratory source, can be used to perform noninvasive 3D virtual histology on unstained paraffin-embedded human cerebellum at isotropic subcellular resolution. The resulting data quality is high enough to visualize and automatically locate \~{}106 neurons within the different layers of the cerebellum, providing unprecedented data on its 3D cytoarchitecture and spatial organization.To quantitatively evaluate brain tissue and its corresponding function, knowledge of the 3D cellular distribution is essential. The gold standard to obtain this information is histology, a destructive and labor-intensive technique where the specimen is sliced and examined under a light microscope, providing 3D information at nonisotropic resolution. To overcome the limitations of conventional histology, we use phase-contrast X-ray tomography with optimized optics, reconstruction, and image analysis, both at a dedicated synchrotron radiation endstation, which we have equipped with X-ray waveguide optics for coherence and wavefront filtering, and at a compact laboratory source. As a proof-of-concept demonstration we probe the 3D cytoarchitecture in millimeter-sized punches of unstained human cerebellum embedded in paraffin and show that isotropic subcellular resolution can be reached at both setups throughout the specimen. To enable a quantitative analysis of the reconstructed data, we demonstrate automatic cell segmentation and localization of over 1 million neurons within the cerebellar cortex. This allows for the analysis of the spatial organization and correlation of cells in all dimensions by borrowing concepts from condensed-matter physics, indicating a strong short-range order and local clustering of the cells in the granular layer. By quantification of 3D neuronal {\textquotedblleft}packing,{\textquotedblright} we can hence shed light on how the human cerebellum accommodates 80\% of the total neurons in the brain in only 10\% of its volume. In addition, we show that the distribution of neighboring neurons in the granular layer is anisotropic with respect to the Purkinje cell dendrites.},
	issn = {0027-8424},
	URL = {https://www.pnas.org/content/115/27/6940},
	eprint = {https://www.pnas.org/content/115/27/6940.full.pdf},
	journal = {Proceedings of the National Academy of Sciences}
}



@Article{Lin2017,
author={Lin, Yu-Chuan
and Hwu, Yeukuang
and Huang, Guo-Shu
and Hsiao, Michael
and Lee, Tsung-Tse
and Yang, Shun-Min
and Lee, Ting-Kuo
and Chen, Nan-Yow
and Yang, Sung-Sen
and Chen, Ann
and Ka, Shuk-Man},
title={Differential synchrotron X-ray imaging markers based on the renal microvasculature for tubulointerstitial lesions and glomerulopathy},
journal={Scientific Reports},
year={2017},
month={Jun},
day={14},
volume={7},
number={1},
pages={3488},
abstract={High resolution synchrotron microtomography capable of revealing microvessels in three dimensional (3D) establishes distinct imaging markers of mouse kidney disease strongly associated to renal tubulointerstitial (TI) lesions and glomerulopathy. Two complementary mouse models of chronic kidney disease (CKD), unilateral ureteral obstruction (UUO) and focal segmental glomerulosclerosis (FSGS), were used and five candidates of unique 3D imaging markers were identified. Our characterization to differentially reflect the altered microvasculature of renal TI lesions and/or glomerulopathy demonstrated these image features can be used to differentiate the disease status and the possible cause therefore qualified as image markers. These 3D imaging markers were further correlated with the histopathology and renal microvessel-based molecular study using antibodies against vascular endothelial cells (CD31), the connective tissue growth factor or the vascular endothelial growth factor. We also found that these 3D imaging markers individually characterize the development of renal TI lesions or glomerulopathy, quantitative and integrated use of all of them provide more information for differentiating the two renal conditions. Our findings thus establish a practical strategy to characterize the CKD-associated renal injuries by the microangiography-based 3D imaging and highlight the impact of dysfunctional microvasculature as a whole on the pathogenesis of the renal lesions.},
issn={2045-2322},
doi={10.1038/s41598-017-03677-x},
url={https://doi.org/10.1038/s41598-017-03677-x}
}



@article{Karreman2016,
    author = {Karreman, Matthia A. and Mercier, Luc and Schieber, Nicole L. and Solecki, Gergely and Allio, Guillaume and Winkler, Frank and Ruthensteiner, Bernhard and Goetz, Jacky G. and Schwab, Yannick},
    title = "{Fast and precise targeting of single tumor cells in vivo by multimodal correlative microscopy}",
    journal = {Journal of Cell Science},
    volume = {129},
    number = {2},
    pages = {444-456},
    year = {2016},
    month = {01},
    abstract = "{Intravital microscopy provides dynamic understanding of multiple cell biological processes, but its limited resolution has so far precluded structural analysis. Because it is difficult to capture rare and transient events, only a few attempts have been made to observe specific developmental and pathological processes in animal models using electron microscopy. The multimodal correlative approach that we propose here combines intravital microscopy, microscopic X-ray computed tomography and three-dimensional electron microscopy. It enables a rapid (c.a. 2 weeks) and accurate (\\&lt;5 µm) correlation of functional imaging to ultrastructural analysis of single cells in a relevant context. We demonstrate the power of our approach by capturing single tumor cells in the vasculature of the cerebral cortex and in subcutaneous tumors, providing unique insights into metastatic events. Providing a significantly improved throughput, our workflow enables multiple sampling, a prerequisite for making correlative imaging a relevant tool to study cell biology in vivo. Owing to the versatility of this workflow, we envision broad applications in various fields of biological research, such as cancer or developmental biology.}",
    issn = {0021-9533},
    doi = {10.1242/jcs.181842},
    url = {https://doi.org/10.1242/jcs.181842},
    eprint = {https://journals.biologists.com/jcs/article-pdf/129/2/444/1944116/jcs181842.pdf}
}





@article{Zdora2020,
author = {Marie-Christine Zdora and Pierre Thibault and Willy Kuo and Vincent Fernandez and Hans Deyhle and Joan Vila-Comamala and Margie P. Olbinado and Alexander Rack and Peter M. Lackie and Orestis L. Katsamenis and Matthew J. Lawson and Vartan Kurtcuoglu and Christoph Rau and Franz Pfeiffer and Irene Zanette},
journal = {Optica},
keywords = {Computed tomography; Image quality; Imaging techniques; Medical imaging; X ray imaging; X ray interferometry},
number = {9},
pages = {1221--1227},
publisher = {OSA},
title = {X-ray phase tomography with near-field speckles for three-dimensional virtual histology},
volume = {7},
month = {Sep},
year = {2020},
url = {http://www.osapublishing.org/optica/abstract.cfm?URI=optica-7-9-1221},
doi = {10.1364/OPTICA.399421},
abstract = {High-contrast, high-resolution imaging of biomedical specimens is indispensable for studying organ function and pathologies. Conventional histology, the gold standard for soft-tissue visualization, is limited by its anisotropic spatial resolution, elaborate sample preparation, and lack of quantitative image information. X-ray absorption or phase tomography have been identified as promising alternatives enabling non-destructive, distortion-free three-dimensional (3D) imaging. However, reaching sufficient contrast and resolution with a simple experimental procedure remains a major challenge. Here, we present a solution based on x-ray phase tomography through speckle-based imaging (SBI). We demonstrate on a mouse kidney that SBI delivers comprehensive 3D maps of hydrated, unstained soft tissue, revealing its microstructure and delivering quantitative tissue-density values at a density resolution of better than 2mg/cm3 and spatial resolution of better than 8 {\textmu}m. We expect that SBI virtual histology will find widespread application in biomedicine and will open up new possibilities for research and histopathology.},
}



@Article{Kunishima2020,
author={Kunishima, Naoki
and Takeda, Yoshihiro
and Hirose, Raita
and Kalasov{\'a}, Dominika
and {\v{S}}alplachta, Jakub
and Omote, Kazuhiko},
title={Visualization of internal 3D structure of small live seed on germination by laboratory-based X-ray microscopy with phase contrast computed tomography},
journal={Plant Methods},
year={2020},
month={Feb},
day={01},
volume={16},
number={1},
pages={7},
abstract={The visualization of internal 3D-structure of tissues at micron resolutions without staining by contrast reagents is desirable in plant researches, and it can be achieved by an X-ray computed tomography (CT) with a phase-retrieval technique. Recently, a laboratory-based X-ray microscope adopting the phase contrast CT was developed as a powerful tool for the observation of weakly absorbing biological samples. Here we report the observation of unstained pansy seeds using the laboratory-based X-ray phase-contrast CT.},
issn={1746-4811},
doi={10.1186/s13007-020-0557-y},
url={https://doi.org/10.1186/s13007-020-0557-y}
}



@Article{Kaneko2017,
author={Kaneko, Yukihiro
and Shinohara, Gen
and Hoshino, Masato
and Morishita, Hiroyuki
and Morita, Kiyozo
and Oshima, Yoshihiro
and Takahashi, Masashi
and Yagi, Naoto
and Okita, Yutaka
and Tsukube, Takuro},
title={Intact Imaging of Human Heart Structure Using X-ray Phase-Contrast Tomography},
journal={Pediatric Cardiology},
year={2017},
month={Feb},
day={01},
volume={38},
number={2},
pages={390-393},
abstract={Structural examination of human heart specimens at the microscopic level is a prerequisite for understanding congenital heart diseases. It is desirable not to destroy or alter the properties of such specimens because of their scarcity. However, many of the currently available imaging techniques either destroy the specimen through sectioning or alter the chemical and mechanical properties of the specimen through staining and contrast agent injection. As a result, subsequent studies may not be possible. X-ray phase-contrast tomography is an imaging modality for biological soft tissues that does not destroy or alter the properties of the specimen. The feasibility of X-ray phase-contrast tomography for the structural examination of heart specimens was tested using infantile and fetal heart specimens without congenital diseases. X-ray phase-contrast tomography was carried out at the SPring-8 synchrotron radiation facility using the Talbot grating interferometer at the bending magnet beamline BL20B2 to visualize the structure of five non-pretreated whole heart specimens obtained by autopsy. High-resolution, three-dimensional images were obtained for all specimens. The images clearly showed the myocardial structure, coronary vessels, and conduction bundle. X-ray phase-contrast tomography allows high-resolution, three-dimensional imaging of human heart specimens. Intact imaging using X-ray phase-contrast tomography can contribute to further structural investigation of heart specimens with congenital heart diseases.},
issn={1432-1971},
doi={10.1007/s00246-016-1527-z},
url={https://doi.org/10.1007/s00246-016-1527-z}
}



@Article{Masis2018,
author={Mas{\'i}s, Javier
and Mankus, David
and Wolff, Steffen B. E.
and Guitchounts, Grigori
and Joesch, Maximilian
and Cox, David D.},
title={A micro-CT-based method for quantitative brain lesion characterization and electrode localization},
journal={Scientific Reports},
year={2018},
month={Mar},
day={26},
volume={8},
number={1},
pages={5184},
abstract={Lesion verification and quantification is traditionally done via histological examination of sectioned brains, a time-consuming process that relies heavily on manual estimation. Such methods are particularly problematic in posterior cortical regions (e.g. visual cortex), where sectioning leads to significant damage and distortion of tissue. Even more challenging is the post hoc localization of micro-electrodes, which relies on the same techniques, suffers from similar drawbacks and requires even higher precision. Here, we propose a new, simple method for quantitative lesion characterization and electrode localization that is less labor-intensive and yields more detailed results than conventional methods. We leverage staining techniques standard in electron microscopy with the use of commodity micro-CT imaging. We stain whole rat and zebra finch brains in osmium tetroxide, embed these in resin and scan entire brains in a micro-CT machine. The scans result in 3D reconstructions of the brains with section thickness dependent on sample size (12--15 and 5--6 microns for rat and zebra finch respectively) that can be segmented manually or automatically. Because the method captures the entire intact brain volume, comparisons within and across studies are more tractable, and the extent of lesions and electrodes may be studied with higher accuracy than with current methods.},
issn={2045-2322},
doi={10.1038/s41598-018-23247-z},
url={https://doi.org/10.1038/s41598-018-23247-z}
}



@Article{Muller2018,
author={M{\"u}ller, Mark
and Kimm, Melanie A.
and Ferstl, Simone
and Allner, Sebastian
and Achterhold, Klaus
and Herzen, Julia
and Pfeiffer, Franz
and Busse, Madleen},
title={Nucleus-specific X-ray stain for 3D virtual histology},
journal={Scientific Reports},
year={2018},
month={Dec},
day={14},
volume={8},
number={1},
pages={17855},
abstract={Histological investigations are indispensable with regards to the identification of structural tissue details but are limited to two-dimensional images, which are often visualized in one and the same plane for comparison reasons. Nondestructive three-dimensional technologies such as X-ray micro- and nanoCT have proven to provide valuable benefits for the understanding of anatomical structures as they allow visualization of structural details in 3D and from arbitrary viewing angles. Nevertheless, low attenuation of soft tissue has hampered their application in the field of 3D virtual histology. We present a hematein-based X-ray staining method that specifically targets the cell nuclei of cells, as demonstrated for a whole liver lobule of a mouse. Combining the novel staining protocol with the high resolving power of a recently developed nanoCT system enables the 3D visualization of tissue architecture in the nanometer range, thereby revealing the real 3D morphology and spatial distribution of the cell nuclei. Furthermore, our technique is compatible with conventional histology, as microscopic slides can be derived from the very same stained soft-tissue sample and further counter staining is possible. Thus, our methodology demonstrates future applicability for modern histopathology using laboratory X-ray CT devices.},
issn={2045-2322},
doi={10.1038/s41598-018-36067-y},
url={https://doi.org/10.1038/s41598-018-36067-y}
}



@article{Bentley2007,
author = {Bentley, Michael D. and Jorgensen, Steven M. and Lerman, Lilach O. and Ritman, Erik L. and Romero, J. Carlos},
title = {Visualization of three-dimensional nephron structure with microcomputed tomography},
journal = {The Anatomical Record},
volume = {290},
number = {3},
pages = {277-283},
keywords = {kidney, renal tubules, tomography, imaging, osmium},
doi = {https://doi.org/10.1002/ar.20422},
url = {https://anatomypubs.onlinelibrary.wiley.com/doi/abs/10.1002/ar.20422},
eprint = {https://anatomypubs.onlinelibrary.wiley.com/doi/pdf/10.1002/ar.20422},
abstract = {Abstract The three-dimensional architecture of nephrons in situ and their interrelationship with other nephrons are difficult to visualize by microscopic methods. The present study uses microcomputed X-ray tomography (micro-CT) to visualize intact nephrons in situ. Rat kidneys were perfusion-fixed with buffered formalin and their vasculature was subsequently perfused with radiopaque silicone. Cortical tissue was stained en bloc with osmium tetroxide, embedded in plastic, scanned, and reconstructed at voxel resolutions of 6, 2, and 1 μm. At 6 μm resolution, large blood vessels and glomeruli could be visualized but nephrons and their lumens were small and difficult to visualize. Optimal images were obtained using a synchrotron radiation source at 2 μm resolution where nephron components could be identified, correlated with histological sections, and traced. Proximal tubules had large diameters and opaque walls, whereas distal tubules, connecting tubules, and collecting ducts had smaller diameters and less opaque walls. Blood vessels could be distinguished from nephrons by the luminal presence of radiopaque silicone. Proximal tubules were three times longer than distal tubules. Proximal and distal tubules were tightly coiled in the outer cortex but were loosely coiled in the middle and inner cortex. The connecting tubules had the narrowest diameters of the tubules and converged to form arcades that paralleled the radial vessels as they extended to the outer cortex. These results illustrate a potential use of micro-CT to obtain three-dimensional information about nephron architecture and nephron interrelationships, which could be useful in evaluating experimental tubular hypertrophy, atrophy, and necrosis. Anat Rec, 2007. © 2007 Wiley-Liss, Inc.},
year = {2007}
}



@Article{Toyota2004,
author={Toyota, Eiji
and Ogasawara, Yasuo
and Fujimoto, Katsukui
and Kajita, Tatsuya
and Shigeto, Fumiyuki
and Asano, Takahisa
and Watanabe, Nozomi
and Kajiya, Fumihiko},
title={Global heterogeneity of glomerular volume distribution in early diabetic nephropathy},
journal={Kidney International},
year={2004},
month={Aug},
day={01},
publisher={Elsevier},
volume={66},
number={2},
pages={855-861},
issn={0085-2538},
doi={10.1111/j.1523-1755.2004.00816.x},
url={https://doi.org/10.1111/j.1523-1755.2004.00816.x}
}



@article {Busse2018,
	author = {Busse, Madleen and M{\"u}ller, Mark and Kimm, Melanie A. and Ferstl, Simone and Allner, Sebastian and Achterhold, Klaus and Herzen, Julia and Pfeiffer, Franz},
	title = {Three-dimensional virtual histology enabled through cytoplasm-specific X-ray stain for microscopic and nanoscopic computed tomography},
	volume = {115},
	number = {10},
	pages = {2293--2298},
	year = {2018},
	doi = {10.1073/pnas.1720862115},
	publisher = {National Academy of Sciences},
	abstract = {Three-dimensional histology of soft-tissue samples has proven to provide crucial benefits for the understanding of tissue structure. Nevertheless, the low attenuation of soft tissue has impaired the use of computed tomography (CT) as a tool for the nondestructive and 3D visualization of external and internal structural details. We present a cytoplasm-specific staining method tailored for X-ray CT that enables a routine and efficient 3D volume screening at high resolutions. Our technique is fully compatible with conventional histology and allows further histological investigations, as demonstrated for a mouse kidney. The comparative analysis of our CT data with conventional 2D histology highlights the future applicability of the cytoplasm-specific X-ray staining method for modern histological and histopathological investigations using laboratory X-ray CT devices.Many histological methods require staining of the cytoplasm, which provides instrumental details for diagnosis. One major limitation is the production of 2D images obtained by destructive preparation of 3D tissue samples. X-ray absorption micro- and nanocomputed tomography (microCT and nanoCT) allows for a nondestructive investigation of a 3D tissue sample, and thus aids to determine regions of interest for further histological examinations. However, application of microCT and nanoCT to biological samples (e.g., biopsies) is limited by the missing contrast within soft tissue, which is important to visualize morphological details. We describe an eosin-based preparation overcoming the challenges of contrast enhancement and selectivity for certain tissues. The eosin-based staining protocol is suitable for whole-organ staining, which then enables high-resolution microCT imaging of whole organs and nanoCT imaging of smaller tissue pieces retrieved from the original sample. Our results demonstrate suitability of the eosin-based staining method for diagnostic screening of 3D tissue samples without impeding further diagnostics through histological methods.},
	issn = {0027-8424},
	URL = {https://www.pnas.org/content/115/10/2293},
	eprint = {https://www.pnas.org/content/115/10/2293.full.pdf},
	journal = {Proceedings of the National Academy of Sciences}
}



@ARTICLE{Zaqout2016,
AUTHOR={Zaqout, Sami and Kaindl, Angela M.},   
TITLE={Golgi-Cox Staining Step by Step},      
JOURNAL={Frontiers in Neuroanatomy},      
VOLUME={10},      
PAGES={38},     
YEAR={2016},      
URL={https://www.frontiersin.org/article/10.3389/fnana.2016.00038},       
DOI={10.3389/fnana.2016.00038},      
ISSN={1662-5129},   
ABSTRACT={Golgi staining remains a key method to study neuronal morphology in vivo. Since most protocols delineating modifications of the original staining method lack details on critical steps, establishing this method in a laboratory can be time-consuming and frustrating. Here, we describe the Golgi-Cox staining in such detail that should turn the staining into an easily feasible method for all scientists working in the neuroscience field.}
}


@article{Andrews2010, title={Nanoscale X-Ray Microscopic Imaging of Mammalian Mineralized Tissue}, volume={16}, DOI={10.1017/S1431927610000231}, number={3}, journal={Microscopy and Microanalysis}, publisher={Cambridge University Press}, author={Andrews, Joy C. and Almeida, Eduardo and van der Meulen, Marjolein C.H. and Alwood, Joshua S. and Lee, Chialing and Liu, Yijin and Chen, Jie and Meirer, Florian and Feser, Michael and Gelb, Jeff and et al.}, year={2010}, pages={327–336}}

@article{Nango2016,
title = {Osteocyte-directed bone demineralization along canaliculi},
journal = {Bone},
volume = {84},
pages = {279-288},
year = {2016},
issn = {8756-3282},
doi = {https://doi.org/10.1016/j.bone.2015.12.006},
url = {https://www.sciencedirect.com/science/article/pii/S8756328215004287},
author = {Nobuhito Nango and Shogo Kubota and Tomoka Hasegawa and Wataru Yashiro and Atsushi Momose and Koichi Matsuo},
keywords = {Demineralization/remineralization, Mineral metabolism, Osteocytic osteolysis, Osteocyte canaliculus, Synchrotron radiation, Talbot-defocus multiscan tomography},
abstract = {The mammalian skeleton stores calcium and phosphate ions in bone matrix. Osteocytes in osteocyte lacunae extend numerous dendrites into canaliculi less than a micron in diameter and which are distributed throughout bone matrix. Although osteoclasts are the primary bone-resorbing cells, osteocytes also reportedly dissolve hydroxyapatite at peri-lacunar bone matrix. However, robust three-dimensional evidence for peri-canalicular bone mineral dissolution has been lacking. Here we applied a previously reported Talbot-defocus multiscan tomography method for synchrotron X-ray microscopy and analyzed the degree of bone mineralization in mouse cortical bone around the lacuno–canalicular network, which is connected both to blood vessels and the peri- and endosteum. We detected cylindrical low mineral density regions spreading around canaliculi derived from a subset of osteocytes. Transmission electron microscopy revealed both intact and demineralized bone matrix around the canaliculus. Peri-canalicular low mineral density regions were also observed in osteopetrotic mice lacking osteoclasts, indicating that osteoclasts are dispensable for peri-canalicular demineralization. These data suggest demineralization can occur from within bone through the canalicular system, and that peri-canalicular demineralization occurs not uniformly but directed by individual osteocytes. Blockade of peri-canalicular demineralization may be a therapeutic strategy to increase bone mass and quality.}
}


@article{Gros2014,
author = "Le Gros, Mark A. and McDermott, Gerry and Cinquin, Bertrand P. and Smith, Elizabeth A. and Do, Myan and Chao, Weilun L. and Naulleau, Patrick P. and Larabell, Carolyn A.",
title = "{Biological soft X-ray tomography on beamline 2.1 at~the Advanced Light Source}",
journal = "Journal of Synchrotron Radiation",
year = "2014",
volume = "21",
number = "6",
pages = "1370--1377",
month = "Nov",
doi = {10.1107/S1600577514015033},
url = {https://doi.org/10.1107/S1600577514015033},
abstract = {Beamline 2.1 (XM-2) is a transmission soft X-ray microscope in sector 2 of the Advanced Light Source at Lawrence Berkeley National Laboratory. XM-2 was designed, built and is now operated by the National Center for X-ray Tomography as a National Institutes of Health Biomedical Technology Research Resource. XM-2 is equipped with a cryogenic rotation stage to enable tomographic data collection from cryo-preserved cells, including large mammalian cells. During data collection the specimen is illuminated with `water window' X-rays (284{--}543eV). Illuminating photons are attenuated an order of magnitude more strongly by biomolecules than by water. Consequently, differences in molecular composition generate quantitative contrast in images of the specimen. Soft X-ray tomography is an information-rich three-dimensional imaging method that can be applied either as a standalone technique or as a component modality in correlative imaging studies.},
keywords = {cell biology, cellular imaging, cryo-preservation, cryogenic fluorescence tomography, cryostage, three-dimensional reconstruction},
}



@article{Larabell2004,
author = {Larabell, Carolyn A. and Le Gros, Mark A.},
title = {X-ray Tomography Generates 3-D Reconstructions of the Yeast, Saccharomyces cerevisiae, at 60-nm Resolution},
journal = {Molecular Biology of the Cell},
volume = {15},
number = {3},
pages = {957-962},
year = {2004},
doi = {10.1091/mbc.e03-07-0522},
note ={PMID: 14699066},
URL = {https://doi.org/10.1091/mbc.e03-07-0522},
eprint = {https://doi.org/10.1091/mbc.e03-07-0522},
    abstract = { We examined the yeast, Saccharomyces cerevisiae, using X-ray tomography and demonstrate unique views of the internal structural organization of these cells at 60-nm resolution. Cryo X-ray tomography is a new imaging technique that generates three-dimensional (3-D) information of whole cells. In the energy range of X-rays used to examine cells, organic material absorbs approximately an order of magnitude more strongly than water. This produces a quantifiable natural contrast in fully hydrated cells and eliminates the need for chemical fixatives or contrast enhancement reagents to visualize cellular structures. Because proteins can be localized in the X-ray microscope using immunogold labeling protocols (Meyer-Ilse et al., 2001. J. Microsc. 201, 395–403), tomography enables 3-D molecular localization. The time required to collect the data for each cell shown here was <15 min and has recently been reduced to 3 min, making it possible to examine numerous yeast and to collect statistically significant high-resolution data. In this video essay, we show examples of 3-D tomographic reconstructions of whole yeast and demonstrate the power of this technology to obtain quantifiable information from whole, hydrated cells. }
}




@article{Hsu2016,
title = {Three-dimensional microCT imaging of mouse development from early post-implantation to early postnatal stages},
journal = {Developmental Biology},
volume = {419},
number = {2},
pages = {229-236},
year = {2016},
issn = {0012-1606},
doi = {https://doi.org/10.1016/j.ydbio.2016.09.011},
url = {https://www.sciencedirect.com/science/article/pii/S0012160616303992},
author = {Chih-Wei Hsu and Leeyean Wong and Tara L. Rasmussen and Sowmya Kalaga and Melissa L. McElwee and Lance C. Keith and Ritu Bohat and John R. Seavitt and Arthur L. Beaudet and Mary E. Dickinson},
keywords = {IMPC, MicroCT, Embryonic lethal screening},
abstract = {In this work, we report the use of iodine-contrast microCT to perform high-throughput 3D morphological analysis of mouse embryos and neonates between embryonic day 8.5 to postnatal day 3, with high spatial resolution up to 3µm/voxel. We show that mouse embryos at early stages can be imaged either within extra embryonic tissues such as the yolk sac or the decidua without physically disturbing the embryos. This method enables a full, undisturbed analysis of embryo turning, allantois development, vitelline vessels remodeling, yolk sac and early placenta development, which provides increased insights into early embryonic lethality in mutant lines. Moreover, these methods are inexpensive, simple to learn and do not require substantial processing time, making them ideal for high throughput analysis of mouse mutants with embryonic and early postnatal lethality.}
}

@article{Hummel2013,
    doi = {10.1371/journal.pone.0053293},
    author = {Hummel, Eric and Guttmann, Peter and Werner, Stephan and Tarek, Basel and Schneider, Gerd and Kunz, Michael and Frangakis, Achilleas S. and Westermann, Benedikt},
    journal = {PLOS ONE},
    publisher = {Public Library of Science},
    title = {3D Ultrastructural Organization of Whole Chlamydomonas reinhardtii Cells Studied by Nanoscale Soft X-Ray Tomography},
    year = {2013},
    month = {12},
    volume = {7},
    url = {https://doi.org/10.1371/journal.pone.0053293},
    pages = {1-9},
    abstract = {The complex architecture of their structural elements and compartments is a hallmark of eukaryotic cells. The creation of high resolution models of whole cells has been limited by the relatively low resolution of conventional light microscopes and the requirement for ultrathin sections in transmission electron microscopy. We used soft x-ray tomography to study the 3D ultrastructural organization of whole cells of the unicellular green alga Chlamydomonas reinhardtii at unprecedented spatial resolution. Intact frozen hydrated cells were imaged using the natural x-ray absorption contrast of the sample without any staining. We applied different fiducial-based and fiducial-less alignment procedures for the 3D reconstructions. The reconstructed 3D volumes of the cells show features down to 30 nm in size. The whole cell tomograms reveal ultrastructural details such as nuclear envelope membranes, thylakoids, basal apparatus, and flagellar microtubule doublets. In addition, the x-ray tomograms provide quantitative data from the cell architecture. Therefore, nanoscale soft x-ray tomography is a new valuable tool for numerous qualitative and quantitative applications in plant cell biology.},
    number = {12},

}


@Article{Rawson2020,
author={Rawson, Shelley D.
and Maksimcuka, Jekaterina
and Withers, Philip J.
and Cartmell, Sarah H.},
title={X-ray computed tomography in life sciences},
journal={BMC Biology},
year={2020},
month={Feb},
day={27},
volume={18},
number={1},
pages={21},
abstract={Recent developments within micro-computed tomography ($\mu$CT) imaging have combined to extend our capacity to image tissue in three (3D) and four (4D) dimensions at micron and sub-micron spatial resolutions, opening the way for virtual histology, live cell imaging, subcellular imaging and correlative microscopy. Pivotal to this has been the development of methods to extend the contrast achievable for soft tissue. Herein, we review the new capabilities within the field of life sciences imaging, and consider how future developments in this field could further benefit the life sciences community.},
issn={1741-7007},
doi={10.1186/s12915-020-0753-2},
url={https://doi.org/10.1186/s12915-020-0753-2}
}



@Article{Strotton2018,
author={Strotton, Merrick C.
and Bodey, Andrew J.
and Wanelik, Kazimir
and Darrow, Michele C.
and Medina, Esau
and Hobbs, Carl
and Rau, Christoph
and Bradbury, Elizabeth J.},
title={Optimising complementary soft tissue synchrotron X-ray microtomography for reversibly-stained central nervous system samples},
journal={Scientific Reports},
year={2018},
month={Aug},
day={13},
volume={8},
number={1},
pages={12017},
abstract={Synchrotron radiation microtomography (SR$\mu$CT) is a nominally non-destructive 3D imaging technique which can visualise the internal structures of whole soft tissues. As a multi-stage technique, the cumulative benefits of optimising sample preparation, scanning parameters and signal processing can improve SR$\mu$CT imaging efficiency, image quality, accuracy and ultimately, data utility. By evaluating different sample preparations (embedding media, tissue stains), imaging (projection number, propagation distance) and reconstruction (artefact correction, phase retrieval) parameters, a novel methodology (combining reversible iodine stain, wax embedding and inline phase contrast) was optimised for fast ({\textasciitilde}12{\thinspace}minutes), high-resolution (3.2--4.8{\thinspace}$\mu$m diameter capillaries resolved) imaging of the full diameter of a 3.5{\thinspace}mm length of rat spinal cord. White-grey matter macro-features and micro-features such as motoneurons and capillary-level vasculature could then be completely segmented from the imaged volume for analysis through the shallow machine learning SuRVoS Workbench. Imaged spinal cord tissue was preserved for subsequent histology, establishing a complementary SR$\mu$CT methodology that can be applied to study spinal cord pathologies or other nervous system tissues such as ganglia, nerves and brain. Further, our `single-scan iterative downsampling' approach and side-by-side comparisons of mounting options, sample stains and phase contrast parameters should inform efficient, effective future soft tissue SR$\mu$CT experiment design.},
issn={2045-2322},
doi={10.1038/s41598-018-30520-8},
url={https://doi.org/10.1038/s41598-018-30520-8}
}



@Article{Moscheni2019,
AUTHOR = {Moscheni, Claudia and Malucelli, Emil and Castiglioni, Sara and Procopio, Alessandra and De Palma, Clara and Sorrentino, Andrea and Sartori, Patrizia and Locatelli, Laura and Pereiro, Eva and Maier, Jeanette A. and Iotti, Stefano},
TITLE = {3D Quantitative and Ultrastructural Analysis of Mitochondria in a Model of Doxorubicin Sensitive and Resistant Human Colon Carcinoma Cells},
JOURNAL = {Cancers},
VOLUME = {11},
YEAR = {2019},
NUMBER = {9},
ARTICLE-NUMBER = {1254},
URL = {https://www.mdpi.com/2072-6694/11/9/1254},
ISSN = {2072-6694},
ABSTRACT = {Drug resistance remains a major obstacle in cancer treatment. Because mitochondria mediate metabolic reprogramming in cancer drug resistance, we focused on these organelles in doxorubicin sensitive and resistant colon carcinoma cells. We employed soft X-ray cryo nano-tomography to map three-dimensionally these cells at nanometer-resolution and investigate the correlation between mitochondrial morphology and drug resistance phenotype. We have identified significant structural differences in the morphology of mitochondria in the two strains of cancer cells, as well as lower amounts of Reactive oxygen species (ROS) in resistant than in sensitive cells. We speculate that these features could elicit an impaired mitochondrial communication in resistant cells, thus preventing the formation of the interconnected mitochondrial network as clearly detected in the sensitive cells. In fact, the qualitative and quantitative three-dimensional assessment of the mitochondrial morphology highlights a different structural organization in resistant cells, which reflects a metabolic cellular adaptation functional to survive to the offense exerted by the antineoplastic treatment.},
DOI = {10.3390/cancers11091254}
}





@article{MIZUTANI2013,
title = {Three-dimensional network of Drosophila brain hemisphere},
journal = {Journal of Structural Biology},
volume = {184},
number = {2},
pages = {271-279},
year = {2013},
issn = {1047-8477},
doi = {https://doi.org/10.1016/j.jsb.2013.08.012},
url = {https://www.sciencedirect.com/science/article/pii/S1047847713002293},
author = {Ryuta Mizutani and Rino Saiga and Akihisa Takeuchi and Kentaro Uesugi and Yoshio Suzuki},
keywords = {Microtomography, micro-CT, Brain, Network, Model building},
abstract = {The first step to understanding brain function is to determine the brain’s network structure. We report a three-dimensional analysis of the brain network of the fruit fly Drosophila melanogaster by synchrotron-radiation tomographic microscopy. A skeletonized wire model of the left half of the brain network was built by tracing the three-dimensional distribution of X-ray absorption coefficients. The obtained models of neuronal processes were classified into groups on the basis of their three-dimensional structures. These classified groups correspond to neuronal tracts that send long-range projections or repeated structures of the optic lobe. The skeletonized model is also composed of neuronal processes that could not be classified into the groups. The distribution of these unclassified structures correlates with the distribution of contacts between neuronal processes. This suggests that neurons that cannot be classified into typical structures should play important roles in brain functions. The quantitative description of the brain network provides a basis for structural and statistical analyses of the Drosophila brain. The challenge is to establish a methodology for reconstructing the brain network in a higher-resolution image, leading to a comprehensive understanding of the brain structure.}
}


@Article{Mizutani2016,
author={Mizutani, Ryuta
and Saiga, Rino
and Ohtsuka, Masato
and Miura, Hiromi
and Hoshino, Masato
and Takeuchi, Akihisa
and Uesugi, Kentaro},
title={Three-dimensional X-ray visualization of axonal tracts in mouse brain hemisphere},
journal={Scientific Reports},
year={2016},
month={Oct},
day={11},
volume={6},
number={1},
pages={35061},
abstract={Neurons transmit active potentials through axons, which are essential for the brain to function. In this study, the axonal networks of the murine brain were visualized with X-ray tomographic microscopy, also known as X-ray microtomography or micro-CT. Murine brain samples were freeze-dried to reconstitute the intrinsic contrast of tissue constituents and subjected to X-ray visualization. A whole brain hemisphere visualized by absorption contrast illustrated three-dimensional structures including those of the striatum, corpus callosum, and anterior commissure. Axonal tracts observed in the striatum start from the basal surface of the cerebral cortex and end at various positions in the basal ganglia. The distribution of X-ray attenuation coefficients indicated that differences in water and phospholipid content between the myelin sheath and surrounding tissue constituents account for the observed contrast. A rod-shaped cutout of brain tissue was also analyzed with a phase retrieval method, wherein tissue microstructures could be resolved with up to 2.7{\thinspace}$\mu$m resolution. Structures of axonal networks of the striatum were reconstructed by tracing axonal tracts. Such an analysis should be able to delineate the functional relationships of the brain regions involved in the observed network.},
issn={2045-2322},
doi={10.1038/srep35061},
url={https://doi.org/10.1038/srep35061}
}



@article{MIZUTANI2012,
title = {X-ray microtomography in biology},
journal = {Micron},
volume = {43},
number = {2},
pages = {104-115},
year = {2012},
issn = {0968-4328},
doi = {https://doi.org/10.1016/j.micron.2011.10.002},
url = {https://www.sciencedirect.com/science/article/pii/S0968432811001788},
author = {Ryuta Mizutani and Yoshio Suzuki},
keywords = {Micro-CT, Microcomputed tomography, Three-dimensional structure, Soft tissue, High-Z element staining, Labeling methods},
abstract = {Progress in high-resolution X-ray microtomography has provided us with a practical approach to determining three-dimensional (3D) structures of opaque samples at micrometer to submicrometer resolution. In this review, we give an introduction to hard X-ray microtomography and its application to the visualization of 3D structures of biological soft tissues. Practical aspects of sample preparation, handling, data collection, 3D reconstruction, and structure analysis are described. Furthermore, different sample contrasting methods are approached in detail. Examples of microtomographic studies are overviewed to present an outline of biological applications of X-ray microtomography. We also provide perspectives of biological microtomography as the convergence of sciences in X-ray optics, biology, and structural analysis.}
}


@Article{Smith2016,
author={Smith, Dylan B.
and Bernhardt, Galina
and Raine, Nigel E.
and Abel, Richard L.
and Sykes, Dan
and Ahmed, Farah
and Pedroso, Inti
and Gill, Richard J.},
title={Exploring miniature insect brains using micro-CT scanning techniques},
journal={Scientific Reports},
year={2016},
month={Feb},
day={24},
volume={6},
number={1},
pages={21768},
abstract={The capacity to explore soft tissue structures in detail is important in understanding animal physiology and how this determines features such as movement, behaviour and the impact of trauma on regular function. Here we use advances in micro-computed tomography (micro-CT) technology to explore the brain of an important insect pollinator and model organism, the bumblebee (Bombus terrestris). Here we present a method for accurate imaging and exploration of insect brains that keeps brain tissue free from trauma and in its natural stereo-geometry and showcase our 3D reconstructions and analyses of 19 individual brains at high resolution. Development of this protocol allows relatively rapid and cost effective brain reconstructions, making it an accessible methodology to the wider scientific community. The protocol describes the necessary steps for sample preparation, tissue staining, micro-CT scanning and 3D reconstruction, followed by a method for image analysis using the freeware SPIERS. These image analysis methods describe how to virtually extract key composite structures from the insect brain and we demonstrate the application and precision of this method by calculating structural volumes and investigating the allometric relationships between bumblebee brain structures.},
issn={2045-2322},
doi={10.1038/srep21768},
url={https://doi.org/10.1038/srep21768}
}



@article{Bushong2015, title={X-Ray Microscopy as an Approach to Increasing Accuracy and Efficiency of Serial Block-Face Imaging for Correlated Light and Electron Microscopy of Biological Specimens}, volume={21}, DOI={10.1017/S1431927614013579}, number={1}, journal={Microscopy and Microanalysis}, publisher={Cambridge University Press}, author={Bushong, Eric A. and Johnson, Donald D. and Kim, Keun-Young and Terada, Masako and Hatori, Megumi and Peltier, Steven T. and Panda, Satchidananda and Merkle, Arno and Ellisman, Mark H.}, year={2015}, pages={231–238}}

@Article{Swart2016,
author={Swart, Peter
and Wicklein, Martina
and Sykes, Dan
and Ahmed, Farah
and Krapp, Holger G.},
title={A quantitative comparison of micro-CT preparations in Dipteran flies},
journal={Scientific Reports},
year={2016},
month={Dec},
day={21},
volume={6},
number={1},
pages={39380},
abstract={X-ray-based 3D-imaging techniques have gained fundamental significance in research areas ranging from taxonomy to bioengineering. There is demand for the characterisation of species-specific morphological adaptations, micro-CT ($\mu$CT) being the method of choice in small-scale animals. This has driven the development of suitable staining techniques to improve absorption-based tissue contrast. A quantitative account on the limits of current staining protocols for preparing $\mu$CT specimen, however, is still missing. Here we present a study that quantifies results obtained by combining a variety of different contrast agents and fixative treatments that provides general guidance for $\mu$CT applications, particularly suitable for insect species. Using a blowfly model system (Calliphora), we enhanced effective spatial resolution and, in particular, optimised tissue contrast enabling semi-automated segmentation of soft and hard tissue from $\mu$CT data. We introduce a novel probabilistic measure of the contrast between tissues: PTC. Our results show that a strong iodine solution provides the greatest overall increase in tissue contrast, however phosphotungstic acid offers better inter-tissue discriminability. We further show that using paraformaldehyde as a fixative as opposed to ethanol, slows down the uptake of a staining solution by approximately a factor of two.},
issn={2045-2322},
doi={10.1038/srep39380},
url={https://doi.org/10.1038/srep39380}
}



@article{Wong2014,
    doi = {10.1371/journal.pone.0084321},
    author = {Wong, Michael D. and Spring, Shoshana and Henkelman, R. Mark},
    journal = {PLOS ONE},
    publisher = {Public Library of Science},
    title = {Structural Stabilization of Tissue for Embryo Phenotyping Using Micro-CT with Iodine Staining},
    year = {2014},
    month = {12},
    volume = {8},
    url = {https://doi.org/10.1371/journal.pone.0084321},
    pages = {1-7},
    abstract = {The International Mouse Phenotyping Consortium has been established to conduct large-scale phenotyping of the approximately 23,000 single-gene knockout mice generated by the International Knockout Mouse Consortium to investigate the role of each gene in the mouse genome. Of the generated mouse lines, 30% are predicted to be embryonic lethal, requiring the implementation of imaging techniques and analysis tools specific to late gestation mouse embryo phenotyping. A well-adopted technique combines the use of iodinated contrast solutions and micro-computed tomography imaging. This simple iodine immersion technique provides superior soft-tissue contrast enhancement, however, the hypertonic nature of iodine promotes dehydration causing moderate to severe tissue deformation. Here, we combine the stabilizing properties of a hydrogel mesh with the enhanced contrast properties of iodine. The protocol promotes cross linking of tissue through formaldehyde fixation and the linking of hydrogel monomers to biomolecules. As a result, the hydrogel supports tissue structure and preserves its conformation taking advantage of iodine-enhanced soft tissue contrast to produce high quality mouse embryo images with minimal tissue distortion. Hydrogel stabilization substantially reduces intersample anatomical variation of mature mouse embryos subjected to iodine preparation protocols. A 20% and 50% reduction in intersample variation of normalized brain and lung volume is achieved through hydrogel stabilization, as well as a 20% reduction in variation in overall embryo anatomy as measured through image registration methods. This increases the sensitivity of computer automated analysis to reveal significant anatomical differences between mutant and wild-type mice.},
    number = {12},

}


@Article{Dickinson2016,
author={Dickinson, Mary E.
and Flenniken, Ann M.
and Ji, Xiao
and Teboul, Lydia
and Wong, Michael D.
and White, Jacqueline K.
and Meehan, Terrence F.
and Weninger, Wolfgang J.
and Westerberg, Henrik
and Adissu, Hibret
and Baker, Candice N.
and Bower, Lynette
and Brown, James M.
and Caddle, L. Brianna
and Chiani, Francesco
and Clary, Dave
and Cleak, James
and Daly, Mark J.
and Denegre, James M.
and Doe, Brendan
and Dolan, Mary E.
and Edie, Sarah M.
and Fuchs, Helmut
and Gailus-Durner, Valerie
and Galli, Antonella
and Gambadoro, Alessia
and Gallegos, Juan
and Guo, Shiying
and Horner, Neil R.
and Hsu, Chih-Wei
and Johnson, Sara J.
and Kalaga, Sowmya
and Keith, Lance C.
and Lanoue, Louise
and Lawson, Thomas N.
and Lek, Monkol
and Mark, Manuel
and Marschall, Susan
and Mason, Jeremy
and McElwee, Melissa L.
and Newbigging, Susan
and Nutter, Lauryl M. J.
and Peterson, Kevin A.
and Ramirez-Solis, Ramiro
and Rowland, Douglas J.
and Ryder, Edward
and Samocha, Kaitlin E.
and Seavitt, John R.
and Selloum, Mohammed
and Szoke-Kovacs, Zsombor
and Tamura, Masaru
and Trainor, Amanda G.
and Tudose, Ilinca
and Wakana, Shigeharu
and Warren, Jonathan
and Wendling, Olivia
and West, David B.
and Wong, Leeyean
and Yoshiki, Atsushi
and McKay, Matthew
and Urban, Barbara
and Lund, Caroline
and Froeter, Erin
and LaCasse, Taylor
and Mehalow, Adrienne
and Gordon, Emily
and Donahue, Leah Rae
and Taft, Robert
and Kutney, Peter
and Dion, Stephanie
and Goodwin, Leslie
and Kales, Susan
and Urban, Rachel
and Palmer, Kristina
and Pertuy, Fabien
and Bitz, Deborah
and Weber, Bruno
and Goetz-Reiner, Patrice
and Jacobs, Hughes
and Le Marchand, Elise
and El Amri, Amal
and El Fertak, Leila
and Ennah, Hamid
and Ali-Hadji, Dalila
and Ayadi, Abdel
and Wattenhofer-Donze, Marie
and Jacquot, Sylvie
and Andr{\'e}, Philippe
and Birling, Marie-Christine
and Pavlovic, Guillaume
and Sorg, Tania
and Morse, Iva
and Benso, Frank
and Stewart, Michelle E.
and Copley, Carol
and Harrison, Jackie
and Joynson, Samantha
and Guo, Ruolin
and Qu, Dawei
and Spring, Shoshana
and Yu, Lisa
and Ellegood, Jacob
and Morikawa, Lily
and Shang, Xueyuan
and Feugas, Pat
and Creighton, Amie
and Castellanos Penton, Patricia
and Danisment, Ozge
and Griggs, Nicola
and Tudor, Catherine L.
and Green, Angela L.
and Icoresi Mazzeo, Cecilia
and Siragher, Emma
and Lillistone, Charlotte
and Tuck, Elizabeth
and Gleeson, Diane
and Sethi, Debarati
and Bayzetinova, Tanya
and Burvill, Jonathan
and Habib, Bishoy
and Weavers, Lauren
and Maswood, Ryea
and Miklejewska, Evelina
and Woods, Michael
and Grau, Evelyn
and Newman, Stuart
and Sinclair, Caroline
and Brown, Ellen
and Ayabe, Shinya
and Iwama, Mizuho
and Murakami, Ayumi
and Wurst, Wolfgang
and MacArthur, Daniel G.
and Tocchini-Valentini, Glauco P.
and Gao, Xiang
and Flicek, Paul
and Bradley, Allan
and Skarnes, William C.
and Justice, Monica J.
and Parkinson, Helen E.
and Moore, Mark
and Wells, Sara
and Braun, Robert E.
and Svenson, Karen L.
and de Angelis, Martin Hrabe
and Herault, Yann
and Mohun, Tim
and Mallon, Ann-Marie
and Henkelman, R. Mark
and Brown, Steve D. M.
and Adams, David J.
and Lloyd, K. C. Kent
and McKerlie, Colin
and Beaudet, Arthur L.
and Bu{\'{c}}an, Maja
and Murray, Stephen A.
and Consortium, The International Mouse Phenotyping
and Laboratory, The Jackson
and Infrastructure Nationale PHENOMIN, Institut Clinique de la Souris (ICS)
and Laboratories, Charles River
and Harwell, M. R. C.
and for Phenogenomics, The Toronto Centre
and Institute, The Wellcome Trust Sanger
and Center, RIKEN BioResource},
title={High-throughput discovery of novel developmental phenotypes},
journal={Nature},
year={2016},
month={Sep},
day={01},
volume={537},
number={7621},
pages={508-514},
abstract={Approximately one-third of all mammalian genes are essential for life. Phenotypes resulting from knockouts of these genes in mice have provided tremendous insight into gene function and congenital disorders. As part of the International Mouse Phenotyping Consortium effort to generate and phenotypically characterize 5,000 knockout mouse lines, here we identify 410 lethal genes during the production of the first 1,751 unique gene knockouts. Using a standardized phenotyping platform that incorporates high-resolution 3D imaging, we identify phenotypes at multiple time points for previously uncharacterized genes and additional phenotypes for genes with previously reported mutant phenotypes. Unexpectedly, our analysis reveals that incomplete penetrance and variable expressivity are common even on a defined genetic background. In addition, we show that human disease genes are enriched for essential genes, thus providing a dataset that facilitates the prioritization and validation of mutations identified in clinical sequencing efforts.},
issn={1476-4687},
doi={10.1038/nature19356},
url={https://doi.org/10.1038/nature19356}
}



@article{Takahashi2018,
    author = {Takahashi, Masanori and Tamura, Masaru and Sato, Shigeru and Kawakami, Kiyoshi},
    title = "{Mice doubly deficient in Six4 and Six5 show ventral body wall defects reproducing human omphalocele}",
    journal = {Disease Models & Mechanisms},
    volume = {11},
    number = {10},
    year = {2018},
    month = {10},
    abstract = "{Omphalocele is a human congenital anomaly in ventral body wall closure and may be caused by impaired formation of the primary abdominal wall (PAW) and/or defects in abdominal muscle development. Here, we report that mice doubly deficient in homeobox genes Six4 and Six5 showed the same ventral body wall closure defects as those seen in human omphalocele. SIX4 and SIX5 were localized in surface ectodermal cells and somatic mesoderm-derived mesenchymal and coelomic epithelial cells (CECs) in the PAW. Six4−/−;Six5−/− fetuses exhibited a large omphalocele with protrusion of both the liver and intestine, or a small omphalocele with protrusion of the intestine, with complete penetrance. The umbilical ring of Six4−/−;Six5−/− embryos was shifted anteriorly and its lateral size was larger than that of normal embryos at the E11.5 stage, before the onset of myoblast migration into the PAW. The proliferation rates of surface ectodermal cells in the left and right PAW and somatic mesoderm-derived cells in the right PAW were lower in Six4−/−;Six5−/− embryos than those of wild-type embryos at E10.5. The transition from CECs of the PAW to rounded mesothelial progenitor cells was impaired and the inner coelomic surface of the PAW was relatively smooth in Six4−/−;Six5−/− embryos at E11.25. Furthermore, Six4 overexpression in CECs of the PAW promoted ingression of CECs. Taken together, our results suggest that Six4 and Six5 are required for growth and morphological change of the PAW, and the impairment of these processes is linked to the abnormal positioning and expansion of the umbilical ring, which results in omphalocele.}",
    issn = {1754-8403},
    doi = {10.1242/dmm.034611},
    url = {https://doi.org/10.1242/dmm.034611},
    note = {dmm034611},
    eprint = {https://journals.biologists.com/dmm/article-pdf/11/10/dmm034611/1861291/dmm034611.pdf},
}





@article {Cole2018,
	author = {Cole, Jason M. and Symes, Daniel R. and Lopes, Nelson C. and Wood, Jonathan C. and Poder, Kristjan and Alatabi, Saleh and Botchway, Stanley W. and Foster, Peta S. and Gratton, Sarah and Johnson, Sara and Kamperidis, Christos and Kononenko, Olena and De Lazzari, Michael and Palmer, Charlotte A. J. and Rusby, Dean and Sanderson, Jeremy and Sandholzer, Michael and Sarri, Gianluca and Szoke-Kovacs, Zsombor and Teboul, Lydia and Thompson, James M. and Warwick, Jonathan R. and Westerberg, Henrik and Hill, Mark A. and Norris, Dominic P. and Mangles, Stuart P. D. and Najmudin, Zulfikar},
	title = {High-resolution μCT of a mouse embryo using a compact laser-driven X-ray betatron source},
	volume = {115},
	number = {25},
	pages = {6335--6340},
	year = {2018},
	doi = {10.1073/pnas.1802314115},
	publisher = {National Academy of Sciences},
	abstract = {High-resolution microcomputed tomography with benchtop X-ray sources requires long scan times because of the heat load limitation on the anode. We present an alternative, high-brightness plasma-based X-ray source that does not suffer from this restriction. A demonstration of tomography of a centimeter-scale complex organism achieves equivalent quality to a commercial scanner. We will soon be able to record such scans in minutes, rather than the hours required by conventional X-ray tubes.In the field of X-ray microcomputed tomography (μCT) there is a growing need to reduce acquisition times at high spatial resolution (approximate micrometers) to facilitate in vivo and high-throughput operations. The state of the art represented by synchrotron light sources is not practical for certain applications, and therefore the development of high-brightness laboratory-scale sources is crucial. We present here imaging of a fixed embryonic mouse sample using a compact laser{\textendash}plasma-based X-ray light source and compare the results to images obtained using a commercial X-ray μCT scanner. The radiation is generated by the betatron motion of electrons inside a dilute and transient plasma, which circumvents the flux limitations imposed by the solid or liquid anodes used in conventional electron-impact X-ray tubes. This X-ray source is pulsed (duration \&lt;30 fs), bright (\&gt;1010 photons per pulse), small (diameter \&lt;1 μm), and has a critical energy \&gt;15 keV. Stable X-ray performance enabled tomographic imaging of equivalent quality to that of the μCT scanner, an important confirmation of the suitability of the laser-driven source for applications. The X-ray flux achievable with this approach scales with the laser repetition rate without compromising the source size, which will allow the recording of high-resolution μCT scans in minutes.},
	issn = {0027-8424},
	URL = {https://www.pnas.org/content/115/25/6335},
	eprint = {https://www.pnas.org/content/115/25/6335.full.pdf},
	journal = {Proceedings of the National Academy of Sciences}
}

@article{Tamura2013,
    author = {Tamura, Masaru and Hosoya, Masaki and Fujita, Motoi and Iida, Tomoko and Amano, Takanori and Maeno, Akiteru and Kataoka, Taro and Otsuka, Taketo and Tanaka, Shigekazu and Tomizawa, Shuichi and Shiroishi, Toshihiko},
    title = "{Overdosage of Hand2 causes limb and heart defects in the human chromosomal disorder partial trisomy distal 4q}",
    journal = {Human Molecular Genetics},
    volume = {22},
    number = {12},
    pages = {2471-2481},
    year = {2013},
    month = {02},
    abstract = "{Partial trisomy distal 4q (denoted 4q+) is a human chromosomal disorder caused by duplication of the distal end of the long arm of chromosome 4 (Chr4). This disorder manifests typical phenotypes, including craniofacial, renal, heart and thumb developmental defects. Although these clinical features are likely caused by a dosage imbalance in the gene network involving the trisomic region, the causative gene or genes and the molecular bases are largely unknown. Here, we report mouse Recombination-induced mutation 4 (Rim4) as a model animal of 4q+. The Rim4 genome contains an insertion of a 6.5 Mb fragment from mouse chromosome 8 into chromosome 6. This insertion fragment contains 17 genes, including Hand2, that encode the basic helix-loop-helix transcription factor and is syntenic to the distal end of human Chr4, 4q32.3 to 4q34.1, which is responsible for 4q+. A comparison of phenotypes between patients with Rim4 and 4q+ revealed that Rim4 shows direct parallels with many phenotypes of 4q+ such as craniofacial, heart, cervical vertebra and limb deformities. Rebalancing the gene dosage by a genetic cross with Hand2 knockout mice ameliorated symptoms of the heart and limb deformities of Rim4. Conversely, an increase in copy number of Hand2 in wild-type mice recaptures the heart and limb deformities of Rim4. Our results collectively demonstrate that overdosage of Hand2 is a major cause for at least the limb and heart phenotypes of 4q+ and that mouse Rim4 provides a unique animal model for understanding the molecular bases underlying the complex phenotypes of 4q+.}",
    issn = {0964-6906},
    doi = {10.1093/hmg/ddt099},
    url = {https://doi.org/10.1093/hmg/ddt099},
    eprint = {https://academic.oup.com/hmg/article-pdf/22/12/2471/14139556/ddt099.pdf},
}


@article{Wong2012,
    author = {Wong, Michael D. and Dorr, Adrienne E. and Walls, Johnathon R. and Lerch, Jason P. and Henkelman, R. Mark},
    title = "{A novel 3D mouse embryo atlas based on micro-CT}",
    journal = {Development},
    volume = {139},
    number = {17},
    pages = {3248-3256},
    year = {2012},
    month = {09},
    abstract = "{The goal of the International Mouse Phenotyping Consortium (IMPC) is to phenotype targeted knockout mouse strains throughout the whole mouse genome (23,000 genes) by 2021. A significant percentage of the generated mice will be embryonic lethal; therefore, phenotyping methods tuned to the mouse embryo are needed. Methods that are robust, quantitative, automated and high-throughput are attractive owing to the numbers of mice involved. Three-dimensional (3D) imaging is a useful method for characterizing morphological phenotypes. However, tools to automatically quantify morphological information of mouse embryos from 3D imaging have not been fully developed. We present a representative mouse embryo average 3D atlas comprising micro-CT images of 35 individual C57BL/6J mouse embryos at 15.5 days post-coitum. The 35 micro-CT images were registered into a consensus average image with our automated image registration software and 48 anatomical structures were segmented manually. We report the mean and variation in volumes for each of the 48 segmented structures. Mouse organ volumes vary by 2.6-4.2\\% on a linear scale when normalized to whole body volume. A power analysis of the volume data reports that a 9-14\\% volume difference can be detected between two classes of mice with sample sizes of eight. This resource will be crucial in establishing baseline anatomical phenotypic measurements for the assessment of mutant mouse phenotypes, as any future mutant embryo image can be registered to the atlas and subsequent organ volumes calculated automatically.}",
    issn = {0950-1991},
    doi = {10.1242/dev.082016},
    url = {https://doi.org/10.1242/dev.082016},
    eprint = {https://journals.biologists.com/dev/article-pdf/139/17/3248/1185500/3248.pdf},
}





@Article{Langer2016,
author={Langer, M.
and Peyrin, F.},
title={3D X-ray ultra-microscopy of bone tissue},
journal={Osteoporosis International},
year={2016},
month={Feb},
day={01},
volume={27},
number={2},
pages={441-455},
abstract={We review the current X-ray techniques with 3D imaging capability at the nano-scale: transmission X-ray microscopy, ptychography and in-line phase nano-tomography. We further review the different ultra-structural features that have so far been resolved: the lacuno-canalicular network, collagen orientation, nano-scale mineralization and their use as basis for mechanical simulations. X-ray computed tomography at the micro-metric scale is increasingly considered as the reference technique in imaging of bone micro-structure. The trend has been to push towards increasingly higher resolution. Due to the difficulty of realizing optics in the hard X-ray regime, the magnification has mainly been due to the use of visible light optics and indirect detection of the X-rays, which limits the attainable resolution with respect to the wavelength of the visible light used in detection. Recent developments in X-ray optics and instrumentation have allowed to implement several types of methods that achieve imaging that is limited in resolution by the X-ray wavelength, thus enabling computed tomography at the nano-scale. We review here the X-ray techniques with 3D imaging capability at the nano-scale: transmission X-ray microscopy, ptychography and in-line phase nano-tomography. Further, we review the different ultra-structural features that have so far been resolved and the applications that have been reported: imaging of the lacuno-canalicular network, direct analysis of collagen orientation, analysis of mineralization on the nano-scale and use of 3D images at the nano-scale to drive mechanical simulations. Finally, we discuss the issue of going beyond qualitative description to quantification of ultra-structural features.},
issn={1433-2965},
doi={10.1007/s00198-015-3257-0},
url={https://doi.org/10.1007/s00198-015-3257-0}
}

@article{Metscher2013,
author = {Metscher, Brian},
year = {2013},
month = {01},
pages = {13-16},
title = {Biological applications of X-ray microtomography: imaging microanatomy, molecular expression and organismal diversity},
volume = {27},
journal = {Microsc Anal (Am Ed)}
}


@Article{Castejon2018,
author={Castej{\'o}n, Diego
and Alba-Tercedor, Javier
and Rotllant, Guiomar
and Ribes, Enric
and Durfort, Merc{\`e}
and Guerao, Guillermo},
title={Micro-computed tomography and histology to explore internal morphology in decapod larvae},
journal={Scientific Reports},
year={2018},
month={Sep},
day={26},
volume={8},
number={1},
pages={14399},
abstract={Traditionally, the internal morphology of crustacean larvae has been studied using destructive techniques such as dissection and microscopy. The present study combines advances in micro-computed tomography (micro-CT) and histology to study the internal morphology of decapod larvae, using the common spider crab (Maja brachydactyla Balss, 1922) as a model and resolving the individual limitations of these techniques. The synergy of micro-CT and histology allows the organs to be easily identified, revealing simultaneously the gross morphology (shape, size, and location) and histological organization (tissue arrangement and cell identification). Micro-CT shows mainly the exoskeleton, musculature, digestive and nervous systems, and secondarily the circulatory and respiratory systems, while histology distinguishes several cell types and confirms the organ identity. Micro-CT resolves a discrepancy in the literature regarding the nervous system of crab larvae. The major changes occur in the metamorphosis to the megalopa stage, specifically the formation of the gastric mill, the shortening of the abdominal nerve cord, the curving of the abdomen beneath the cephalothorax, and the development of functional pereiopods, pleopods, and lamellate gills. The combination of micro-CT and histology provides better results than either one alone.},
issn={2045-2322},
doi={10.1038/s41598-018-32709-3},
url={https://doi.org/10.1038/s41598-018-32709-3}
}



@Article{Chaurand2018,
author={Chaurand, Perrine
and Liu, Wei
and Borschneck, Daniel
and Levard, Cl{\'e}ment
and Auffan, M{\'e}lanie
and Paul, Emmanuel
and Collin, Blanche
and Kieffer, Isabelle
and Lanone, Sophie
and Rose, J{\'e}r{\^o}me
and Perrin, Jeanne},
title={Multi-scale X-ray computed tomography to detect and localize metal-based nanomaterials in lung tissues of in vivo exposed mice},
journal={Scientific Reports},
year={2018},
month={Mar},
day={13},
volume={8},
number={1},
pages={4408},
abstract={In this methodological study, we demonstrated the relevance of 3D imaging performed at various scales for the ex vivo detection and location of cerium oxide nanomaterials (CeO2-NMs) in mouse lung. X-ray micro-computed tomography (micro-CT) with a voxel size from 14{\thinspace}{\textmu}m to 1{\thinspace}{\textmu}m (micro-CT) was combined with X-ray nano-computed tomography with a voxel size of 63{\thinspace}nm (nano-CT). An optimized protocol was proposed to facilitate the sample preparation, to minimize the experimental artifacts and to optimize the contrast of soft tissues exposed to metal-based nanomaterials (NMs). 3D imaging of the NMs biodistribution in lung tissues was consolidated by combining a vast variety of techniques in a correlative approach: histological observations, 2D chemical mapping and speciation analysis were performed for an unambiguous detection of NMs. This original methodological approach was developed following a worst-case scenario of exposure, i.e. high dose of exposure with administration via intra-tracheal instillation. Results highlighted both (i) the non-uniform distribution of CeO2-NMs within the entire lung lobe (using large field-of-view micro-CT) and (ii) the detection of CeO2-NMs down to the individual cell scale, e.g. macrophage scale (using nano-CT with a voxel size of 63{\thinspace}nm).},
issn={2045-2322},
doi={10.1038/s41598-018-21862-4},
url={https://doi.org/10.1038/s41598-018-21862-4}
}



@article{Foster2016,
author = {Taryn Foster  and James L. Falter  and Malcolm T. McCulloch  and Peta L. Clode },
title = {Ocean acidification causes structural deformities in juvenile coral skeletons},
journal = {Science Advances},
volume = {2},
number = {2},
pages = {e1501130},
year = {2016},
doi = {10.1126/sciadv.1501130},
URL = {https://www.science.org/doi/abs/10.1126/sciadv.1501130},
eprint = {https://www.science.org/doi/pdf/10.1126/sciadv.1501130},
    abstract = { 3D imaging exposes deformities and shows how ocean acidification can change the way juvenile corals build their skeletons. Rising atmospheric CO2 is causing the oceans to both warm and acidify, which could reduce the calcification rates of corals globally. Successful coral recruitment and high rates of juvenile calcification are critical to the replenishment and ultimate viability of coral reef ecosystems. Although elevated Pco2 (partial pressure of CO2) has been shown to reduce the skeletal weight of coral recruits, the structural changes caused by acidification during initial skeletal deposition are unknown. We show, using high-resolution three-dimensional x-ray microscopy, that ocean acidification (Pco2 ~900 μatm, pH ~7.7) not only causes reduced overall mineral deposition but also a deformed and porous skeletal structure in newly settled coral recruits. In contrast, elevated temperature (+3°C) had little effect on skeletal formation except to partially mitigate the effects of elevated Pco2. The striking structural deformities we observed show that new recruits are at significant risk, being unable to effectively build their skeletons in the Pco2 conditions predicted to occur for open ocean surface waters under a “business-as-usual” emissions scenario [RCP (representative concentration pathway) 8.5] by the year 2100. }
}



@Article{deBoer2015,
author={de Boer, Pascal
and Hoogenboom, Jacob P.
and Giepmans, Ben N. G.},
title={Correlated light and electron microscopy: ultrastructure lights up!},
journal={Nature Methods},
year={2015},
month={Jun},
day={01},
volume={12},
number={6},
pages={503-513},
abstract={Correlated light and electron microscopy (CLEM) gives context to biomolecules studied with fluorescence microscopy. This Review discusses recent improvements and guides readers on probes, instrumentation and sample preparation to implement CLEM.},
issn={1548-7105},
doi={10.1038/nmeth.3400},
url={https://doi.org/10.1038/nmeth.3400}
}

@article{Swedlow2009,
author = {Swedlow, Jason R. and Goldberg, Ilya G. and Eliceiri, Kevin W. and },
title = {Bioimage Informatics for Experimental Biology},
journal = {Annual Review of Biophysics},
volume = {38},
number = {1},
pages = {327-346},
year = {2009},
doi = {10.1146/annurev.biophys.050708.133641},
note ={PMID: 19416072},
URL = {https://doi.org/10.1146/annurev.biophys.050708.133641},
eprint = {https://doi.org/10.1146/annurev.biophys.050708.133641},
    abstract = { Over the past twenty years there have been great advances in light microscopy with the result that multidimensional imaging has driven a revolution in modern biology. The development of new approaches of data acquisition is reported frequently, and yet the significant data management and analysis challenges presented by these new complex datasets remain largely unsolved. As in the well-developed field of genome bioinformatics, central repositories are and will be key resources, but there is a critical need for informatics tools in individual laboratories to help manage, share, visualize, and analyze image data. In this article we present the recent efforts by the bioimage informatics community to tackle these challenges, and discuss our own vision for future development of bioimage informatics solutions. }
}

@Article{Stringer2021,
author={Stringer, Carsen
and Wang, Tim
and Michaelos, Michalis
and Pachitariu, Marius},
title={Cellpose: a generalist algorithm for cellular segmentation},
journal={Nature Methods},
year={2021},
month={Jan},
day={01},
volume={18},
number={1},
pages={100-106},
abstract={Many biological applications require the segmentation of cell bodies, membranes and nuclei from microscopy images. Deep learning has enabled great progress on this problem, but current methods are specialized for images that have large training datasets. Here we introduce a generalist, deep learning-based segmentation method called Cellpose, which can precisely segment cells from a wide range of image types and does not require model retraining or parameter adjustments. Cellpose was trained on a new dataset of highly varied images of cells, containing over 70,000 segmented objects. We also demonstrate a three-dimensional (3D) extension of Cellpose that reuses the two-dimensional (2D) model and does not require 3D-labeled data. To support community contributions to the training data, we developed software for manual labeling and for curation of the automated results. Periodically retraining the model on the community-contributed data will ensure that Cellpose improves constantly.},
issn={1548-7105},
doi={10.1038/s41592-020-01018-x},
url={https://doi.org/10.1038/s41592-020-01018-x}
}



@Article{Shorten2019,
author={Shorten, Connor
and Khoshgoftaar, Taghi M.},
title={A survey on Image Data Augmentation for Deep Learning},
journal={Journal of Big Data},
year={2019},
month={Jul},
day={06},
volume={6},
number={1},
pages={60},
abstract={Deep convolutional neural networks have performed remarkably well on many Computer Vision tasks. However, these networks are heavily reliant on big data to avoid overfitting. Overfitting refers to the phenomenon when a network learns a function with very high variance such as to perfectly model the training data. Unfortunately, many application domains do not have access to big data, such as medical image analysis. This survey focuses on Data Augmentation, a data-space solution to the problem of limited data. Data Augmentation encompasses a suite of techniques that enhance the size and quality of training datasets such that better Deep Learning models can be built using them. The image augmentation algorithms discussed in this survey include geometric transformations, color space augmentations, kernel filters, mixing images, random erasing, feature space augmentation, adversarial training, generative adversarial networks, neural style transfer, and meta-learning. The application of augmentation methods based on GANs are heavily covered in this survey. In addition to augmentation techniques, this paper will briefly discuss other characteristics of Data Augmentation such as test-time augmentation, resolution impact, final dataset size, and curriculum learning. This survey will present existing methods for Data Augmentation, promising developments, and meta-level decisions for implementing Data Augmentation. Readers will understand how Data Augmentation can improve the performance of their models and expand limited datasets to take advantage of the capabilities of big data.},
issn={2196-1115},
doi={10.1186/s40537-019-0197-0},
url={https://doi.org/10.1186/s40537-019-0197-0}
}



@Article{Sarkans2021,
author={Sarkans, Ugis
and Chiu, Wah
and Collinson, Lucy
and Darrow, Michele C.
and Ellenberg, Jan
and Grunwald, David
and H{\'e}rich{\'e}, Jean-Karim
and Iudin, Andrii
and Martins, Gabriel G.
and Meehan, Terry
and Narayan, Kedar
and Patwardhan, Ardan
and Russell, Matthew Robert Geoffrey
and Saibil, Helen R.
and Strambio-De-Castillia, Caterina
and Swedlow, Jason R.
and Tischer, Christian
and Uhlmann, Virginie
and Verkade, Paul
and Barlow, Mary
and Bayraktar, Omer
and Birney, Ewan
and Catavitello, Cesare
and Cawthorne, Christopher
and Wagner-Conrad, Stephan
and Duke, Elizabeth
and Paul-Gilloteaux, Perrine
and Gustin, Emmanuel
and Harkiolaki, Maria
and Kankaanp{\"a}{\"a}, Pasi
and Lemberger, Thomas
and McEntyre, Jo
and Moore, Josh
and Nicholls, Andrew W.
and Onami, Shuichi
and Parkinson, Helen
and Parsons, Maddy
and Romanchikova, Marina
and Sofroniew, Nicholas
and Swoger, Jim
and Utz, Nadine
and Voortman, Lenard M.
and Wong, Frances
and Zhang, Peijun
and Kleywegt, Gerard J.
and Brazma, Alvis},
title={REMBI: Recommended Metadata for Biological Images---enabling reuse of microscopy data in biology},
journal={Nature Methods},
year={2021},
month={May},
day={21},
abstract={Bioimaging data have significant potential for reuse, but unlocking this potential requires systematic archiving of data and metadata in public databases. We propose draft metadata guidelines to begin addressing the needs of diverse communities within light and electron microscopy. We hope this publication and the proposed Recommended Metadata for Biological Images (REMBI) will stimulate discussions about their implementation and future extension.},
issn={1548-7105},
doi={10.1038/s41592-021-01166-8},
url={https://doi.org/10.1038/s41592-021-01166-8}
}





@article{Merkle2013, title={The Ascent of 3D X-ray Microscopy in the Laboratory}, volume={21}, DOI={10.1017/S1551929513000060}, number={2}, journal={Microscopy Today}, publisher={Cambridge University Press}, author={Merkle, Arno P. and Gelb, Jeff}, year={2013}, pages={10–15}}

@Article{Sato2020,
author={Sato, Yuki
and Boor, Peter
and Fukuma, Shingo
and Klinkhammer, Barbara M.
and Haga, Hironori
and Ogawa, Osamu
and Floege, J{\"u}rgen
and Yanagita, Motoko},
title={Developmental stages of tertiary lymphoid tissue reflect local injury and inflammation in mouse and human kidneys},
journal={Kidney International},
year={2020},
month={Aug},
day={01},
publisher={Elsevier},
volume={98},
number={2},
pages={448-463},
issn={0085-2538},
doi={10.1016/j.kint.2020.02.023},
url={https://doi.org/10.1016/j.kint.2020.02.023}
}

@article{DROBNE2005,
author = {DROBNE, D. and MILANI, M. and ZRIMEC, A. and LEŠER, V. and BERDEN ZRIMEC, M.},
title = {Electron and ion imaging of gland cells using the FIB/SEM system},
journal = {Journal of Microscopy},
volume = {219},
number = {1},
pages = {29-35},
keywords = {biological cell, digestive gland epithelium, FIB/ SEM system, Porcellio scaber, ultramicroscopy},
doi = {https://doi.org/10.1111/j.1365-2818.2005.01490.x},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-2818.2005.01490.x},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2818.2005.01490.x},
abstract = {Summary The FIB/SEM system was satisfactorily used for scanning ion (SIM) and scanning electron microscopy (SEM) of gland epithelial cells of a terrestrial isopod Porcellio scaber (Isopoda, Crustacea). The interior of cells was exposed by site-specific in situ focused ion beam (FIB) milling. Scanning ion (SI) imaging was an adequate substitution for scanning electron (SE) imaging when charging rendered SE imaging impossible. No significant differences in resolution between the SI and SE images were observed. The contrast on both the SI and SE images is a topographic. The consequences of SI imaging are, among others, introduction of Ga+ ions on/into the samples and destruction of the imaged surface. These two characteristics of SI imaging can be used advantageously. Introduction of Ga+ ions onto the specimen neutralizes the charge effect in the subsequent SE imaging. In addition, the destructive nature of SI imaging can be used as a tool for the gradual removal of the exposed layer of the imaged surface, uncovering the structures lying beneath. Alternative SEM and SIM in combination with site-specific in situ FIB sample sectioning made it possible to image the submicrometre structures of gland epithelium cells with reproducibility, repeatability and in the same range of magnifications as in transmission electron microscopy (TEM). At the present state of technology, ultrastructural elements imaged by the FIB/SEM system cannot be directly identified by comparison with TEM images.},
year = {2005}
}

@Article{Hirashima2020,
author={Hirashima, Shingo
and Kanazawa, Tomonoshin
and Ohta, Keisuke
and Nakamura, Kei-ichiro},
title={Three-dimensional ultrastructural imaging and quantitative analysis of the periodontal ligament},
journal={Anatomical Science International},
year={2020},
month={Jan},
day={01},
volume={95},
number={1},
pages={1-11},
abstract={The periodontal ligament (PDL) is a unique connective tissue mainly comprising collagen fiber bundles and cells between the roots of teeth and inner walls of the alveolar-bone socket. PDL fiber bundles are arrayed between teeth and bone, with both ends embedded in the cementum or alveolar bone as Sharpey's fiber. These bundles, synthesized by PDL fibroblasts (PDLFs), form several distinct groups within the PDL which has important functions besides tooth anchoring including tooth nutrition, proprioception, sensory detection, homoeostasis, and repair of damaged tissue. However, little is known about how the regular-PDL fiber bundle arrays are formed, maintained, and remodeled over large distances from cementum to alveolar bone. Recently, novel instruments and 3D-imaging methods have been developed that have been applied to the investigation of hard tissues including the PDL. Work from our laboratory has revealed the three-dimensional (3D) ultrastructure of PDLFs and PDL collagen bundles by focused ion beam/scanning electron microscope tomography. We have shown that PDLFs have a flat shape with long processes or a wing-like shape, while PDL bundles are a multiple-branched structure wrapped in thin sheets of PDLF cytoplasm. Furthermore, PDLFs form an extensive cellular network between the cementum and alveolar bone. The PDL cellular network is presumed to synchronize PDL fiber bundles and regulate arrays of PDL fiber bundles via gap junctions. In this review, we summarize and discuss our current 3D-histomorphometric studies of the PDL at the mesoscale level.},
issn={1447-073X},
doi={10.1007/s12565-019-00502-5},
url={https://doi.org/10.1007/s12565-019-00502-5}
}

@ARTICLE{Rodriguez2018,
AUTHOR={Rodríguez, José-Rodrigo and Turégano-López, Marta and DeFelipe, Javier and Merchán-Pérez, Angel},   	 
TITLE={Neuroanatomy from Mesoscopic to Nanoscopic Scales: An Improved Method for the Observation of Semithin Sections by High-Resolution Scanning Electron Microscopy},      
JOURNAL={Frontiers in Neuroanatomy},      	
VOLUME={12},      
PAGES={14},     
YEAR={2018},      
URL={https://www.frontiersin.org/article/10.3389/fnana.2018.00014},       
DOI={10.3389/fnana.2018.00014},      
ISSN={1662-5129},   
ABSTRACT={Semithin sections are commonly used to examine large areas of tissue with an optical microscope, in order to locate and trim the regions that will later be studied with the electron microscope. Ideally, the observation of semithin sections would be from mesoscopic to nanoscopic scales directly, instead of using light microscopy and then electron microscopy (EM). Here we propose a method that makes it possible to obtain high-resolution scanning EM images of large areas of the brain in the millimeter to nanometer range. Since our method is compatible with light microscopy, it is also feasible to generate hybrid light and electron microscopic maps. Additionally, the same tissue blocks that have been used to obtain semithin sections can later be used, if necessary, for transmission EM, or for focused ion beam milling and scanning electron microscopy (FIB-SEM).}
}

@ARTICLE{Kubota2018,
AUTHOR={Kubota, Yoshiyuki and Sohn, Jaerin and Kawaguchi, Yasuo},   
TITLE={Large Volume Electron Microscopy and Neural Microcircuit Analysis},      
JOURNAL={Frontiers in Neural Circuits},      
VOLUME={12},      
PAGES={98},     
YEAR={2018},      
URL={https://www.frontiersin.org/article/10.3389/fncir.2018.00098},       
DOI={10.3389/fncir.2018.00098},      
ISSN={1662-5110},   
ABSTRACT={One recent technical innovation in neuroscience is microcircuit analysis using three-dimensional reconstructions of neural elements with a large volume Electron microscopy (EM) data set. Large-scale data sets are acquired with newly-developed electron microscope systems such as automated tape-collecting ultramicrotomy (ATUM) with scanning EM (SEM), serial block-face EM (SBEM) and focused ion beam-SEM (FIB-SEM). Currently, projects are also underway to develop computer applications for the registration and segmentation of the serially-captured electron micrographs that are suitable for analyzing large volume EM data sets thoroughly and efficiently. The analysis of large volume data sets can bring innovative research results. These recently available techniques promote our understanding of the functional architecture of the brain.}
}

@article{Sun2017,
title = {Rate effects on localized shear deformation during nanosectioning of an amorphous thermoplastic polymer},
journal = {International Journal of Solids and Structures},
volume = {129},
pages = {40-48},
year = {2017},
issn = {0020-7683},
doi = {https://doi.org/10.1016/j.ijsolstr.2017.09.016},
url = {https://www.sciencedirect.com/science/article/pii/S0020768317304274},
author = {Fengzhen Sun and Hu Li and Klaus Leifer and E. Kristofer Gamstedt},
keywords = {Shear localization, Adiabatic shearing, Thermal softening, Nanosectioning},
abstract = {To investigate the effects of loading rate on the thermomechanical behavior of thermoplastic polymer during sectioning, polymethyl methacrylate (PMMA) sections with a thickness below 100 nm were made at different sectioning speeds by an instrumented ultramicrotome and the sectioning forces were measured. Atomic force microscopy was used to characterize the topographical features of the sectioned surfaces. Periodic structures of shear localizations were observed to form when the sectioning speed exceeded a critical value. With the measured sectioning parameters and other parameters determined based on previous studies, the effects of sectioning speed on the thermomechanical response of this polymer were analyzed using an existing adiabatic shearing model and a suitable constitutive law. A sectioning speed for the onset of shear localization was predicted, agreeing with the experimental results. The method presented in this work provides an approach to analyze the formation of shear localizations in polymers at the nanometer scale deformation.}
}

@article{Jesior1986,
title = {How to avoid compression II. The influence of sectioning conditions},
journal = {Journal of Ultrastructure and Molecular Structure Research},
volume = {95},
number = {1},
pages = {210-217},
year = {1986},
issn = {0889-1605},
doi = {https://doi.org/10.1016/0889-1605(86)90042-X},
url = {https://www.sciencedirect.com/science/article/pii/088916058690042X},
author = {Jean-Claude Jésior},
abstract = {The influence of sectioning conditions on the compression of polystyrene spheres embedded in an epoxy resin was investigated. Sections were performed on both native and hardened polystyrene spheres. The sectioning parameters were varied: diamond knife angle (26.6, 35.7, and 48.3°), clearance angle (1.8 to 8.8°), section thickness (10 to 90 nm), and sectioning speed (0.1 to 10 mm/sec). The results show that the highest compression factor was observed when sections were very thin and when the sectioning angle (defined as the sum of knife and clearance angles) was high. The compression factor was proportional to the sectioning angle whereas it was independent of the sectioning speed. Thus, to obtain reduced compression the microtomist should cut thicker ultrathin sections (50–90 nm) with a low-angle diamond knife (smaller than 30°) set at the smallest possible clearance angle. Under these conditions a reduction of compression by a factor of three to five can be obtained in ultrathin sections of soft specimens. The reader is reminded that compression can be completely eliminated when specimens are properly hardened during the preparation. Finally a two-region model based on the experimental results is proposed to explain the origin of compression.}
}

@article{Thomas2021,
 title={Targeting Functionally Characterized Synaptic Architecture Using Inherent Fiducials and 3D Correlative Microscopy}, volume={27}, DOI={10.1017/S1431927620024757}, number={1}, journal={Microscopy and Microanalysis}, publisher={Cambridge University Press}, author={Thomas, Connon I. and Ryan, Melissa A. and Scholl, Benjamin and Guerrero-Given, Debbie and Fitzpatrick, David and Kamasawa, Naomi}, year={2021}, pages={156–169}}

@article{Kurokawa2019,
    author = {Kurokawa, Kazuo and Osakada, Hiroko and Kojidani, Tomoko and Waga, Miho and Suda, Yasuyuki and Asakawa, Haruhiko and Haraguchi, Tokuko and Nakano, Akihiko},
    title = "{Visualization of secretory cargo transport within the Golgi apparatus}",
    journal = {Journal of Cell Biology},
    volume = {218},
    number = {5},
    pages = {1602-1618},
    year = {2019},
    month = {03},
    abstract = "{To describe trafficking of secretory cargo within the Golgi apparatus, the cisternal maturation model predicts that Golgi cisternae change their properties from cis to trans while cargo remains in the cisternae. Cisternal change has been demonstrated in living yeast Saccharomyces cerevisiae; however, the behavior of cargo has yet to be examined directly. In this study, we conducted simultaneous three-color and four-dimensional visualization of secretory transmembrane cargo together with early and late Golgi resident proteins. We show that cargo stays in a Golgi cisterna during maturation from cis-Golgi to trans-Golgi and further to the trans-Golgi network (TGN), which involves dynamic mixing and segregation of two zones of the earlier and later Golgi resident proteins. The location of cargo changes from the early to the late zone within the cisterna during the progression of maturation. In addition, cargo shows an interesting behavior during the maturation to the TGN. After most cargo has reached the TGN zone, a small amount of cargo frequently reappears in the earlier zone.}",
    issn = {0021-9525},
    doi = {10.1083/jcb.201807194},
    url = {https://doi.org/10.1083/jcb.201807194},
    eprint = {https://rupress.org/jcb/article-pdf/218/5/1602/1380577/jcb\_201807194.pdf},
}



@article {Collman2015,
	author = {Collman, Forrest and Buchanan, JoAnn and Phend, Kristen D. and Micheva, Kristina D. and Weinberg, Richard J. and Smith, Stephen J},
	title = {Mapping Synapses by Conjugate Light-Electron Array Tomography},
	volume = {35},
	number = {14},
	pages = {5792--5807},
	year = {2015},
	doi = {10.1523/JNEUROSCI.4274-14.2015},
	publisher = {Society for Neuroscience},
	abstract = {Synapses of the mammalian CNS are diverse in size, structure, molecular composition, and function. Synapses in their myriad variations are fundamental to neural circuit development, homeostasis, plasticity, and memory storage. Unfortunately, quantitative analysis and mapping of the brain{\textquoteright}s heterogeneous synapse populations has been limited by the lack of adequate single-synapse measurement methods. Electron microscopy (EM) is the definitive means to recognize and measure individual synaptic contacts, but EM has only limited abilities to measure the molecular composition of synapses. This report describes conjugate array tomography (AT), a volumetric imaging method that integrates immunofluorescence and EM imaging modalities in voxel-conjugate fashion. We illustrate the use of conjugate AT to advance the proteometric measurement of EM-validated single-synapse analysis in a study of mouse cortex.},
	issn = {0270-6474},
	URL = {https://www.jneurosci.org/content/35/14/5792},
	eprint = {https://www.jneurosci.org/content/35/14/5792.full.pdf},
	journal = {Journal of Neuroscience}
}

@article{Barajas1970,
  title={The ultrastructure of the juxtaglomerular apparatus as disclosed by three-dimensional reconstructions from serial sections. The anatomical relationship between the tubular and vascular components.},
  author={L. Barajas},
  journal={Journal of ultrastructure research},
  year={1970},
  volume={33 1},
  pages={116-47}
}

@Article{Lee2016,
author={Lee, Song-Yi
and Kang, Myeong-Gyun
and Park, Jong-Seok
and Lee, Geunsik
and Ting, Alice Y.
and Rhee, Hyun-Woo},
title={APEX Fingerprinting Reveals the Subcellular Localization of Proteins of Interest},
journal={Cell Reports},
year={2016},
month={May},
day={24},
publisher={Elsevier},
volume={15},
number={8},
pages={1837-1847},
issn={2211-1247},
doi={10.1016/j.celrep.2016.04.064},
url={https://doi.org/10.1016/j.celrep.2016.04.064}
}



@article{ Mavlyutov2017,
author = {Mavlyutov, Timur A and Yang, Huan and Epstein, Miles L and Ruoho, Arnold E and Yang, Jay and Guo, Lian-Wang}, 
title = {APEX2-enhanced electron microscopy distinguishes sigma-1 receptor localization in the nucleoplasmic reticulum}, 
journal = {Oncotarget},  
volume = {8}, 
number = {31}, 
publisher = {Impact Journals, LLC},  
issn = {1949-2553},  
url = {https://www.oncotarget.com/article/17906/}, 
doi = {https://doi.org/10.18632/oncotarget.17906}, 
pages = {51317-51330}, 
year = {2017}, 
} 

@article{Goo2017,
    author = {Goo, Marisa S. and Sancho, Laura and Slepak, Natalia and Boassa, Daniela and Deerinck, Thomas J. and Ellisman, Mark H. and Bloodgood, Brenda L. and Patrick, Gentry N.},
    title = "{Activity-dependent trafficking of lysosomes in dendrites and dendritic spines}",
    journal = {Journal of Cell Biology},
    volume = {216},
    number = {8},
    pages = {2499-2513},
    year = {2017},
    month = {06},
    abstract = "{In neurons, lysosomes, which degrade membrane and cytoplasmic components, are thought to primarily reside in somatic and axonal compartments, but there is little understanding of their distribution and function in dendrites. Here, we used conventional and two-photon imaging and electron microscopy to show that lysosomes traffic bidirectionally in dendrites and are present in dendritic spines. We find that lysosome inhibition alters their mobility and also decreases dendritic spine number. Furthermore, perturbing microtubule and actin cytoskeletal dynamics has an inverse relationship on the distribution and motility of lysosomes in dendrites. We also find trafficking of lysosomes is correlated with synaptic α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid–type glutamate receptors. Strikingly, lysosomes traffic to dendritic spines in an activity-dependent manner and can be recruited to individual spines in response to local activation. These data indicate the position of lysosomes is regulated by synaptic activity and thus plays an instructive role in the turnover of synaptic membrane proteins.}",
    issn = {0021-9525},
    doi = {10.1083/jcb.201704068},
    url = {https://doi.org/10.1083/jcb.201704068},
    eprint = {https://rupress.org/jcb/article-pdf/216/8/2499/1376236/jcb\_201704068.pdf},
}





@article{Ariotti2018,
    doi = {10.1371/journal.pbio.2005473},
    author = {Ariotti, Nicholas and Rae, James and Giles, Nichole and Martel, Nick and Sierecki, Emma and Gambin, Yann and Hall, Thomas E. and Parton, Robert G.},
    journal = {PLOS Biology},
    publisher = {Public Library of Science},
    title = {Ultrastructural localisation of protein interactions using conditionally stable nanobodies},
    year = {2018},
    month = {04},
    volume = {16},
    url = {https://doi.org/10.1371/journal.pbio.2005473},
    pages = {1-11},
    abstract = {We describe the development and application of a suite of modular tools for high-resolution detection of proteins and intracellular protein complexes by electron microscopy (EM). Conditionally stable GFP- and mCherry-binding nanobodies (termed csGBP and csChBP, respectively) are characterized using a cell-free expression and analysis system and subsequently fused to an ascorbate peroxidase (APEX) enzyme. Expression of these cassettes alongside fluorescently labelled proteins results in recruitment and stabilisation of APEX, whereas unbound APEX nanobodies are efficiently degraded by the proteasome. This greatly simplifies correlative analyses, enables detection of less-abundant proteins, and eliminates the need to balance expression levels between fluorescently labelled and APEX nanobody proteins. Furthermore, we demonstrate the application of this system to bimolecular complementation (‘EM split-fluorescent protein’), for localisation of protein–protein interactions at the ultrastructural level.},
    number = {4},

}

@Article{Martell2017,
author={Martell, Jeffrey D.
and Deerinck, Thomas J.
and Lam, Stephanie S.
and Ellisman, Mark H.
and Ting, Alice Y.},
title={Electron microscopy using the genetically encoded APEX2 tag in cultured mammalian cells},
journal={Nature Protocols},
year={2017},
month={Sep},
day={01},
volume={12},
number={9},
pages={1792-1816},
abstract={This protocol describes procedures for using the genetic tag APEX2 to generate contrast for electron microscopy in cultured cells.},
issn={1750-2799},
doi={10.1038/nprot.2017.065},
url={https://doi.org/10.1038/nprot.2017.065}
}



@Article{Lam2015,
author={Lam, Stephanie S.
and Martell, Jeffrey D.
and Kamer, Kimberli J.
and Deerinck, Thomas J.
and Ellisman, Mark H.
and Mootha, Vamsi K.
and Ting, Alice Y.},
title={Directed evolution of APEX2 for electron microscopy and proximity labeling},
journal={Nature Methods},
year={2015},
month={Jan},
day={01},
volume={12},
number={1},
pages={51-54},
abstract={A genetically encoded peroxidase with improved sensitivity, APEX2, is reported for electron microscopy and proximity labeling at low expression levels.},
issn={1548-7105},
doi={10.1038/nmeth.3179},
url={https://doi.org/10.1038/nmeth.3179}
}



@article {Hung2017,
article_type = {journal},
title = {Proteomic mapping of cytosol-facing outer mitochondrial and ER membranes in living human cells by proximity biotinylation},
author = {Hung, Victoria and Lam, Stephanie S and Udeshi, Namrata D and Svinkina, Tanya and Guzman, Gaelen and Mootha, Vamsi K and Carr, Steven A and Ting, Alice Y},
editor = {Pagliarini, David},
volume = 6,
year = 2017,
month = {apr},
pub_date = {2017-04-25},
pages = {e24463},
citation = {eLife 2017;6:e24463},
doi = {10.7554/eLife.24463},
url = {https://doi.org/10.7554/eLife.24463},
abstract = {The cytosol-facing membranes of cellular organelles contain proteins that enable signal transduction, regulation of morphology and trafficking, protein import and export, and other specialized processes. Discovery of these proteins by traditional biochemical fractionation can be plagued with contaminants and loss of key components. Using peroxidase-mediated proximity biotinylation, we captured and identified endogenous proteins on the outer mitochondrial membrane (OMM) and endoplasmic reticulum membrane (ERM) of living human fibroblasts. The proteomes of 137 and 634 proteins, respectively, are highly specific and highlight 94 potentially novel mitochondrial or ER proteins. Dataset intersection identified protein candidates potentially localized to mitochondria-ER contact sites. We found that one candidate, the tail-anchored, PDZ-domain-containing OMM protein SYNJ2BP, dramatically increases mitochondrial contacts with rough ER when overexpressed. Immunoprecipitation-mass spectrometry identified ribosome-binding protein 1 (RRBP1) as SYNJ2BP’s ERM binding partner. Our results highlight the power of proximity biotinylation to yield insights into the molecular composition and function of intracellular membranes.},
keywords = {microscopy, promiscuous enzymatic labeling, subcellular regions, APEX2, mitochondria-ER junctions, mitochondria-associated membrane},
journal = {eLife},
issn = {2050-084X},
publisher = {eLife Sciences Publications, Ltd},
}


@Article{Livet2007,
author={Livet, Jean
and Weissman, Tamily A.
and Kang, Hyuno
and Draft, Ryan W.
and Lu, Ju
and Bennis, Robyn A.
and Sanes, Joshua R.
and Lichtman, Jeff W.},
title={Transgenic strategies for combinatorial expression of fluorescent proteins in the nervous system},
journal={Nature},
year={2007},
month={Nov},
day={01},
volume={450},
number={7166},
pages={56-62},
abstract={Detailed analysis of neuronal network architecture requires the development of new methods. Here we present strategies to visualize synaptic circuits by genetically labelling neurons with multiple, distinct colours. In Brainbow transgenes, Cre/lox recombination is used to create a stochastic choice of expression between three or more fluorescent proteins (XFPs). Integration of tandem Brainbow copies in transgenic mice yielded combinatorial XFP expression, and thus many colours, thereby providing a way to distinguish adjacent neurons and visualize other cellular interactions. As a demonstration, we reconstructed hundreds of neighbouring axons and multiple synaptic contacts in one small volume of a cerebellar lobe exhibiting approximately 90 colours. The expression in some lines also allowed us to map glial territories and follow glial cells and neurons over time in vivo. The ability of the Brainbow system to label uniquely many individual cells within a population may facilitate the analysis of neuronal circuitry on a large scale.},
issn={1476-4687},
doi={10.1038/nature06293},
url={https://doi.org/10.1038/nature06293}
}



@article{Weissman2015,
    author = {Weissman, Tamily A and Pan, Y Albert},
    title = "{Brainbow: New Resources and Emerging Biological Applications for Multicolor Genetic Labeling and Analysis}",
    journal = {Genetics},
    volume = {199},
    number = {2},
    pages = {293-306},
    year = {2015},
    month = {02},
    abstract = "{Brainbow is a genetic cell-labeling technique where hundreds of different hues can be generated by stochastic and combinatorial expression of a few spectrally distinct fluorescent proteins. Unique color profiles can be used as cellular identification tags for multiple applications such as tracing axons through the nervous system, following individual cells during development, or analyzing cell lineage. In recent years, Brainbow and other combinatorial expression strategies have expanded from the mouse nervous system to other model organisms and a wide variety of tissues. Particularly exciting is the application of Brainbow in lineage tracing, where this technique has been instrumental in parsing out complex cellular relationships during organogenesis. Here we review recent findings, new technical improvements, and exciting potential genetic and genomic applications for harnessing this colorful technique in anatomical, developmental, and genetic studies.}",
    issn = {1943-2631},
    doi = {10.1534/genetics.114.172510},
    url = {https://doi.org/10.1534/genetics.114.172510},
    eprint = {https://academic.oup.com/genetics/article-pdf/199/2/293/37802699/genetics0293.pdf},
}





@article{Pan2013,
    author = {Pan, Y. Albert and Freundlich, Tom and Weissman, Tamily A. and Schoppik, David and Wang, X. Cindy and Zimmerman, Steve and Ciruna, Brian and Sanes, Joshua R. and Lichtman, Jeff W. and Schier, Alexander F.},
    title = "{Zebrabow: multispectral cell labeling for cell tracing and lineage analysis in zebrafish}",
    journal = {Development},
    volume = {140},
    number = {13},
    pages = {2835-2846},
    year = {2013},
    month = {07},
    abstract = "{Advances in imaging and cell-labeling techniques have greatly enhanced our understanding of developmental and neurobiological processes. Among vertebrates, zebrafish is uniquely suited for in vivo imaging owing to its small size and optical translucency. However, distinguishing and following cells over extended time periods remains difficult. Previous studies have demonstrated that Cre recombinase-mediated recombination can lead to combinatorial expression of spectrally distinct fluorescent proteins (RFP, YFP and CFP) in neighboring cells, creating a ‘Brainbow’ of colors. The random combination of fluorescent proteins provides a way to distinguish adjacent cells, visualize cellular interactions and perform lineage analyses. Here, we describe Zebrabow (Zebrafish Brainbow) tools for in vivo multicolor imaging in zebrafish. First, we show that the broadly expressed ubi:Zebrabow line provides diverse color profiles that can be optimized by modulating Cre activity. Second, we find that colors are inherited equally among daughter cells and remain stable throughout embryonic and larval stages. Third, we show that UAS:Zebrabow lines can be used in combination with Gal4 to generate broad or tissue-specific expression patterns and facilitate tracing of axonal processes. Fourth, we demonstrate that Zebrabow can be used for long-term lineage analysis. Using the cornea as a model system, we provide evidence that embryonic corneal epithelial clones are replaced by large, wedge-shaped clones formed by centripetal expansion of cells from the peripheral cornea. The Zebrabow tool set presented here provides a resource for next-generation color-based anatomical and lineage analyses in zebrafish.}",
    issn = {0950-1991},
    doi = {10.1242/dev.094631},
    url = {https://doi.org/10.1242/dev.094631},
    eprint = {https://journals.biologists.com/dev/article-pdf/140/13/2835/1162571/2835.pdf},
}





@article{Barajas1973,
title = {The innervation of the juxtaglomerular apparatus and surrounding tubules: A quantitative analysis by serial section electron microscopy},
journal = {Journal of Ultrastructure Research},
volume = {43},
number = {1},
pages = {107-132},
year = {1973},
issn = {0022-5320},
doi = {https://doi.org/10.1016/S0022-5320(73)90073-7},
url = {https://www.sciencedirect.com/science/article/pii/S0022532073900737},
author = {Luciano Barajas and Jacqueline Müller},
abstract = {In electron micrographs of serial sections of a rat juxtaglomerular apparatus “axon segments” were analyzed for contact with the cells of the vascular component and surrounding tubules. Slightly less than one-fourth of the cells of the vascular component were innervated. Nerve endings were seen on less than one-third of the cells of the afferent arteriole and about one-third of the cells of the efferent arteriole. The mesangial region had only 3 of its 30 cells innervated. Of these 3 cells, 2 were in contact with the distal tubule. The majority of the innervated cells were contacted by nerve endings belonging to more than one axon segment. Frequently en passant nerve endings from the same axon were seen to contact several different cells (granular and agranular) of the vascular component. Individual axons also established en passant contact with granular and agranular cells of the vascular component and tubular cells. These findings support the view that the neural effect on renin secretion is t the result of a complex response to neural activity which includes, besides direct action on granular cells, indirect action mediated through its effect on arteriolar and renal tubular systems.}
}

@Article{Kamdar2021,
author={Kamdar, Maulik R.
and Musen, Mark A.},
title={An empirical meta-analysis of the life sciences linked open data on the web},
journal={Scientific Data},
year={2021},
month={Jan},
day={21},
volume={8},
number={1},
pages={24},
abstract={While the biomedical community has published several ``open data'' sources in the last decade, most researchers still endure severe logistical and technical challenges to discover, query, and integrate heterogeneous data and knowledge from multiple sources. To tackle these challenges, the community has experimented with Semantic Web and linked data technologies to create the Life Sciences Linked Open Data (LSLOD) cloud. In this paper, we extract schemas from more than 80 biomedical linked open data sources into an LSLOD schema graph and conduct an empirical meta-analysis to evaluate the extent of semantic heterogeneity across the LSLOD cloud. We observe that several LSLOD sources exist as stand-alone data sources that are not inter-linked with other sources, use unpublished schemas with minimal reuse or mappings, and have elements that are not useful for data integration from a biomedical perspective. We envision that the LSLOD schema graph and the findings from this research will aid researchers who wish to query and integrate data and knowledge from multiple biomedical sources simultaneously on the Web.},
issn={2052-4463},
doi={10.1038/s41597-021-00797-y},
url={https://doi.org/10.1038/s41597-021-00797-y}
}



@article{Spiers2021,
author = {Spiers, Helen and Songhurst, Harry and Nightingale, Luke and de Folter, Joost and The Zooniverse Volunteer Community and Hutchings, Roger and Peddie, Christopher J. and Weston, Anne and Strange, Amy and Hindmarsh, Steve and Lintott, Chris and Collinson, Lucy M. and Jones, Martin L.},
title = {Deep learning for automatic segmentation of the nuclear envelope in electron microscopy data, trained with volunteer segmentations},
journal = {Traffic},
volume = {22},
number = {7},
pages = {240-253},
keywords = {cell biology, cellular imaging, citizen science, image processing, machine learning, segmentation, volume electron microscopy},
doi = {https://doi.org/10.1111/tra.12789},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/tra.12789},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/tra.12789},
abstract = {Abstract Advancements in volume electron microscopy mean it is now possible to generate thousands of serial images at nanometre resolution overnight, yet the gold standard approach for data analysis remains manual segmentation by an expert microscopist, resulting in a critical research bottleneck. Although some machine learning approaches exist in this domain, we remain far from realizing the aspiration of a highly accurate, yet generic, automated analysis approach, with a major obstacle being lack of sufficient high-quality ground-truth data. To address this, we developed a novel citizen science project, Etch a Cell, to enable volunteers to manually segment the nuclear envelope (NE) of HeLa cells imaged with serial blockface scanning electron microscopy. We present our approach for aggregating multiple volunteer annotations to generate a high-quality consensus segmentation and demonstrate that data produced exclusively by volunteers can be used to train a highly accurate machine learning algorithm for automatic segmentation of the NE, which we share here, in addition to our archived benchmark data.},
year = {2021}
}

@article{Melia2019,
author = {Charlotte E. Melia  and Christopher J. Peddie  and Anja W. M. de Jong  and Eric J. Snijder  and Lucy M. Collinson  and Abraham J. Koster  and Hilde M. van der Schaar  and Frank J. M. van Kuppeveld  and Montserrat Bárcena  and Michael J. Buchmeier  and Benjamin Neuman  and Stanley Lemon },
title = {Origins of Enterovirus Replication Organelles Established by Whole-Cell Electron Microscopy},
journal = {mBio},
volume = {10},
number = {3},
pages = {e00951-19},
year = {2019},
doi = {10.1128/mBio.00951-19},
URL = {https://journals.asm.org/doi/abs/10.1128/mBio.00951-19},
eprint = {https://journals.asm.org/doi/pdf/10.1128/mBio.00951-19},
    abstract = { Enteroviruses are causative agents of a range of human diseases. The replication of these viruses within cells relies on specialized membranous structures termed replication organelles (ROs) that form during infection but whose origin remains elusive. To capture the emergence of enterovirus ROs, we use correlative light and serial block-face scanning electron microscopy, a powerful method to pinpoint rare events in their whole-cell ultrastructural context. RO biogenesis was found to occur first at ER and then at Golgi membranes. Extensive contacts were found between early ROs and lipid droplets (LDs), which likely serve to provide LD-derived lipids required for replication. Together, these data establish the dual origin of enterovirus ROs and the chronology of their biogenesis at different supporting cellular membranes. Enterovirus genome replication occurs at virus-induced structures derived from cellular membranes and lipids. However, the origin of these replication organelles (ROs) remains uncertain. Ultrastructural evidence of the membrane donor is lacking, suggesting that the sites of its transition into ROs are rare or fleeting. To overcome this challenge, we combined live-cell imaging and serial block-face scanning electron microscopy of whole cells to capture emerging enterovirus ROs. The first foci of fluorescently labeled viral protein correlated with ROs connected to the endoplasmic reticulum (ER) and preceded the appearance of ROs stemming from the trans-Golgi network. Whole-cell data sets further revealed striking contact regions between ROs and lipid droplets that may represent a route for lipid shuttling to facilitate RO proliferation and genome replication. Our data provide direct evidence that enteroviruses use ER and then Golgi membranes to initiate RO formation, demonstrating the remarkable flexibility with which enteroviruses usurp cellular organelles. IMPORTANCE Enteroviruses are causative agents of a range of human diseases. The replication of these viruses within cells relies on specialized membranous structures termed replication organelles (ROs) that form during infection but whose origin remains elusive. To capture the emergence of enterovirus ROs, we use correlative light and serial block-face scanning electron microscopy, a powerful method to pinpoint rare events in their whole-cell ultrastructural context. RO biogenesis was found to occur first at ER and then at Golgi membranes. Extensive contacts were found between early ROs and lipid droplets (LDs), which likely serve to provide LD-derived lipids required for replication. Together, these data establish the dual origin of enterovirus ROs and the chronology of their biogenesis at different supporting cellular membranes. }
}




@article{Puhka2012,
author = {Puhka, Maija and Joensuu, Merja and Vihinen, Helena and Belevich, Ilya and Jokitalo, Eija},
title = {Progressive sheet-to-tubule transformation is a general mechanism for endoplasmic reticulum partitioning in dividing mammalian cells},
journal = {Molecular Biology of the Cell},
volume = {23},
number = {13},
pages = {2424-2432},
year = {2012},
doi = {10.1091/mbc.e10-12-0950},
note ={PMID: 22573885},
URL = {https://doi.org/10.1091/mbc.e10-12-0950},
eprint = {https://doi.org/10.1091/mbc.e10-12-0950},
    abstract = { The endoplasmic reticulum (ER) is both structurally and functionally complex, consisting of a dynamic network of interconnected sheets and tubules. To achieve a more comprehensive view of ER organization in interphase and mitotic cells and to address a discrepancy in the field (i.e., whether ER sheets persist, or are transformed to tubules, during mitosis), we analyzed the ER in four different mammalian cell lines using live-cell imaging, high-resolution electron microscopy, and three dimensional electron microscopy. In interphase cells, we found great variation in network organization and sheet structures among different cell lines. In mitotic cells, we show that the ER undergoes both spatial reorganization and structural transformation of sheets toward more fenestrated and tubular forms. However, the extent of spatial reorganization and sheet-to-tubule transformation varies among cell lines. Fenestration and tubulation of the ER correlates with a reduced number of membrane-bound ribosomes. }
}




@article{Russell2017,
    author = {Russell, Matthew R. G. and Lerner, Thomas R. and Burden, Jemima J. and Nkwe, David O. and Pelchen-Matthews, Annegret and Domart, Marie-Charlotte and Durgan, Joanne and Weston, Anne and Jones, Martin L. and Peddie, Christopher J. and Carzaniga, Raffaella and Florey, Oliver and Marsh, Mark and Gutierrez, Maximiliano G. and Collinson, Lucy M. and Ewald, Andrew},
    title = "{3D correlative light and electron microscopy of cultured cells using serial blockface scanning electron microscopy}",
    journal = {Journal of Cell Science},
    volume = {130},
    number = {1},
    pages = {278-291},
    year = {2017},
    month = {01},
    abstract = "{The processes of life take place in multiple dimensions, but imaging these processes in even three dimensions is challenging. Here, we describe a workflow for 3D correlative light and electron microscopy (CLEM) of cell monolayers using fluorescence microscopy to identify and follow biological events, combined with serial blockface scanning electron microscopy to analyse the underlying ultrastructure. The workflow encompasses all steps from cell culture to sample processing, imaging strategy, and 3D image processing and analysis. We demonstrate successful application of the workflow to three studies, each aiming to better understand complex and dynamic biological processes, including bacterial and viral infections of cultured cells and formation of entotic cell-in-cell structures commonly observed in tumours. Our workflow revealed new insight into the replicative niche of Mycobacterium tuberculosis in primary human lymphatic endothelial cells, HIV-1 in human monocyte-derived macrophages, and the composition of the entotic vacuole. The broad application of this 3D CLEM technique will make it a useful addition to the correlative imaging toolbox for biomedical research.}",
    issn = {0021-9533},
    doi = {10.1242/jcs.188433},
    url = {https://doi.org/10.1242/jcs.188433},
    eprint = {https://journals.biologists.com/jcs/article-pdf/130/1/278/1962022/jcs188433.pdf},
}





@article{KREMER2015,
author = {KREMER, A. and LIPPENS, S. and BARTUNKOVA, S. and ASSELBERGH, B. and BLANPAIN, C. and FENDRYCH, M. and GOOSSENS, A. and HOLT, M. and JANSSENS, S. and KROLS, M. and LARSIMONT, J.-C. and Mc GUIRE, C. and NOWACK, M.K. and SAELENS, X. and SCHERTEL, A. and SCHEPENS, B. and SLEZAK, M. and TIMMERMAN, V. and THEUNIS, C. and VAN BREMPT, R. and VISSER, Y. and GUÉRIN, C.J.},
title = {Developing 3D SEM in a broad biological context},
journal = {Journal of Microscopy},
volume = {259},
number = {2},
pages = {80-96},
keywords = {Correlative light and electron microscopy, focused ion beam scanning electron microscopy, sample preparation, serial block-face scanning electron microscopy},
doi = {https://doi.org/10.1111/jmi.12211},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/jmi.12211},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/jmi.12211},
abstract = {Summary When electron microscopy (EM) was introduced in the 1930s it gave scientists their first look into the nanoworld of cells. Over the last 80 years EM has vastly increased our understanding of the complex cellular structures that underlie the diverse functions that cells need to maintain life. One drawback that has been difficult to overcome was the inherent lack of volume information, mainly due to the limit on the thickness of sections that could be viewed in a transmission electron microscope (TEM). For many years scientists struggled to achieve three-dimensional (3D) EM using serial section reconstructions, TEM tomography, and scanning EM (SEM) techniques such as freeze-fracture. Although each technique yielded some special information, they required a significant amount of time and specialist expertise to obtain even a very small 3D EM dataset. Almost 20 years ago scientists began to exploit SEMs to image blocks of embedded tissues and perform serial sectioning of these tissues inside the SEM chamber. Using first focused ion beams (FIB) and subsequently robotic ultramicrotomes (serial block-face, SBF-SEM) microscopists were able to collect large volumes of 3D EM information at resolutions that could address many important biological questions, and do so in an efficient manner. We present here some examples of 3D EM taken from the many diverse specimens that have been imaged in our core facility. We propose that the next major step forward will be to efficiently correlate functional information obtained using light microscopy (LM) with 3D EM datasets to more completely investigate the important links between cell structures and their functions.},
year = {2015}
}



@Article{Miyazono2018,
author={Miyazono, Yoshihiro
and Hirashima, Shingo
and Ishihara, Naotada
and Kusukawa, Jingo
and Nakamura, Kei-ichiro
and Ohta, Keisuke},
title={Uncoupled mitochondria quickly shorten along their long axis to form indented spheroids, instead of rings, in a fission-independent manner},
journal={Scientific Reports},
year={2018},
month={Jan},
day={10},
volume={8},
number={1},
pages={350},
abstract={Loss of mitochondrial membrane potential ($\Delta$$\Psi$m) triggers dramatic structural changes in mitochondria from a tubular to globular shape, referred to as mitochondrial fragmentation; the resulting globular mitochondria are called swelled or ring/doughnut mitochondria. We evaluated the early period of structural changes during the $\Delta$$\Psi$m loss-induced transformation after carbonyl cyanide m-chlorophenyl hydrazine (CCCP) administration using a newly developed correlative microscopic method combined with fluorescence microscopic live imaging and volume electron microscopy. We found that most mitochondria changed from a tubular shape to a globular shape without fusion or fission and typically showed ring shapes within 10{\thinspace}min after CCCP exposure. In contrast, most ring mitochondria did not have a true through hole; rather, they had various indents, and 47{\%} showed stomatocyte shapes with vase-shaped cavities, which is the most stable physical structure without any structural support if the long tubular shape shortens into a sphere. Our results suggested that loss of $\Delta$$\Psi$m triggered collapse of mitochondrial structural support mechanisms.},
issn={2045-2322},
doi={10.1038/s41598-017-18582-6},
url={https://doi.org/10.1038/s41598-017-18582-6}
}



@Article{Smith2018,
author={Smith, Stephen J.},
title={Q{\&}A: Array tomography},
journal={BMC Biology},
year={2018},
month={Sep},
day={06},
volume={16},
number={1},
pages={98},
abstract={Array tomography encompasses light and electron microscopy modalities that offer unparalleled opportunities to explore three-dimensional cellular architectures in extremely fine structural and molecular detail. Fluorescence array tomography achieves much higher resolution and molecular multiplexing than most other fluorescence microscopy methods, while electron array tomography can capture three-dimensional ultrastructure much more easily and rapidly than traditional serial-section electron microscopy methods. A correlative fluorescence/electron microscopy mode of array tomography furthermore offers a unique capacity to merge the molecular discrimination strengths of multichannel fluorescence microscopy with the ultrastructural imaging strengths of electron microscopy. This essay samples the first decade of array tomography, highlighting applications in neuroscience.},
issn={1741-7007},
doi={10.1186/s12915-018-0560-1},
url={https://doi.org/10.1186/s12915-018-0560-1}
}



@article{Booth2019,
    author = {Booth, Daniel G. and Beckett, Alison J. and Prior, Ian A. and Meijer, Dies},
    title = "{SuperCLEM: an accessible correlative light and electron microscopy approach for investigation of neurons and glia in vitro}",
    journal = {Biology Open},
    volume = {8},
    number = {5},
    year = {2019},
    month = {05},
    abstract = "{The rapid evolution of super-resolution light microscopy has narrowed the gap between light and electron microscopy, allowing the imaging of molecules and cellular structures at high resolution within their normal cellular and tissue context. Multimodal imaging approaches such as correlative light electron microscopy (CLEM) combine these techniques to create a tool with unique imaging capacity. However, these approaches are typically reserved for specialists, and their application to the analysis of neural tissue is challenging. Here we present SuperCLEM, a relatively simple approach that combines super-resolution fluorescence light microscopy (FLM), 3D electron microscopy (3D-EM) and rendering into 3D models. We demonstrate our workflow using neuron-glia cultures from which we first acquire high-resolution fluorescent light images of myelinated axons. After resin embedding and re-identification of the region of interest, serially aligned EM sections are acquired and imaged using a serial block face scanning electron microscope (SBF-SEM). The FLM and 3D-EM datasets are then combined to render 3D models of the myelinated axons. Thus, the SuperCLEM imaging pipeline is a useful new tool for researchers pursuing similar questions in neuronal and other complex tissue culture systems.}",
    issn = {2046-6390},
    doi = {10.1242/bio.042085},
    url = {https://doi.org/10.1242/bio.042085},
    note = {bio042085},
    eprint = {https://journals.biologists.com/bio/article-pdf/8/5/bio042085/1829285/bio042085.pdf},
}





@inproceedings{Pishak2002,
author = {Vasyl P. Pishak and K. B. Tymochko and O. P. Antoniuk},
title = {{Automative morphome analysis of medical-biological images}},
volume = {4607},
booktitle = {Selected Papers from Fifth International Conference on Correlation Optics},
editor = {Oleg V. Angelsky},
organization = {International Society for Optics and Photonics},
publisher = {SPIE},
pages = {411 -- 413},
year = {2002},
doi = {},
URL = {https://doi.org/10.1117/12.455225}
}

@inproceedings{Kaynig2010tem,
author = {Kaynig, Verena and Fuchs, Thomas and Buhmann, Joachim},
year = {2010},
month = {06},
pages = {2902-2909},
title = {Neuron geometry extraction by perceptual grouping in ssTEM images},
journal = {Computer Vision and Pattern Recognition (CVPR), 2010 IEEE Conference on. IEEE},
doi = {10.1109/CVPR.2010.5540029}
}

@article{Meijering2020,
title = {A bird’s-eye view of deep learning in bioimage analysis},
journal = {Computational and Structural Biotechnology Journal},
volume = {18},
pages = {2312-2325},
year = {2020},
issn = {2001-0370},
doi = {https://doi.org/10.1016/j.csbj.2020.08.003},
url = {https://www.sciencedirect.com/science/article/pii/S2001037020303561},
author = {Erik Meijering},
keywords = {Deep learning, Artificial neural networks, Bioimage analysis, Microscopy imaging, Computer vision},
abstract = {Deep learning of artificial neural networks has become the de facto standard approach to solving data analysis problems in virtually all fields of science and engineering. Also in biology and medicine, deep learning technologies are fundamentally transforming how we acquire, process, analyze, and interpret data, with potentially far-reaching consequences for healthcare. In this mini-review, we take a bird’s-eye view at the past, present, and future developments of deep learning, starting from science at large, to biomedical imaging, and bioimage analysis in particular.}
}





@article{Liu2019,
author = {Wei Liu and Heng Shi and Xingyang He and Shang Pan and Zhiwei Ye and Yingbin Wang},
title ={An application of optimized Otsu multi-threshold segmentation based on fireworks algorithm in cement SEM image},
journal = {Journal of Algorithms \& Computational Technology},
volume = {13},
number = {},
pages = {1748301818797025},
year = {2019},
doi = {10.1177/1748301818797025},

URL = { 
        https://doi.org/10.1177/1748301818797025
    
},
eprint = { 
        https://doi.org/10.1177/1748301818797025
    
}

}


@incollection{ROGOWSKA2009,
title = {Chapter 5 - Overview and Fundamentals of Medical Image Segmentation},
editor = {ISAAC N. BANKMAN},
booktitle = {Handbook of Medical Image Processing and Analysis (Second Edition)},
publisher = {Academic Press},
edition = {Second Edition},
address = {Burlington},
pages = {73-90},
year = {2009},
isbn = {978-0-12-373904-9},
doi = {https://doi.org/10.1016/B978-012373904-9.50013-1},
url = {https://www.sciencedirect.com/science/article/pii/B9780123739049500131},
author = {Jadwiga Rogowska}
}


@misc{Swedlow2020,
title = "Open Microscopy Environment: OME is a consortium of universities, research labs, industry and developers producing open-source software and format standards for microscopy data.",
abstract = "Despite significant advances in biological imaging and analysis, major informatics challenges remain unsolved: file formats are proprietary, storage and analysis facilities are lacking, as are standards for sharing image data and results. The Open Microscopy Environment (OME) is an open-source software framework developed to address these challenges. OME releases specifications and software for managing image datasets and integrating them with other scientific data. OME{\textquoteright}s Bio-Formats is a file translator that enables scientists to open and work with imaging data in the software application of their choice. OMERO is an image database application that provides data management and sharing capabilities to imaging scientists. Bio-Formats and OMERO are used in 1000{\textquoteright}s of labs worldwide to enable discovery with imaging. Additionally, we have used Bio-Formats and OMERO to build a system for publishing imaging data associated with peer-reviewed publications. The Image Data Resource (IDR) has published >85 studies and > 176 TB of imaging data annotated with >19,000 genes and 31,000 small molecules inhibitors and drugs. IDR includes a cloud-based analysis portal to catalyse the re-use and re-analysis of published imaging data. ",
author = "Jason Swedlow",
year = "2020",
language = "English"
}

@article{Heuser2000,
author = {Heuser, John},
title = {How to Convert a Traditional Electron Microscopy Laboratory to Digital Imaging: Follow the ‘Middle Road’},
journal = {Traffic},
volume = {1},
number = {8},
pages = {614-621},
keywords = {Digital imaging, electron microscopy, resolution},
doi = {https://doi.org/10.1034/j.1600-0854.2000.010805.x},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1034/j.1600-0854.2000.010805.x},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1034/j.1600-0854.2000.010805.x},
abstract = {Today, electron microscopy (EM) is increasingly confronted by the revolution in image-processing technology provoked by modern computers. Digital cameras are fast replacing film-based cameras in EM, as elsewhere, and the procedures for digital image-archiving, image-analysis, and image publication are rapidly evolving. To take advantage of these advances, we have chosen for the moment a ‘middle road’, in which film remains our basic recording medium in the electron microscope, but immediately thereafter, all film-based images are converted to digital files for further analysis and processing. The rationale behind this approach is that film still offers far greater sensitivity and resolution (providing an image equivalent to> 10 000 pixels per inch in a 1-s exposure), and film is still far easier to organize and archive than digital images of comparable resolution. However, digital manipulation of EM images has become mandatory. Hence, we explain here, in some detail, how we convert from film to digital.},
year = {2000}
}

@Article{Eliceiri2012,
author={Eliceiri, Kevin W.
and Berthold, Michael R.
and Goldberg, Ilya G.
and Ib{\'a}{\~{n}}ez, Luis
and Manjunath, B. S.
and Martone, Maryann E.
and Murphy, Robert F.
and Peng, Hanchuan
and Plant, Anne L.
and Roysam, Badrinath
and Stuurman, Nico
and Swedlow, Jason R.
and Tomancak, Pavel
and Carpenter, Anne E.},
title={Biological imaging software tools},
journal={Nature Methods},
year={2012},
month={Jul},
day={01},
volume={9},
number={7},
pages={697-710},
abstract={Representative members of the bioimage informatics community review the computational steps and some of the primary software tools available to biologists who are acquiring and analyzing microscopy-based digital image data, with a focus on open-source options.},
issn={1548-7105},
doi={10.1038/nmeth.2084},
url={https://doi.org/10.1038/nmeth.2084}
}

@Article{Kim2020,
author={Kim, Eunjin
and Lee, Jiyoung
and Noh, Seulgi
and Kwon, Ohkyung
and Mun, Ji Young},
title={Double staining method for array tomography using scanning electron microscopy},
journal={Applied Microscopy},
year={2020},
month={Jun},
day={22},
volume={50},
number={1},
pages={14},
abstract={Scanning electron microscopy (SEM) plays a central role in analyzing structures by imaging a large area of brain tissue at nanometer scales. A vast amount of data in the large area are required to study structural changes of cellular organelles in a specific cell, such as neurons, astrocytes, oligodendrocytes, and microglia among brain tissue, at sufficient resolution. Array tomography is a useful method for large-area imaging, and the osmium-thiocarbohydrazide-osmium (OTO) and ferrocyanide-reduced osmium methods are commonly used to enhance membrane contrast.},
issn={2287-4445},
doi={10.1186/s42649-020-00033-8},
url={https://doi.org/10.1186/s42649-020-00033-8}
}



@Inbook{Swedlow2007,
author="Swedlow, Jason R.",
editor="Shorte, Spencer L.
and Frischknecht, Friedrich",
title="The Open Microscopy Environment: A Collaborative Data Modeling and Software Development Project for Biological Image Informatics",
bookTitle="Imaging Cellular and Molecular Biological Functions",
year="2007",
publisher="Springer Berlin Heidelberg",
address="Berlin, Heidelberg",
pages="71--92",
abstract="The transition of a microscope's output from an ``image,'' recorded on paper or film, to digitally recorded ``data'' has created new demands for storage, analysis and visualization that are not adequately met in current software packages. The Open Microscopy Environment (OME) Consortium is dedicated to developing open available tools to meet this challenge. We have developed and released the OME data model that provides a thorough description of the image data acquisition, structure and analysis results. An XML representation of the OME data model provides convenient standardized file formats known as OME-XML and OME-TIFF. In addition, OME has built two software tools, the OME and OME Remote Objects (OMERO) servers that enable visualization, management and analysis of multidimensional image data in structures that enable remote access. The OME server provides a flexible data model and an interface into complex analysis workflows. The OMERO server and clients provide image data visualization and management. A major goal for the next year is the provision of well-developed libraries and documentation to support the OME file formats, and enhanced functionality in our OME and OMERO applications to provide complete solutions for imaging in cell biology.",
isbn="978-3-540-71331-9",
doi="10.1007/978-3-540-71331-9_3",
url="https://doi.org/10.1007/978-3-540-71331-9_3"
}

@article{Nelson2021,
author = {Nelson, Glyn and Boehm, Ulrike and Bagley, Steve and Bajcsy, Peter and Bischof, Johanna and Brown, Claire M. and Dauphin, Aurélien and Dobbie, Ian M. and Eriksson, John E. and Faklaris, Orestis and Fernandez-Rodriguez, Julia and Ferrand, Alexia and Gelman, Laurent and Gheisari, Ali and Hartmann, Hella and Kukat, Christian and Laude, Alex and Mitkovski, Miso and Munck, Sebastian and North, Alison J. and Rasse, Tobias M. and Resch-Genger, Ute and Schuetz, Lucas C. and Seitz, Arne and Strambio-De-Castillia, Caterina and Swedlow, Jason R. and Alexopoulos, Ioannis and Aumayr, Karin and Avilov, Sergiy and Bakker, Gert-Jan and Bammann, Rodrigo R. and Bassi, Andrea and Beckert, Hannes and Beer, Sebastian and Belyaev, Yury and Bierwagen, Jakob and Birngruber, Konstantin A. and Bosch, Manel and Breitlow, Juergen and Cameron, Lisa A. and Chalfoun, Joe and Chambers, James J. and Chen, Chieh-Li and Conde-Sousa, Eduardo and Corbett, Alexander D. and Cordelieres, Fabrice P. and Nery, Elaine Del and Dietzel, Ralf and Eismann, Frank and Fazeli, Elnaz and Felscher, Andreas and Fried, Hans and Gaudreault, Nathalie and Goh, Wah Ing and Guilbert, Thomas and Hadleigh, Roland and Hemmerich, Peter and Holst, Gerhard A. and Itano, Michelle S. and Jaffe, Claudia B. and Jambor, Helena K. and Jarvis, Stuart C. and Keppler, Antje and Kirchenbuechler, David and Kirchner, Marcel and Kobayashi, Norio and Krens, Gabriel and Kunis, Susanne and Lacoste, Judith and Marcello, Marco and Martins, Gabriel G. and Metcalf, Daniel J. and Mitchell, Claire A. and Moore, Joshua and Mueller, Tobias and Nelson, Michael S. and Ogg, Stephen and Onami, Shuichi and Palmer, Alexandra L. and Paul-Gilloteaux, Perrine and Pimentel, Jaime A. and Plantard, Laure and Podder, Santosh and Rexhepaj, Elton and Royon, Arnaud and Saari, Markku A. and Schapman, Damien and Schoonderwoert, Vincent and Schroth-Diez, Britta and Schwartz, Stanley and Shaw, Michael and Spitaler, Martin and Stoeckl, Martin T. and Sudar, Damir and Teillon, Jeremie and Terjung, Stefan and Thuenauer, Roland and Wilms, Christian D. and Wright, Graham D. and Nitschke, Roland},
title = {QUAREP-LiMi: A community-driven initiative to establish guidelines for quality assessment and reproducibility for instruments and images in light microscopy},
journal = {Journal of Microscopy},
volume = {n/a},
number = {n/a},
pages = {},
keywords = {confocal, light microscopy, metadata, quality assessment, quality control, reproducibility, widefield},
doi = {https://doi.org/10.1111/jmi.13041},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/jmi.13041},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/jmi.13041},
abstract = {Abstract A modern day light microscope has evolved from a tool devoted to making primarily empirical observations to what is now a sophisticated , quantitative device that is an integral part of both physical and life science research. Nowadays, microscopes are found in nearly every experimental laboratory. However, despite their prevalent use in capturing and quantifying scientific phenomena, neither a thorough understanding of the principles underlying quantitative imaging techniques nor appropriate knowledge of how to calibrate, operate and maintain microscopes can be taken for granted. This is clearly demonstrated by the well-documented and widespread difficulties that are routinely encountered in evaluating acquired data and reproducing scientific experiments. Indeed, studies have shown that more than 70\% of researchers have tried and failed to repeat another scientist's experiments, while more than half have even failed to reproduce their own experiments. One factor behind the reproducibility crisis of experiments published in scientific journals is the frequent underreporting of imaging methods caused by a lack of awareness and/or a lack of knowledge of the applied technique. Whereas quality control procedures for some methods used in biomedical research, such as genomics (e.g. DNA sequencing, RNA-seq) or cytometry, have been introduced (e.g. ENCODE), this issue has not been tackled for optical microscopy instrumentation and images. Although many calibration standards and protocols have been published, there is a lack of awareness and agreement on common standards and guidelines for quality assessment and reproducibility. In April 2020, the QUality Assessment and REProducibility for instruments and images in Light Microscopy (QUAREP-LiMi) initiative was formed. This initiative comprises imaging scientists from academia and industry who share a common interest in achieving a better understanding of the performance and limitations of microscopes and improved quality control (QC) in light microscopy. The ultimate goal of the QUAREP-LiMi initiative is to establish a set of common QC standards, guidelines, metadata models and tools, including detailed protocols, with the ultimate aim of improving reproducible advances in scientific research. This White Paper (1) summarizes the major obstacles identified in the field that motivated the launch of the QUAREP-LiMi initiative; (2) identifies the urgent need to address these obstacles in a grassroots manner, through a community of stakeholders including, researchers, imaging scientists, bioimage analysts, bioimage informatics developers, corporate partners, funding agencies, standards organizations, scientific publishers and observers of such; (3) outlines the current actions of the QUAREP-LiMi initiative and (4) proposes future steps that can be taken to improve the dissemination and acceptance of the proposed guidelines to manage QC. To summarize, the principal goal of the QUAREP-LiMi initiative is to improve the overall quality and reproducibility of light microscope image data by introducing broadly accepted standard practices and accurately captured image data metrics.}
}

@Article{Ellenberg2018,
author={Ellenberg, Jan
and Swedlow, Jason R.
and Barlow, Mary
and Cook, Charles E.
and Sarkans, Ugis
and Patwardhan, Ardan
and Brazma, Alvis
and Birney, Ewan},
title={A call for public archives for biological image data},
journal={Nature Methods},
year={2018},
month={Nov},
day={01},
volume={15},
number={11},
pages={849-854},
abstract={Public data archives are the backbone of modern biological research. Biomolecular archives are well established, but bioimaging resources lag behind them. The technology required for imaging archives is now available, thus enabling the creation of the first public bioimage datasets. We present the rationale for the construction of bioimage archives and their associated databases to underpin the next revolution in bioinformatics discovery.},
issn={1548-7105},
doi={10.1038/s41592-018-0195-8},
url={https://doi.org/10.1038/s41592-018-0195-8}
}

@Article{Swedlow2021,
author={Swedlow, Jason R.
and Kankaanp{\"a}{\"a}, Pasi
and Sarkans, Ugis
and Goscinski, Wojtek
and Galloway, Graham
and Malacrida, Leonel
and Sullivan, Ryan P.
and H{\"a}rtel, Steffen
and Brown, Claire M.
and Wood, Christopher
and Keppler, Antje
and Paina, Federica
and Loos, Ben
and Zullino, Sara
and Longo, Dario Livio
and Aime, Silvio
and Onami, Shuichi},
title={A global view of standards for open image data formats and repositories},
journal={Nature Methods},
year={2021},
month={May},
day={04},
abstract={Imaging technologies are used throughout the life and biomedical sciences to understand mechanisms in biology and diagnosis and therapy in animal and human medicine. We present criteria for globally applicable guidelines for open image data tools and resources for the rapidly developing fields of biological and biomedical imaging.},
issn={1548-7105},
doi={10.1038/s41592-021-01113-7},
url={https://doi.org/10.1038/s41592-021-01113-7}
}


@InProceedings{Suzanne2004,
author="Little, Suzanne
and Hunter, Jane",
editor="McIlraith, Sheila A.
and Plexousakis, Dimitris
and van Harmelen, Frank",
title="Rules-By-Example -- A Novel Approach to Semantic Indexing and Querying of Images",
booktitle="The Semantic Web -- ISWC 2004",
year="2004",
publisher="Springer Berlin Heidelberg",
address="Berlin, Heidelberg",
pages="534--548",
abstract="Images represent a key source of information in many domains and the ability to exploit them through their discovery, analysis and integration by services and agents on the Semantic Web is a challenging and significant problem. To date the semantic indexing of images has concentrated on applying machine-learning techniques to a set of manually-annotated images in order to automatically label images with keywords. In this paper we propose a new hybrid, user-assisted approach, Rules-By-Example (RBE), which is based on a combination of RuleML and Query-By-Example. Our RBE user interface enables domain-experts to graphically define domain-specific rules that can infer high-level semantic descriptions of images from combinations of low-level visual features (e.g., color, texture, shape, size of regions) which have been specified through examples. Using these rules, the system is able to analyze the visual features of any given image from this domain and generate semantically meaningful labels, using terms defined in the domain-specific ontology. We believe that this approach, in combination with traditional solutions, will enable faster, more flexible, cost-effective and accurate semantic indexing of images and hence maximize their potential for discovery, re-use, integration and processing by Semantic Web services, tools and agents.",
isbn="978-3-540-30475-3"
}


@Article{Allan2012,
author={Allan, Chris
and Burel, Jean-Marie
and Moore, Josh
and Blackburn, Colin
and Linkert, Melissa
and Loynton, Scott
and MacDonald, Donald
and Moore, William J.
and Neves, Carlos
and Patterson, Andrew
and Porter, Michael
and Tarkowska, Aleksandra
and Loranger, Brian
and Avondo, Jerome
and Lagerstedt, Ingvar
and Lianas, Luca
and Leo, Simone
and Hands, Katherine
and Hay, Ron T.
and Patwardhan, Ardan
and Best, Christoph
and Kleywegt, Gerard J.
and Zanetti, Gianluigi
and Swedlow, Jason R.},
title={OMERO: flexible, model-driven data management for experimental biology},
journal={Nature Methods},
year={2012},
month={Mar},
day={01},
volume={9},
number={3},
pages={245-253},
abstract={The Open Microscopy Environment Remote Objects (OMERO) software platform provides a server-based system for managing and analyzing microscopy images and non-image data.},
issn={1548-7105},
doi={10.1038/nmeth.1896},
url={https://doi.org/10.1038/nmeth.1896}
}

@Article{Goldberg2005,
author={Goldberg, Ilya G.
and Allan, Chris
and Burel, Jean-Marie
and Creager, Doug
and Falconi, Andrea
and Hochheiser, Harry
and Johnston, Josiah
and Mellen, Jeff
and Sorger, Peter K.
and Swedlow, Jason R.},
title={The Open Microscopy Environment (OME) Data Model and XML file: open tools for informatics and quantitative analysis in biological imaging},
journal={Genome Biology},
year={2005},
month={May},
day={03},
volume={6},
number={5},
pages={R47},
abstract={The Open Microscopy Environment (OME) defines a data model and a software implementation to serve as an informatics framework for imaging in biological microscopy experiments, including representation of acquisition parameters, annotations and image analysis results. OME is designed to support high-content cell-based screening as well as traditional image analysis applications. The OME Data Model, expressed in Extensible Markup Language (XML) and realized in a traditional database, is both extensible and self-describing, allowing it to meet emerging imaging and analysis needs.},
issn={1474-760X},
doi={10.1186/gb-2005-6-5-r47},
url={https://doi.org/10.1186/gb-2005-6-5-r47}
}




@article{Lucocq2015,
title = {Systems biology in 3D space – enter the morphome},
journal = {Trends in Cell Biology},
volume = {25},
number = {2},
pages = {59-64},
year = {2015},
issn = {0962-8924},
doi = {https://doi.org/10.1016/j.tcb.2014.09.008},
url = {https://www.sciencedirect.com/science/article/pii/S0962892414001664},
author = {John M. Lucocq and Terry M. Mayhew and Yannick Schwab and Anna M. Steyer and Christian Hacker},
keywords = {morphome, morphomics, stereology, electron microscopy, quantitation, serial EM},
abstract = {Systems-based understanding of living organisms depends on acquiring huge datasets from arrays of genes, transcripts, proteins, and lipids. These data, referred to as ‘omes’, are assembled using ‘omics’ methodologies. Currently a comprehensive, quantitative view of cellular and organellar systems in 3D space at nanoscale/molecular resolution is missing. We introduce here the term ‘morphome’ for the distribution of living matter within a 3D biological system, and ‘morphomics’ for methods of collecting 3D data systematically and quantitatively. A sampling-based approach termed stereology currently provides rapid, precise, and minimally biased morphomics. We propose that stereology solves the ‘big data’ problem posed by emerging wide-scale electron microscopy (EM) and can establish quantitative links between the newer nanoimaging platforms such as electron tomography, cryo-EM, and correlative microscopy.}
}

@article{Jesior1986,
title = {How to avoid compression II. The influence of sectioning conditions},
journal = {Journal of Ultrastructure and Molecular Structure Research},
volume = {95},
number = {1},
pages = {210-217},
year = {1986},
issn = {0889-1605},
doi = {https://doi.org/10.1016/0889-1605(86)90042-X},
url = {https://www.sciencedirect.com/science/article/pii/088916058690042X},
author = {Jean-Claude Jésior},
abstract = {The influence of sectioning conditions on the compression of polystyrene spheres embedded in an epoxy resin was investigated. Sections were performed on both native and hardened polystyrene spheres. The sectioning parameters were varied: diamond knife angle (26.6, 35.7, and 48.3°), clearance angle (1.8 to 8.8°), section thickness (10 to 90 nm), and sectioning speed (0.1 to 10 mm/sec). The results show that the highest compression factor was observed when sections were very thin and when the sectioning angle (defined as the sum of knife and clearance angles) was high. The compression factor was proportional to the sectioning angle whereas it was independent of the sectioning speed. Thus, to obtain reduced compression the microtomist should cut thicker ultrathin sections (50–90 nm) with a low-angle diamond knife (smaller than 30°) set at the smallest possible clearance angle. Under these conditions a reduction of compression by a factor of three to five can be obtained in ultrathin sections of soft specimens. The reader is reminded that compression can be completely eliminated when specimens are properly hardened during the preparation. Finally a two-region model based on the experimental results is proposed to explain the origin of compression.}
}

@article{Ando2018,
	doi = {10.1088/1361-6463/aad055},
	url = {https://doi.org/10.1088/1361-6463/aad055},
	year = 2018,
	month = {aug},
	publisher = {{IOP} Publishing},
	volume = {51},
	number = {44},
	pages = {443001},
	author = {Toshio Ando and Satya Prathyusha Bhamidimarri and Niklas Brending and H Colin-York and Lucy Collinson and Niels De Jonge and P J de Pablo and Elke Debroye and Christian Eggeling and Christian Franck and Marco Fritzsche and Hans Gerritsen and Ben N G Giepmans and Kay Grunewald and Johan Hofkens and Jacob P Hoogenboom and Kris P F Janssen and Rainer Kaufmann and Judith Klumperman and Nyoman Kurniawan and Jana Kusch and Nalan Liv and Viha Parekh and Diana B Peckys and Florian Rehfeldt and David C Reutens and Maarten B J Roeffaers and Tim Salditt and Iwan A T Schaap and Ulrich S Schwarz and Paul Verkade and Michael W Vogel and Richard Wagner and Mathias Winterhalter and Haifeng Yuan and Giovanni Zifarelli},
	title = {The 2018 correlative microscopy techniques roadmap},
	journal = {Journal of Physics D: Applied Physics},
	abstract = {Developments in microscopy have been instrumental to progress in the life sciences, and many new techniques have been introduced and led to new discoveries throughout the last century. A wide and diverse range of methodologies is now available, including electron microscopy, atomic force microscopy, magnetic resonance imaging, small-angle x-ray scattering and multiple super-resolution fluorescence techniques, and each of these methods provides valuable read-outs to meet the demands set by the samples under study. Yet, the investigation of cell development requires a multi-parametric approach to address both the structure and spatio-temporal organization of organelles, and also the transduction of chemical signals and forces involved in cell–cell interactions. Although the microscopy technologies for observing each of these characteristics are well developed, none of them can offer read-out of all characteristics simultaneously, which limits the information content of a measurement. For example, while electron microscopy is able to disclose the structural layout of cells and the macromolecular arrangement of proteins, it cannot directly follow dynamics in living cells. The latter can be achieved with fluorescence microscopy which, however, requires labelling and lacks spatial resolution. A remedy is to combine and correlate different readouts from the same specimen, which opens new avenues to understand structure–function relations in biomedical research. At the same time, such correlative approaches pose new challenges concerning sample preparation, instrument stability, region of interest retrieval, and data analysis. Because the field of correlative microscopy is relatively young, the capabilities of the various approaches have yet to be fully explored, and uncertainties remain when considering the best choice of strategy and workflow for the correlative experiment. With this in mind, the Journal of Physics D: Applied Physics presents a special roadmap on the correlative microscopy techniques, giving a comprehensive overview from various leading scientists in this field, via a collection of multiple short viewpoints.}
}


@Article{Han2019,
author={Han, Yisu
and Branon, Tess Caroline
and Martell, Jeffrey D.
and Boassa, Daniela
and Shechner, David
and Ellisman, Mark H.
and Ting, Alice},
title={Directed Evolution of Split APEX2 Peroxidase},
journal={ACS Chemical Biology},
year={2019},
month={Apr},
day={19},
publisher={American Chemical Society},
volume={14},
number={4},
pages={619-635},
issn={1554-8929},
doi={10.1021/acschembio.8b00919},
url={https://doi.org/10.1021/acschembio.8b00919}
}

@Article{Mavylutov2018,
author={Mavylutov, Timur
and Chen, Xi
and Guo, Lianwang
and Yang, Jay},
title={APEX2- tagging of Sigma 1-receptor indicates subcellular protein topology with cytosolic N-terminus and ER luminal C-terminus},
journal={Protein {\&} Cell},
year={2018},
month={Aug},
day={01},
volume={9},
number={8},
pages={733-737},
issn={1674-8018},
doi={10.1007/s13238-017-0468-5},
url={https://doi.org/10.1007/s13238-017-0468-5}
}




@Article{Adams2016,
author={Adams, Stephen R.
and Mackey, Mason R.
and Ramachandra, Ranjan
and Palida Lemieux, Sakina F.
and Steinbach, Paul
and Bushong, Eric A.
and Butko, Margaret T.
and Giepmans, Ben N.G.
and Ellisman, Mark H.
and Tsien, Roger Y.},
title={Multicolor Electron Microscopy for Simultaneous Visualization of Multiple Molecular Species},
journal={Cell Chemical Biology},
year={2016},
month={Nov},
day={17},
publisher={Elsevier},
volume={23},
number={11},
pages={1417-1427},
issn={2451-9456},
doi={10.1016/j.chembiol.2016.10.006},
url={https://doi.org/10.1016/j.chembiol.2016.10.006}
}



@Article{Fu2020,
author={Fu, Zhifei
and Peng, Dingming
and Zhang, Mingshu
and Xue, Fudong
and Zhang, Rui
and He, Wenting
and Xu, Tao
and Xu, Pingyong},
title={mEosEM withstands osmium staining and Epon embedding for super-resolution CLEM},
journal={Nature Methods},
year={2020},
month={Jan},
day={01},
volume={17},
number={1},
pages={55-58},
abstract={Super-resolution correlative light and electron microscopy (SR-CLEM) is a powerful approach for imaging specific molecules at the nanoscale in the context of the cellular ultrastructure. Epon epoxy resin embedding offers advantages for SR-CLEM, including ultrastructural preservation and high quality sectioning. However, Epon embedding eliminates fluorescence from most fluorescent proteins. We describe a photocontrollable fluorescent protein, mEosEM, that can survive Epon embedding after osmium tetroxide (OsO4) treatment for improved SR-CLEM.},
issn={1548-7105},
doi={10.1038/s41592-019-0613-6},
url={https://doi.org/10.1038/s41592-019-0613-6}
}

@article{Hoffman2020,
author = {David P. Hoffman  and Gleb Shtengel  and C. Shan Xu  and Kirby R. Campbell  and Melanie Freeman  and Lei Wang  and Daniel E. Milkie  and H. Amalia Pasolli  and Nirmala Iyer  and John A. Bogovic  and Daniel R. Stabley  and Abbas Shirinifard  and Song Pang  and David Peale  and Kathy Schaefer  and Wim Pomp  and Chi-Lun Chang  and Jennifer Lippincott-Schwartz  and Tom Kirchhausen  and David J. Solecki  and Eric Betzig  and Harald F. Hess },
title = {Correlative three-dimensional super-resolution and block-face electron microscopy of whole vitreously frozen cells},
journal = {Science},
volume = {367},
number = {6475},
pages = {eaaz5357},
year = {2020},
doi = {10.1126/science.aaz5357},
URL = {https://www.science.org/doi/abs/10.1126/science.aaz5357},
eprint = {https://www.science.org/doi/pdf/10.1126/science.aaz5357}
,
    abstract = { Cells need to compartmentalize thousands of distinct proteins, but the nanoscale spatial relationship of many proteins to overall intracellular ultrastructure remains poorly understood. Correlated light and electron microscopy approaches can help. Hoffman et al. combined cryogenic super-resolution fluorescence microscopy and focused ion beam–milling scanning electron microscopy to visualize protein-ultrastructure relationships in three dimensions across whole cells. The fusion of the two imaging modalities enabled identification and three-dimensional segmentation of morphologically complex structures within the crowded intracellular environment. The researchers observed unexpected relationships within a variety of cell types, including a web-like protein adhesion network between juxtaposed cerebellar granule neurons. Science, this issue p. eaaz5357 Cryogenic super-resolution fluorescence and electron microscopy reveals protein-ultrastructure relationships in whole cells. Within cells, the spatial compartmentalization of thousands of distinct proteins serves a multitude of diverse biochemical needs. Correlative super-resolution (SR) fluorescence and electron microscopy (EM) can elucidate protein spatial relationships to global ultrastructure, but has suffered from tradeoffs of structure preservation, fluorescence retention, resolution, and field of view. We developed a platform for three-dimensional cryogenic SR and focused ion beam–milled block-face EM across entire vitreously frozen cells. The approach preserves ultrastructure while enabling independent SR and EM workflow optimization. We discovered unexpected protein-ultrastructure relationships in mammalian cells including intranuclear vesicles containing endoplasmic reticulum–associated proteins, web-like adhesions between cultured neurons, and chromatin domains subclassified on the basis of transcriptional activity. Our findings illustrate the value of a comprehensive multimodal view of ultrastructural variability across whole cells. }
}



@Article{Yin2020,
author={Yin, Wenjing
and Brittain, Derrick
and Borseth, Jay
and Scott, Marie E.
and Williams, Derric
and Perkins, Jedediah
and Own, Christopher S.
and Murfitt, Matthew
and Torres, Russel M.
and Kapner, Daniel
and Mahalingam, Gayathri
and Bleckert, Adam
and Castelli, Daniel
and Reid, David
and Lee, Wei-Chung Allen
and Graham, Brett J.
and Takeno, Marc
and Bumbarger, Daniel J.
and Farrell, Colin
and Reid, R. Clay
and da Costa, Nuno Macarico},
title={A petascale automated imaging pipeline for mapping neuronal circuits with high-throughput transmission electron microscopy},
journal={Nature Communications},
year={2020},
month={Oct},
day={02},
volume={11},
number={1},
pages={4949},
abstract={Electron microscopy (EM) is widely used for studying cellular structure and network connectivity in the brain. We have built a parallel imaging pipeline using transmission electron microscopes that scales this technology, implements 24/7 continuous autonomous imaging, and enables the acquisition of petascale datasets. The suitability of this architecture for large-scale imaging was demonstrated by acquiring a volume of more than 1{\thinspace}mm3 of mouse neocortex, spanning four different visual areas at synaptic resolution, in less than 6 months. Over 26,500 ultrathin tissue sections from the same block were imaged, yielding a dataset of more than 2 petabytes. The combined burst acquisition rate of the pipeline is 3 Gpixel per sec and the net rate is 600 Mpixel per sec with six microscopes running in parallel. This work demonstrates the feasibility of acquiring EM datasets at the scale of cortical microcircuits in multiple brain regions and species.},
issn={2041-1723},
doi={10.1038/s41467-020-18659-3},
url={https://doi.org/10.1038/s41467-020-18659-3}
}



@article{Hayworth2006, 
title={Automating the Collection of Ultrathin Serial Sections for Large Volume TEM Reconstructions}, volume={12}, 
DOI={10.1017/S1431927606066268}, number={S02}, 
journal={Microscopy and Microanalysis}, 
publisher={Cambridge University Press}, 
author={Hayworth, KJ and Kasthuri, N and Schalek, R and Lichtman, JW}, year={2006}, pages={86–87}}

@article{Koike2017,
  title={A Device for Ribbon Collection for Array Tomography with Scanning Electron Microscopy},
  author={Taro Koike and Yosky Kataoka and Mitsuyo Maeda and Yuji Hasebe and Yuuki Yamaguchi and Mitsuo Suga and Akira Saito and Hisao Yamada},
  journal={ACTA HISTOCHEMICA ET CYTOCHEMICA},
  volume={50},
  number={5},
  pages={135-140},
  year={2017},
  doi={10.1267/ahc.17013}
}

@article {Betzig2006,
	author = {Betzig, Eric and Patterson, George H. and Sougrat, Rachid and Lindwasser, O. Wolf and Olenych, Scott and Bonifacino, Juan S. and Davidson, Michael W. and Lippincott-Schwartz, Jennifer and Hess, Harald F.},
	title = {Imaging Intracellular Fluorescent Proteins at Nanometer Resolution},
	volume = {313},
	number = {5793},
	pages = {1642--1645},
	year = {2006},
	doi = {10.1126/science.1127344},
	publisher = {American Association for the Advancement of Science},
	abstract = {We introduce a method for optically imaging intracellular proteins at nanometer spatial resolution. Numerous sparse subsets of photoactivatable fluorescent protein molecules were activated, localized (to \~{}2 to 25 nanometers), and then bleached. The aggregate position information from all subsets was then assembled into a superresolution image. We used this method{\textemdash}termed photoactivated localization microscopy{\textemdash}to image specific target proteins in thin sections of lysosomes and mitochondria; in fixed whole cells, we imaged vinculin at focal adhesions, actin within a lamellipodium, and the distribution of the retroviral protein Gag at the plasma membrane.},
	issn = {0036-8075},
	URL = {https://science.sciencemag.org/content/313/5793/1642},
	eprint = {https://science.sciencemag.org/content/313/5793/1642.full.pdf},
	journal = {Science}
}

@article {Graham2019,
	title = {High-throughput transmission electron microscopy with automated serial sectioning},
	journal = {bioRxiv},
	year = {2019},
	publisher = {Cold Spring Harbor Laboratory},
	abstract = {Transmission electron microscopy (TEM) is an essential tool for studying cells and molecules. We present a tape-based, reel-to-reel pipeline that combines automated serial sectioning with automated high-throughput TEM imaging. This acquisition platform provides nanometer-resolution imaging at fast rates for a fraction of the cost of alternative approaches. We demonstrate the utility of this imaging platform for generating datasets of biological tissues with a focus on examining brain circuits.},
	doi = {10.1101/657346},
	url = {https://www.biorxiv.org/content/early/2019/06/02/657346},
	author = {Graham, Brett J. and Hildebrand, David Grant Colburn and Aaron T. Kuan and Maniates-Selvin, Jasper T. and Logan A. Thomas and Shanny, Brendan L. and Wei-Chung Allen Lee}
}



@Article{Phelps2021,
author={Phelps, Jasper S.
and Hildebrand, David Grant Colburn
and Graham, Brett J.
and Kuan, Aaron T.
and Thomas, Logan A.
and Nguyen, Tri M.
and Buhmann, Julia
and Azevedo, Anthony W.
and Sustar, Anne
and Agrawal, Sweta
and Liu, Mingguan
and Shanny, Brendan L.
and Funke, Jan
and Tuthill, John C.
and Lee, Wei-Chung Allen},
title={Reconstruction of motor control circuits in adult <em>Drosophila</em> using automated transmission electron microscopy},
journal={Cell},
year={2021},
month={Feb},
day={04},
publisher={Elsevier},
volume={184},
number={3},
pages={759-774.e18},
issn={0092-8674},
doi={10.1016/j.cell.2020.12.013},
url={https://doi.org/10.1016/j.cell.2020.12.013}
}


@Article{Koike2019,
author={Koike, Taro
and Yamada, Hisao},
title={Methods for array tomography with correlative light and electron microscopy},
journal={Medical Molecular Morphology},
year={2019},
month={Mar},
day={01},
volume={52},
number={1},
pages={8-14},
abstract={The three-dimensional ultra-structure is the comprehensive structure that cannot be observed from a two-dimensional electron micrograph. Array tomography is one method for three-dimensional electron microscopy. In this method, to obtain consecutive cross sections of tissue, connected consecutive sections of a resin block are mounted on a flat substrate, and these are observed with scanning electron microscopy. Although array tomography requires some bothersome manual procedures to prepare specimens, a recent study has introduced some techniques to ease specimen preparation. In addition, array tomography has some advantages compared with other three-dimensional electron microscopy techniques. For example, sections on the substrate are stored semi-eternally, so they can be observed at different magnifications. Furthermore, various staining methods, including post-embedding immunocytochemistry, can be adopted. In the present review, the preparation of specimens for array tomography, including ribbon collection and the staining method, and the adaptability for correlative light and electron microscopy are discussed.},
issn={1860-1499},
doi={10.1007/s00795-018-0194-y},
url={https://doi.org/10.1007/s00795-018-0194-y}
}

@Article{CalcifiedTissueInternational1983,
title={Abstracts Fifth annual scientific meeting of the American Society for bone and mineral research June 5--7, 1993 Hotel Intercontinental San Antonio, Texas},
journal={Calcified Tissue International},
year={1983},
month={Dec},
day={01},
volume={35},
number={1},
pages={631-706},
issn={1432-0827},
doi={10.1007/BF02405107},
url={https://doi.org/10.1007/BF02405107}
}

@Article{Busse2019,
author={Busse, Madleen
and M{\"u}ller, Mark
and Kimm, Melanie A.
and Ferstl, Simone
and AU - Allner, Sebastian
and AU - Achterhold, Klaus
and AU - Herzen, Julia
and AU - Pfeiffer, Franz},
title={3D Imaging of Soft-Tissue Samples using an X-ray Specific Staining Method and Nanoscopic Computed Tomography},
journal={JoVE},
year={2019},
month={Oct},
day={24},
publisher={MyJoVE Corp},
number={152},
pages={e60251},
keywords={Retraction; X-ray staining method; microscopic X-ray computed tomography; nanoscopic X-ray computed tomography; nondestructive; multiscale imaging; high-resolution; 3D imaging; soft tissue imaging; microstructure; eosin stain; cytoplasm-specific staining},
abstract={We demonstrate a laboratory-based method combining X-ray microCT and nanoCT with a specific X-ray stain, which targets the cell cytoplasm. The described protocol is easy to apply, fast and suitable for larger soft-tissue samples. The presented methodology enables the characterization of crucial tissue structures in three dimensions and is demonstrated on a whole mouse kidney. The multiscale approach allows to image the entire mouse kidney and supports the selection of further volumes of interest, which are acquired with higher resolutions ranging into the nanometer range. Thereby, soft-tissue morphology with a similar detail level as the corresponding histological light microscopy images is reproduced. Deeper insights into the 3D configuration of tissue structures are achieved without impeding further investigations through histological methods.},
issn={1940-087X},
doi={10.3791/60251},
url={https://www.jove.com/t/60251},
url={https://doi.org/10.3791/60251}
}



@Article{Muller2018,
author={M{\"u}ller, Mark
and Kimm, Melanie A.
and Ferstl, Simone
and Allner, Sebastian
and Achterhold, Klaus
and Herzen, Julia
and Pfeiffer, Franz
and Busse, Madleen},
title={Nucleus-specific X-ray stain for 3D virtual histology},
journal={Scientific Reports},
year={2018},
month={Dec},
day={14},
volume={8},
number={1},
pages={17855},
abstract={Histological investigations are indispensable with regards to the identification of structural tissue details but are limited to two-dimensional images, which are often visualized in one and the same plane for comparison reasons. Nondestructive three-dimensional technologies such as X-ray micro- and nanoCT have proven to provide valuable benefits for the understanding of anatomical structures as they allow visualization of structural details in 3D and from arbitrary viewing angles. Nevertheless, low attenuation of soft tissue has hampered their application in the field of 3D virtual histology. We present a hematein-based X-ray staining method that specifically targets the cell nuclei of cells, as demonstrated for a whole liver lobule of a mouse. Combining the novel staining protocol with the high resolving power of a recently developed nanoCT system enables the 3D visualization of tissue architecture in the nanometer range, thereby revealing the real 3D morphology and spatial distribution of the cell nuclei. Furthermore, our technique is compatible with conventional histology, as microscopic slides can be derived from the very same stained soft-tissue sample and further counter staining is possible. Thus, our methodology demonstrates future applicability for modern histopathology using laboratory X-ray CT devices.},
issn={2045-2322},
doi={10.1038/s41598-018-36067-y},
url={https://doi.org/10.1038/s41598-018-36067-y}
}


@article {Muller2017,
	author = {M{\"u}ller, Mark and de Sena Oliveira, Ivo and Allner, Sebastian and Ferstl, Simone and Bidola, Pidassa and Mechlem, Korbinian and Fehringer, Andreas and Hehn, Lorenz and Dierolf, Martin and Achterhold, Klaus and Gleich, Bernhard and Hammel, J{\"o}rg U. and Jahn, Henry and Mayer, Georg and Pfeiffer, Franz},
	title = {Myoanatomy of the velvet worm leg revealed by laboratory-based nanofocus X-ray source tomography},
	volume = {114},
	number = {47},
	pages = {12378--12383},
	year = {2017},
	doi = {10.1073/pnas.1710742114},
	publisher = {National Academy of Sciences},
	abstract = {X-ray computed tomography (CT) imaging has become popular for investigating, nondestructively and three-dimensionally, both external and internal structures of various specimens. However, the limited resolution of conventional laboratory-based CT systems (>=500 nm) still hampers the detailed visualization of features on the low nanometer level. We present a laboratory CT device and data processing pipeline to routinely and efficiently generate high-resolution 3D data (≈100 nm) without requiring synchrotron radiation facilities. Our setup is especially relevant for conducting detailed analysis of very small biological samples, as demonstrated for a walking appendage of a velvet worm. Comparative analyses of our CT data with those obtained from other popular imaging methods highlight the advantages and future applicability of the nanoCT setup.X-ray computed tomography (CT) is a powerful noninvasive technique for investigating the inner structure of objects and organisms. However, the resolution of laboratory CT systems is typically limited to the micrometer range. In this paper, we present a table-top nanoCT system in conjunction with standard processing tools that is able to routinely reach resolutions down to 100 nm without using X-ray optics. We demonstrate its potential for biological investigations by imaging a walking appendage of Euperipatoides rowelli, a representative of Onychophora{\textemdash}an invertebrate group pivotal for understanding animal evolution. Comparative analyses proved that the nanoCT can depict the external morphology of the limb with an image quality similar to scanning electron microscopy, while simultaneously visualizing internal muscular structures at higher resolutions than confocal laser scanning microscopy. The obtained nanoCT data revealed hitherto unknown aspects of the onychophoran limb musculature, enabling the 3D reconstruction of individual muscle fibers, which was previously impossible using any laboratory-based imaging technique.},
	issn = {0027-8424},
	URL = {https://www.pnas.org/content/114/47/12378},
	eprint = {https://www.pnas.org/content/114/47/12378.full.pdf},
	journal = {Proceedings of the National Academy of Sciences}
}


@Article{Burnett2014,
author={Burnett, T. L.
and McDonald, S. A.
and Gholinia, A.
and Geurts, R.
and Janus, M.
and Slater, T.
and Haigh, S. J.
and Ornek, C.
and Almuaili, F.
and Engelberg, D. L.
and Thompson, G. E.
and Withers, P. J.},
title={Correlative Tomography},
journal={Scientific Reports},
year={2014},
month={Apr},
day={16},
volume={4},
number={1},
pages={4711},
abstract={Increasingly researchers are looking to bring together perspectives across multiple scales, or to combine insights from different techniques, for the same region of interest. To this end, correlative microscopy has already yielded substantial new insights in two dimensions (2D). Here we develop correlative tomography where the correlative task is somewhat more challenging because the volume of interest is typically hidden beneath the sample surface. We have threaded together x-ray computed tomography, serial section FIB-SEM tomography, electron backscatter diffraction and finally TEM elemental analysis all for the same 3D region. This has allowed observation of the competition between pitting corrosion and intergranular corrosion at multiple scales revealing the structural hierarchy, crystallography and chemistry of veiled corrosion pits in stainless steel. With automated correlative workflows and co-visualization of the multi-scale or multi-modal datasets the technique promises to provide insights across biological, geological and materials science that are impossible using either individual or multiple uncorrelated techniques.},
issn={2045-2322},
doi={10.1038/srep04711},
url={https://doi.org/10.1038/srep04711}
}

@Article{Parlanti2017,
author={Parlanti, P.
and Cappello, V.
and Brun, F.
and Tromba, G.
and Rigolio, R.
and Tonazzini, I.
and Cecchini, M.
and Piazza, V.
and Gemmi, M.},
title={Size and specimen-dependent strategy for x-ray micro-ct and tem correlative analysis of nervous system samples},
journal={Scientific Reports},
year={2017},
month={Jun},
day={06},
volume={7},
number={1},
pages={2858},
abstract={Correlative approaches are a powerful tool in the investigation of biological samples, but require specific preparation procedures to maintain the strength of the employed methods. Here we report the optimization of the embedding protocol of nervous system samples for a correlative synchrotron X-ray computed microtomography (micro-CT) and transmission electron microscopy (TEM) approach. We demonstrate that it is possible to locate, with the micrometric resolution of micro-CT, specific volumes of interest for a further ultrastructural characterization to be performed with TEM. This approach can be applied to samples of different size and morphology up to several cm. Our optimized method represents an invaluable tool for investigating those pathologies in which microscopic alterations are localized in few confined regions, rather than diffused in entire tissues, organs or systems. We present a proof of concept of our method in a mouse model of Globoid Cells Leukodistrophy.},
issn={2045-2322},
doi={10.1038/s41598-017-02998-1},
url={https://doi.org/10.1038/s41598-017-02998-1}
}



@article{Gerhard2013,
author = {Gerhard Sengle and Sara F. Tufa and Lynn Y. Sakai and Martin A. Zulliger and Douglas R. Keene},
title ={A Correlative Method for Imaging Identical Regions of Samples by Micro-CT, Light Microscopy, and Electron Microscopy: Imaging Adipose Tissue in a Model System},
journal = {Journal of Histochemistry \& Cytochemistry},
volume = {61},
number = {4},
pages = {263-271},
year = {2013},
doi = {10.1369/0022155412473757},
    note ={PMID: 23264636},
URL = {https://doi.org/10.1369/0022155412473757},
eprint = {https://doi.org/10.1369/0022155412473757   },
    abstract = { We present a method in which a precise region of interest within an intact organism is spatially mapped in three dimensions by non-invasive micro-computed X-ray tomography (micro-CT), then further evaluated by light microscopy (LM) and transmission electron microscopy (TEM). Tissues are prepared as if for TEM including osmium fixation, which imparts soft tissue contrast in the micro-CT due to its strong X-ray attenuation. This method may therefore be applied to embedded, archived TEM samples. Upon selection of a two-dimensional (2-D) projection from a region of interest (ROI) within the three-dimensional volume, the epoxy-embedded sample is oriented for microtomy so that the sectioning plane is aligned with the micro-CT projection. Registration is verified by overlaying LM images with 2-D micro-CT projections. Structures that are poorly resolved in the micro-CT may be evaluated at TEM resolution by observing the next serial ultrathin section, thereby accessing the same ROI by all three imaging techniques. We compare white adipose tissue within the forelimbs of mice harboring a lipid-altering mutation with their littermate controls. We demonstrate that individual osmium-stained lipid droplets as small as 15 µm and separated by as little as 35 µm may be discerned as separate entities in the micro-CT, validating this to be a high-resolution, non-destructive technique for evaluation of fat content. }
}




@Article{Handschuh2013,
author={Handschuh, Stephan
and Baeumler, Natalie
and Schwaha, Thomas
and Ruthensteiner, Bernhard},
title={A correlative approach for combining microCT, light and transmission electron microscopy in a single 3D scenario},
journal={Frontiers in Zoology},
year={2013},
month={Aug},
day={03},
volume={10},
number={1},
pages={44},
abstract={In biomedical research, a huge variety of different techniques is currently available for the structural examination of small specimens, including conventional light microscopy (LM), transmission electron microscopy (TEM), confocal laser scanning microscopy (CLSM), microscopic X-ray computed tomography (microCT), and many others. Since every imaging method is physically limited by certain parameters, a correlative use of complementary methods often yields a significant broader range of information. Here we demonstrate the advantages of the correlative use of microCT, light microscopy, and transmission electron microscopy for the analysis of small biological samples.},
issn={1742-9994},
doi={10.1186/1742-9994-10-44},
url={https://doi.org/10.1186/1742-9994-10-44}
}

@incollection{PIROZZI2021,
title = {Chapter 5 - Sample preparation for energy dispersive X-ray imaging of biological tissues},
editor = {Thomas Müller-Reichert and Paul Verkade},
series = {Methods in Cell Biology},
publisher = {Academic Press},
volume = {162},
pages = {89-114},
year = {2021},
booktitle = {Correlative Light and Electron Microscopy IV},
issn = {0091-679X},
doi = {https://doi.org/10.1016/bs.mcb.2020.10.023},
url = {https://www.sciencedirect.com/science/article/pii/S0091679X20302065},
author = {Nicole M. Pirozzi and Jeroen Kuipers and Ben N.G. Giepmans},
keywords = {EDX, EDS, EM, ColorEM},
abstract = {Traditional electron microscopy (EM) can be complemented with analytical EM to increase objective sample information enabling feature identification. Energy dispersive X-ray (EDX) imaging provides semi-quantitative elemental composition of the sample with high spatial resolution (~10nm) in ultrathin sections. However, EDX imaging of biological samples is still challenging as a routine method because many elements are at the detection limit for this technique. Moreover, samples undergo extensive preparation before analysis, which can introduce disruptive X-ray cross-talk or artifacts. EDX data can, for instance, be skewed by (i) osmium interference with endogenous phosphorus, (ii) chlorine present in EPON-embedded tissues, (iii) lead interference with endogenous sulfur, and (iv) potential spectral overlaps with grid material, contrast agents, and the in-microscope sample holder. Here, we highlight how to circumvent these potential pitfalls and outline how we approach sample preparation and analysis for detection of different elements of interest. Utilization of well-considered a priori sample preparation techniques will best ensure conclusive EDX experiments.}
}


@Article{Pirozzi2018,
author={Pirozzi, Nicole M.
and Hoogenboom, Jacob P.
and Giepmans, Ben N. G.},
title={ColorEM: analytical electron microscopy for element-guided identification and imaging of the building blocks of life},
journal={Histochemistry and Cell Biology},
year={2018},
month={Nov},
day={01},
volume={150},
number={5},
pages={509-520},
abstract={Nanometer-scale identification of multiple targets is crucial to understand how biomolecules regulate life. Markers, or probes, of specific biomolecules help to visualize and to identify. Electron microscopy (EM), the highest resolution imaging modality, provides ultrastructural information where several subcellular structures can be readily identified. For precise tagging of (macro)molecules, electron-dense probes, distinguishable in gray-scale EM, are being used. However, practically these genetically-encoded or immune-targeted probes are limited to three targets. In correlated microscopy, fluorescent signals are overlaid on the EM image, but typically without the nanometer-scale resolution and limited to visualization of few targets. Recently, analytical methods have become more sensitive, which has led to a renewed interest to explore these for imaging of elements and molecules in cells and tissues in EM. Here, we present the current state of nanoscale imaging of cells and tissues using energy dispersive X-ray analysis (EDX), electron energy loss spectroscopy (EELS), cathodoluminescence (CL), and touch upon secondary ion mass spectroscopy at the nanoscale (NanoSIMS). ColorEM is the term encompassing these analytical techniques the results of which are then displayed as false-color at the EM scale. We highlight how ColorEM will become a strong analytical nano-imaging tool in life science microscopy.},
issn={1432-119X},
doi={10.1007/s00418-018-1707-4},
url={https://doi.org/10.1007/s00418-018-1707-4}
}



@Article{Hildebrand2017,
author={Hildebrand, David Grant Colburn
and Cicconet, Marcelo
and Torres, Russel Miguel
and Choi, Woohyuk
and Quan, Tran Minh
and Moon, Jungmin
and Wetzel, Arthur Willis
and Scott Champion, Andrew
and Graham, Brett Jesse
and Randlett, Owen
and Plummer, George Scott
and Portugues, Ruben
and Bianco, Isaac Henry
and Saalfeld, Stephan
and Baden, Alexander David
and Lillaney, Kunal
and Burns, Randal
and Vogelstein, Joshua Tzvi
and Schier, Alexander Franz
and Lee, Wei-Chung Allen
and Jeong, Won-Ki
and Lichtman, Jeff William
and Engert, Florian},
title={Whole-brain serial-section electron microscopy in larval zebrafish},
journal={Nature},
year={2017},
month={May},
day={01},
volume={545},
number={7654},
pages={345-349},
abstract={A complete larval zebrafish brain is examined and its myelinated axons reconstructed using serial-section electron microscopy, revealing remarkable symmetry and providing a valuable resource.},
issn={1476-4687},
doi={10.1038/nature22356},
url={https://doi.org/10.1038/nature22356}
}



@article{Fermie2018,
author = {Fermie, Job and Liv, Nalan and ten Brink, Corlinda and van Donselaar, Elly G. and Müller, Wally H. and Schieber, Nicole L. and Schwab, Yannick and Gerritsen, Hans C. and Klumperman, Judith},
title = {Single organelle dynamics linked to 3D structure by correlative live-cell imaging and 3D electron microscopy},
journal = {Traffic},
volume = {19},
number = {5},
pages = {354-369},
keywords = {correlative light-electron microscopy, endolysosomal system, focused ion beam scanning electron microscopy, organelle dynamics, time-lapse microscopy, volume electron microscopy},
doi = {https://doi.org/10.1111/tra.12557},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/tra.12557},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/tra.12557},
abstract = {Live-cell correlative light-electron microscopy (live-cell-CLEM) integrates live movies with the corresponding electron microscopy (EM) image, but a major challenge is to relate the dynamic characteristics of single organelles to their 3-dimensional (3D) ultrastructure. Here, we introduce focused ion beam scanning electron microscopy (FIB-SEM) in a modular live-cell-CLEM pipeline for a single organelle CLEM. We transfected cells with lysosomal-associated membrane protein 1-green fluorescent protein (LAMP-1-GFP), analyzed the dynamics of individual GFP-positive spots, and correlated these to their corresponding fine-architecture and immediate cellular environment. By FIB-SEM we quantitatively assessed morphological characteristics, like number of intraluminal vesicles and contact sites with endoplasmic reticulum and mitochondria. Hence, we present a novel way to integrate multiple parameters of subcellular dynamics and architecture onto a single organelle, which is relevant to address biological questions related to membrane trafficking, organelle biogenesis and positioning. Furthermore, by using CLEM to select regions of interest, our method allows for targeted FIB-SEM, which significantly reduces time required for image acquisition and data processing.},
year = {2018}
}



@ARTICLE{Hayworth2014,
AUTHOR={Hayworth, Kenneth J. and Morgan, Josh L. and Schalek, Richard and Berger, Daniel R. and Hildebrand, David G. C. and Lichtman, Jeff W.},   
TITLE={Imaging ATUM ultrathin section libraries with WaferMapper: a multi-scale approach to EM reconstruction of neural circuits},      	
JOURNAL={Frontiers in Neural Circuits},      
VOLUME={8},      
PAGES={68},     
YEAR={2014},      
URL={https://www.frontiersin.org/article/10.3389/fncir.2014.00068},       
DOI={10.3389/fncir.2014.00068},      
ISSN={1662-5110},   
ABSTRACT={The automated tape-collecting ultramicrotome (ATUM) makes it possible to collect large numbers of ultrathin sections quickly—the equivalent of a petabyte of high resolution images each day. However, even high throughput image acquisition strategies generate images far more slowly (at present ~1 terabyte per day). We therefore developed WaferMapper, a software package that takes a multi-resolution approach to mapping and imaging select regions within a library of ultrathin sections. This automated method selects and directs imaging of corresponding regions within each section of an ultrathin section library (UTSL) that may contain many thousands of sections. Using WaferMapper, it is possible to map thousands of tissue sections at low resolution and target multiple points of interest for high resolution imaging based on anatomical landmarks. The program can also be used to expand previously imaged regions, acquire data under different imaging conditions, or re-image after additional tissue treatments.}
}

@article {Gay1954,
	author = {Gay, Helen and Anderson, Thomas F.},
	title = {Serial Sections for Electron Microscopy},
	volume = {120},
	number = {3130},
	pages = {1071--1073},
	year = {1954},
	doi = {10.1126/science.120.3130.1071},
	publisher = {American Association for the Advancement of Science},
	issn = {0036-8075},
	URL = {https://science.sciencemag.org/content/120/3130/1071},
	eprint = {https://science.sciencemag.org/content/120/3130/1071.full.pdf},
	journal = {Science}
}

@Article{Micheva2007,
author={Micheva, Kristina D.
and Smith, Stephen J.},
title={Array Tomography: A New Tool for Imaging the Molecular Architecture and Ultrastructure of Neural Circuits},
journal={Neuron},
year={2007},
month={Jul},
day={05},
publisher={Elsevier},
volume={55},
number={1},
pages={25-36},
issn={0896-6273},
doi={10.1016/j.neuron.2007.06.014},
url={https://doi.org/10.1016/j.neuron.2007.06.014}
}


@Article{Zheng2018,
author={Zheng, Zhihao
and Lauritzen, J. Scott
and Perlman, Eric
and Robinson, Camenzind G.
and Nichols, Matthew
and Milkie, Daniel
and Torrens, Omar
and Price, John
and Fisher, Corey B.
and Sharifi, Nadiya
and Calle-Schuler, Steven A.
and Kmecova, Lucia
and Ali, Iqbal J.
and Karsh, Bill
and Trautman, Eric T.
and Bogovic, John A.
and Hanslovsky, Philipp
and Jefferis, Gregory S.X.E.
and Kazhdan, Michael
and Khairy, Khaled
and Saalfeld, Stephan
and Fetter, Richard D.
and Bock, Davi D.},
title={A Complete Electron Microscopy Volume of the Brain of Adult <em>Drosophila melanogaster</em>},
journal={Cell},
year={2018},
month={Jul},
day={26},
publisher={Elsevier},
volume={174},
number={3},
pages={730-743.e22},
issn={0092-8674},
doi={10.1016/j.cell.2018.06.019},
url={https://doi.org/10.1016/j.cell.2018.06.019}
}



@article {Motta2019,
	author = {Motta, Alessandro and Berning, Manuel and Boergens, Kevin M. and Staffler, Benedikt and Beining, Marcel and Loomba, Sahil and Hennig, Philipp and Wissler, Heiko and Helmstaedter, Moritz},
	title = {Dense connectomic reconstruction in layer 4 of the somatosensory cortex},
	volume = {366},
	number = {6469},
	elocation-id = {eaay3134},
	year = {2019},
	doi = {10.1126/science.aay3134},
	publisher = {American Association for the Advancement of Science},
	abstract = {The mammalian cerebral cortex is an enormously complex network of neuronal processes that are long and thin, branching, and extremely densely packed. This high packing density has made the reconstruction of cortical neuronal networks challenging. Motta et al. used advanced automated imaging and analysis tools to reconstruct with high spatial resolution the morphological features of 89 neurons and their connections in the mouse barrel cortex. The reconstruction covered an area more than two orders of magnitude larger than earlier neuroanatomical mapping attempts. This approach revealed information about the connectivity of inhibitory and excitatory synapses of corticocortical as well as excitatory thalamocortical connections.Science, this issue p. eaay3134INTRODUCTIONThe brain of mammals consists of an enormously dense network of neuronal wires: the axons and dendrites of nerve cells. Their packing density is so high that light-based imaging methods have so far only been able to resolve a very small fraction of nerve cells and their interaction sites, the synapses, in mammalian cortex. Recent advances in three-dimensional (3D) electron microscopy allow researchers to image every nerve cell and all chemical synapses in a given piece of brain tissue, opening up the possibility of mapping neuronal networks densely, not just sparsely. Although there have been substantial advances in imaging speed, the analysis of such 3D image data is still the limiting step. Therefore, dense reconstructions of cortical tissue have thus far been limited to femtoliter-scale volumes, keeping the systematic analysis of axons, neuronal cell bodies and their dendrites of different types, and the dense connectome between them out of reach.RATIONALEImage analysis has made decisive progress using artificial intelligence{\textendash}based methods, but the resulting reconstructions of dense nerve tissue are still too error-prone to be scientifically meaningful as is. To address this, human data analysis has been integrated into the generation of connectomes and it is the efficiency of this human{\textendash}machine data analysis that now determines progress in connectomics. We therefore focused on efficiency gains by: (i) improving the automated segmentation quality, (ii) analyzing the automated segmentation for locations of likely errors and directing the human work to these locations only, and (iii) optimizing human data interaction by helping annotators to immediately understand the problem to be solved, allowing fast, in-browser parallel data flight, and by minimizing latency between annotator queries. With this, close to 100 student annotators solved hundreds of thousands of reconstruction problems within just 29 s each, including all preparation and transition time.RESULTSWe reconstructed 2.7 m of neuronal wires densely in layer 4 of mouse somatosensory cortex within only ~4000 invested human work hours, yielding a reconstruction ~300 times larger than previous dense cortical reconstructions at ~20-fold increased efficiency, a leap for the dense reconstruction of connectomes. The resulting connectome between 6979 presynaptic and 3719 postsynaptic neurites with at least 10 synapses each, comprising 153,171 synapses total, was then analyzed for the dense circuit structure in the cerebral cortex. We found that connectomic data alone allowed the definition of inhibitory axon types that showed established principles of synaptic specificity for subcellular postsynaptic compartments, but that at scales beyond ~5 μm, geometric predictability of the circuit structure was low and coarser models of random wiring needed to be rejected for dense cortical neuropil. A gradient of thalamocortical synapse density along the cortical axis yielded an enhanced variability of synaptic input composition at the level of single L4 cell dendrites. Finally, we quantified connectomic imprints consistent with Hebbian synaptic weight adaptation, obtaining upper bounds for the fraction of the circuit that could have undergone long-term potentiation.CONCLUSIONBy leveraging human{\textendash}machine interaction for connectomic analysis of neuronal tissue, we acquired the largest connectome from the cerebral cortex to date. Using these data for connectomic cell-type definition and the mapping of upper bounds for the learned circuit fraction, we establish an approach for connectomic phenotyping of local dense neuronal circuitry in the mammalian cortex, opening the possibility for the connectomic screening of nervous tissue from various cortices, layers, species, developmental stages, sensory experience, and disease conditions.Dense reconstruction of ~500,000 cubic micrometers of cortical tissue yielding 2.7 m of neuronal cables (~3\% shown, front) implementing a connectome of ~400,000 synapses between 34,221 axons and 11,400 postsynaptic processes (fraction shown, back).These data were used for connectomic cell-type definition, geometrical circuit analysis, and measurement of the possible plastic fraction (the {\textquotedblleft}learnedness{\textquotedblright}) of the circuit.The dense circuit structure of mammalian cerebral cortex is still unknown. With developments in three-dimensional electron microscopy, the imaging of sizable volumes of neuropil has become possible, but dense reconstruction of connectomes is the limiting step. We reconstructed a volume of ~500,000 cubic micrometers from layer 4 of mouse barrel cortex, ~300 times larger than previous dense reconstructions from the mammalian cerebral cortex. The connectomic data allowed the extraction of inhibitory and excitatory neuron subtypes that were not predictable from geometric information. We quantified connectomic imprints consistent with Hebbian synaptic weight adaptation, which yielded upper bounds for the fraction of the circuit consistent with saturated long-term potentiation. These data establish an approach for the locally dense connectomic phenotyping of neuronal circuitry in the mammalian cortex.},
	issn = {0036-8075},
	URL = {https://science.sciencemag.org/content/366/6469/eaay3134},
	eprint = {https://science.sciencemag.org/content/366/6469/eaay3134.full.pdf},
	journal = {Science}
}


@article{Miyamoto2020,
author = {Miyamoto, Tatsuo and Hosoba, Kosuke and Itabashi, Takeshi and Iwane, Atsuko H and Akutsu, Silvia Natsuko and Ochiai, Hiroshi and Saito, Yumiko and Yamamoto, Takashi and Matsuura, Shinya},
title = {Insufficiency of ciliary cholesterol in hereditary Zellweger syndrome},
journal = {The EMBO Journal},
volume = {39},
number = {12},
pages = {e103499},
keywords = {cholesterol, ciliopathy, primary cilia, Zellweger syndrome},
doi = {https://doi.org/10.15252/embj.2019103499},
url = {https://www.embopress.org/doi/abs/10.15252/embj.2019103499},
eprint = {https://www.embopress.org/doi/pdf/10.15252/embj.2019103499},
abstract = {Abstract Primary cilia are antenna-like organelles on the surface of most mammalian cells that receive sonic hedgehog (Shh) signaling in embryogenesis and carcinogenesis. Cellular cholesterol functions as a direct activator of a seven-transmembrane oncoprotein called Smoothened (Smo) and thereby induces Smo accumulation on the ciliary membrane where it transduces the Shh signal. However, how cholesterol is supplied to the ciliary membrane remains unclear. Here, we report that peroxisomes are essential for the transport of cholesterol into the ciliary membrane. Zellweger syndrome (ZS) is a peroxisome-deficient hereditary disorder with several ciliopathy-related features and cells from these patients showed a reduced cholesterol level in the ciliary membrane. Reverse genetics approaches revealed that the GTP exchange factor Rabin8, the Rab GTPase Rab10, and the microtubule minus-end-directed kinesin KIFC3 form a peroxisome-associated complex to control the movement of peroxisomes along microtubules, enabling communication between peroxisomes and ciliary pocket membranes. Our findings suggest that insufficient ciliary cholesterol levels may underlie ciliopathies.},
year = {2020}
}

@article{Hughes2017,
    author = {Hughes, Louise and Borrett, Samantha and Towers, Katie and Starborg, Tobias and Vaughan, Sue},
    title = "{Patterns of organelle ontogeny through a cell cycle revealed by whole-cell reconstructions using 3D electron microscopy}",
    journal = {Journal of Cell Science},
    volume = {130},
    number = {3},
    pages = {637-647},
    year = {2017},
    month = {02},
    abstract = "{The major mammalian bloodstream form of the African sleeping sickness parasite Trypanosoma brucei multiplies rapidly, and it is important to understand how these cells divide. Organelle inheritance involves complex spatiotemporal re-arrangements to ensure correct distribution to daughter cells. Here, serial block face scanning electron microscopy (SBF-SEM) was used to reconstruct whole individual cells at different stages of the cell cycle to give an unprecedented temporal, spatial and quantitative view of organelle division, inheritance and abscission in a eukaryotic cell. Extensive mitochondrial branching occurred only along the ventral surface of the parasite, but the mitochondria returned to a tubular form during cytokinesis. Fission of the mitochondrion occurred within the cytoplasmic bridge during the final stage of cell division, correlating with cell abscission. The nuclei were located underneath each flagellum at mitosis and the mitotic spindle was located along the ventral surface, further demonstrating the asymmetric arrangement of cell cleavage in trypanosomes. Finally, measurements demonstrated that multiple Golgi bodies were accurately positioned along the flagellum attachment zone, suggesting a mechanism for determining the location of Golgi bodies along each flagellum during the cell cycle.}",
    issn = {0021-9533},
    doi = {10.1242/jcs.198887},
    url = {https://doi.org/10.1242/jcs.198887},
    eprint = {https://journals.biologists.com/jcs/article-pdf/130/3/637/1948638/jcs198887.pdf},
}





@article{Murata2014,
title = {Whole-cell imaging of the budding yeast Saccharomyces cerevisiae by high-voltage scanning transmission electron tomography},
journal = {Ultramicroscopy},
volume = {146},
pages = {39-45},
year = {2014},
issn = {0304-3991},
doi = {https://doi.org/10.1016/j.ultramic.2014.05.008},
url = {https://www.sciencedirect.com/science/article/pii/S0304399114001089},
author = {Kazuyoshi Murata and Masatoshi Esaki and Teru Ogura and Shigeo Arai and Yuta Yamamoto and Nobuo Tanaka},
keywords = {Electron tomography, Scanning transmission electron microscopy, High-voltage electron microscopy, Yeast, Organelle, Thick specimen},
abstract = {Electron tomography using a high-voltage electron microscope (HVEM) provides three-dimensional information about cellular components in sections thicker than 1μm, although in bright-field mode image degradation caused by multiple inelastic scattering of transmitted electrons limit the attainable resolution. Scanning transmission electron microscopy (STEM) is believed to give enhanced contrast and resolution compared to conventional transmission electron microscopy (CTEM). Samples up to 1μm in thickness have been analyzed with an intermediate-voltage electron microscope because inelastic scattering is not a critical limitation, and probe broadening can be minimized. Here, we employed STEM at 1MeV high-voltage to extend the useful specimen thickness for electron tomography, which we demonstrate by a seamless tomographic reconstruction of a whole, budding Saccharomyces cerevisiae yeast cell, which is ~3μm in thickness. High-voltage STEM tomography, especially in the bright-field mode, demonstrated sufficiently enhanced contrast and intensity, compared to CTEM tomography, to permit segmentation of major organelles in the whole cell. STEM imaging also reduced specimen shrinkage during tilt-series acquisition. The fidelity of structural preservation was limited by cytoplasmic extraction, and the spatial resolution was limited by the relatively large convergence angle of the scanning probe. However, the new technique has potential to solve longstanding problems of image blurring in biological specimens beyond 1μm in thickness, and may facilitate new research in cellular structural biology.}
}

@article{Miyazaki2014,
title = {Serial block-face scanning electron microscopy for three-dimensional analysis of morphological changes in mitochondria regulated by Cdc48p/p97 ATPase},
journal = {Journal of Structural Biology},
volume = {187},
number = {2},
pages = {187-193},
year = {2014},
issn = {1047-8477},
doi = {https://doi.org/10.1016/j.jsb.2014.05.010},
url = {https://www.sciencedirect.com/science/article/pii/S1047847714001257},
author = {Naoyuki Miyazaki and Masatoshi Esaki and Teru Ogura and Kazuyoshi Murata},
keywords = {Cdc48p/p97, AAA ATPase, Mitochondrial morphology, Mitochondrial fusion, Protein degradation, Serial block-face SEM},
abstract = {Cdc48p is a highly conserved cytosolic AAA chaperone that is involved in a wide range of cellular processes. It consists of two ATPase domains (D1 and D2), with regulatory regions at the N- and C-terminals. We have recently shown that Cdc48p regulates mitochondrial morphology, in that a loss of the ATPase activity or positive cooperativity in the D2 domain leads to severe fragmentations and aggregations of mitochondria in the cytoplasm. We have now used serial block-face scanning electron microscopy (SBF-SEM), an advanced three-dimensional (3D) electron microscopic technique to examine the structures and morphological changes of mitochondria in the yeast Saccharomyces cerevisiae. We found that mutants lacking ATPase activity of Cdc48p showed mitochondrial fragmentations and aggregations, without fusion of the outer membrane. This suggests that the ATPase activity of Cdc48p is necessary for fusion of the outer membranes of mitochondria. Our results also show that SBF-SEM has considerable advantages in morphological and quantitative studies on organelles and intracellular structures in entire cells.}
}

@Article{Arkill2014,
author={Arkill, Kenton P.
and Qvortrup, Klaus
and Starborg, Tobias
and Mantell, Judith M.
and Knupp, Carlo
and Michel, C. Charles
and Harper, Steve J.
and Salmon, Andy HJ
and Squire, John M.
and Bates, Dave O.
and Neal, Chris R.},
title={Resolution of the three dimensional structure of components of the glomerular filtration barrier},
journal={BMC Nephrology},
year={2014},
month={Feb},
day={01},
volume={15},
number={1},
pages={24},
abstract={The human glomerulus is the primary filtration unit of the kidney, and contains the Glomerular Filtration Barrier (GFB). The GFB had been thought to comprise 3 layers - the endothelium, the basement membrane and the podocyte foot processes. However, recent studies have suggested that at least two additional layers contribute to the function of the GFB, the endothelial glycocalyx on the vascular side, and the sub-podocyte space on the urinary side. To investigate the structure of these additional layers is difficult as it requires three-dimensional reconstruction of delicate sub-microscopic (<1 $\mu$m) cellular and extracellular elements.},
issn={1471-2369},
doi={10.1186/1471-2369-15-24},
url={https://doi.org/10.1186/1471-2369-15-24}
}



@Article{Randles2016,
author={Randles, Michael J.
and Collinson, Sophie
and Starborg, Tobias
and Mironov, Aleksandr
and Krendel, Mira
and K{\"o}nigshausen, Eva
and Sellin, Lorenz
and Roberts, Ian S. D.
and Kadler, Karl E.
and Miner, Jeffrey H.
and Lennon, Rachel},
title={Three-dimensional electron microscopy reveals the evolution of glomerular barrier injury},
journal={Scientific Reports},
year={2016},
month={Oct},
day={11},
volume={6},
number={1},
pages={35068},
abstract={Glomeruli are highly sophisticated filters and glomerular disease is the leading cause of kidney failure. Morphological change in glomerular podocytes and the underlying basement membrane are frequently observed in disease, irrespective of the underlying molecular etiology. Standard electron microscopy techniques have enabled the identification and classification of glomerular diseases based on two-dimensional information, however complex three-dimensional ultrastructural relationships between cells and their extracellular matrix cannot be easily resolved with this approach. We employed serial block face-scanning electron microscopy to investigate Alport syndrome, the commonest monogenic glomerular disease, and compared findings to other genetic mouse models of glomerular disease (Myo1e−/−, Ptpro−/−). These analyses revealed the evolution of basement membrane and cellular defects through the progression of glomerular injury. Specifically we identified sub-podocyte expansions of the basement membrane with both cellular and matrix gene defects and found a corresponding reduction in podocyte foot process number. Furthermore, we discovered novel podocyte protrusions invading into the glomerular basement membrane in disease and these occurred frequently in expanded regions of basement membrane. These findings provide new insights into mechanisms of glomerular barrier dysfunction and suggest that common cell-matrix-adhesion pathways are involved in the progression of disease regardless of the primary insult.},
issn={2045-2322},
doi={10.1038/srep35068},
url={https://doi.org/10.1038/srep35068}
}



@Article{Nguyen2016,
author={Nguyen, Huy Bang
and Thai, Truc Quynh
and Saitoh, Sei
and Wu, Bao
and Saitoh, Yurika
and Shimo, Satoshi
and Fujitani, Hiroshi
and Otobe, Hirohide
and Ohno, Nobuhiko},
title={Conductive resins improve charging and resolution of acquired images in electron microscopic volume imaging},
journal={Scientific Reports},
year={2016},
month={Mar},
day={29},
volume={6},
number={1},
pages={23721},
abstract={Recent advances in serial block-face imaging using scanning electron microscopy (SEM) have enabled the rapid and efficient acquisition of 3-dimensional (3D) ultrastructural information from a large volume of biological specimens including brain tissues. However, volume imaging under SEM is often hampered by sample charging and typically requires specific sample preparation to reduce charging and increase image contrast. In the present study, we introduced carbon-based conductive resins for 3D analyses of subcellular ultrastructures, using serial block-face SEM (SBF-SEM) to image samples. Conductive resins were produced by adding the carbon black filler, Ketjen black, to resins commonly used for electron microscopic observations of biological specimens. Carbon black mostly localized around tissues and did not penetrate cells, whereas the conductive resins significantly reduced the charging of samples during SBF-SEM imaging. When serial images were acquired, embedding into the conductive resins improved the resolution of images by facilitating the successful cutting of samples in SBF-SEM. These results suggest that improving the conductivities of resins with a carbon black filler is a simple and useful option for reducing charging and enhancing the resolution of images obtained for volume imaging with SEM.},
issn={2045-2322},
doi={10.1038/srep23721},
url={https://doi.org/10.1038/srep23721}
}



@article{Falkenberg2017,
    doi = {10.1371/journal.pcbi.1005433},
    author = {Falkenberg, Cibele V. and Azeloglu, Evren U. and Stothers, Mark and Deerinck, Thomas J. and Chen, Yibang and He, John C. and Ellisman, Mark H. and Hone, James C. and Iyengar, Ravi and Loew, Leslie M.},
    journal = {PLOS Computational Biology},
    publisher = {Public Library of Science},
    title = {Fragility of foot process morphology in kidney podocytes arises from chaotic spatial propagation of cytoskeletal instability},
    year = {2017},
    month = {03},
    volume = {13},
    url = {https://doi.org/10.1371/journal.pcbi.1005433},
    pages = {1-21},
    abstract = {Kidney podocytes’ function depends on fingerlike projections (foot processes) that interdigitate with those from neighboring cells to form the glomerular filtration barrier. The integrity of the barrier depends on spatial control of dynamics of actin cytoskeleton in the foot processes. We determined how imbalances in regulation of actin cytoskeletal dynamics could result in pathological morphology. We obtained 3-D electron microscopy images of podocytes and used quantitative features to build dynamical models to investigate how regulation of actin dynamics within foot processes controls local morphology. We find that imbalances in regulation of actin bundling lead to chaotic spatial patterns that could impair the foot process morphology. Simulation results are consistent with experimental observations for cytoskeletal reconfiguration through dysregulated RhoA or Rac1, and they predict compensatory mechanisms for biochemical stability. We conclude that podocyte morphology, optimized for filtration, is intrinsically fragile, whereby local transient biochemical imbalances may lead to permanent morphological changes associated with pathophysiology.},
    number = {3}
}

@Article{Shami2016,
author={Shami, Gerald John
and Cheng, Delfine
and Huynh, Minh
and Vreuls, Celien
and Wisse, Eddie
and Braet, Filip},
title={3-D EM exploration of the hepatic microarchitecture -- lessons learned from large-volume in situ serial sectioning},
journal={Scientific Reports},
year={2016},
month={Nov},
day={11},
volume={6},
number={1},
pages={36744},
abstract={To-date serial block-face scanning electron microscopy (SBF-SEM) dominates as the premier technique for generating three-dimensional (3-D) data of resin-embedded biological samples at an unprecedented depth volume. Given the infancy of the technique, limited literature is currently available regarding the applicability of SBF-SEM for the ultrastructural investigation of tissues. Herein, we provide a comprehensive and rigorous appraisal of five different SBF-SEM sample preparation protocols for the large-volume exploration of the hepatic microarchitecture at an unparalleled X, Y and Z resolution. In so doing, we qualitatively and quantitatively validate the use of a comprehensive SBF-SEM sample preparation protocol, based on the application of heavy metal fixatives, stains and mordanting agents. Employing the best-tested SBF-SEM approach, enabled us to assess large-volume morphometric data on murine parenchymal cells, sinusoids and bile canaliculi. Finally, we integrated the validated SBF-SEM protocol with a correlative light and electron microscopy (CLEM) approach. The combination of confocal scanning laser microscopy and SBF-SEM provided a novel way to picture subcellular detail. We appreciate that this multidimensional approach will aid the subsequent research of liver tissue under relevant experimental and disease conditions.},
issn={2045-2322},
doi={10.1038/srep36744},
url={https://doi.org/10.1038/srep36744}
}



@article{Thaunat2012,
author = {Olivier Thaunat  and Aitor G. Granja  and Patricia Barral  and Andrew Filby  and Beatriz Montaner  and Lucy Collinson  and Nuria Martinez-Martin  and Naomi E. Harwood  and Andreas Bruckbauer  and Facundo D. Batista },
title = {Asymmetric Segregation of Polarized Antigen on B Cell Division Shapes Presentation Capacity},
journal = {Science},
volume = {335},
number = {6067},
pages = {475-479},
year = {2012},
doi = {10.1126/science.1214100},
URL = {https://www.science.org/doi/abs/10.1126/science.1214100},
eprint = {https://www.science.org/doi/pdf/10.1126/science.1214100},
    abstract = { Communication received through cell contact is critical for the differentiation of specialized effector cell populations during the immune response. For example, B lymphocytes acquire antigen that they present to helper T lymphocytes. T lymphocytes, in turn, provide key differentiation signals to B lymphocytes. In order to learn more about this process, Thaunat et al. (p. 475; see the Perspective by Dustin and Meyer-Hermann) used multiphoton microscopy and imaging flow cytometry to visualize the localization of antigen in B lymphocytes during an immune response. Antigen acquired by B lymphocytes exhibited a polarized distribution that was sustained over several rounds of cell division. This produced a population of activated B lymphocytes that contained very low levels of antigen. Daughter cells that received more antigen were better able to stimulate T cells. Because cues received through T lymphocyte interactions are likely to influence B lymphocyte fate decisions, unequal distribution of antigen in dividing B lymphocytes may influence their differentiation. Antigen distribution across activated B cells influences B-T lymphocyte interactions. During the activation of humoral immune responses, B cells acquire antigen for subsequent presentation to cognate T cells. Here we show that after mouse B cells accumulate antigen, it is maintained in a polarized distribution for extended periods in vivo. Using high-throughput imaging flow cytometry, we observed that this polarization is preserved during B cell division, promoting asymmetric antigen segregation among progeny. Antigen inheritance correlates with the ability of progeny to activate T cells: Daughter cells receiving larger antigen stores exhibit a prolonged capacity to present antigen, which renders them more effective in competing for T cell help. The generation of progeny with differential capacities for antigen presentation may have implications for somatic hypermutation and class switching during affinity maturation and as B cells commit to effector cell fates. }
}

@article{PEDDIE2014,
title = {Exploring the third dimension: Volume electron microscopy comes of age},
journal = {Micron},
volume = {61},
pages = {9-19},
year = {2014},
issn = {0968-4328},
doi = {https://doi.org/10.1016/j.micron.2014.01.009},
url = {https://www.sciencedirect.com/science/article/pii/S0968432814000250},
author = {Christopher J. Peddie and Lucy M. Collinson},
keywords = {Volume EM, Correlative microscopy, CLEM, CLVEM, SBF SEM, FIB SEM},
abstract = {Groundbreaking advances in volume electron microscopy and specimen preparation are enabling the 3-dimensional visualisation of specimens with unprecedented detail, and driving a gratifying resurgence of interest in the ultrastructural examination of cellular systems. Serial section techniques, previously the domain of specialists, are becoming increasingly automated with the development of systems such as the automatic tape-collecting ultramicrotome, and serial blockface and focused ion beam scanning electron microscopes. These changes are rapidly broadening the scope of biomedical studies to which volume electron microscopy techniques can be applied beyond the brain. Further innovations in microscope design are also in the pipeline, which have the potential to enhance the speed and quality of data collection. The recent introduction of integrated light and electron microscopy systems will revolutionise correlative light and volume electron microscopy studies, by enabling the sequential collection of data from light and electron imaging modalities without intermediate specimen manipulation. In doing so, the acquisition of comprehensive functional information and direct correlation with ultrastructural details within a 3-dimensional reference space will become routine. The prospects for volume electron microscopy are therefore bright, and the stage is set for a challenging and exciting future.}
}

@article{Armer2009,
    doi = {10.1371/journal.pone.0007716},
    author = {Armer, Hannah E. J. and Mariggi, Giovanni and Png, Ken M. Y. and Genoud, Christel and Monteith, Alexander G. and Bushby, Andrew J. and Gerhardt, Holger and Collinson, Lucy M.},
    journal = {PLOS ONE},
    publisher = {Public Library of Science},
    title = {Imaging Transient Blood Vessel Fusion Events in Zebrafish by Correlative Volume Electron Microscopy},
    year = {2009},
    month = {11},
    volume = {4},
    url = {https://doi.org/10.1371/journal.pone.0007716},
    pages = {1-10},
    abstract = {The study of biological processes has become increasingly reliant on obtaining high-resolution spatial and temporal data through imaging techniques. As researchers demand molecular resolution of cellular events in the context of whole organisms, correlation of non-invasive live-organism imaging with electron microscopy in complex three-dimensional samples becomes critical. The developing blood vessels of vertebrates form a highly complex network which cannot be imaged at high resolution using traditional methods. Here we show that the point of fusion between growing blood vessels of transgenic zebrafish, identified in live confocal microscopy, can subsequently be traced through the structure of the organism using Focused Ion Beam/Scanning Electron Microscopy (FIB/SEM) and Serial Block Face/Scanning Electron Microscopy (SBF/SEM). The resulting data give unprecedented microanatomical detail of the zebrafish and, for the first time, allow visualization of the ultrastructure of a time-limited biological event within the context of a whole organism.},
    number = {11}
}

@Article{Daniel2018,
author={Daniel, Emeline
and Daud{\'e}, Marion
and Kolotuev, Irina
and Charish, Kristi
and Auld, Vanessa
and Le Borgne, Roland},
title={Coordination of Septate Junctions Assembly and Completion of Cytokinesis in Proliferative Epithelial Tissues},
journal={Current Biology},
year={2018},
month={May},
day={07},
publisher={Elsevier},
volume={28},
number={9},
pages={1380-1391.e4},
issn={0960-9822},
doi={10.1016/j.cub.2018.03.034},
url={https://doi.org/10.1016/j.cub.2018.03.034}
}



@Article{Ichimura2015,
author={Ichimura, Koichiro
and Miyazaki, Naoyuki
and Sadayama, Shoji
and Murata, Kazuyoshi
and Koike, Masato
and Nakamura, Kei-ichiro
and Ohta, Keisuke
and Sakai, Tatsuo},
title={Three-dimensional architecture of podocytes revealed by block-face scanning electron microscopy},
journal={Scientific Reports},
year={2015},
month={Mar},
day={11},
volume={5},
number={1},
pages={8993},
abstract={Block-face imaging is a scanning electron microscopic technique which enables easier acquisition of serial ultrastructural images directly from the surface of resin-embedded biological samples with a similar quality to transmission electron micrographs. In the present study, we analyzed the three-dimensional architecture of podocytes using serial block-face imaging. It was previously believed that podocytes are divided into three kinds of subcellular compartment: cell body, primary process and foot process, which are simply aligned in this order. When the reconstructed podocytes were viewed from their basal side, the foot processes were branched from a ridge-like prominence, which was formed on the basal surface of the primary process and was similar to the usual foot processes in structure. Moreover, from the cell body, the foot processes were also emerged via the ridge-like prominence, as found in the primary process. The ridge-like prominence anchored the cell body and primary process to the glomerular basement membrane and connected the foot processes to the cell body and primary process. In conclusion, serial block-face imaging is a powerful tool for clear understanding the three-dimensional architecture of podocytes through its ability to reveal novel structures which were difficult to determine by conventional transmission and scanning electron microscopes alone.},
issn={2045-2322},
doi={10.1038/srep08993},
url={https://doi.org/10.1038/srep08993}
}



@article{Ichimura2017,
    author = {Ichimura, Koichiro and Kakuta, Soichiro and Kawasaki, Yuto and Miyaki, Takayuki and Nonami, Takahiro and Miyazaki, Naoyuki and Nakao, Tomoyo and Enomoto, Sakiko and Arai, Shigeo and Koike, Masato and Murata, Kazuyoshi and Sakai, Tatsuo and Ewald, Andrew},
    title = "{Morphological process of podocyte development revealed by block-face scanning electron microscopy}",
    journal = {Journal of Cell Science},
    volume = {130},
    number = {1},
    pages = {132-142},
    year = {2017},
    month = {01},
    abstract = "{Podocytes present a unique 3D architecture specialized for glomerular filtration. However, several 3D morphological aspects on podocyte development remain partially understood because they are difficult to reveal using conventional scanning electron microscopy (SEM). Here, we adopted serial block-face SEM imaging, a powerful tool for analyzing the 3D cellular ultrastructure, to precisely reveal the morphological process of podocyte development, such as the formation of foot processes. Development of foot processes gives rise to three morphological states: the primitive, immature and mature foot processes. Immature podocytes were columnar in shape and connected to each other by the junctional complex, which migrated toward the basal side of the cell. When the junctional complex was close to the basement membrane, immature podocytes started to interdigitate with primitive foot processes under the level of junctional complex. As primitive foot processes lengthened, the junctional complex moved between primitive foot processes to form immature foot processes. Finally, the junctional complex was gradually replaced by the slit diaphragm, resulting in the maturation of immature foot processes into mature foot processes. In conclusion, the developmental process of podocytes is now clearly visualized by block-face SEM imaging.}",
    issn = {0021-9533},
    doi = {10.1242/jcs.187815},
    url = {https://doi.org/10.1242/jcs.187815},
    eprint = {https://journals.biologists.com/jcs/article-pdf/130/1/132/1963022/jcs187815.pdf}
}


@article{Briggman2012,
title = {Volume electron microscopy for neuronal circuit reconstruction},
journal = {Current Opinion in Neurobiology},
volume = {22},
number = {1},
pages = {154-161},
year = {2012},
note = {Neurotechnology},
issn = {0959-4388},
doi = {https://doi.org/10.1016/j.conb.2011.10.022},
url = {https://www.sciencedirect.com/science/article/pii/S0959438811001887},
author = {Kevin L Briggman and Davi D Bock},
abstract = {The last decade has seen a rapid increase in the number of tools to acquire volume electron microscopy (EM) data. Several new scanning EM (SEM) imaging methods have emerged, and classical transmission EM (TEM) methods are being scaled up and automated. Here we summarize the new methods for acquiring large EM volumes, and discuss the tradeoffs in terms of resolution, acquisition speed, and reliability. We then assess each method's applicability to the problem of reconstructing anatomical connectivity between neurons, considering both the current capabilities and future prospects of the method. Finally, we argue that neuronal ‘wiring diagrams’ are likely necessary, but not sufficient, to understand the operation of most neuronal circuits: volume EM imaging will likely find its best application in combination with other methods in neuroscience, such as molecular biology, optogenetics, and physiology.}
}

@article{Kevin2006,
title = {Towards neural circuit reconstruction with volume electron microscopy techniques},
journal = {Current Opinion in Neurobiology},
volume = {16},
number = {5},
pages = {562-570},
year = {2006},
note = {Neuronal and glial cell biology / New technologies},
issn = {0959-4388},
doi = {https://doi.org/10.1016/j.conb.2006.08.010},
url = {https://www.sciencedirect.com/science/article/pii/S0959438806001140},
author = {Kevin L Briggman and Winfried Denk},
abstract = {Electron microscopy is the only currently available technique with a resolution adequate to identify and follow every axon and dendrite in dense neuropil. Reconstructions of large volumes of neural tissue, necessary to reconstruct even local neural circuits, have, however, been inhibited by the daunting task of serially sectioning and reconstructing thousands of sections. Recent technological developments have improved the quality of volume electron microscopy data and automated its acquisition. This opens up the prospect of reconstructing almost complete invertebrate and sizable fractions of vertebrate nervous systems. Such reconstructions of complete neural wiring diagrams could rekindle the tradition of relating neural function to the underlying neuroanatomical circuitry.}
}

@article{Denk2004,
    doi = {10.1371/journal.pbio.0020329},
    author = {Denk, Winfried and Horstmann, Heinz},
    journal = {PLOS Biology},
    publisher = {Public Library of Science},
    title = {Serial Block-Face Scanning Electron Microscopy to Reconstruct Three-Dimensional Tissue Nanostructure},
    year = {2004},
    month = {10},
    volume = {2},
    url = {https://doi.org/10.1371/journal.pbio.0020329},
    pages = {null},
    abstract = {Three-dimensional (3D) structural information on many length scales is of central importance in biological research. Excellent methods exist to obtain structures of molecules at atomic, organelles at electron microscopic, and tissue at light-microscopic resolution. A gap exists, however, when 3D tissue structure needs to be reconstructed over hundreds of micrometers with a resolution sufficient to follow the thinnest cellular processes and to identify small organelles such as synaptic vesicles. Such 3D data are, however, essential to understand cellular networks that, particularly in the nervous system, need to be completely reconstructed throughout a substantial spatial volume. Here we demonstrate that datasets meeting these requirements can be obtained by automated block-face imaging combined with serial sectioning inside the chamber of a scanning electron microscope. Backscattering contrast is used to visualize the heavy-metal staining of tissue prepared using techniques that are routine for transmission electron microscopy. Low-vacuum (20–60 Pa H2O) conditions prevent charging of the uncoated block face. The resolution is sufficient to trace even the thinnest axons and to identify synapses. Stacks of several hundred sections, 50–70 nm thick, have been obtained at a lateral position jitter of typically under 10 nm. This opens the possibility of automatically obtaining the electron-microscope-level 3D datasets needed to completely reconstruct the connectivity of neuronal circuits.},
    number = {11}
}

@article{Wei2012,
author = {Wei, Dongguang and Jacobs, Scott and Modla, Shannon and Zhang, Shuang and Young, Carissa L. and Cirino, Robert and Caplan, Jeffrey and Czymmek, Kirk},
title = {High-resolution three-dimensional reconstruction of a whole yeast cell using focused-ion beam scanning electron microscopy},
journal = {BioTechniques},
volume = {53},
number = {1},
pages = {41-48},
year = {2012},
doi = {10.2144/000113850},
note ={PMID: 22780318},
URL = {https://doi.org/10.2144/000113850},
eprint = {https://doi.org/10.2144/000113850},
    abstract = { We developed an approach for focused gallium-ion beam scanning electron microscopy with energy filtered detection of backscattered electrons to create near isometric voxels for high-resolution whole cell visualization. Specifically, this method allowed us to create three-dimensional volumes of high-pressure frozen, freeze-substituted Saccharomyces cerevisiae yeast cells with pixel resolutions down to 3 nm/pixel in x, y, and z, supported by both empirical data and Monte Carlo simulations. As a result, we were able to segment and quantify data sets of numerous targeted subcellular structures/organelles at high-resolution, including the volume, volume percentage, and surface area of the endoplasmic reticulum, cell wall, vacuoles, and mitochondria from an entire cell. Sites of mitochondrial and endoplasmic reticulum interconnectivity were readily identified in rendered data sets. The ability to visualize, segment, and quantify entire eukaryotic cells at high-resolution (potentially sub-5 nanometers isotropic voxels) will provide new perspectives and insights of the inner workings of cells. }
}




@article{YOUNG1993,
author = {YOUNG, R. J. and DINGLE, T. and ROBINSON, K. and PUGH, P. J. A.},
title = {An application of scanned focused ion beam milling to studies on the internal morphology of small arthropods},
journal = {Journal of Microscopy},
volume = {172},
number = {1},
pages = {81-88},
keywords = {Arthropods, morphology, ion beam milling, focused ion beam milling, scanning electron microscopy},
doi = {https://doi.org/10.1111/j.1365-2818.1993.tb03396.x},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-2818.1993.tb03396.x},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2818.1993.tb03396.x},
abstract = {Summary For the first time a scanned focused ion beam of approximately 50 nm diameter has been used to prepare biological material. Small defined areas of the surface were removed by ion etching to allow examination of the underlying structures with a scanning electron microscope. Different milling procedures were carried out on two anatomical features in mites of the genus Halarachne (Halarachnidae: Mesostigmata). In the first, square holes were milled into the surface of the peritrematal plate to reveal the structure of the underlying respiratory peritrematal groove. In the second, transverse cuts were made across the shafts of the sensory sensilli which make up the sensory Haller's organ on tarsus I. This latter procedure revealed detail both within the core and walls of sensilli. Details of specimen preparation and milling procedures, as well as suitability and interpretation of results, are presented.},
year = {1993}
}




@article{Eberle2014Mission,
    author = {Eberle, Anna Lena and Selchow, Olaf and Thaler, Marlene and Zeidler, Dirk and Kirmse, Robert},
    title = "{Mission (im)possible – mapping the brain becomes a reality}",
    journal = {Microscopy},
    volume = {64},
    number = {1},
    pages = {45-55},
    year = {2014},
    month = {12},
    abstract = "{Charting and understanding the full wiring diagram of complex neuronal structures such as the central nervous system or the brain (Connectomics) is one of the big remaining challenges in life sciences. Although at first it appears nearly impossible to map out a full diagram of, e.g., a mouse brain with sufficient resolution to identify each and every connection between neurons, recent technological advances move such an ambitious undertaking into the realms of possibility without spending decades at a microscope. However there are still many challenges to address in order to pave the way for fast and systematic neurobiological understanding of whole networks. These challenges range from a more robust and reproducible sample preparation to automated image data acquisition, more efficient data storage strategies and powerful data analysis tools. Here we will review novel imaging techniques developed for the challenge of mapping out the full connectome of a nervous system, brain or eye to name just a few examples. The imaging techniques reviewed cover light sheet illumination methods, single and multi-beam scanning electron microscopy, and we will briefly mention the possible combination of both light and electron microscopy. In particular we will review ‘clearing’ and in vivo methods that can be performed with light sheet fluroescence microscopes such as the ZEISS Lightsheet Z.1. We will then focus on scanning electron microscopy with single and multi-beam instruments including methods such as serial blockface imaging and array tomography methods.}",
    issn = {2050-5698},
    doi = {10.1093/jmicro/dfu104},
    url = {https://doi.org/10.1093/jmicro/dfu104},
    eprint = {https://academic.oup.com/jmicro/article-pdf/64/1/45/26556719/dfu104.pdf},
}

@article{IRENE2015,
author = {WACKER, IRENE and CHOCKLEY, PETER and BARTELS, CAROLIN and SPOMER, WALDEMAR and HOFMANN, ANDREAS and GENGENBACH, ULRICH and SINGH, SACHIN and THALER, MARLENE and GRABHER, CLEMENS and SCHRÖDER, RASMUS R.},
title = {Array tomography: characterizing FAC-sorted populations of zebrafish immune cells by their 3D ultrastructure},
journal = {Journal of Microscopy},
volume = {259},
number = {2},
pages = {105-113},
keywords = {3D reconstruction, array tomography, cytotoxic cells, immunological synapse, large volume ultrastructure, zebrafish},
doi = {https://doi.org/10.1111/jmi.12223},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/jmi.12223},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/jmi.12223},
abstract = {Summary For 3D reconstructions of whole immune cells from zebrafish, isolated from adult animals by FAC-sorting we employed array tomography on hundreds of serial sections deposited on silicon wafers. Image stacks were either recorded manually or automatically with the newly released ZEISS Atlas 5 Array Tomography platform on a Zeiss FEGSEM. To characterize different populations of immune cells, organelle inventories were created by segmenting individual cells. In addition, arrays were used for quantification of cell populations with respect to the various cell types they contained. The detection of immunological synapses in cocultures of cell populations from thymus or WKM with cancer cells helped to identify the cytotoxic nature of these cells. Our results demonstrate the practicality and benefit of AT for high-throughput ultrastructural imaging of substantial volumes.},
year = {2015}
}



@article{Koga2015,
    author = {Koga, Daisuke and Kusumi, Satoshi and Ushiki, Tatsuo},
    title = "{ Three-dimensional shape of the Golgi apparatus in different cell types: serial section scanning electron microscopy of the osmium-impregnated Golgi apparatus †}",
    journal = {Microscopy},
    volume = {65},
    number = {2},
    pages = {145-157},
    year = {2015},
    month = {11},
    abstract = "{Although many studies of the Golgi apparatus structure have been performed by light and electron microscopy, the full shape of the Golgi apparatus remained unclear due to the technical limitations of the previously applied microscopy techniques. In this study, we used serial section scanning electron microscopy (SEM) for the morphological study of the Golgi apparatus. This method is useful for three-dimensional (3D) reconstruction of cellular structures without requiring specialized instruments, unlike focused ion beam SEM (FIB-SEM) and serial block face SEM (SBF-SEM). Using the serial section SEM method developed by our laboratory, we investigate the 3D shape of the osmium-impregnated Golgi apparatus in rat epididymal cells, pancreatic acinar cells and gonadotropes. The combination of serial section SEM and a 3D reconstruction technique enabled us to elucidate the entire shape of the Golgi apparatus in these cells. The full shape of the Golgi apparatus in epididymal cells formed a basket-like structure with oval-shaped cisterns, while the Golgi apparatus in an acinar cell from the pancreas was composed of elongated ribbon-like structures that were connected to each other, making a coarse network. The overall image of the Golgi apparatus cisterns from a gonadotrope looked like a spherical cage. This study has clearly shown that entire 3D shape of the Golgi apparatus varies depending on the cell type and that the Golgi cisterns network appears as a single mass located in the large region of the cytoplasm.}",
    issn = {2050-5698},
    doi = {10.1093/jmicro/dfv360},
    url = {https://doi.org/10.1093/jmicro/dfv360},
    eprint = {https://academic.oup.com/jmicro/article-pdf/65/2/145/7952449/dfv360.pdf},
}







@Article{Kubota2018,
author={Kubota, Yoshiyuki
and Sohn, Jaerin
and Hatada, Sayuri
and Schurr, Meike
and Straehle, Jakob
and Gour, Anjali
and Neujahr, Ralph
and Miki, Takafumi
and Mikula, Shawn
and Kawaguchi, Yasuo},
title={A carbon nanotube tape for serial-section electron microscopy of brain ultrastructure},
journal={Nature Communications},
year={2018},
month={Jan},
day={30},
volume={9},
number={1},
pages={437},
abstract={Automated tape-collecting ultramicrotomy in conjunction with scanning electron microscopy (SEM) is a powerful approach for volume electron microscopy and three-dimensional neuronal circuit analysis. Current tapes are limited by section wrinkle formation, surface scratches and sample charging during imaging. Here we show that a plasma-hydrophilized carbon nanotube (CNT)-coated polyethylene terephthalate (PET) tape effectively resolves these issues and produces SEM images of comparable quality to those from transmission electron microscopy. CNT tape can withstand multiple rounds of imaging, offer low surface resistance across the entire tape length and generate no wrinkles during the collection of ultrathin sections. When combined with an enhanced en bloc staining protocol, CNT tape-processed brain sections reveal detailed synaptic ultrastructure. In addition, CNT tape is compatible with post-embedding immunostaining for light and electron microscopy. We conclude that CNT tape can enable high-resolution volume electron microscopy for brain ultrastructure analysis.},
issn={2041-1723},
doi={10.1038/s41467-017-02768-7},
url={https://doi.org/10.1038/s41467-017-02768-7}
}
¥¥
@Article{Trzaskoma2020,
author={Trzaskoma, Pawe{\l}
and Ruszczycki, B{\l}a{\.{z}}ej
and Lee, Byoungkoo
and Pels, Katarzyna K.
and Krawczyk, Katarzyna
and Bokota, Grzegorz
and Szczepankiewicz, Andrzej A.
and Aaron, Jesse
and Walczak, Agnieszka
and {\'{S}}liwi{\'{n}}ska, Ma{\l}gorzata A.
and Magalska, Adriana
and Kadlof, Michal
and Wolny, Artur
and Parteka, Zofia
and Arabasz, Sebastian
and Kiss-Arabasz, Magdalena
and Plewczy{\'{n}}ski, Dariusz
and Ruan, Yijun
and Wilczy{\'{n}}ski, Grzegorz M.},
title={Ultrastructural visualization of 3D chromatin folding using volume electron microscopy and DNA in situ hybridization},
journal={Nature Communications},
year={2020},
month={May},
day={01},
volume={11},
number={1},
pages={2120},
abstract={The human genome is extensively folded into 3-dimensional organization. However, the detailed 3D chromatin folding structures have not been fully visualized due to the lack of robust and ultra-resolution imaging capability. Here, we report the development of an electron microscopy method that combines serial block-face scanning electron microscopy with in situ hybridization (3D-EMISH) to visualize 3D chromatin folding at targeted genomic regions with ultra-resolution (5 {\texttimes} 5 {\texttimes} 30{\thinspace}nm in xyz dimensions) that is superior to the current super-resolution by fluorescence light microscopy. We apply 3D-EMISH to human lymphoblastoid cells at a 1.7{\thinspace}Mb segment of the genome and visualize a large number of distinctive 3D chromatin folding structures in ultra-resolution. We further quantitatively characterize the reconstituted chromatin folding structures by identifying sub-domains, and uncover a high level heterogeneity of chromatin folding ultrastructures in individual nuclei, suggestive of extensive dynamic fluidity in 3D chromatin states.},
issn={2041-1723},
doi={10.1038/s41467-020-15987-2},
url={https://doi.org/10.1038/s41467-020-15987-2}
}



@article{Burel2018,
    author = {Burel, Agnes and Lavault, Marie-Thérèse and Chevalier, Clément and Gnaegi, Helmut and Prigent, Sylvain and Mucciolo, Antonio and Dutertre, Stéphanie and Humbel, Bruno M. and Guillaudeux, Thierry and Kolotuev, Irina},
    title = "{A targeted 3D EM and correlative microscopy method using SEM array tomography}",
    journal = {Development},
    volume = {145},
    number = {12},
    year = {2018},
    month = {06},
    abstract = "{Using electron microscopy to localize rare cellular events or structures in complex tissue is challenging. Correlative light and electron microscopy procedures have been developed to link fluorescent protein expression with ultrastructural resolution. Here, we present an optimized scanning electron microscopy (SEM) workflow for volumetric array tomography for asymmetric samples and model organisms (Caenorhabditis elegans, Drosophila melanogaster, Danio rerio). We modified a diamond knife to simplify serial section array acquisition with minimal artifacts. After array acquisition, the arrays were transferred to a glass coverslip or silicon wafer support. Using light microscopy, the arrays were screened rapidly for initial recognition of global anatomical features (organs or body traits). Then, using SEM, an in-depth study of the cells and/or organs of interest was performed. Our manual and automatic data acquisition strategies make 3D data acquisition and correlation simpler and more precise than alternative methods. This method can be used to address questions in cell and developmental biology that require the efficient identification of a labeled cell or organelle.}",
    issn = {0950-1991},
    doi = {10.1242/dev.160879},
    url = {https://doi.org/10.1242/dev.160879},
    note = {dev160879},
    eprint = {https://journals.biologists.com/dev/article-pdf/145/12/dev160879/1853364/dev160879.pdf}
}





@article {Templier2019,
article_type = {journal},
title = {MagC, magnetic collection of ultrathin sections for volumetric correlative light and electron microscopy},
author = {Templier, Thomas},
editor = {Helmstaedter, Moritz and Marder, Eve},
volume = 8,
year = 2019,
month = {jul},
pub_date = {2019-07-11},
pages = {e45696},
citation = {eLife 2019;8:e45696},
doi = {10.7554/eLife.45696},
url = {https://doi.org/10.7554/eLife.45696},
abstract = {The non-destructive collection of ultrathin sections on silicon wafers for post-embedding staining and volumetric correlative light and electron microscopy traditionally requires exquisite manual skills and is tedious and unreliable. In MagC introduced here, sample blocks are augmented with a magnetic resin enabling the remote actuation and collection of hundreds of sections on wafer. MagC allowed the correlative visualization of neuroanatomical tracers within their ultrastructural volumetric electron microscopy context.},
keywords = {ultramicrotomy, correlative light and electron microscopy, connectomics, Zebra Finch},
journal = {eLife},
issn = {2050-084X},
publisher = {eLife Sciences Publications, Ltd},
}



@Article{Kasthuri2015,
author={Kasthuri, Narayanan
and Hayworth, Kenneth Jeffrey
and Berger, Daniel Raimund
and Schalek, Richard Lee
and Conchello, Jos{\'e} Angel
and Knowles-Barley, Seymour
and Lee, Dongil
and V{\'a}zquez-Reina, Amelio
and Kaynig, Verena
and Jones, Thouis Raymond
and Roberts, Mike
and Morgan, Josh Lyskowski
and Tapia, Juan Carlos
and Seung, H. Sebastian
and Roncal, William Gray
and Vogelstein, Joshua Tzvi
and Burns, Randal
and Sussman, Daniel Lewis
and Priebe, Carey Eldin
and Pfister, Hanspeter
and Lichtman, Jeff William},
title={Saturated Reconstruction of a Volume of Neocortex},
journal={Cell},
year={2015},
month={Jul},
day={30},
publisher={Elsevier},
volume={162},
number={3},
pages={648-661},
issn={0092-8674},
doi={10.1016/j.cell.2015.06.054},
url={https://doi.org/10.1016/j.cell.2015.06.054}
}



@ARTICLE{Eberle2018,
AUTHOR={Eberle, Anna Lena and Zeidler, Dirk},
TITLE={Multi-Beam Scanning Electron Microscopy for High-Throughput Imaging in Connectomics Research},
JOURNAL={Frontiers in Neuroanatomy},
VOLUME={12},
PAGES={112},
YEAR={2018},
URL={https://www.frontiersin.org/article/10.3389/fnana.2018.00112},
DOI={10.3389/fnana.2018.00112},
ISSN={1662-5129},
ABSTRACT={Major progress has been achieved in recent years in three-dimensional microscopy techniques. This applies to the life sciences in general, but specifically the neuroscientific field has been a main driver for developments regarding volume imaging. In particular, scanning electron microscopy offers new insights into the organization of cells and tissues by volume imaging methods, such as serial section array tomography, serial block-face imaging or focused ion beam tomography. However, most of these techniques are restricted to relatively small tissue volumes due to the limited acquisition throughput of most standard imaging techniques. Recently, a novel multi-beam scanning electron microscope technology optimized to the imaging of large sample areas has been developed. Complemented by the commercialization of automated sample preparation robots, the mapping of larger, cubic millimeter range tissue volumes at high-resolution is now within reach. This Mini Review will provide a brief overview of the various approaches to electron microscopic volume imaging, with an emphasis on serial section array tomography and multi-beam scanning electron microscopic imaging.}
}

@article{EBERLE2015microscopy,
author = {EBERLE, A.L. and MIKULA, S. and SCHALEK, R. and LICHTMAN, J. and TATE, M.L. KNOTHE and ZEIDLER, D.},
title = {High-resolution, high-throughput imaging with a multibeam scanning electron microscope},
journal = {Journal of Microscopy},
volume = {259},
number = {2},
pages = {114-120},
keywords = {High-throughput imaging, multibeam, parallel data acquisition, scanning electron microscopy},
doi = {https://doi.org/10.1111/jmi.12224},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/jmi.12224},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/jmi.12224},
abstract = {Summary Electron–electron interactions and detector bandwidth limit the maximal imaging speed of single-beam scanning electron microscopes. We use multiple electron beams in a single column and detect secondary electrons in parallel to increase the imaging speed by close to two orders of magnitude and demonstrate imaging for a variety of samples ranging from biological brain tissue to semiconductor wafers.},
year = {2015}
}


@article{Eberle2015, 
title={Multiple-Beam Scanning Electron Microscopy},
 volume={23}, 
 DOI={10.1017/S1551929515000012}, number={2}, journal={Microscopy Today}, publisher={Cambridge University Press}, 
 author={Lena Eberle, Anna and Schalek, Richard and Lichtman, Jeff W. and Malloy, Matt and Thiel, Brad and Zeidler, Dirk}, year={2015}, pages={12–19}}


@article{Ren2016,
author = {Ren,Yan  and Kruit,Pieter },
title = {Transmission electron imaging in the Delft multibeam scanning electron microscope 1},
journal = {Journal of Vacuum Science \& Technology B},
volume = {34},
number = {6},
pages = {06KF02},
year = {2016},
doi = {10.1116/1.4966216},
URL = {https://doi.org/10.1116/1.4966216},
eprint = {https://doi.org/10.1116/1.4966216}
}



@book{Hooke1665,
title = {Micrographia, or, Some physiological descriptions of minute bodies made by magnifying glasses :with observations and inquiries thereupon  },
copyright = {Public domain.  The BHL considers that this work is no longer under copyright protection.},
url = {https://www.biodiversitylibrary.org/item/15485},
note = {https://www.biodiversitylibrary.org/bibliography/904},
publisher = {London :Printed by Jo. Martyn and Ja. Allestry, printers to the Royal Society ... ,},
author = {Hooke, Robert and Allestry, James and Martyn, John},
year = {1665},
pages = {323},
keywords = {Early works to 1800|Microscopy|Natural history|Pre-Linnean works},
}

@Article{Ruska1987,
author={Ruska, Ernst},
title={The development of the electron microscope and of electron microscopy},
journal={Bioscience Reports},
year={1987},
month={Aug},
day={01},
volume={7},
number={8},
pages={607-629},
issn={1573-4935},
doi={10.1007/BF01127674},
url={https://doi.org/10.1007/BF01127674}
}

@article{Knoll1932,
  title={Das Elektronenmikroskop},
  author={Knoll, M. and Ruska, E.},
  journal={Zeitschrift für Physik},
  year={1932},
  volume={78},
  pages={318 --339},
  url={https://link.springer.com/article/10.1007/BF01342199}
}

@InProceedings{Kume2017,
author="Kume, Satoshi and Masuya, Hiroshi and Maeda, Mitsuyo and Suga, Mitsuo and Kataoka, Yosky and Kobayashi, Norio",
editor="Wang, Zhe and Turhan, Anni-Yasmin and Wang, Kewen and Zhang, Xiaowang",
title="Development of Semantic Web-Based Imaging Database for Biological Morphome",
booktitle="Semantic Technology",
year="2017",
publisher="Springer International Publishing",
address="Cham",
pages="277--285",
abstract="We introduce the RIKEN Microstructural Imaging Metadatabase, a semantic web-based imaging database in which image metadata are described using the Resource Description Framework (RDF) and detailed biological properties observed in the images can be represented as Linked Open Data. The metadata are used to develop a large-scale imaging viewer that provides a straightforward graphical user interface to visualise a large microstructural tiling image at the gigabyte level. We applied the database to accumulate comprehensive microstructural imaging data produced by automated scanning electron microscopy. As a result, we have successfully managed vast numbers of images and their metadata, including the interpretation of morphological phenotypes occurring in sub-cellular components and biosamples captured in the images. We also discuss advanced utilisation of morphological imaging data that can be promoted by this database.",
isbn="978-3-319-70682-5"
}

@article{Kobayashi2018,
  title={RIKEN MetaDatabase: A Database Platform for Health Care and Life Sciences as a Microcosm of Linked Open Data Cloud},
  author={Norio Kobayashi and S. Kume and K. Lenz and H. Masuya},
  journal={Int. J. Semantic Web Inf. Syst.},
  year={2018},
  volume={14},
  pages={140-164}
}

@article{Kiernan2007,
author = {John A. Kiernan},
title = {Histochemistry of Staining Methods for Normal and Degenerating Myelin in the Central and Peripheral Nervous Systems},
journal = {Journal of Histotechnology},
volume = {30},
number = {2},
pages = {87-106},
year  = {2007},
publisher = {Taylor & Francis},
doi = {10.1179/his.2007.30.2.87},
URL = {https://doi.org/10.1179/his.2007.30.2.87},
eprint = {https://doi.org/10.1179/his.2007.30.2.87}
}

@article{Moran1964,
    author = {Fernández-Morán , H.  and Oda , T.  and Blair , P. V.  and Green , D. E. },
    title = "{A MACROMOLECULAR REPEATING UNIT OF MITOCHONDRIAL STRUCTURE AND FUNCTION : Correlated Electron Microscopic and Biochemical Studies of Isolated Mitochondria and Submitochondrial Particles of Beef Heart Muscle }",
    journal = {Journal of Cell Biology},
    volume = {22},
    number = {1},
    pages = {63-100},
    year = {1964},
    month = {07},
    abstract = "{A repeating particle associated with the cristae and the inner membrane of the external envelope has been recognized and characterized in beef heart mitochondria by correlated electron microscopic and biochemical studies. Many thousands (ca. 104 to 105) of these particles, disposed in regular arrays, are present in a single mitochondrion. The repeating particle, called the elementary particle (EP), consists of three parts: (1) a spherical or polyhedral head piece (80 to 100 A in diameter); (2) a cylindrical stalk (about 50 A long and 30 to 40 A wide); and (3) a base piece (40 x 110 A). The base pieces of the elementary particles form an integral part of the outer dense layers of the cristae. The elementary particles can be seen in electron micrographs of mitochondria in situ, of isolated mitochondria, and of submitochondrial particles with a complete electron transfer chain. Negative staining with phosphotungstate is only one of several techniques that can be used for reproducible demonstration of the repeating particles and underlying subunit organization of mitochondrial membranes. A particulate unit containing a complete electron transfer chain can be isolated from beef heart mitochondria. The isolated unit approximates in size that of the elementary particle in situ. The molecular weight of the particle in situ is calculated to be 1.3 x 106. Evidence is presented for identifying the isolated unit with the elementary particle visualized in situ. The elementary particle of the mitochondrion is believed to be a prototype of a class of functional particles or macromolecular assemblies of similar size found in association with membranes generally. }",
    issn = {0021-9525},
    doi = {10.1083/jcb.22.1.63},
    url = {https://doi.org/10.1083/jcb.22.1.63},
    eprint = {https://rupress.org/jcb/article-pdf/22/1/63/1402067/63.pdf},
}





@article{Moran1953,
title = {A diamond knife for ultrathin sectioning},
journal = {Experimental Cell Research},
volume = {5},
number = {1},
pages = {255-256},
year = {1953},
issn = {0014-4827},
doi = {https://doi.org/10.1016/0014-4827(53)90112-8},
url = {https://www.sciencedirect.com/science/article/pii/0014482753901128},
author = {Fern{\'a}ndez-Mor{\'a}n, Humberto}
}

@Article{MORAN1956,
author={Fern{\'a}ndez-Mor{\'a}n, Humberto},
title={Fine Structure of the Insect Retinula as Revealed by Electron Microscopy},
journal={Nature},
year={1956},
month={Apr},
day={01},
volume={177},
number={4512},
pages={742-743},
issn={1476-4687},
doi={10.1038/177742a0},
url={https://doi.org/10.1038/177742a0}
}

@article{Konyuba2018,
    author = {Konyuba, Yuji and Haruta, Tomohiro and Ikeda, Yuta and Fukuda, Tomohisa},
    title = "{Fabrication and characterization of sample-supporting film made of silicon nitride for large-area observation in transmission electron microscopy}",
    journal = {Microscopy},
    volume = {67},
    number = {6},
    pages = {367--370},
    year = {2018},
    month = {09},
    abstract = "{In transmission electron microscopy (TEM), silicon nitride (SiN) films are widely used as sample-supporting films owing to their robustness. We fabricated large-scale SiN films deposited by low-pressure chemical vapor deposition (LPCVD). This preparation method is advantageous for large window areas, since it yields films with control over properties such as tension and thickness. We fabricated large SiN windows for mounting large ultrathin sections and for acquiring large-area TEM images. Thus, sample sections sliced by conventional sample preparation techniques were successfully mounted on these sample-supporting films. We successfully obtained a 680 × 250 μm2 TEM montage image of a whole Drosophila embryo.}",
    issn = {2050-5698},
    doi = {10.1093/jmicro/dfy039},
    url = {https://doi.org/10.1093/jmicro/dfy039},
    eprint = {https://academic.oup.com/jmicro/article-pdf/67/6/367/27008907/dfy039.pdf},
}

@Article{Koch1882,
author={Koch, Robert},
title={Die Aetiologie der Tuberculose},
journal={Berliner Klinische Wochenschrift},
year={1882},
volume={15},
pages={221--232},
url={https://pubmed.ncbi.nlm.nih.gov/6805152/}
}

@article{Noguchi1911,
    author = {Noguchi, Hideyo},
    title = "{METHOD FOR THE PURE CULTIVATION OF PATHOGENIC TREPONEMA PALLIDUM (SPIROCHÆTA PALLIDA) }",
    journal = {Journal of Experimental Medicine},
    volume = {14},
    number = {2},
    pages = {99-108},
    year = {1911},
    month = {08},
    abstract = "{In conclusion, it may be pointed out that this is the first time that Treponema pallidum of Schaudinn has been proven beyond all doubt to have been obtained in pure culture. The method of cultivation described would appear also to be suitable for obtaining indefinite generations of the microorganism. Doubtless slight modifications will adapt it to a larger number of strains and possibly to the cultivation of all strains and to still other species of treponema. Finally, it may now be accepted as established that the testicular lesions produced in rabbits by means of syphilitic materials are the result of the multiplication of the pallida and not of some associated indefinite parasite. }",
    issn = {0022-1007},
    doi = {10.1084/jem.14.2.99},
    url = {https://doi.org/10.1084/jem.14.2.99},
    eprint = {https://rupress.org/jem/article-pdf/14/2/99/1090122/99.pdf},
}

@Article{Adelmann1882,
author={Adelmann, HB.},
title={Marcello Malpighi and the Evolution of Embryology},
journal={Ithaca, NY: Cornell Univ. Press},
year={1966},
url={https://pubmed.ncbi.nlm.nih.gov/6805152/}
}

@article{Hwa2007,
author = {Hwa, Charlotte and Aird, William C.},
title = {The history of the capillary wall: doctors, discoveries, and debates},
journal = {American Journal of Physiology-Heart and Circulatory Physiology},
volume = {293},
number = {5},
pages = {H2667-H2679},
year = {2007},
doi = {10.1152/ajpheart.00704.2007},
note ={PMID: 17693543},
URL = { https://doi.org/10.1152/ajpheart.00704.2007 },
eprint = { https://doi.org/10.1152/ajpheart.00704.2007},
abstract = { In 1628, William Harvey provided definitive evidence that blood circulates. The notion that blood travels around the body in a circle raised the important question of how nutrients pass between blood and underlying tissue. Perhaps, Harvey posited, arterial blood pours into the flesh as into a sponge, only then to find its way into the veins. Far from solving this problem, Marcello Malpighi's discovery of the capillaries in 1661 only added to the dilemma: surely, some argued, these entities are little more than channels drilled into tissues around them. As we discuss in this review, it would take over 200 years to arrive at a consensus on the basic structure and function of the capillary wall. A consideration of the history of this period provides interesting insights into not only the central importance of the capillary as a focus of investigation, but also the enormous challenges associated with studying these elusive structures. }
}

@article{Leeuwenhoeck1674,
author = {Leeuwenhoeck, M },
title = {Microscopical observations from Leeuwenhoeck, concerning blood, milk, bones, the brain, spitle, and cuticula, \&amp;c. communicated by the said observer to the Publisher in a letter, dated June 1. 1674},
journal = {Philosophical Transactions of the Royal Society of London},
volume = {9},
number = {106},
pages = {121-131},
year = {1674},
doi = {10.1098/rstl.1674.0030},
URL = {https://royalsocietypublishing.org/doi/abs/10.1098/rstl.1674.0030},
eprint = {https://royalsocietypublishing.org/doi/pdf/10.1098/rstl.1674.0030},
abstract = { Sir, Yours of 24th of April last was very welcome to me; Whence I understood with great contentment, that my Microscopical Communications had not been unacceptable to you and your Philosophical Friends; which hath encouraged me to prosecute such observations, concerning which I shall at present impart to you what follows }
}

@Article{Cajal1888,
author={Cajal, Santiago Ramón},
title={Estructura de los centros nerviosos de las aves},
journal={Rev. Trim. Histol. Norm. Patol.},
volume = {1},
pages = {1--10},
year={1888}
}

@ARTICLE{DeFelipe2015,
AUTHOR={DeFelipe, Javier},   	 
TITLE={The dendritic spine story: an intriguing process of discovery},      
JOURNAL={Frontiers in Neuroanatomy},      	
VOLUME={9},      
PAGES={14},     
YEAR={2015},      
URL={https://www.frontiersin.org/article/10.3389/fnana.2015.00014},       	
DOI={10.3389/fnana.2015.00014},      
ISSN={1662-5129},      
ABSTRACT={Dendritic spines are key components of a variety of microcircuits and they represent the majority of postsynaptic targets of glutamatergic axon terminals in the brain. The present article will focus on the discovery of dendritic spines, which was possible thanks to the application of the Golgi technique to the study of the nervous system, and will also explore the early interpretation of these elements. This discovery represents an interesting chapter in the history of neuroscience as it shows us that progress in the study of the structure of the nervous system is based not only on the emergence of new techniques but also on our ability to exploit the methods already available and correctly interpret their microscopic images.}
}

@article{Francisco2006,
title = {Neuron theory, the cornerstone of neuroscience, on the centenary of the Nobel Prize award to Santiago Ramón y Cajal},
journal = {Brain Research Bulletin},
volume = {70},
number = {4},
pages = {391-405},
year = {2006},
issn = {0361-9230},
doi = {https://doi.org/10.1016/j.brainresbull.2006.07.010},
url = {https://www.sciencedirect.com/science/article/pii/S0361923006002334},
author = {Francisco López-Muñoz and Jesús Boya and Cecilio Alamo},
keywords = {History of neuroscience, Neuron theory, Reticular theory, Cajal},
abstract = {Exactly 100 years ago, the Nobel Prize for Physiology and Medicine was awarded to Santiago Ramón y Cajal, “in recognition of his meritorious work on the structure of the nervous system”. Cajal's great contribution to the history of science is undoubtedly the postulate of neuron theory. The present work makes a historical analysis of the circumstances in which Cajal formulated his theory, considering the authors and works that influenced his postulate, the difficulties he encountered for its dissemination, and the way it finally became established. At the time when Cajal began his neurohistological studies, in 1887, Gerlach's reticular theory (a diffuse protoplasmic network of the grey matter of the nerve centres), also defended by Golgi, prevailed among the scientific community. In the first issue of the Revista Trimestral de Histología Normal y Patológica (May, 1888), Cajal presented the definitive evidence underpinning neuron theory, thanks to staining of the axon of the small, star-shaped cells of the molecular layer of the cerebellum of birds, whose collaterals end up surrounding the Purkinje cell bodies, in the form of baskets or nests. He thus demonstrated once and for all that the relationship between nerve cells was not one of continuity, but rather of contiguity. Neuron theory is one of the principal scientific conquests of the 20th century, and which has withstood, with scarcely any modifications, the passage of more than a 100 years, being reaffirmed by new technologies, as the electron microscopy. Today, no neuroscientific discipline could be understood without recourse to the concept of neuronal individuality and nervous transmission at a synaptic level, as basic units of the nervous system.}
}

@article{Hall2021, 
title={DNA translated: Friedrich Miescher's discovery of nuclein in its original context}, 
volume={54}, 
DOI={10.1017/S000708742000062X}, 
number={1}, 
journal={The British Journal for the History of Science}, 
publisher={Cambridge University Press}, 
author={Hall, Kersten and Sankaran, Neeraja}, 
year={2021}, 
pages={99–107}
}

@Article{Ackermann2011,
author={Ackermann, Hans-W},
title={Ruska H. Visualization of bacteriophage lysis in the hypermicroscope. Naturwissenschaften1940; 28:45-6},
journal={Bacteriophage},
year={2011},
month={Jul},
day={01},
publisher={Landes Bioscience},
volume={1},
number={4},
pages={183-185},
note={23616930[pmid]},
issn={2159-7073},
doi={10.4161/bact.1.4.17624},
url={https://pubmed.ncbi.nlm.nih.gov/23616930},
url={https://doi.org/10.4161/bact.1.4.17624},
language={eng}
}

@article{Porter1953,
author = {Porter, Keith R. and Blum, J.},
title = {A study in microtomy for electron microscopy},
journal = {The Anatomical Record},
volume = {117},
number = {4},
pages = {685-709},
doi = {https://doi.org/10.1002/ar.1091170403},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/ar.1091170403},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/ar.1091170403},
year = {1953}
}

@article{Sjostrand1953,
author = {Sjöstrand, Fritiof S.},
title = {The ultrastructure of the inner segments of the retinal rods of the guinea pig eye as revealed by electron microscopy},
journal = {Journal of Cellular and Comparative Physiology},
volume = {42},
number = {1},
pages = {45-70},
doi = {https://doi.org/10.1002/jcp.1030420104},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/jcp.1030420104},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcp.1030420104},
year = {1953}
}






@article{Pease1948,
author = {Daniel C. Pease and Richard F. Baker},
title ={Sectioning Techniques for Electron Microscopy Using a Conventional Microtome},
journal = {Proceedings of the Society for Experimental Biology and Medicine},
volume = {67},
number = {4},
pages = {470-474},
year = {19481948},
doi = {10.3181/00379727-67-16344},
URL = {https://doi.org/10.3181/00379727-67-16344},
eprint = {https://doi.org/10.3181/00379727-67-16344},
    abstract = { SummaryConventional histological techniques have been modified so that is is possible consistently to cut 0.2 micron sections for use with the electron microscope. The material must be doubly embedded in strong collodion and hard paraffin. The face of the block to be cut must be small, and the tilt of the knife must be precisely adjusted.Procedures have been developed for partly or wholly removing the embedding media, and mounting the sections for the electron microscope.Micrographs of rat liver sections show that the principal artefacts are due to fixation rather than subsequent treatments. }
}




@incollection{Gelderblom2014,
title = {1 - Helmut Ruska (1908–1973): His Role in the Evolution of Electron Microscopy in the Life Sciences, and Especially Virology},
editor = {Peter W. Hawkes},
series = {Advances in Imaging and Electron Physics},
publisher = {Elsevier},
volume = {182},
pages = {1-94},
year = {2014},
issn = {1076-5670},
doi = {https://doi.org/10.1016/B978-0-12-800146-2.00001-1},
url = {https://www.sciencedirect.com/science/article/pii/B9780128001462000011},
author = {Gelderblom, Hans R.  and Krüger, Detlev H. },
keywords = {Helmut Ruska, Richard Siebeck, Early history of electron microscopy, electron microscopy in the life sciences, phage morphology, virus morphology, virus classification},
abstract = {The electron microscope first appeared in the 1930s in Berlin, where three groups competed in its construction: Ramsauer, Brüche, Scherzer and Mahl at AEG, the independent entrepreneur Manfred von Ardenne and Knoll, Ernst Ruska and Bodo von Borries at the Technical High School. All three developed instruments but further progress required industrial involvement. Industry was reluctant to launch serial production until pressure was exerted by Richard Siebeck, a senior clinician, persuaded of the importance of the electron microscope in medicine by Ernst Ruska's brother Helmut. Siemens then embarked on development and production of the instrument and when the first two prototype Übermikroskope went into action early in 1938, Helmut Ruska took over sample preparation and application in the life sciences. Development of the instrument and virology benefited each other mutually. Still in 1938, images of bacteria and of poxviruses - the first viruses ever to be shown - were presented in lectures and publications. In 1939, Helmut Ruska published numerous papers, notably on plant viruses together with G. Kausche, and in 1940, Siemens set up a “Laboratorium für Übermikroskopie” headed by Ruska to be used also by guest scientists. In the same year, he described the life cycle and morphology of phages. Helmut Ruska was a major figure in electron microscopy in the life sciences throughout his life. His career is traced here from its beginnings in the 1930s and during WWII, after which he spent several years in the USA. Bodo von Borries had founded an Institut für Übermikroskopie in Düsseldorf and on his early death in 1956, Helmut Ruska returned to Germany as head of this institute. He was a never-resting advocate of electron microscopy, furthered the field in many ways and is remembered as a pioneer in vertebrate, plant and bacterial virology and in virus classification.}
}

@Article{MARTON1934,
author={MARTON, L.},
title={Electron Microscopy of Biological Objects},
journal={Nature},
year={1934},
month={Jun},
day={01},
volume={133},
number={3372},
pages={911-911},
abstract={IN a recent paper Ruska1 demonstrated experimentally the possibility of surpassing considerably the resolving power of an ordinary microscope by the use of an electron microscope. This high resolving power cannot be applied in biological research, however, without developing a new histological technique to prevent the destruction of the organic cells by the intense electronic bombardment.},
issn={1476-4687},
doi={10.1038/133911b0},
url={https://doi.org/10.1038/133911b0}
}

@article{Brenner1959,
title = {A negative staining method for high resolution electron microscopy of viruses},
journal = {Biochimica et Biophysica Acta},
volume = {34},
pages = {103-110},
year = {1959},
issn = {0006-3002},
doi = {https://doi.org/10.1016/0006-3002(59)90237-9},
url = {https://www.sciencedirect.com/science/article/pii/0006300259902379},
author = {Brenner, S. and Horne, R.W. },
abstract = {A simple technique has been developed for the study of the external form and structure of virus particles. High contrast with good preservation is obtained by mixing virus preparations with 1% phosphotungstic acid adjusted to pH 7.5 and spraying directly onto electron microscope supporting films made from evaporated carbon. The application of the technique to tobacco mosaic virus and turnip yellow mosaic virus is described. Structural details suggested by X-ray diffraction methods have been resolved.}
}

@article{Willingham1984,
author = {Willingham, M C  and Rutherford, A V },
title ={The use of osmium-thiocarbohydrazide-osmium (OTO) and ferrocyanide-reduced osmium methods to enhance membrane contrast and preservation in cultured cells.},
journal = {Journal of Histochemistry \& Cytochemistry},
volume = {32},
number = {4},
pages = {455-460},
year = {1984},
doi = {10.1177/32.4.6323574},
    note ={PMID: 6323574},
URL = {https://doi.org/10.1177/32.4.6323574},
eprint = {https://doi.org/10.1177/32.4.6323574},
abstract = { The preservation and contrast of membranous structures in cultured cells using various postfixation procedures prior to embedding have been investigated. These include routine OsO4, ferrocyanide-reduced OsO4, osmium-thiocarbohydrazide-osmium (OTO), and ferrocyanide-reduced osmium-thiocarbohydrazide-ferrocyanide-reduced osmium (R-OTO). With standard ethanol-Epon dehydration/embedding techniques, a dramatic improvement in both membrane contrast and preservation of bilayer membrane structure was achieved using preembedding OTO in cultured cells. R-OTO yielded similar enhanced preservation and contrast of membranes. Both of these methods also resulted in an increase in the contrast of diaminobenzidine reaction product from horseradish peroxidase activity, and of lipid droplets and lipoprotein particles. However, R-OTO did not cause the same increase in the density of proteinaceous elements as was seen with the OTO method. Ferrocyanide-reduced osmium alone showed significant advantages for quantitation of immunocytochemistry using ferritin labels with bismuth subnitrate counterstain. These methods should have general usefulness for the preservation of lipid-containing structures in cultured cells. }
}

@article{Reynolds1963,
    author = {Reynolds, Edward S. },
    title = {THE USE OF LEAD CITRATE AT HIGH pH AS AN ELECTRON-OPAQUE STAIN IN ELECTRON MICROSCOPY },
    journal = {Journal of Cell Biology},
    volume = {17},
    number = {1},
    pages = {208-212},
    year = {1963},
    month = {04},
    issn = {0021-9525},
    doi = {10.1083/jcb.17.1.208},
    url = {https://doi.org/10.1083/jcb.17.1.208},
    eprint = {https://rupress.org/jcb/article-pdf/17/1/208/1334038/208.pdf},
}

@article{HANAICHI1986,
    author = {HANAICHI, Takamasa and SATO, Taizan and IWAMOTO, Tohru and MALAVASI-YAMASHIRO, Jollyanna and HOSHINO, Munemitsu and MIZUNO, Noboru},
    title = "{A Stable Lead by Modification of Sato's Method}",
    journal = {Journal of Electron Microscopy},
    volume = {35},
    number = {3},
    pages = {304-306},
    year = {1986},
    month = {10},
    abstract = "{We modified Sato's lead stain in order to obtain a more stable staining solution. The staining solution formed no lead carbonate film on the surface for periods up to 3 hr after exposure to the air. No precipitates were formed in the solution kept at room temperature for over 1 year. The best results were obtained when Epon sections were stained with the new stain for 2 min.}",
    issn = {0022-0744},
    doi = {10.1093/oxfordjournals.jmicro.a050582},
    url = {https://doi.org/10.1093/oxfordjournals.jmicro.a050582},
    eprint = {https://academic.oup.com/jmicro/article-pdf/35/3/304/2517842/35-3-304.pdf},
}

@Article{Lewinson1989,
author={Lewinson, Dina},
title={Application of the ferrocyanide-reduced osmium method for mineralizing cartilage: Further evidence for the enhancement of intracellular glycogen and visualization of matrix components},
journal={The Histochemical Journal},
year={1989},
month={May},
day={01},
volume={21},
number={5},
pages={259-270},
abstract={The ferrocyanide-reduced osmium (FRO) fixation method was applied to neonatal mouse mandibular condylar cartilage for its processing for electron microscopy. The results were compared to those obtained by the conventional glutaraldehyde---osmium tetroxide fixation method. Three different stages in the life cycle of condylar cartilage cells were examined. FRO enabled the visualization of delicate fibrillar mesh in the matrix of all three zones of the cartilage, resulting in a dense appearance of the intercellular matrix. The classical stellate shape of matric granules seen in cartilage fixed with glutaraldehyde---osmium tetroxide was not observed in FRO-processed tissues. Chondrocytes that were FRO-processed almost entirely filled their lacunar space. In their pericellular area, fibrillar material and electron-dense aggregates could be demonstrated by the FRO method. As a conclusion of this study, it is recommended to supplement a conventional protocol with the FRO fixation method for routine and research purposes.},
issn={1573-6865},
doi={10.1007/BF01757178},
url={https://doi.org/10.1007/BF01757178}
}

@incollection{Daniel1964,
editor = {Daniel C. Pease},
booktitle = {Histological Techniques for Electron Microscopy (Second Edition)},
author = {Daniel C. Pease},
publisher = {Academic Press},
edition = {Second Edition},
year = {1964}
}

@article{Watson1958,
    author = {Watson, Michael L. },
    title = {Staining of Tissue Sections for Electron Microscopy with Heavy Metals},
    journal = {The Journal of Biophysical and Biochemical Cytology},
    volume = {4},
    number = {4},
    pages = {475-478},
    year = {1958},
    month = {07},
    abstract = "{Heavy metals may be incorporated from solution into tissue sections for electron microscopy. The resulting increase in density of the tissue provides greatly enhanced contrast with minimal distortion. Relative densities of various structures are found to depend on the heavy metal ions present and on the conditions of staining. Certain hitherto unobserved details are revealed and some sort of specificity exists, although the factors involved are not yet understood. }",
    issn = {0095-9901},
    doi = {10.1083/jcb.4.4.475},
    url = {https://doi.org/10.1083/jcb.4.4.475},
    eprint = {https://rupress.org/jcb/article-pdf/4/4/475/1069933/475.pdf},
}

@article{Watson1958b,
    author = {Watson , Michael L. },
    title = "{Staining of Tissue Sections for Electron Microscopy with Heavy Metals : II. Application of Solutions Containing Lead and Barium }",
    journal = {The Journal of Biophysical and Biochemical Cytology},
    volume = {4},
    number = {6},
    pages = {727-730},
    year = {1958},
    month = {11},
    abstract = "{Descriptions of three heavy metal stains and methods of application to tissue sections for electron microscopy are presented. Lead hydroxide stains rather selectively two types of particles in liver: those associated with the endoplasmic reticulum and containing ribonucleic acid and other somewhat larger particles. Barium hydroxide emphasizes certain bodies within vesicles of the Golgi region of hepatic cells. Alkalized lead acetate is useful as a general stain, as are also lead and barium hydroxides. }",
    issn = {0095-9901},
    doi = {10.1083/jcb.4.6.727},
    url = {https://doi.org/10.1083/jcb.4.6.727},
    eprint = {https://rupress.org/jcb/article-pdf/4/6/727/1385577/727.pdf},
}

@article{Stempak1964,
    author = {Stempak , Jerome G.  and Ward , Robert T. },
    title = "{AN IMPROVED STAINING METHOD FOR ELECTRON MICROSCOPY }",
    journal = {Journal of Cell Biology},
    volume = {22},
    number = {3},
    pages = {697-701},
    year = {1964},
    month = {09},
    issn = {0021-9525},
    doi = {10.1083/jcb.22.3.697},
    url = {https://doi.org/10.1083/jcb.22.3.697},
    eprint = {https://rupress.org/jcb/article-pdf/22/3/697/1067464/697.pdf},
}

@article{Walton1979,
author = {Walton, Judie },
title ={Lead asparate, an en bloc contrast stain particularly useful for ultrastructural enzymology.},
journal = {Journal of Histochemistry \& Cytochemistry},
volume = {27},
number = {10},
pages = {1337-1342},
year = {1979},
doi = {10.1177/27.10.512319},
note ={PMID: 512319},
URL = {https://doi.org/10.1177/27.10.512319},
eprint = {https://doi.org/10.1177/27.10.512319},
    abstract = { Lead aspartate is a new en bloc stain for electron microscopy. Its predictable staining depends on chelation that results from the interaction of the two stain components, lead nitrate and aspartic acid, which must be present in a specific ratio. Lead aspartate stain is 0.02 M in lead nitrate and 0.03 M in aspartic acid, adjusted to pH 5.5. Cells or tissues are stained at 60 degrees C for 30 to 60 min. Cells stained en bloc with lead aspartate closely resemble cells stained on grids by lead citrate, except that the former seldom have contamination. En bloc staining with lead aspartate bypasses the grid-staining step so that samples can be viewed and photographed immediately after they are thin-sectioned. The lower pH of the lead aspartate solution allows counterstaining of enzyme reaction products that dissolve in the highly alkaline lead citrate stain. Lead aspartate en bloc staining to enhance contrast should especially benefit studies of ultrastructure requiring a clean and predictably lead stain. }
}

@article{Gould1989,
author = {Gould, R M  and Armstrong, R},
title ={Use of lead aspartate block staining in quantitative EM autoradiography of phospholipids: application to myelinating peripheral nerve.},
journal = {Journal of Histochemistry \& Cytochemistry},
volume = {37},
number = {9},
pages = {1393-1399},
year = {1989},
doi = {10.1177/37.9.2475541},
note ={PMID: 2475541},
URL = {https://doi.org/10.1177/37.9.2475541},
eprint = {https://doi.org/10.1177/37.9.2475541},
    abstract = { For quantitation of electron microscope (EM) autoradiographs, micrographs must contain clear images which are relatively free of heavy metal precipitates. Satisfactory contrast is usually obtained by staining individual ultra-thin sections with lead citrate. It was recently reported that sequential block staining of tissue with ferrocyanide-reduced osmium tetroxide and lead aspartate produced excellent contrast for EM autoradiography, with sections relatively free of lead precipitate. This protocol avoids the manipulation involved in staining individual ultra-thin sections. We have adapted this method to quantitative EM autoradiographic studies, primarily of phospholipid metabolism in peripheral nerve. We show that block staining with lead aspartate provides: (a) ultrastructural contrast of routinely high quality for myelinated peripheral nerve; (b) high (greater than 98\%) retention of glycero-labeled lipid during dehydration and embedment; and (c) a distribution of de novo tritiated glycerol-labeled lipid in ultra-thin sections that is quantitatively identical to the distribution recorded for samples stained by the more laborious post-embedment method. During a 2-hr labeling period in vivo, tritiated glycerol is incorporated into phosphatidylcholine (44\%), phosphatidylethanolamine (22\%), other phospholipids (16\%), and neutral lipids (15\%). The analysis of grain distribution in developing sciatic nerve labeled for 2 hr with tritiated glycerol demonstrates that myelinating Schwann cells play the major role in synthesis of endoneurial lipids. Lipid synthesis in myelinated fibers is localized in perinuclear regions of Schwann cell cytoplasm. These regions lie external to compact myelin. Unmyelinated fibers and other endoneurial cells independently incorporate glycerol into lipids. }
}

@article{OSUMI1965,
  title={Electron Microscopical Observations on the Formation of Yeast-mitochondria},
  author={OSUMI, Masako},
  journal={The botanical magazine, Tokyo},
  volume={78},
  number={925},
  pages={231-239},
  year={1965},
  doi={10.15281/jplantres1887.78.231}
}

@Article{Osumi1974,
author={Osumi, M.
and Shimoda, C.
and Yanagishima, N.},
title={Mating reaction in Saccharomyces cerevisiae},
journal={Archives of Microbiology},
year={1974},
month={Jan},
day={01},
volume={97},
number={1},
pages={27-38},
abstract={The process of mating reaction of Saccharomyces cerevisiae was studied by electron microscopy. Prior to the dissolution of the part of the cell walls separating the conjugating pair of cells, the thinning of the electron transparent layer of the cell wall occurs at the part toward which the nuclei are migrating.},
issn={1432-072X},
doi={10.1007/BF00403042},
url={https://doi.org/10.1007/BF00403042}
}

@article{Seligman1966,
    author = {Seligman, Arnold M. and Wasserkrug, Hannah L. and Hanker, Jacob S. },
    title = "{A NEW STAINING METHOD (OTO) FOR ENHANCING CONTRAST OF LIPID-CONTAINING MEMBRANES AND DROPLETS IN OSMIUM TETROXIDE-FIXED TISSUE WITH OSMIOPHILIC THIOCARBOHYDRAZIDE (TCH) }",
    journal = {Journal of Cell Biology},
    volume = {30},
    number = {2},
    pages = {424-432},
    year = {1966},
    month = {08},
    issn = {0021-9525},
    doi = {10.1083/jcb.30.2.424},
    url = {https://doi.org/10.1083/jcb.30.2.424},
    eprint = {https://rupress.org/jcb/article-pdf/30/2/424/1068110/424.pdf},
}

@article{Cerro1981,
author = {Cerro, M Del  and Cogen, J P  and Cerro, C Del },
title ={Retrospective demonstration of endogenous peroxidase activity in plastic-embedded tissues conventionally prepared for electron microscopy.},
journal = {Journal of Histochemistry \& Cytochemistry},
volume = {29},
number = {7},
pages = {874-876},
year = {1981},
doi = {10.1177/29.7.7021672},
note ={PMID: 7021672},
URL = {https://doi.org/10.1177/29.7.7021672},
eprint = {https://doi.org/10.1177/29.7.7021672},
    abstract = { A procedure is described that permits retrospective demonstration of intracellular endogenous peroxidase activity in tissue conventionally prepared for electron microscopy, i.e., doubly fixed with aldehydes and osmium tetroxide, "stained" in block with uranyl acetate, and embedded in epoxy resins. Using sodium ethoxide, plastic was removed from 1 micrometer sections; subsequently, the sections were incubated for 20 min in diaminobenzidine solution (44 mg/100 ml) made in acetate-citric acid buffer, pH 5.6, with 0.01\% hydrogen peroxide. After this treatment, the sections were rinsed, dehydrated, and mounted. Cell types known to have endogenous peroxidase activity (red blood cells, macrophages, and retinal pigment epithelium cells in our preparations) show positive granules in their cytoplasm--control sections were uniformly negative. This method, which could also be used prospectively, cytochemically demonstrates endogenous peroxidase activity upon optical microscopical examination of the treated tissues; correlative electron microscopic studies may be performed on the same tissue block, or even adjacent sections. }
}

@article{Takeshige1992,
    author = {Takeshige, K and Baba, M and Tsuboi, S and Noda, T and Ohsumi, Y},
    title = "{Autophagy in yeast demonstrated with proteinase-deficient mutants and
                    conditions for its induction.}",
    journal = {Journal of Cell Biology},
    volume = {119},
    number = {2},
    pages = {301-311},
    year = {1992},
    month = {10},
    abstract = "{For determination of the physiological role and mechanism of vacuolar proteolysis
                    in the yeast Saccharomyces cerevisiae, mutant cells lacking proteinase A, B, and
                    carboxypeptidase Y were transferred from a nutrient medium to a synthetic medium
                    devoid of various nutrients and morphological changes of their vacuoles were
                    investigated. After incubation for 1 h in nutrient-deficient media, a few
                    spherical bodies appeared in the vacuoles and moved actively by Brownian
                    movement. These bodies gradually increased in number and after 3 h they filled
                    the vacuoles almost completely. During their accumulation, the volume of the
                    vacuolar compartment also increased. Electron microscopic examination showed
                    that these bodies were surrounded by a unit membrane which appeared thinner than
                    any other intracellular membrane. The contents of the bodies were
                    morphologically indistinguishable from the cytosol; these bodies contained
                    cytoplasmic ribosomes, RER, mitochondria, lipid granules and glycogen granules,
                    and the density of the cytoplasmic ribosomes in the bodies was almost the same
                    as that of ribosomes in the cytosol. The diameter of the bodies ranged from 400
                    to 900 nm. Vacuoles that had accumulated these bodies were prepared by a
                    modification of the method of Ohsumi and Anraku (Ohsumi, Y., and Y. Anraku.
                    1981. J. Biol. Chem. 256:2079-2082). The isolated vacuoles contained ribosomes
                    and showed latent activity of the cytosolic enzyme glucose-6-phosphate
                    dehydrogenase. These results suggest that these bodies sequestered the cytosol
                    in the vacuoles. We named these spherical bodies "autophagic bodies."
                    Accumulation of autophagic bodies in the vacuoles was induced not only by
                    nitrogen starvation, but also by depletion of nutrients such as carbon and
                    single amino acids that caused cessation of the cell cycle. Genetic analysis
                    revealed that the accumulation of autophagic bodies in the vacuoles was the
                    result of lack of the PRB1 product proteinase B, and disruption of the PRB1 gene
                    confirmed this result. In the presence of PMSF, wild-type cells accumulated
                    autophagic bodies in the vacuoles under nutrient-deficient conditions in the
                    same manner as did multiple protease-deficient mutants or cells with a disrupted
                    PRB1 gene. As the autophagic bodies disappeared rapidly after removal of PMSF
                    from cultures of normal cells, they must be an intermediate in the normal
                    autophagic process. This is the first report that nutrient-deficient conditions
                    induce extensive autophagic degradation of cytosolic components in the vacuoles
                    of yeast cells.}",
    issn = {0021-9525},
    doi = {10.1083/jcb.119.2.301},
    url = {https://doi.org/10.1083/jcb.119.2.301},
    eprint = {https://rupress.org/jcb/article-pdf/119/2/301/1418421/301.pdf},
}

@Article{Kazimierczak1980,
author={Kazimierczak, Jerzy},
title={A study by scanning (SEM) and transmission (TEM) electron microscopy of the glomerular capillaries in developing rat kidney},
journal={Cell and Tissue Research},
year={1980},
month={Nov},
day={01},
volume={212},
number={2},
pages={241-255},
abstract={Kidneys of 2 to 10 day-old rats of Wistar and Sprague-Dawley strains were fixed with glutaraldehyde by retrograde vascular perfusion and then prepared for observation in TEM and SEM. In addition methacrylate casts of differentiating glomerular capillaries were examined by SEM. Although the glomerular vascular pattern differs from one glomerulus to another, its differentiation proceeds according to the following general plan. First the glomerular capillary splits longitudinally, finally to form 3 to 5 lobules consisting of a capillary network, sustained centrally by the mesangium.},
issn={1432-0878},
doi={10.1007/BF00233959},
url={https://doi.org/10.1007/BF00233959}
}

@Article{Chen2019,
author={Chen, Xianwu
and Li, Chao
and Chen, Yong
and Xi, Haitao
and Zhao, Shenzhi
and Ma, Leikai
and Xu, Zhangye
and Han, Zhao
and Zhao, Junzhao
and Ge, Renshan
and Guo, Xiaoling},
title={Differentiation of human induced pluripotent stem cells into Leydig-like cells with molecular compounds},
journal={Cell Death {\&} Disease},
year={2019},
month={Mar},
day={04},
volume={10},
number={3},
pages={220},
abstract={Leydig cells (LCs) play crucial roles in producing testosterone, which is critical in the regulation of male reproduction and development. Low levels of testosterone will lead to male hypogonadism. LC transplantation is a promising alternative therapy for male hypogonadism. However, the source of LCs limits this strategy for clinical applications. Thus far, others have reported that LCs can be derived from stem cells by gene transfection, but the safe and effective induction method has not yet been reported. Here, we report that Leydig-like cells can be derived from human induced pluripotent stem cells (iPSCs) using a novel differentiation protocol based on molecular compounds. The iPSCs-derived Leydig-like cells (iPSC-LCs) acquired testosterone synthesis capabilities, had the similar gene expression profiles with LCs, and positively expressed Leydig cell lineage-specific protein markers LHCGR, STAR, SCARB1, SF-1, CYP11A1, HSD3B1, and HSD17B3 as well as negatively expressed iPSC-specific markers NANOG, OCT4, and SOX2. When iPSC-LCs labeled with lipophilic red dye (PKH26) were transplanted into rat testes that were selectively eliminated endogenous LCs using EDS (75{\thinspace}mg/kg), the transplanted iPSC-LCs could survive and function in the interstitium of testes, and accelerate the recovery of serum testosterone levels and testis weights. Collectively, these findings demonstrated that the iPSCs were able to be differentiated into Leydig-like cells by few defined molecular compounds, which may lay the safer groundwork for further clinical application of iPSC-LCs for hypogonadism.},
issn={2041-4889},
doi={10.1038/s41419-019-1461-0},
url={https://doi.org/10.1038/s41419-019-1461-0}
}

@article{Ohmine2011,
  title={Induced pluripotent stem cells from GMP-grade hematopoietic progenitor cells and mononuclear myeloid cells},
  author={S. Ohmine and A. Dietz and M. Deeds and Katherine A. Hartjes and David R Miller and Tayaramma Thatava and T. Sakuma and Y. Kudva and Y. Ikeda},
  journal={Stem Cell Research \& Therapy},
  year={2011},
  volume={2},
  pages={46 - 46}
}

@Article{Irene2016,
author={Wacker, Irene
and Spomer, Waldemar
and Hofmann, Andreas
and Thaler, Marlene
and Hillmer, Stefan
and Gengenbach, Ulrich
and Schr{\"o}der, Rasmus R.},
title={Hierarchical imaging: a new concept for targeted imaging of large volumes from cells to tissues},
journal={BMC Cell Biology},
year={2016},
month={Dec},
day={12},
volume={17},
number={1},
pages={38},
abstract={Imaging large volumes such as entire cells or small model organisms at nanoscale resolution seemed an unrealistic, rather tedious task so far. Now, technical advances have lead to several electron microscopy (EM) large volume imaging techniques. One is array tomography, where ribbons of ultrathin serial sections are deposited on solid substrates like silicon wafers or glass coverslips.},
issn={1471-2121},
doi={10.1186/s12860-016-0122-8},
url={https://doi.org/10.1186/s12860-016-0122-8}
}

@inproceedings{Kume2016,
  title={Development of an Ontology for an Integrated Image Analysis Platform to enable Global Sharing of Microscopy Imaging Data},
  author={S. Kume and H. Masuya and Y. Kataoka and Norio Kobayashi},
  booktitle={International Semantic Web Conference},
  year={2016}
}

@article{Kobayashi2018ome,
author = "Norio Kobayashi and Satoshi Kume and Josh Moore and Jason R. Swedlow",
title = "{OME Ontology: A Novel Data and Tool Integration Methodology for Multi-Modal Imaging in the Life Sciences}",
journal={Proceeding of SWAT4HCLS},
year = "2018",
month = "12",
url = "https://swat4hcls.figshare.com/articles/journal_contribution/OME_Ontology_A_Novel_Data_and_Tool_Integration_Methodology_for_Multi-Modal_Imaging_in_the_Life_Sciences/7325063",
doi = "10.6084/m9.figshare.7325063.v1"
}

@inproceedings{Kobayashi2019,
  title={OME Core Ontology: An OWL-based Life Science Imaging Data Model},
  author={Norio Kobayashi and Josh Moore and S. Onami and J. Swedlow},
  booktitle={SWAT4HCLS},
  year={2019}
}

@ARTICLE{Walter2020,
AUTHOR={Walter, Andreas and Paul-Gilloteaux, Perrine and Plochberger, Birgit and Sefc, Ludek and Verkade, Paul and Mannheim, Julia G. and Slezak, Paul and Unterhuber, Angelika and Marchetti-Deschmann, Martina and Ogris, Manfred and Bühler, Katja and Fixler, Dror and Geyer, Stefan H. and Weninger, Wolfgang J. and Glösmann, Martin and Handschuh, Stephan and Wanek, Thomas},   
TITLE={Correlated Multimodal Imaging in Life Sciences: Expanding the Biomedical Horizon},      
JOURNAL={Frontiers in Physics},      
VOLUME={8},      
PAGES={47},     
YEAR={2020},      
URL={https://www.frontiersin.org/article/10.3389/fphy.2020.00047},       
DOI={10.3389/fphy.2020.00047},      
ISSN={2296-424X},   
ABSTRACT={The frontiers of bioimaging are currently being pushed toward the integration and correlation of several modalities to tackle biomedical research questions holistically and across multiple scales. Correlated Multimodal Imaging (CMI) gathers information about exactly the same specimen with two or more complementary modalities that—in combination—create a composite and complementary view of the sample (including insights into structure, function, dynamics and molecular composition). CMI allows to describe biomedical processes within their overall spatio-temporal context and gain a mechanistic understanding of cells, tissues, diseases or organisms by untangling their molecular mechanisms within their native environment. The two best-established CMI implementations for small animals and model organisms are hardware-fused platforms in preclinical imaging (Hybrid Imaging) and Correlated Light and Electron Microscopy (CLEM) in biological imaging. Although the merits of Preclinical Hybrid Imaging (PHI) and CLEM are well-established, both approaches would benefit from standardization of protocols, ontologies and data handling, and the development of optimized and advanced implementations. Specifically, CMI pipelines that aim at bridging preclinical and biological imaging beyond CLEM and PHI are rare but bear great potential to substantially advance both bioimaging and biomedical research. CMI faces three main challenges for its routine use in biomedical research: (1) Sample handling and preparation procedures that are compatible across modalities without compromising data quality, (2) soft- and hardware solutions to relocate the same region of interest (ROI) after transfer between imaging platforms including fiducial markers, and (3) automated software solutions to correlate complex, multiscale, multimodal and volumetric image data including reconstruction, segmentation and visualization. This review goes beyond preclinical imaging and puts accessible information into a broader imaging context. We present a comprehensive overview of the field of CMI from preclinical hybrid imaging to correlative microscopy, highlight requirements for optimization and standardization, present a synopsis of current solutions to challenges of the field and focus on current efforts to bridge the gap between preclinical and biological imaging (from small animals down to single cells and molecules). The review is in line with major European initiatives, such as COMULIS (CA17121), a COST Action to promote and foster Correlated Multimodal Imaging in Life Sciences.}
}

@article{Schalek2011, 
title={Development of High-Throughput, High-Resolution 3D Reconstruction of Large-Volume Biological Tissue Using Automated Tape Collection Ultramicrotomy and Scanning Electron Microscopy}, 
volume={17}, 
DOI={10.1017/S1431927611005708}, 
number={S2}, 
journal={Microscopy and Microanalysis}, 
publisher={Cambridge University Press}, 
author={Schalek, R and Kasthuri, N and Hayworth, K and Berger, D and Tapia, J and Morgan, J and Turaga, S and Fagerholm, E and Seung, H and Lichtman, J and et al.}, 
year={2011}, 
pages={966–967}
}

@Article{Casares2019,
AUTHOR = {Casares, Doralicia and Escribá, Pablo V. and Rosselló, Catalina Ana},
TITLE = {Membrane Lipid Composition: Effect on Membrane and Organelle Structure, Function and Compartmentalization and Therapeutic Avenues},
JOURNAL = {International Journal of Molecular Sciences},
VOLUME = {20},
YEAR = {2019},
NUMBER = {9},
ARTICLE-NUMBER = {2167},
URL = {https://www.mdpi.com/1422-0067/20/9/2167},
PubMedID = {31052427},
ISSN = {1422-0067},
ABSTRACT = {Biological membranes are key elements for the maintenance of cell architecture and physiology. Beyond a pure barrier separating the inner space of the cell from the outer, the plasma membrane is a scaffold and player in cell-to-cell communication and the initiation of intracellular signals among other functions. Critical to this function is the plasma membrane compartmentalization in lipid microdomains that control the localization and productive interactions of proteins involved in cell signal propagation. In addition, cells are divided into compartments limited by other membranes whose integrity and homeostasis are finely controlled, and which determine the identity and function of the different organelles. Here, we review current knowledge on membrane lipid composition in the plasma membrane and endomembrane compartments, emphasizing its role in sustaining organelle structure and function. The correct composition and structure of cell membranes define key pathophysiological aspects of cells. Therefore, we explore the therapeutic potential of manipulating membrane lipid composition with approaches like membrane lipid therapy, aiming to normalize cell functions through the modification of membrane lipid bilayers.},
DOI = {10.3390/ijms20092167}
}

@article{OConnor2010,
	author = {O'Connor, C. M. and Adams, J. U.},
	title = { Essentials of Cell Biology},
	journal = {Cambridge, MA: NPG Education},
	year = {2010}
}

@Article{Baruzzi2008,
author={Baruzzi, A.
and Caveggion, E.
and Berton, G.},
title={Regulation of phagocyte migration and recruitment by Src-family kinases},
journal={Cellular and Molecular Life Sciences},
year={2008},
month={Jul},
day={01},
volume={65},
number={14},
pages={2175-2190},
abstract={Src-family kinases (SFKs) regulate different granulocyte and monocyte/macrophage responses. Accumulating evidence suggests that members of this family are implicated in signal transduction pathways regulating phagocytic cell migration and recruitment into inflammatory sites. Macrophages with a genetic deficiency of SFKs display marked alterations in cytoskeleton dynamics, polarization and migration. This same phenotype is found in cells with either a lack of SFK substrates and/or interacting proteins such as Pyk2/FAK, c-Cbl and p190RhoGAP. Notably, SFKs and their downstream targets also regulate monocyte recruitment into inflammatory sites. Depending on the type of assay used, neutrophil migration in vitro may be either dependent on or independent of SFKs. Also neutrophil recruitment in in vivo models of inflammation may be regulated differently by SFKs depending on the tissue involved. In this review we will discuss possible mechanisms by which SFKs may regulate phagocytic cell migratory abilities.},
issn={1420-9071},
doi={10.1007/s00018-008-8005-6},
url={https://doi.org/10.1007/s00018-008-8005-6}
}

@article{Wigglesworth1957,
author = {Wigglesworth, Vincent Brian },
title = {The use of osmium in the fixation and staining of tissues},
journal = {Proceedings of the Royal Society of London. Series B - Biological Sciences},
volume = {147},
number = {927},
pages = {185-199},
year = {1957},
doi = {10.1098/rspb.1957.0043},
URL = {https://royalsocietypublishing.org/doi/abs/10.1098/rspb.1957.0043},
eprint = {https://royalsocietypublishing.org/doi/pdf/10.1098/rspb.1957.0043},
abstract = { The use of gallic acid derivatives in the visualization of osmium in tissue sections has been re-investigated. By the use of alkyl esters of gallic acid greatly improved results can be obtained. Fixation with buffered osmium textroxide followed by ethyl gallate affords a simple and reliable method for staining fat droplets, mitochondria, etc. According to the hypothesis put forward the distribution of osmium is determined chiefly by the distribution of unsaturated fatty acids; none is bound by nucleic acids and relatively little by protein. The result is claimed to be an histology based primarily on lipids, which is contrasted with the customary histology based on nucleic acids and proteins. Evidence is given that osmium tetroxide causes polymerization of unsaturated lipids by the cross-linking of ethylenic double bonds. This is particularly liable to occur in layers of oriented lipids. Such layers are widely distributed in living cells; their stabilization by linkage through osmium is considered to play the most important part in cytological fixation by osmium tetroxide. }
}

@Article{GLAUERT1956,
author={GLAUERT, AUDREY M.
and ROGERS, G. E.
and GLAUERT, R. H.},
title={A New Embedding Medium for Electron Microscopy},
journal={Nature},
year={1956},
month={Oct},
day={01},
volume={178},
number={4537},
pages={803-803},
abstract={THE introduction of n-butyl and methyl meth-acrylates as embedding media1 constituted an important development in the preparation of ultra-thin sections of biological material; but their use is attended by various major difficulties. Shrinkage occurs on polymerization, hard objects are not penetrated by the monomer so that the plastic shrinks away and does not provide sufficient support, and sometimes there is an unaccountable appearance of bubbles around the specimen. Moreover, the polymerization process is not uniform and sometimes causes severe damage. This is perhaps most strikingly seen in bacteria where often only empty remnants of cell walls remain.},
issn={1476-4687},
doi={10.1038/178803a0},
url={https://doi.org/10.1038/178803a0}
}

@article{Glauert1958,
    author = {Glauert , Audrey M.  and Glauert , R. H. },
    title = {Araldite as an Embedding Medium for Electron Microscopy },
    journal = {The Journal of Biophysical and Biochemical Cytology},
    volume = {4},
    number = {2},
    pages = {191-194},
    year = {1958},
    month = {03},
    abstract = "{Epoxy resins are suitable media for embedding for electron microscopy, as they set uniformly with virtually no shrinkage. A mixture of araldite epoxy resins has been developed which is soluble in ethanol, and which yields a block of the required hardness for thin sectioning. The critical modifications to the conventional mixtures are the choice of a plasticized resin in conjunction with an aliphatic anhydride as the hardener. The hardness of the final block can be varied by incorporating additional plasticizer, and the rate of setting can be controlled by the use of an amine accelerator. The properties of the araldite mixture can be varied quite widely by adjusting the proportions of the various constituents. The procedure for embedding biological specimens is similar to that employed with methacrylates, although longer soaking times are recommended to ensure the complete penetration of the more viscous epoxy resin. An improvement in the preservation of the fine structure of a variety of specimens has already been reported, and a typical electron microgram illustrates the present paper. }",
    issn = {0095-9901},
    doi = {10.1083/jcb.4.2.191},
    url = {https://doi.org/10.1083/jcb.4.2.191},
    eprint = {https://rupress.org/jcb/article-pdf/4/2/191/1263570/191.pdf},
}

@Article{Maeda2019,
AUTHOR = {Maeda, Mitsuyo and Seto, Toshiyuki and Kadono, Chiho and Morimoto, Hideto and Kida, Sachiho and Suga, Mitsuo and Nakamura, Motohiro and Kataoka, Yosky and Hamazaki, Takashi and Shintaku, Haruo},
TITLE = {Autophagy in the Central Nervous System and Effects of Chloroquine in Mucopolysaccharidosis Type II Mice},
JOURNAL = {International Journal of Molecular Sciences},
VOLUME = {20},
YEAR = {2019},
NUMBER = {23},
ARTICLE-NUMBER = {5829},
URL = {https://www.mdpi.com/1422-0067/20/23/5829},
PubMedID = {31757021},
ISSN = {1422-0067},
ABSTRACT = {Mucopolysaccharidosis type II (MPS II) is a rare lysosomal storage disease (LSD) involving a genetic error in iduronic acid-2-sulfatase (IDS) metabolism that leads to accumulation of glycosaminoglycans within intracellular lysosomes. The primary treatment for MPS II, enzyme replacement therapy, is not effective for central nervous system (CNS) symptoms, such as intellectual disability, because the drugs do not cross the blood–brain barrier. Recently, autophagy has been associated with LSDs. In this study, we examined the morphologic relationship between neuronal damage and autophagy in IDS knockout mice using antibodies against subunit c of mitochondrial adenosine triphosphate (ATP) synthetase and p62. Immunohistological changes suggesting autophagy, such as vacuolation, were observed in neurons, microglia, and pericytes throughout the CNS, and the numbers increased over postnatal development. Oral administration of chloroquine, which inhibits autophagy, did not suppress damage to microglia and pericytes, but greatly reduced neuronal vacuolation and eliminated neuronal cells with abnormal inclusions. Thus, decreasing autophagy appears to prevent neuronal degeneration. These results suggest that an autophagy modulator could be used in addition to conventional enzyme replacement therapy to preserve the CNS in patients with MPS II.},
DOI = {10.3390/ijms20235829}
}

@article{KRUMEICH2018,
	author = {KRUMEICH, FRANK},
	title = {INTRODUCTION INTO TRANSMISSION AND SCANNING TRANSMISSION ELECTRON MICROSCOPY},
	journal = {},
	pages = {},
	year = {2018}
}

@ARTICLE{Richert2019,  
AUTHOR={Richert-Pöggeler, Katja R. and Franzke, Kati and Hipp, Katharina and Kleespies, Regina G.},   
TITLE={Electron Microscopy Methods for Virus Diagnosis and High Resolution Analysis of Viruses},    
JOURNAL={Frontiers in Microbiology},      
VOLUME={9},     
PAGES={3255},     
YEAR={2019},      
URL={https://www.frontiersin.org/article/10.3389/fmicb.2018.03255},       
DOI={10.3389/fmicb.2018.03255},      
ISSN={1664-302X},   
ABSTRACT={The term “virosphere” describes both the space where viruses are found and the space they influence, and can extend to their impact on the environment, highlighting the complexity of the interactions involved. Studying the biology of viruses and the etiology of virus disease is crucial to the prevention of viral disease, efficient and reliable virus diagnosis, and virus control. Electron microscopy (EM) is an essential tool in the detection and analysis of virus replication. New EM methods and ongoing technical improvements offer a broad spectrum of applications, allowing in-depth investigation of viral impact on not only the host but also the environment. Indeed, using the most up-to-date electron cryomicroscopy methods, such investigations are now close to atomic resolution. In combination with bioinformatics, the transition from 2D imaging to 3D remodeling allows structural and functional analyses that extend and augment our knowledge of the astonishing diversity in virus structure and lifestyle. In combination with confocal laser scanning microscopy, EM enables live imaging of cells and tissues with high-resolution analysis. Here, we describe the pivotal role played by EM in the study of viruses, from structural analysis to the biological relevance of the viral metagenome (virome).}
}

@article{Plummer1997, 
title={Reflections on the Use of Microtomy for Materials Science Specimen Preparation}, 
volume={3}, 
DOI={10.1017/S1431927697970197},
 number={3},
  journal={Microscopy and Microanalysis}, 
  publisher={Cambridge University Press}, 
  author={Plummer, H.K.}, 
  year={1997}, 
  pages={239–260}
  }

@Article{Xu2007,
author={Xu, Qiaobing
and Rioux, Robert M.
and Whitesides, George M.},
title={Fabrication of Complex Metallic Nanostructures by Nanoskiving},
journal={ACS Nano},
year={2007},
month={Oct},
day={31},
publisher={American Chemical Society},
volume={1},
number={3},
pages={215-227},
issn={1936-0851},
doi={10.1021/nn700172c},
url={https://doi.org/10.1021/nn700172c}
}

@Article{Ravelli2013,
author={Ravelli, Raimond B. G.
and Kalicharan, Ruby D.
and Avramut, M. Cristina
and Sjollema, Klaas A.
and Pronk, Joachim W.
and Dijk, Freark
and Koster, Abraham J.
and Visser, Jeroen T. J.
and Faas, Frank G. A.
and Giepmans, Ben N. G.},
title={Destruction of Tissue, Cells and Organelles in Type 1 Diabetic Rats Presented at Macromolecular Resolution},
journal={Scientific Reports},
year={2013},
month={May},
day={08},
volume={3},
number={1},
pages={1804},
abstract={Finding alternatives for insulin therapy and making advances in etiology of type 1 diabetes benefits from a full structural and functional insight into Islets of Langerhans. Electron microscopy (EM) can visualize Islet morphology at the highest possible resolution, however, conventional EM only provides biased snapshots and lacks context. We developed and employed large scale EM and compiled a resource of complete cross sections of rat Islets during immuno-destruction to provide unbiased structural insight of thousands of cells at macromolecular resolution. The resource includes six datasets, totalling 25.000 micrographs, annotated for cellular and ultrastructural changes during autoimmune diabetes. Granulocytes are attracted to the endocrine tissue, followed by extravasation of a pleiotrophy of leukocytes. Subcellullar changes in beta cells include endoplasmic reticulum stress, insulin degranulation and glycogen accumulation. Rare findings include erythrocyte extravasation and nuclear actin-like fibers. While we focus on a rat model of autoimmune diabetes, our approach is general applicable.},
issn={2045-2322},
doi={10.1038/srep01804},
url={https://doi.org/10.1038/srep01804}
}

@Inbook{Gordon2014,
author="Gordon, Ronald E.",
editor="Day, Christina E.",
title="Electron Microscopy: A Brief History and Review of Current Clinical Application",
bookTitle="Histopathology: Methods and Protocols",
year="2014",
publisher="Springer New York",
address="New York, NY",
pages="119--135",
abstract="This chapter describes the historic development of techniques that has made it possible to use electron microscopy, principally transmission electron microscopy, for diagnostic purposes. It was described how the standard techniques for preparing tissue for light microscopy had been modified to make it possible to view the ultrastructural components of a cell, tissue, or organ that cannot be resolved with a light microscope. There is a discussion of the types of tissues and cells that were and are currently observed by electron microscopy for diagnostic purposes. All of the materials that are used in tissue preparation and the general protocols for processing the tissues are also included. There are also notes which describe steps that can be changed or modified and why depending on conditions and anticipated outcome.",
isbn="978-1-4939-1050-2",
doi="10.1007/978-1-4939-1050-2_7",
url="https://doi.org/10.1007/978-1-4939-1050-2_7"
}

@article{Toyooka2014,
    author = {Toyooka, Kiminori and Sato, Mayuko and Kutsuna, Natsumaro and Higaki, Takumi and Sawaki, Fumie and Wakazaki, Mayumi and Goto, Yumi and Hasezawa, Seiichiro and Nagata, Noriko and Matsuoka, Ken},
    title = "{Wide-Range High-Resolution Transmission Electron Microscopy Reveals Morphological and Distributional Changes of Endomembrane Compartments during Log to Stationary Transition of Growth Phase in Tobacco BY-2 Cells}",
    journal = {Plant and Cell Physiology},
    volume = {55},
    number = {9},
    pages = {1544-1555},
    year = {2014},
    month = {06},
    abstract = "{Rapid growth of plant cells by cell division and expansion requires an endomembrane trafficking system. The endomembrane compartments, such as the Golgi stacks, endosome and vesicles, are important in the synthesis and trafficking of cell wall materials during cell elongation. However, changes in the morphology, distribution and number of these compartments during the different stages of cell proliferation and differentiation have not yet been clarified. In this study, we examined these changes at the ultrastructural level in tobacco Bright yellow 2 (BY-2) cells during the log and stationary phases of growth. We analyzed images of the BY-2 cells prepared by the high-pressure freezing/freeze substitution technique with the aid of an auto-acquisition transmission electron microscope system. We quantified the distribution of secretory and endosomal compartments in longitudinal sections of whole cells by using wide-range gigapixel-class images obtained by merging thousands of transmission electron micrographs. During the log phase, all Golgi stacks were composed of several thick cisternae. Approximately 20 vesicle clusters (VCs), including the trans-Golgi network and secretory vesicle cluster, were observed throughout the cell. In the stationary-phase cells, Golgi stacks were thin with small cisternae, and only a few VCs were observed. Nearly the same number of multivesicular body and small high-density vesicles were observed in both the stationary and log phases. Results from electron microscopy and live fluorescence imaging indicate that the morphology and distribution of secretory-related compartments dramatically change when cells transition from log to stationary phases of growth.}",
    issn = {0032-0781},
    doi = {10.1093/pcp/pcu084},
    url = {https://doi.org/10.1093/pcp/pcu084},
    eprint = {https://academic.oup.com/pcp/article-pdf/55/9/1544/17117557/pcu084.pdf},
}

@Article{Higaki2015,
author={Higaki, Takumi
and Kutsuna, Natsumaro
and Akita, Kae
and Sato, Mayuko
and Sawaki, Fumie
and Kobayashi, Megumi
and Nagata, Noriko
and Toyooka, Kiminori
and Hasezawa, Seiichiro},
title={Semi-automatic organelle detection on transmission electron microscopic images},
journal={Scientific Reports},
year={2015},
month={Jan},
day={15},
volume={5},
number={1},
pages={7794},
abstract={Recent advances in the acquisition of large-scale datasets of transmission electron microscope images have allowed researchers to determine the number and the distribution of subcellular ultrastructures at both the cellular level and the tissue level. For this purpose, it would be very useful to have a computer-assisted system to detect the structures of interest, such as organelles. Using our original image recognition framework CARTA (Clustering-Aided Rapid Training Agent), combined with procedures to highlight and enlarge regions of interest on the image, we have developed a successful method for the semi-automatic detection of plant organelles including mitochondria, amyloplasts, chloroplasts, etioplasts and Golgi stacks in transmission electron microscope images. Our proposed semi-automatic detection system will be helpful for labelling organelles in the interpretation and/or quantitative analysis of large-scale electron microscope imaging data.},
issn={2045-2322},
doi={10.1038/srep07794},
url={https://doi.org/10.1038/srep07794}
}

@article{Toyooka2016,
author = {Toyooka, Kiminori  and Sato, Mayuko  and Wakazaki, Mayumi  and Matsuoka, Ken },
title = {Morphological and quantitative changes in mitochondria, plastids, and peroxisomes during the log-to-stationary transition of the growth phase in cultured tobacco BY-2 cells},
journal = {Plant Signaling \& Behavior},
volume = {11},
number = {3},
pages = {e1149669},
year  = {2016},
publisher = {Taylor & Francis},
doi = {10.1080/15592324.2016.1149669},
note ={PMID: 26855065},
URL = {https://doi.org/10.1080/15592324.2016.1149669},
eprint = {https://doi.org/10.1080/15592324.2016.1149669}
}

@article {Lichtman2011,
	author = {Lichtman, Jeff W. and Denk, Winfried},
	title = {The Big and the Small: Challenges of Imaging the Brain{\textquoteright}s Circuits},
	volume = {334},
	number = {6056},
	pages = {618--623},
	year = {2011},
	doi = {10.1126/science.1209168},
	publisher = {American Association for the Advancement of Science},
	abstract = {The relation between the structure of the nervous system and its function is more poorly understood than the relation between structure and function in any other organ system. We explore why bridging the structure-function divide is uniquely difficult in the brain. These difficulties also explain the thrust behind the enormous amount of innovation centered on microscopy in neuroscience. We highlight some recent progress and the challenges that remain.},
	issn = {0036-8075},
	URL = {https://science.sciencemag.org/content/334/6056/618},
	eprint = {https://science.sciencemag.org/content/334/6056/618.full.pdf},
	journal = {Science}
}

@article {Hoffpauir2006,
	author = {Hoffpauir, Brian K. and Grimes, Janelle L. and Mathers, Peter H. and Spirou, George A.},
	title = {Synaptogenesis of the Calyx of Held: Rapid Onset of Function and One-to-One Morphological Innervation},
	volume = {26},
	number = {20},
	pages = {5511--5523},
	year = {2006},
	doi = {10.1523/JNEUROSCI.5525-05.2006},
	publisher = {Society for Neuroscience},
	abstract = {Synaptogenesis during early development is thought to follow a canonical program whereby synapses increase rapidly in number and individual axons multiply-innervate nearby targets. Typically, a subset of inputs then out-competes all others through experience-driven processes to establish stable, long-lasting contacts. We investigated the formation of the calyx of Held, probably the largest nerve terminal in the mammalian CNS. Many basic functional and morphological features of calyx growth have not been studied previously, including whether mono-innervation, a hallmark of this system in adult animals, is established early in development. Evoked postsynaptic currents, recorded from neonatal mice between postnatal day 1 (P1) and P4, increased dramatically from -0.14 {\textpm} 0.04 nA at P1 to -6.71 {\textpm} 0.65 nA at P4 with sharp jumps between P2 and P4. These are the first functional assays of these nascent synapses for ages less than P3. AMPA and NMDA receptor-mediated currents were prominent across this age range. Electron microscopy (EM) revealed a concomitant increase, beginning at P2, in the prevalence of postsynaptic densities (16-fold) and adhering contacts (73-fold) by P4. Therefore, both functional and structural data showed that young calyces could form within 2 d, well before the onset of hearing around P8. Convergence of developing calyces onto postsynaptic targets, indicative of competitive processes that precede mono-innervation, was rare (4 of 29) at P4 as assessed using minimal stimulation electrophysiology protocols. Serial EM sectioning through 19 P4 cells further established the paucity (2 of 19) of convergence. These data indicate that calyces of Held follow a noncanonical program to establish targeted innervation that occurs over a rapid time course and precedes auditory experience.},
	issn = {0270-6474},
	URL = {https://www.jneurosci.org/content/26/20/5511},
	eprint = {https://www.jneurosci.org/content/26/20/5511.full.pdf},
	journal = {Journal of Neuroscience}
}

@article{Preibisch2009,
    author = {Preibisch, Stephan and Saalfeld, Stephan and Tomancak, Pavel},
    title = "{Globally optimal stitching of tiled 3D microscopic image acquisitions}",
    journal = {Bioinformatics},
    volume = {25},
    number = {11},
    pages = {1463-1465},
    year = {2009},
    month = {04},
    abstract = "{Motivation: Modern anatomical and developmental studies often require high-resolution imaging of large specimens in three dimensions (3D). Confocal microscopy produces high-resolution 3D images, but is limited by a relatively small field of view compared with the size of large biological specimens. Therefore, motorized stages that move the sample are used to create a tiled scan of the whole specimen. The physical coordinates provided by the microscope stage are not precise enough to allow direct reconstruction (Stitching) of the whole image from individual image stacks.Results: To optimally stitch a large collection of 3D confocal images, we developed a method that, based on the Fourier Shift Theorem, computes all possible translations between pairs of 3D images, yielding the best overlap in terms of the cross-correlation measure and subsequently finds the globally optimal configuration of the whole group of 3D images. This method avoids the propagation of errors by consecutive registration steps. Additionally, to compensate the brightness differences between tiles, we apply a smooth, non-linear intensity transition between the overlapping images. Our stitching approach is fast, works on 2D and 3D images, and for small image sets does not require prior knowledge about the tile configuration.Availability: The implementation of this method is available as an ImageJ plugin distributed as a part of the Fiji project (FijiisjustImageJ: http://pacific.mpi-cbg.de/).Contact:tomancak@mpi-cbg.de}",
    issn = {1367-4803},
    doi = {10.1093/bioinformatics/btp184},
    url = {https://doi.org/10.1093/bioinformatics/btp184},
    eprint = {https://academic.oup.com/bioinformatics/article-pdf/25/11/1463/950295/btp184.pdf},
}

@Inbook{McMullan2008,
author="McMullan, Dennis",
editor="Schatten, Heide
and Pawley, James B.",
title="The Early Development of the Scanning Electron Microscope",
bookTitle="Biological Low-Voltage Scanning Electron Microscopy",
year="2008",
publisher="Springer New York",
address="New York, NY",
pages="1--25",
isbn="978-0-387-72972-5",
doi="10.1007/978-0-387-72972-5_1",
url="https://doi.org/10.1007/978-0-387-72972-5_1"
}

@article{BOGNER2007,
title = {A history of scanning electron microscopy developments: Towards “wet-STEM” imaging},
journal = {Micron},
volume = {38},
number = {4},
pages = {390-401},
year = {2007},
note = {Microscopy of Nanostructures},
issn = {0968-4328},
doi = {https://doi.org/10.1016/j.micron.2006.06.008},
url = {https://www.sciencedirect.com/science/article/pii/S0968432806001016},
author = {A. Bogner and P.-H. Jouneau and G. Thollet and D. Basset and C. Gauthier},
keywords = {Electron microscopy, STEM-in-SEM, Transmission mode, Scattered electrons, Environmental scanning electron microscopy, ESEM},
abstract = {A recently developed imaging mode called “wet-STEM” and new developments in environmental scanning electron microscopy (ESEM) allows the observation of nano-objects suspended in a liquid phase, with a few manometers resolution and a good signal to noise ratio. The idea behind this technique is simply to perform STEM-in-SEM, that is SEM in transmission mode, in an environmental SEM. The purpose of the present contribution is to highlight the main advances that contributed to development of the wet-STEM technique. Although simple in principle, the wet-STEM imaging mode would have been limited before high brightness electron sources became available, and needed some progresses and improvements in ESEM. This new technique extends the scope of SEM as a high-resolution microscope, relatively cheap and widely available imaging tool, for a wider variety of samples.}
}

@article{Cardona2012,
doi = {10.1371/journal.pone.0038011},
author = {Cardona, Albert and Saalfeld, Stephan and Schindelin, Johannes and Arganda-Carreras, Ignacio and Preibisch, Stephan and Longair, Mark and Tomancak, Pavel and Hartenstein, Volker and Douglas, Rodney J.},
journal = {PLOS ONE},
publisher = {Public Library of Science},
title = {TrakEM2 Software for Neural Circuit Reconstruction},
year = {2012},
month = {06},
volume = {7},
url = {https://doi.org/10.1371/journal.pone.0038011},
pages = {1-8},
abstract = {A key challenge in neuroscience is the expeditious reconstruction of neuronal circuits. For model systems such as Drosophila and C. elegans, the limiting step is no longer the acquisition of imagery but the extraction of the circuit from images. For this purpose, we designed a software application, TrakEM2, that addresses the systematic reconstruction of neuronal circuits from large electron microscopical and optical image volumes. We address the challenges of image volume composition from individual, deformed images; of the reconstruction of neuronal arbors and annotation of synapses with fast manual and semi-automatic methods; and the management of large collections of both images and annotations. The output is a neural circuit of 3d arbors and synapses, encoded in NeuroML and other formats, ready for analysis.},
number = {6}
}

@article{Titze2016,
author = {Titze, Benjamin and Genoud, Christel},
title = {Volume scanning electron microscopy for imaging biological ultrastructure},
journal = {Biology of the Cell},
volume = {108},
number = {11},
pages = {307-323},
keywords = {Brain/nervous system, Cellular imaging, Electron microscopy, Systems biology},
doi = {https://doi.org/10.1111/boc.201600024},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/boc.201600024},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/boc.201600024},
abstract = {Electron microscopy (EM) has been a key imaging method to investigate biological ultrastructure for over six decades. In recent years, novel volume EM techniques have significantly advanced nanometre-scale imaging of cells and tissues in three dimensions. Previously, this had depended on the slow and error-prone manual tasks of cutting and handling large numbers of sections, and imaging them one-by-one with transmission EM. Now, automated volume imaging methods mostly based on scanning EM (SEM) allow faster and more reliable acquisition of serial images through tissue volumes and achieve higher z-resolution. Various software tools have been developed to manipulate the acquired image stacks and facilitate quantitative analysis. Here, we introduce three volume SEM methods: serial block-face electron microscopy (SBEM), focused ion beam SEM (FIB-SEM) and automated tape-collecting ultramicrotome SEM (ATUM-SEM). We discuss and compare their capabilities, provide an overview of the full volume SEM workflow for obtaining 3D datasets and showcase different applications for biological research.},
year = {2016}
}

@article{Jeroen2015,
title = {Scanning EM of non-heavy metal stained biosamples: Large-field of view, high contrast and highly efficient immunolabeling},
journal = {Experimental Cell Research},
volume = {337},
number = {2},
pages = {202-207},
year = {2015},
note = {Cell Biology at High Resolution},
issn = {0014-4827},
doi = {https://doi.org/10.1016/j.yexcr.2015.07.012},
url = {https://www.sciencedirect.com/science/article/pii/S0014482715300422},
author = {Jeroen Kuipers and Pascal {de Boer} and Ben N.G. Giepmans},
keywords = {Scanning transmission EM, Transmission EM, Scanning EM, Nanotomy, Virtual EM, Quantum dots, Immuno-EM, Contrasting},
abstract = {Scanning electron microscopy (SEM) is increasing its application in life sciences for electron density measurements of ultrathin sections. These are traditionally analyzed with transmission electron microscopy (TEM); by most labs, SEM analysis still is associated with surface imaging only. Here we report several advantages of SEM for thin sections over TEM, both for structural inspection, as well as analyzing immuno-targeted labels such as quantum dots (QDs) and gold, where we find that QD-labeling is ten times more efficient than gold-labeling. Furthermore, we find that omitting post-staining with uranyl and lead leads to QDs readily detectable over the ultrastructure, but under these conditions ultrastructural contrast was even almost invisible in TEM examination. Importantly, imaging in SEM with STEM detection leads to both outstanding QDs and ultrastructural contrast. STEM imaging is superior over back-scattered electron imaging of these non-contrasted samples, whereas secondary electron detection cannot be used at all. We conclude that examination of ultrathin sections by SEM, which may be immunolabeled with QDs, will allow rapid and straightforward analysis of large fields with more efficient labeling than can be achieved with immunogold. The large fields of view routinely achieved with SEM, but not with TEM, allows straightforward raw data sharing using virtual microscopy, also known as nanotomy when this concerns EM data in the life sciences.}
}

@Article{Bock2011,
author={Bock, Davi D.
and Lee, Wei-Chung Allen
and Kerlin, Aaron M.
and Andermann, Mark L.
and Hood, Greg
and Wetzel, Arthur W.
and Yurgenson, Sergey
and Soucy, Edward R.
and Kim, Hyon Suk
and Reid, R. Clay},
title={Network anatomy and in vivo physiology of visual cortical neurons},
journal={Nature},
year={2011},
month={Mar},
day={01},
volume={471},
number={7337},
pages={177-182},
abstract={In the cerebral cortex, local circuits consist of tens of thousands of neurons, each of which makes thousands of synaptic connections. Perhaps the biggest impediment to understanding these networks is that we have no wiring diagrams of their interconnections. Even if we had a partial or complete wiring diagram, however, understanding the network would also require information about each neuron's function. Here we show that the relationship between structure and function can be studied in the cortex with a combination of in vivo physiology and network anatomy. We used two-photon calcium imaging to characterize a functional property---the preferred stimulus orientation---of a group of neurons in the mouse primary visual cortex. Large-scale electron microscopy of serial thin sections was then used to trace a portion of these neurons' local network. Consistent with a prediction from recent physiological experiments, inhibitory interneurons received convergent anatomical input from nearby excitatory neurons with a broad range of preferred orientations, although weak biases could not be rejected.},
issn={1476-4687},
doi={10.1038/nature09802},
url={https://doi.org/10.1038/nature09802}
}

@article {Miron2020,
	author = {Miron, Ezequiel and Oldenkamp, Roel and Brown, Jill M. and Pinto, David M. S. and Xu, C. Shan and Faria, Ana R. and Shaban, Haitham A. and Rhodes, James D. P. and Innocent, Cassandravictoria and de Ornellas, Sara and Hess, Harald F. and Buckle, Veronica and Schermelleh, Lothar},
	title = {Chromatin arranges in chains of mesoscale domains with nanoscale functional topography independent of cohesin},
	volume = {6},
	number = {39},
	elocation-id = {eaba8811},
	year = {2020},
	doi = {10.1126/sciadv.aba8811},
	publisher = {American Association for the Advancement of Science},
	abstract = {Three-dimensional (3D) chromatin organization plays a key role in regulating mammalian genome function; however, many of its physical features at the single-cell level remain underexplored. Here, we use live- and fixed-cell 3D super-resolution and scanning electron microscopy to analyze structural and functional nuclear organization in somatic cells. We identify chains of interlinked ~200- to 300-nm-wide chromatin domains (CDs) composed of aggregated nucleosomes that can overlap with individual topologically associating domains and are distinct from a surrounding RNA-populated interchromatin compartment. High-content mapping uncovers confinement of cohesin and active histone modifications to surfaces and enrichment of repressive modifications toward the core of CDs in both hetero- and euchromatic regions. This nanoscale functional topography is temporarily relaxed in postreplicative chromatin but remarkably persists after ablation of cohesin. Our findings establish CDs as physical and functional modules of mesoscale genome organization.},
	URL = {https://advances.sciencemag.org/content/6/39/eaba8811},
	eprint = {https://advances.sciencemag.org/content/6/39/eaba8811.full.pdf},
	journal = {Science Advances}
}


@ARTICLE{Mironov2019,
AUTHOR={Mironov, Alexander A. and Beznoussenko, Galina V.},   	 
TITLE={Models of Intracellular Transport: Pros and Cons},      
JOURNAL={Frontiers in Cell and Developmental Biology},      
VOLUME={7},      
PAGES={146},     
YEAR={2019},      
URL={https://www.frontiersin.org/article/10.3389/fcell.2019.00146},       
DOI={10.3389/fcell.2019.00146},      
ISSN={2296-634X},   
ABSTRACT={Intracellular transport is one of the most confusing issues in the field of cell biology. Many different models and their combinations have been proposed to explain the experimental data on intracellular transport. Here, we analyse the data related to the mechanisms of endoplasmic reticulum-to-Golgi and intra-Golgi transport from the point of view of the main models of intracellular transport; namely: the vesicular model, the diffusion model, the compartment maturation–progression model, and the kiss-and-run model. This review initially describes our current understanding of Golgi function, while highlighting the recent progress that has been made. It then continues to discuss the outstanding questions and potential avenues for future research with regard to the models of these transport steps. To compare the power of these models, we have applied the method proposed by K. Popper; namely, the formulation of prohibitive observations according to, and the consecutive evaluation of, previous data, on the basis on the new models. The levels to which the different models can explain the experimental observations are different, and to date, the most powerful has been the kiss-and-run model, whereas the least powerful has been the diffusion model.}
}

@article{Lawson2015,
    author = {Lawson, Catherine L. and Patwardhan, Ardan and Baker, Matthew L. and Hryc, Corey and Garcia, Eduardo Sanz and Hudson, Brian P. and Lagerstedt, Ingvar and Ludtke, Steven J. and Pintilie, Grigore and Sala, Raul and Westbrook, John D. and Berman, Helen M. and Kleywegt, Gerard J. and Chiu, Wah},
    title = "{EMDataBank unified data resource for 3DEM}",
    journal = {Nucleic Acids Research},
    volume = {44},
    number = {D1},
    pages = {D396-D403},
    year = {2015},
    month = {11},
    abstract = "{Three-dimensional Electron Microscopy (3DEM) has become a key experimental method in structural biology for a broad spectrum of biological specimens from molecules to cells. The EMDataBank project provides a unified portal for deposition, retrieval and analysis of 3DEM density maps, atomic models and associated metadata (emdatabank.org). We provide here an overview of the rapidly growing 3DEM structural data archives, which include maps in EM Data Bank and map-derived models in the Protein Data Bank. In addition, we describe progress and approaches toward development of validation protocols and methods, working with the scientific community, in order to create a validation pipeline for 3DEM data.}",
    issn = {0305-1048},
    doi = {10.1093/nar/gkv1126},
    url = {https://doi.org/10.1093/nar/gkv1126},
    eprint = {https://academic.oup.com/nar/article-pdf/44/D1/D396/9482557/gkv1126.pdf}
}

@Article{Iudin2016,
author={Iudin, Andrii
and Korir, Paul K.
and Salavert-Torres, Jos{\'e}
and Kleywegt, Gerard J.
and Patwardhan, Ardan},
title={EMPIAR: a public archive for raw electron microscopy image data},
journal={Nature Methods},
year={2016},
month={May},
day={01},
volume={13},
number={5},
pages={387-388},
issn={1548-7105},
doi={10.1038/nmeth.3806},
url={https://doi.org/10.1038/nmeth.3806}
}

@article{Mohamed2002,
title = {New electron microscopy database and deposition system},
journal = {Trends in Biochemical Sciences},
volume = {27},
number = {11},
pages = {589},
year = {2002},
issn = {0968-0004},
doi = {https://doi.org/10.1016/S0968-0004(02)02176-X},
url = {https://www.sciencedirect.com/science/article/pii/S096800040202176X},
author = {Mohamed Tagari and Richard Newman and Monica Chagoyen and Jose-Maria Carazo and Kim Henrick},
keywords = {electron microscopy, cryo-EM, protein structure, databases, EBI}
}

@Article{Hartigan2016,
author={Hartigan, A.
and Estensoro, I.
and Vancov{\'a}, M.
and B{\'i}l{\'y}, T.
and Patra, S.
and Eszterbauer, E.
and Holzer, A. S.},
title={New cell motility model observed in parasitic cnidarian Sphaerospora molnari (Myxozoa:Myxosporea) blood stages in fish},
journal={Scientific Reports},
year={2016},
month={Dec},
day={16},
volume={6},
number={1},
pages={39093},
abstract={Cellular motility is essential for microscopic parasites, it is used to reach the host, migrate through tissues, or evade host immune reactions. Many cells employ an evolutionary conserved motor protein-- actin, to crawl or glide along a substrate. We describe the peculiar movement of Sphaerospora molnari, a myxozoan parasite with proliferating blood stages in its host, common carp. Myxozoa are highly adapted parasitic cnidarians alternately infecting vertebrates and invertebrates. S. molnari blood stages (SMBS) have developed a unique ``dancing'' behaviour, using the external membrane as a motility effector to rotate and move the cell. SMBS movement is exceptionally fast compared to other myxozoans, non-directional and constant. The movement is based on two cytoplasmic actins that are highly divergent from those of other metazoans. We produced a specific polyclonal actin antibody for the staining and immunolabelling of S. molnari's microfilaments since we found that neither commercial antibodies nor phalloidin recognised the protein or microfilaments. We show the in situ localization of this actin in the parasite and discuss the importance of this motility for evasion from the cellular host immune response in vitro. This new type of motility holds key insights into the evolution of cellular motility and associated proteins.},
issn={2045-2322},
doi={10.1038/srep39093},
url={https://doi.org/10.1038/srep39093}
}



@Article{Caldas2020,
author={Caldas, Lucio Ayres
and Carneiro, Fabiana Avila
and Higa, Luiza Mendon{\c{c}}a
and Monteiro, F{\'a}bio Luiz
and da Silva, Gustavo Peixoto
and da Costa, Luciana Jesus
and Durigon, Edison Luiz
and Tanuri, Amilcar
and de Souza, Wanderley},
title={Ultrastructural analysis of SARS-CoV-2 interactions with the host cell via high resolution scanning electron microscopy},
journal={Scientific Reports},
year={2020},
month={Sep},
day={30},
volume={10},
number={1},
pages={16099},
abstract={SARS-CoV-2 is the cause of the ongoing COVID-19 pandemic. Here, we investigated the interaction of this new coronavirus with Vero cells using high resolution scanning electron microscopy. Surface morphology, the interior of infected cells and the distribution of viral particles in both environments were observed 2 and 48 h after infection. We showed areas of viral processing, details of vacuole contents, and viral interactions with the cell surface. Intercellular connections were also approached, and viral particles were adhered to these extensions suggesting direct cell-to-cell transmission of SARS-CoV-2.},
issn={2045-2322},
doi={10.1038/s41598-020-73162-5},
url={https://doi.org/10.1038/s41598-020-73162-5}
}



@article{Faas2012,
    author = {Faas , Frank G.A.  and Avramut , M. Cristina  and M. van den Berg , Bernard  and Mommaas , A. Mieke  and Koster , Abraham J.  and Ravelli , Raimond B.G. },
    title = "{Virtual nanoscopy: Generation of ultra-large high resolution electron microscopy maps }",
    journal = {Journal of Cell Biology},
    volume = {198},
    number = {3},
    pages = {457-469},
    year = {2012},
    month = {08},
    abstract = "{A key obstacle in uncovering the orchestration between molecular and cellular events is the vastly different length scales on which they occur. We describe here a methodology for ultrastructurally mapping regions of cells and tissue as large as 1 mm2 at nanometer resolution. Our approach employs standard transmission electron microscopy, rapid automated data collection, and stitching to create large virtual slides. It greatly facilitates correlative light-electron microscopy studies to relate structure and function and provides a genuine representation of ultrastructural events. The method is scalable as illustrated by slides up to 281 gigapixels in size. Here, we applied virtual nanoscopy in a correlative light-electron microscopy study to address the role of the endothelial glycocalyx in protein leakage over the glomerular filtration barrier, in an immunogold labeling study of internalization of oncolytic reovirus in human dendritic cells, in a cryo-electron microscopy study of intact vitrified mouse embryonic cells, and in an ultrastructural mapping of a complete zebrafish embryo slice. }",
    issn = {0021-9525},
    doi = {10.1083/jcb.201201140},
    url = {https://doi.org/10.1083/jcb.201201140},
    eprint = {https://rupress.org/jcb/article-pdf/198/3/457/1357323/jcb\_201201140.pdf},
}

@Article{Mikula2012,
author={Mikula, Shawn
and Binding, Jonas
and Denk, Winfried},
title={Staining and embedding the whole mouse brain for electron microscopy},
journal={Nature Methods},
year={2012},
month={Dec},
day={01},
volume={9},
number={12},
pages={1198-1201},
abstract={A method for staining and embedding the entire mouse brain for electron microscopy is reported. The method results in uniform myelin staining and will allow reconstructions of myelinated long-range axons using serial block-face electron microscopy.},
issn={1548-7105},
doi={10.1038/nmeth.2213},
url={https://doi.org/10.1038/nmeth.2213}
}

@article{Deerinck2010, 
title={Enhancing Serial Block-Face Scanning Electron Microscopy to Enable High Resolution 3-D Nanohistology of Cells and Tissues}, 
volume={16}, DOI={10.1017/S1431927610055170}, 
number={S2}, journal={Microscopy and Microanalysis}, 
publisher={Cambridge University Press}, 
author={Deerinck, TJ and Bushong, EA and Lev-Ram, V and Shu, X and Tsien, RY and Ellisman, MH}, year={2010}, 
pages={1138–1139}
}

@article{Ardenne1939, 
title={ }, 
volume={56}, 
DOI={}, 
number={8}, 
journal={Mikroskope}, 
publisher={}, 
author={Ardenne, M. Von and Wissensch, Z. }, 
year={1939}, 
pages={8}
}

@article{Hua2021,
title = {Electron Microscopic Reconstruction of Neural Circuitry in the Cochlea},
journal = {Cell Reports},
volume = {34},
number = {1},
pages = {108551},
year = {2021},
issn = {2211-1247},
doi = {https://doi.org/10.1016/j.celrep.2020.108551},
url = {https://www.sciencedirect.com/science/article/pii/S2211124720315400},
author = {Yunfeng Hua and Xu Ding and Haoyu Wang and Fangfang Wang and Yan Lu and Jakob Neef and Yunge Gao and Tobias Moser and Hao Wu},
keywords = {mmouse cochlea, volume electron microscopy, inner hair cell, spiral ganglion neuron, ribbon synapse, efferent innervation},
abstract = {Summary
Recent studies reveal great diversity in the structure, function, and efferent innervation of afferent synaptic connections between the cochlear inner hair cells (IHCs) and spiral ganglion neurons (SGNs), which likely enables audition to process a wide range of sound pressures. By performing an extensive electron microscopic (EM) reconstruction of the neural circuitry in the mature mouse organ of Corti, we demonstrate that afferent SGN dendrites differ in abundance and composition of efferent innervation in a manner dependent on their afferent synaptic connectivity with IHCs. SGNs that sample glutamate release from several presynaptic ribbons receive more efferent innervation from lateral olivocochlear projections than those driven by a single ribbon. Next to the prevailing unbranched SGN dendrites, we found branched SGN dendrites that can contact several ribbons of 1–2 IHCs. Unexpectedly, medial olivocochlear neurons provide efferent innervation of SGN dendrites, preferring those forming single-ribbon, pillar-side synapses. We propose a fine-tuning of afferent and efferent SGN innervation.}
}

@Article{Mikula2015,
author={Mikula, Shawn
and Denk, Winfried},
title={High-resolution whole-brain staining for electron microscopic circuit reconstruction},
journal={Nature Methods},
year={2015},
month={Jun},
day={01},
volume={12},
number={6},
pages={541-546},
abstract={An improved method for preparing mouse brains for electron microscopy allows reliable tracing of neurites and identification of synapses and appears suitable for whole-brain connectomic reconstruction.},
issn={1548-7105},
doi={10.1038/nmeth.3361},
url={https://doi.org/10.1038/nmeth.3361}
}



@Article{Hua2015,
author={Hua, Yunfeng
and Laserstein, Philip
and Helmstaedter, Moritz},
title={Large-volume en-bloc staining for electron microscopy-based connectomics},
journal={Nature Communications},
year={2015},
month={Aug},
day={03},
volume={6},
number={1},
pages={7923},
abstract={Large-scale connectomics requires dense staining of neuronal tissue blocks for electron microscopy (EM). Here we report a large-volume dense en-bloc EM staining protocol that overcomes the staining gradients, which so far substantially limited the reconstructable volumes in three-dimensional (3D) EM. Our protocol provides densely reconstructable tissue blocks from mouse neocortex sized at least 1{\thinspace}mm in diameter. By relaxing the constraints on precise topographic sample targeting, it makes the correlated functional and structural analysis of neuronal circuits realistic.},
issn={2041-1723},
doi={10.1038/ncomms8923},
url={https://doi.org/10.1038/ncomms8923}
}

@article{Nakakoshi2011,
    author = {Nakakoshi, Masamichi and Nishioka, Hideo and Katayama, Eisaku},
    title = "{New versatile staining reagents for biological transmission electron microscopy that substitute for uranyl acetate}",
    journal = {Journal of Electron Microscopy},
    volume = {60},
    number = {6},
    pages = {401-407},
    year = {2011},
    month = {12},
    abstract = "{Aqueous uranyl acetate has been extensively used as a superb staining reagent for transmission electron microscopy of biological materials. However, recent regulation of nuclear fuel material severely restricts its use even for purely scientific purposes. Since uranyl salts are hazardous due to biological toxicity and remaining radioactivity, development of safe and non-radioactive substitutes is greatly anticipated. We examined two lanthanide salts, samarium triacetate and gadolinium triacetate, and found that 1–10\\% solution of these reagents was safe but still possess excellent capability for staining thin sections of plastic-embedded materials of animal and plant origin. Although post-fixation with osmium tetroxide was essential for high-contrast staining, post-staining with lead citrate could be eliminated if a slow-scan CCD camera is available for observation. These lanthanide salts can also be utilized as good negative-staining reagents to study supramolecular architecture of biological macromolecules. They were not as effective as a fixative of protein assembly, reflecting the non-hazardous nature of the reagents.}",
    issn = {0022-0744},
    doi = {10.1093/jmicro/dfr084},
    url = {https://doi.org/10.1093/jmicro/dfr084},
    eprint = {https://academic.oup.com/jmicro/article-pdf/60/6/401/5854475/dfr084.pdf},
}

@Article{Kuipers2020,
author={Kuipers, Jeroen
and Giepmans, Ben N. G.},
title={Neodymium as an alternative contrast for uranium in electron microscopy},
journal={Histochemistry and Cell Biology},
year={2020},
month={Apr},
day={01},
volume={153},
number={4},
pages={271-277},
abstract={Uranyl acetate is the standard contrasting agent in electron microscopy (EM), but it is toxic and radioactive. We reasoned neodymium acetate might substitute uranyl acetate as a contrasting agent, and we find that neodymium acetate indeed can replace uranyl acetate in several routine applications. Since neodymium acetate is not toxic, not radioactive and easy to use, we foresee neodymium will replace uranyl in many EM sample preparation applications worldwide.},
issn={1432-119X},
doi={10.1007/s00418-020-01846-0},
url={https://doi.org/10.1007/s00418-020-01846-0}
}

@inproceedings{Cortadellas2012,
  title={Transmission electron microscopy in cell biology: sample preparation techniques and image information},
  author={N{\'u}ria Cortadellas i Ram{\'e}ntol and Almudena Garc{\'i}a and Eva Fern{\'a}ndez},
  year={2012}
}

@article{Anthony1984,
    author = {Sant’ Agnese, P. Anthony DI and De Mesy Jensen, Karen L.},
    title = "{Dibasic Staining of Large Epoxy Tissue Sections and Applications to Surgical Pathology}",
    journal = {American Journal of Clinical Pathology},
    volume = {81},
    number = {1},
    pages = {25-29},
    year = {1984},
    month = {01},
    abstract = "{A variety of normal and pathologic aldehyde-fixed osmiumpostfixed human tissues were prepared as large sections embedded in Spurr epoxy. They were stained with a sequential basic fuchsin—methylene blue stain which gives “hematoxylin- and eosin-like” staining and additionally functions as several special stains. This technic also allows for electron microscopy directly on the embedded tissue. The histologic and cytologic preservation and overall staining was superior to tissue embedded in glycol methacrylate. The methods and technics presented in this article have important applications in diagnostic surgical pathology and histology in general.}",
    issn = {0002-9173},
    doi = {10.1093/ajcp/81.1.25},
    url = {https://doi.org/10.1093/ajcp/81.1.25},
    eprint = {https://academic.oup.com/ajcp/article-pdf/81/1/25/26431210/ajcpath81-0025.pdf},
}

@article{Luft1961,
    author = {Luft , John H. },
    title = "{IMPROVEMENTS IN EPOXY RESIN EMBEDDING METHODS }",
    journal = {The Journal of Biophysical and Biochemical Cytology},
    volume = {9},
    number = {2},
    pages = {409-414},
    year = {1961},
    month = {02},
    abstract = "{Epoxy embedding methods of Glauert and Kushida have been modified so as to yield rapid, reproducible, and convenient embedding methods for electron microscopy. The sections are robust and tissue damage is less than with methacrylate embedding. }",
    issn = {0095-9901},
    doi = {10.1083/jcb.9.2.409},
    url = {https://doi.org/10.1083/jcb.9.2.409},
    eprint = {https://rupress.org/jcb/article-pdf/9/2/409/1078074/409.pdf}
}

@article{Trump1961,
title = {A method for staining epoxy sections for light microscopy},
journal = {Journal of Ultrastructure Research},
volume = {5},
number = {4},
pages = {343-348},
year = {1961},
issn = {0022-5320},
doi = {https://doi.org/10.1016/S0022-5320(61)80011-7},
url = {https://www.sciencedirect.com/science/article/pii/S0022532061800117},
author = {Benjamin F. Trump and Edward A. Smuckler and Earl P. Benditt},
abstract = {A technique for staining sections of osmium-fixed, epoxy-embedded tissues for light microscopy is presented. The method employs aqueous toluidine blue at pH 11.1 and does not require prior removal of embedding medium. When stained with this technique and viewed with an oil immersion objective, the images are striking because of their great definition and resemblance to the images are striking because of their great definition and resemblance to of areas seen in the electron microscope; it also permits better utilization of the full resolving power of the light microscope.}
}

@Inbook{Nagashima2011,
author="Nagashima, Kunio
and Zheng, Jiwen
and Parmiter, David
and Patri, Anil K.",
editor="McNeil, Scott E.",
title="Biological Tissue and Cell Culture Specimen Preparation for TEM Nanoparticle Characterization",
bookTitle="Characterization of Nanoparticles Intended for Drug Delivery",
year="2011",
publisher="Humana Press",
address="Totowa, NJ",
pages="83--91",
abstract="This chapter outlines the procedures for ex vivo TEM preparation of nanoparticle-containing tissue or cell culture samples using an epoxy resin embedding method. The purpose of this procedure is to preserve the structure of tissue in a hardened epoxy block with minimal disruption of cellular structures, to aid in the meaningful analysis of in vivo or cell culture experiments. The process begins with hydrated tissue and ends with tissue that is virtually water-free and preserved in a static state within a plastic resin matrix. The resin mixture permeates the dehydrated tissue, making the sample firm enough to cut. Procedures are also given for fixing nanoparticle-containing cell culture samples.",
isbn="978-1-60327-198-1",
doi="10.1007/978-1-60327-198-1_8",
url="https://doi.org/10.1007/978-1-60327-198-1_8"
}

@article{Winey2014,
author = {Winey, Mark and Meehl, Janet B. and O'Toole, Eileen T. and Giddings, Thomas H.},
title = {Conventional transmission electron microscopy},
journal = {Molecular Biology of the Cell},
volume = {25},
number = {3},
pages = {319-323},
year = {2014},
doi = {10.1091/mbc.e12-12-0863},
note ={PMID: 24482357},
URL = {https://doi.org/10.1091/mbc.e12-12-0863},
eprint = {https://doi.org/10.1091/mbc.e12-12-0863},
abstract = { Researchers have used transmission electron microscopy (TEM) to make contributions to cell biology for well over 50 years, and TEM continues to be an important technology in our field. We briefly present for the neophyte the components of a TEM-based study, beginning with sample preparation through imaging of the samples. We point out the limitations of TEM and issues to be considered during experimental design. Advanced electron microscopy techniques are listed as well. Finally, we point potential new users of TEM to resources to help launch their project. }
}

@article{Kremer1996,
title = {Computer Visualization of Three-Dimensional Image Data Using IMOD},
journal = {Journal of Structural Biology},
volume = {116},
number = {1},
pages = {71-76},
year = {1996},
issn = {1047-8477},
doi = {https://doi.org/10.1006/jsbi.1996.0013},
url = {https://www.sciencedirect.com/science/article/pii/S1047847796900131},
author = {James R. Kremer and David N. Mastronarde and J.Richard McIntosh},
abstract = {We have developed a computer software package, IMOD, as a tool for analyzing and viewing three-dimensional biological image data. IMOD is useful for studying and modeling data from tomographic, serial section, and optical section reconstructions. The software allows image data to be visualized by several different methods. Models of the image data can be visualized by volume or contour surface rendering and can yield quantitative information.}
}

@article{Pereira2016,
    doi = {10.1371/journal.pcbi.1005217},
    author = {Pereira, André F. and Hageman, Daniel J. and Garbowski, Tomasz and Riedesel, Christof and Knothe, Ulf and Zeidler, Dirk and Knothe Tate, Melissa L.},
    journal = {PLOS Computational Biology},
    publisher = {Public Library of Science},
    title = {Creating High-Resolution Multiscale Maps of Human Tissue Using Multi-beam SEM},
    year = {2016},
    month = {11},
    volume = {12},
    url = {https://doi.org/10.1371/journal.pcbi.1005217},
    pages = {1-17},
    abstract = {Multi-beam scanning electron microscopy (mSEM) enables high-throughput, nano-resolution imaging of macroscopic tissue samples, providing an unprecedented means for structure-function characterization of biological tissues and their cellular inhabitants, seamlessly across multiple length scales. Here we describe computational methods to reconstruct and navigate a multitude of high-resolution mSEM images of the human hip. We calculated cross-correlation shift vectors between overlapping images and used a mass-spring-damper model for optimal global registration. We utilized the Google Maps API to create an interactive map and provide open access to our reconstructed mSEM datasets to both the public and scientific communities via our website www.mechbio.org. The nano- to macro-scale map reveals the tissue’s biological and material constituents. Living inhabitants of the hip bone (e.g. osteocytes) are visible in their local extracellular matrix milieu (comprising collagen and mineral) and embedded in bone’s structural tissue architecture, i.e. the osteonal structures in which layers of mineralized tissue are organized in lamellae around a central blood vessel. Multi-beam SEM and our presented methodology enable an unprecedented, comprehensive understanding of health and disease from the molecular to organ length scale.},
    number = {11}
}

@inproceedings{Krumeich2015,
  title={Properties of Electrons, their Interactions with Matter and Applications in Electron Microscopy},
  author={Krumeich, Frank},
  year={2015}
}

@article{Buckman2014,
title = "Use of automated image acquisition and stitching in scanning electron microscopy: Imaging of large scale areas of materials at high resolution: SEM image stitching",
author = "Buckman, Jim ",
year = "2014",
month = jan,
language = "English",
volume = "January 2014",
pages = "s13--16",
journal = "Microscopy and Analysis",
issn = "0958-1952",
}

@article{Kaynig2010,
title = {Fully automatic stitching and distortion correction of transmission electron microscope images},
journal = {Journal of Structural Biology},
volume = {171},
number = {2},
pages = {163-173},
year = {2010},
issn = {1047-8477},
doi = {https://doi.org/10.1016/j.jsb.2010.04.012},
url = {https://www.sciencedirect.com/science/article/pii/S1047847710001401},
author = {Verena Kaynig and Bernd Fischer and Elisabeth Müller and Joachim M. Buhmann},
keywords = {Automatic stitching, Auto-calibration, SIFT features, Robust transformation, Transmission electron microscopy, Image distortion, Electromagnetic lenses},
abstract = {In electron microscopy, a large field of view is commonly captured by taking several images of a sample region and then by stitching these images together. Non-linear lens distortions induced by the electromagnetic lenses of the microscope render a seamless stitching with linear transformations impossible. This problem is aggravated by large CCD cameras, as they are commonly in use nowadays. We propose a new calibration method based on ridge regression that compensates non-linear lens distortions, while ensuring that the geometry of the image is preserved. Our method estimates the distortion correction from overlapping image areas using automatically extracted correspondence points. Therefore, the estimation of the correction transform does not require any special calibration samples. We evaluate our method on simulated ground truth data as well as on real electron microscopy data. Our experiments demonstrate that the lens calibration robustly corrects large distortions with an average stitching error exceeding 10 pixels to sub-pixel accuracy within two iteration steps.}
}

@article{Ma2007,
title = {Use of Autostitch for automatic stitching of microscope images},
journal = {Micron},
volume = {38},
number = {5},
pages = {492-499},
year = {2007},
issn = {0968-4328},
doi = {https://doi.org/10.1016/j.micron.2006.07.027},
url = {https://www.sciencedirect.com/science/article/pii/S0968432806001648},
author = {Bin Ma and Timo Zimmermann and Manfred Rohde and Simon Winkelbach and Feng He and Werner Lindenmaier and Kurt E.J. Dittmar},
keywords = {Autostitch, Image stitching, Automatic microscopy, Image masaicing, Virtual microscopy},
abstract = {Image stitching is the process of combining multiple images to produce a panorama or larger image. In many biomedical studies, including those of cancer and infection, the use of this approach is highly desirable in order to acquire large areas of certain structures or whole sections, while retaining microscopic resolution. In this study, we describe the application of Autostitch, viz. software that is normally used for the generation of panoramas in photography, in the seamless stitching of microscope images. First, we tested this software on image sets manually acquired by normal light microscopy and compared the performance with a manual stitching approach performed with Paint Shop Pro. Secondly, this software was applied to an image stack acquired by an automatic microscope. The stitching results were then compared with that generated by a self-programmed rectangular tiling macro integrated in Image J. Thirdly, this program was applied in the image stitching of images from electron microscopy. Thus, the automatic stitching program described here may find applications in convenient image stitching and virtual microscopy in the biomedical research.}
}

@Article{Chalfoun2017,
author={Chalfoun, Joe
and Majurski, Michael
and Blattner, Tim
and Bhadriraju, Kiran
and Keyrouz, Walid
and Bajcsy, Peter
and Brady, Mary},
title={MIST: Accurate and Scalable Microscopy Image Stitching Tool with Stage Modeling and Error Minimization},
journal={Scientific Reports},
year={2017},
month={Jul},
day={10},
volume={7},
number={1},
pages={4988},
abstract={Automated microscopy can image specimens larger than the microscope's field of view (FOV) by stitching overlapping image tiles. It also enables time-lapse studies of entire cell cultures in multiple imaging modalities. We created MIST (Microscopy Image Stitching Tool) for rapid and accurate stitching of large 2D time-lapse mosaics. MIST estimates the mechanical stage model parameters (actuator backlash, and stage repeatability `r') from computed pairwise translations and then minimizes stitching errors by optimizing the translations within a (4r)2 square area. MIST has a performance-oriented implementation utilizing multicore hybrid CPU/GPU computing resources, which can process terabytes of time-lapse multi-channel mosaics 15 to 100 times faster than existing tools. We created 15 reference datasets to quantify MIST's stitching accuracy. The datasets consist of three preparations of stem cell colonies seeded at low density and imaged with varying overlap (10 to 50{\%}). The location and size of 1150 colonies are measured to quantify stitching accuracy. MIST generated stitched images with an average centroid distance error that is less than 2{\%} of a FOV. The sources of these errors include mechanical uncertainties, specimen photobleaching, segmentation, and stitching inaccuracies. MIST produced higher stitching accuracy than three open-source tools. MIST is available in ImageJ at isg.nist.gov.},
issn={2045-2322},
doi={10.1038/s41598-017-04567-y},
url={https://doi.org/10.1038/s41598-017-04567-y}
}

@article{Lefman2007,
title = {Automated 100-position specimen loader and image acquisition system for transmission electron microscopy},
journal = {Journal of Structural Biology},
volume = {158},
number = {3},
pages = {318-326},
year = {2007},
issn = {1047-8477},
doi = {https://doi.org/10.1016/j.jsb.2006.11.007},
url = {https://www.sciencedirect.com/science/article/pii/S1047847706003819},
author = {Jonathan Lefman and Robert Morrison and Sriram Subramaniam},
keywords = {High-throughput electron microscopy, Nanotechnology, Remote microscopy, Electron crystallography},
abstract = {We report the development of a novel, multi-specimen imaging system for high-throughput transmission electron microscopy. Our cartridge-based loading system, called the “Gatling”, permits the sequential examination of as many as 100 specimens in the microscope for room temperature electron microscopy using mechanisms for rapid and automated specimen exchange. The software for the operation of the Gatling and automated data acquisition has been implemented in an updated version of our in-house program AutoEM. In the current implementation of the system, the time required to deliver 95 specimens into the microscope and collect overview images from each is about 13h. Regions of interest are identified from a low magnification atlas generation from each specimen and an unlimited number of higher magnifications images can be subsequently acquired from these regions using fully automated data acquisition procedures that can be controlled from a remote interface. We anticipate that the availability of the Gatling will greatly accelerate the speed of data acquisition for a variety of applications in biology, materials science, and nanotechnology that require rapid screening and image analysis of multiple specimens.}
}

@INPROCEEDINGS{Quan2019,
  author={Quan, Tran Minh and Hildebrand, David Grant Colburn and Lee, Kanggeun and Thomas, Logan A. and Kuan, Aaron T. and Lee, Wei-Chung Allen and Jeong, Won-Ki},
  booktitle={2019 IEEE/CVF International Conference on Computer Vision Workshop (ICCVW)}, 
  title={Removing Imaging Artifacts in Electron Microscopy using an Asymmetrically Cyclic Adversarial Network without Paired Training Data}, 
  year={2019},
  volume={},
  number={},
  pages={3804-3813},
  doi={10.1109/ICCVW.2019.00473}}

@article{Amoudi2005,
title = {Cutting artefacts and cutting process in vitreous sections for cryo-electron microscopy},
journal = {Journal of Structural Biology},
volume = {150},
number = {1},
pages = {109-121},
year = {2005},
issn = {1047-8477},
doi = {https://doi.org/10.1016/j.jsb.2005.01.003},
url = {https://www.sciencedirect.com/science/article/pii/S1047847705000237},
author = { Al-Amoudi, Ashraf and Studer, Daniel and Dubochet, Jacques},
keywords = {CEMOVIS, Knife marks, Compression, Crevasses, Chatter, Cutting artefacts},
abstract = {Cryo-electron microscopy of vitreous sections (CEMOVIS) has recently been shown to provide images of biological specimens with unprecedented quality and resolution. Cutting the sections remains however the major difficulty. Here, we examine the parameters influencing the quality of the sections and analyse the resulting artefacts. They are in particular: knife marks, compression, crevasses, and chatter. We propose a model taking into account the interplay between viscous flow and fracture. We confirm that crevasses are formed on only one side of the section, and define conditions by which they can be avoided. Chatter is an effect of irregular compression due to friction of the section of the knife edge and conditions to prevent this are also explored. In absence of crevasses and chatter, the bulk of the section is compressed approximately homogeneously. Within this approximation, it is possible to correct for compression by a simple linear transformation for the bulk of the section. A research program is proposed to test and refine our understanding of the sectioning process.}
}

@Article{Schorb2019,
author={Schorb, Martin
and Haberbosch, Isabella
and Hagen, Wim J. H.
and Schwab, Yannick
and Mastronarde, David N.},
title={Software tools for automated transmission electron microscopy},
journal={Nature Methods},
year={2019},
month={Jun},
day={01},
volume={16},
number={6},
pages={471-477},
abstract={The demand for high-throughput data collection in electron microscopy is increasing for applications in structural and cellular biology. Here we present a combination of software tools that enable automated acquisition guided by image analysis for a variety of transmission electron microscopy acquisition schemes. SerialEM controls microscopes and detectors and can trigger automated tasks at multiple positions with high flexibility. Py-EM interfaces with SerialEM to enact specimen-specific image-analysis pipelines that enable feedback microscopy. As example applications, we demonstrate dose reduction in cryo-electron microscopy experiments, fully automated acquisition of every cell in a plastic section and automated targeting on serial sections for 3D volume imaging across multiple grids.},
issn={1548-7105},
doi={10.1038/s41592-019-0396-9},
url={https://doi.org/10.1038/s41592-019-0396-9}
}

@Article{Graham2007,
author={Graham, Lesley
and Orenstein, Jan Marc},
title={Processing tissue and cells for transmission electron microscopy in diagnostic pathology and research},
journal={Nature Protocols},
year={2007},
month={Oct},
day={01},
volume={2},
number={10},
pages={2439-2450},
abstract={In transmission electron microscopy (TEM), electrons are transmitted through a plastic-embedded specimen, and an image is formed. TEM enables the resolution and visualization of detail not apparent via light microscopy, even when combined with immunohistochemical analysis. Ultrastructural examination of tissues, cells and microorganisms plays a vital role in diagnostic pathology and biologic research. TEM is used to study the morphology of cells and their organelles, and in the identification and characterization of viruses, bacteria, protozoa and fungi. In this protocol, we present a TEM method for preparing specimens obtained in clinical or research settings, discussing the particular requirements for tissue and cell preparation and analysis, the need for rapid fixation and the possibility of analysis of tissue already fixed in formalin or processed into paraffin blocks. Details of fixation, embedding and how to prepare thin and semi-thin sections, which can be used for analysis complementary to that performed ultimately using TEM, are also described.},
issn={1750-2799},
doi={10.1038/nprot.2007.304},
url={https://doi.org/10.1038/nprot.2007.304}
}

@Article{Scotuzzi2017,
author={Scotuzzi, Marijke
and Kuipers, Jeroen
and Wensveen, Dasha I.
and de Boer, Pascal
and Hagen, Kees (C.) W.
and Hoogenboom, Jacob P.
and Giepmans, Ben N. G.},
title={Multi-color electron microscopy by element-guided identification of cells, organelles and molecules},
journal={Scientific Reports},
year={2017},
month={Apr},
day={07},
volume={7},
number={1},
pages={45970},
abstract={Cellular complexity is unraveled at nanometer resolution using electron microscopy (EM), but interpretation of macromolecular functionality is hampered by the difficulty in interpreting grey-scale images and the unidentified molecular content. We perform large-scale EM on mammalian tissue complemented with energy-dispersive X-ray analysis (EDX) to allow EM-data analysis based on elemental composition. Endogenous elements, labels (gold and cadmium-based nanoparticles) as well as stains are analyzed at ultrastructural resolution. This provides a wide palette of colors to paint the traditional grey-scale EM images for composition-based interpretation. Our proof-of-principle application of EM-EDX reveals that endocrine and exocrine vesicles exist in single cells in Islets of Langerhans. This highlights how elemental mapping reveals unbiased biomedical relevant information. Broad application of EM-EDX will further allow experimental analysis on large-scale tissue using endogenous elements, multiple stains, and multiple markers and thus brings nanometer-scale `color-EM' as a promising tool to unravel molecular (de)regulation in biomedicine.},
issn={2045-2322},
doi={10.1038/srep45970},
url={https://doi.org/10.1038/srep45970}
}

@Article{AU-Kuipers2016,
author={AU - Kuipers, Jeroen
and AU - Kalicharan, Ruby D.
and AU - Wolters, Anouk H. G.
and AU - van Ham, Tjakko J.
and AU - Giepmans, Ben N.G.},
title={Large-scale Scanning Transmission Electron Microscopy (Nanotomy) of Healthy and Injured Zebrafish Brain},
journal={JoVE},
year={2016},
month={May},
day={25},
publisher={MyJoVE Corp},
number={111},
pages={e53635},
keywords={Developmental Biology; Large-scale electron microscopy; scanning EM; nanotomy; zebrafish; quantitative EM; correlated microscopy},
abstract={Large-scale 2D electron microscopy (EM), or nanotomy, is the tissue-wide application of nanoscale resolution electron microscopy. Others and we previously applied large scale EM to human skin pancreatic islets, tissue culture and whole zebrafish larvae1-7. Here we describe a universally applicable method for tissue-scale scanning EM for unbiased detection of sub-cellular and molecular features. Nanotomy was applied to investigate the healthy and a neurodegenerative zebrafish brain. Our method is based on standardized EM sample preparation protocols: Fixation with glutaraldehyde and osmium, followed by epoxy-resin embedding, ultrathin sectioning and mounting of ultrathin-sections on one-hole grids, followed by post staining with uranyl and lead. Large-scale 2D EM mosaic images are acquired using a scanning EM connected to an external large area scan generator using scanning transmission EM (STEM). Large scale EM images are typically {\textasciitilde} 5 - 50 G pixels in size, and best viewed using zoomable HTML files, which can be opened in any web browser, similar to online geographical HTML maps. This method can be applied to (human) tissue, cross sections of whole animals as well as tissue culture1-5. Here, zebrafish brains were analyzed in a non-invasive neuronal ablation model. We visualize within a single dataset tissue, cellular and subcellular changes which can be quantified in various cell types including neurons and microglia, the brain's macrophages. In addition, nanotomy facilitates the correlation of EM with light microscopy (CLEM)8 on the same tissue, as large surface areas previously imaged using fluorescent microscopy, can subsequently be subjected to large area EM, resulting in the nano-anatomy (nanotomy) of tissues. In all, nanotomy allows unbiased detection of features at EM level in a tissue-wide quantifiable manner.},
issn={1940-087X},
doi={10.3791/53635},
url={https://www.jove.com/t/53635},
url={https://doi.org/10.3791/53635}
}

@Article{Grudniewska2018,
author={Grudniewska, Magda
and Mouton, Stijn
and Grelling, Margriet
and Wolters, Anouk H. G.
and Kuipers, Jeroen
and Giepmans, Ben N. G.
and Berezikov, Eugene},
title={A novel flatworm-specific gene implicated in reproduction in Macrostomum lignano},
journal={Scientific Reports},
year={2018},
month={Feb},
day={16},
volume={8},
number={1},
pages={3192},
abstract={Free-living flatworms, such as the planarian Schmidtea mediterranea, are extensively used as model organisms to study stem cells and regeneration. The majority of flatworm studies so far focused on broadly conserved genes. However, investigating what makes these animals different is equally informative for understanding its biology and might have biomedical value. We re-analyzed the neoblast and germline transcriptional signatures of the flatworm M. lignano using an improved transcriptome assembly and show that germline-enriched genes have a high fraction of flatworm-specific genes. We further identified the Mlig-sperm1 gene as a member of a novel gene family conserved only in free-living flatworms and essential for producing healthy spermatozoa. In addition, we established a whole-animal electron microscopy atlas (nanotomy) to visualize the ultrastructure of the testes in wild type worms, but also as a reference platform for different ultrastructural studies in M. lignano. This work demonstrates that investigation of flatworm-specific genes is crucial for understanding flatworm biology and establishes a basis for such future research in M. lignano.},
issn={2045-2322},
doi={10.1038/s41598-018-21107-4},
url={https://doi.org/10.1038/s41598-018-21107-4}
}

@Article{deBoer2020,
author={de Boer, Pascal
and Pirozzi, Nicole M.
and Wolters, Anouk H. G.
and Kuipers, Jeroen
and Kusmartseva, Irina
and Atkinson, Mark A.
and Campbell-Thompson, Martha
and Giepmans, Ben N. G.},
title={Large-scale electron microscopy database for human type 1 diabetes},
journal={Nature Communications},
year={2020},
month={May},
day={18},
volume={11},
number={1},
pages={2475},
abstract={Autoimmune $\beta$-cell destruction leads to type 1 diabetes, but the pathophysiological mechanisms remain unclear. To help address this void, we created an open-access online repository, unprecedented in its size, composed of large-scale electron microscopy images (`nanotomy') of human pancreas tissue obtained from the Network for Pancreatic Organ donors with Diabetes (nPOD; www.nanotomy.org). Nanotomy allows analyses of complete donor islets with up to macromolecular resolution. Anomalies we found in type 1 diabetes included (i) an increase of `intermediate cells' containing granules resembling those of exocrine zymogen and endocrine hormone secreting cells; and (ii) elevated presence of innate immune cells. These are our first results of mining the database and support recent findings that suggest that type 1 diabetes includes abnormalities in the exocrine pancreas that may induce endocrine cellular stress as a trigger for autoimmunity.},
issn={2041-1723},
doi={10.1038/s41467-020-16287-5},
url={https://doi.org/10.1038/s41467-020-16287-5}
}

@Article{Maimets2016,
author={Maimets, Martti
and Rocchi, Cecilia
and Bron, Reinier
and Pringle, Sarah
and Kuipers, Jeroen
and Giepmans, Ben N.G.
and Vries, Robert G.J.
and Clevers, Hans
and de Haan, Gerald
and van Os, Ronald
and Coppes, Robert P.},
title={Long-Term In{\&}{\#}xa0;Vitro Expansion of Salivary Gland Stem Cells Driven by Wnt Signals},
journal={Stem Cell Reports},
year={2016},
month={Jan},
day={12},
publisher={Elsevier},
volume={6},
number={1},
pages={150-162},
issn={2213-6711},
doi={10.1016/j.stemcr.2015.11.009},
url={https://doi.org/10.1016/j.stemcr.2015.11.009}
}

@article{Sokol2015,
title = {Large-Scale Electron Microscopy Maps of Patient Skin and Mucosa Provide Insight into Pathogenesis of Blistering Diseases},
journal = {Journal of Investigative Dermatology},
volume = {135},
number = {7},
pages = {1763-1770},
year = {2015},
issn = {0022-202X},
doi = {https://doi.org/10.1038/jid.2015.109},
url = {https://www.sciencedirect.com/science/article/pii/S0022202X1537322X},
author = {Ena Sokol and Duco Kramer and Gilles F.H. Diercks and Jeroen Kuipers and Marcel F. Jonkman and Hendri H. Pas and Ben N.G. Giepmans},
abstract = {Large-scale electron microscopy (“nanotomy”) allows straight forward ultrastructural examination of tissue, cells, organelles, and macromolecules in a single data set. Such data set equals thousands of conventional electron microscopy images and is freely accessible (www.nanotomy.org). The software allows zooming in and out of the image from total overview to nanometer scale resolution in a ‘Google Earth’ approach. We studied the life-threatening human autoimmune blistering disease pemphigus, using nanotomy. The pathomechanism of cell–cell separation (acantholysis) that underlies the blistering is poorly understood. Ultrastructural examination of pemphigus tissue revealed previously unreported findings: (i) the presence of double-membrane structures between cells in all pemphigus types; (ii) the absence of desmosomes around spontaneous blisters in pemphigus foliaceus (PF); (iii) lower level blistering in PF when force induced; and (iv) intercellular widening at non-acantholytic cell layers. Thus, nanotomy delivers open-source electron microscopic maps of patient tissue, which can be analyzed for additional anomalies from any computer by experts from different fields.}
}

@article{Capala2015,
    doi = {10.1371/journal.pone.0128585},
    author = {Capala, Marta E. and Maat, Henny and Bonardi, Francesco and van den Boom, Vincent and Kuipers, Jeroen and Vellenga, Edo and Giepmans, Ben N. G. and Schuringa, Jan Jacob},
    journal = {PLOS ONE},
    publisher = {Public Library of Science},
    title = {Mitochondrial Dysfunction in Human Leukemic Stem/Progenitor Cells upon Loss of RAC2},
    year = {2015},
    month = {05},
    volume = {10},
    url = {https://doi.org/10.1371/journal.pone.0128585},
    pages = {1-20},
    abstract = {Leukemic stem cells (LSCs) reside within bone marrow niches that maintain their relatively quiescent state and convey resistance to conventional treatment. Many of the microenvironmental signals converge on RAC GTPases. Although it has become clear that RAC proteins fulfill important roles in the hematopoietic compartment, little has been revealed about the downstream effectors and molecular mechanisms. We observed that in BCR-ABL-transduced human hematopoietic stem/progenitor cells (HSPCs) depletion of RAC2 but not RAC1 induced a marked and immediate decrease in proliferation, progenitor frequency, cobblestone formation and replating capacity, indicative for reduced self-renewal. Cell cycle analyses showed reduced cell cycle activity in RAC2-depleted BCR-ABL leukemic cobblestones coinciding with an increased apoptosis. Moreover, a decrease in mitochondrial membrane potential was observed upon RAC2 downregulation, paralleled by severe mitochondrial ultrastructural malformations as determined by automated electron microscopy. Proteome analysis revealed that RAC2 specifically interacted with a set of mitochondrial proteins including mitochondrial transport proteins SAM50 and Metaxin 1, and interactions were confirmed in independent co-immunoprecipitation studies. Downregulation of SAM50 also impaired the proliferation and replating capacity of BCR-ABL-expressing cells, again associated with a decreased mitochondrial membrane potential. Taken together, these data suggest an important role for RAC2 in maintaining mitochondrial integrity.},
    number = {5}
}

@article{deVos2016,
    doi = {10.1371/journal.pone.0147992},
    author = {de Vos, Paul and Smink, Alexandra M. and Paredes, Genaro and Lakey, Jonathan R. T. and Kuipers, Jeroen and Giepmans, Ben N. G. and de Haan, Bart J. and Faas, Marijke M.},
    journal = {PLOS ONE},
    publisher = {Public Library of Science},
    title = {Enzymes for Pancreatic Islet Isolation Impact Chemokine-Production and Polarization of Insulin-Producing β-Cells with Reduced Functional Survival of Immunoisolated Rat Islet-Allografts as a Consequence},
    year = {2016},
    month = {01},
    volume = {11},
    url = {https://doi.org/10.1371/journal.pone.0147992},
    pages = {1-18},
    abstract = {The primary aim of this study was to determine whether normal variations in enzyme-activities of collagenases applied for rat-islet isolation impact longevity of encapsulated islet grafts. Also we studied the functional and immunological properties of rat islets isolated with different enzyme preparations to determine whether this impacts these parameters. Rat-islets were isolated from the pancreas with two different collagenases with commonly accepted collagenase, neutral protease, and clostripain activities. Islets had a similar and acceptable glucose-induced insulin-release profile but a profound statistical significant difference in production of the chemokines IP-10 and Gro-α. The islets were studied with nanotomy which is an EM-based technology for unbiased study of ultrastructural features of islets such as cell-cell contacts, endocrine-cell condition, ER stress, mitochondrial conditions, and cell polarization. The islet-batch with higher chemokine-production had a lower amount of polarized insulin-producing β-cells. All islets had more intercellular spaces and less interconnected areas with tight cell-cell junctions when compared to islets in the pancreas. Islet-graft function was studied by implanting encapsulated and free islet grafts in rat recipients. Alginate-based encapsulated grafts isolated with the enzyme-lot inducing higher chemokine production and lower polarization survived for a two-fold shorter period of time. The lower survival-time of the encapsulated grafts was correlated with a higher influx of inflammatory cells at 7 days after implantation. Islets from the same two batches transplanted as free unencapsulated-graft, did not show any difference in survival or function in vivo. Lack of insight in factors contributing to the current lab-to-lab variation in longevity of encapsulated islet-grafts is considered to be a threat for clinical application. Our data suggest that seemingly minor variations in activity of enzymes applied for islet-isolation might contribute to longevity-variations of immunoisolated islet-grafts.},
    number = {1}
}

@article{Carsten2018,
title = {Modern field emission scanning electron microscopy provides new perspectives for imaging kidney ultrastructure},
journal = {Kidney International},
volume = {94},
number = {3},
pages = {625-631},
year = {2018},
issn = {0085-2538},
doi = {https://doi.org/10.1016/j.kint.2018.05.017},
url = {https://www.sciencedirect.com/science/article/pii/S0085253818303910},
author = {Carsten Dittmayer and Eckhard Völcker and Irene Wacker and Rasmus R. Schröder and Sebastian Bachmann},
keywords = {array tomography, correlative light-electron microscopy, kidney ultrastructure, nanotomy, scanning electron microscopy},
abstract = {Recent progress in electron microscopy (EM) techniques has opened new pathways to study renal tissue in research and pathology. Modern field emission scanning EM may be utilized to scan thin sections of resin-embedded tissue mounted on a conductive support. Here we sought to achieve automated imaging without the typical limitations of transmission EM with equivalent or superior quality. Extended areas of tissue were either imaged in two (nanotomy) or in three dimensions (volume EM) by serial-section-based array tomography. Single-beam and fast-recording multi-beam field emission scanning EM instruments were compared using perfusion-fixed rodent kidneys. High-resolution scans produced excellent images of tissue, cells, and organelles down to macromolecular complexes. Digital stitching of image tiles in both modes allowed seamless Google Earth–like zooming from overview to regions of interest at the nanoscale. Large datasets were created that can be rapidly shared between scientists of different disciplines or pathologists using open source software. Three-dimensional array tomography of thin sections was followed by segmentation to visualize selected features in a large volume. Furthermore, correlative light-EM enabled the identification of functional information in a structural context. Thus, limitations in biomedical transmission EM can be overcome by introducing field emission scanning EM-based technology that permits high-quality, large field-of-view nanotomy, volume EM, and correlative light-EM modes. Advantages of virtual microscopy in clinical and experimental nephrology are illustrated.}
}

@Article{deVrij2021,
author={de Vrij, Edwin L.
and Bouma, Hjalmar R.
and Goris, Maaike
and Weerman, Ulrike
and de Groot, Anne P.
and Kuipers, Jeroen
and Giepmans, Ben N. G.
and Henning, Robert H.},
title={Reversible thrombocytopenia during hibernation originates from storage and release of platelets in liver sinusoids},
journal={Journal of Comparative Physiology B},
year={2021},
month={May},
day={01},
volume={191},
number={3},
pages={603-615},
abstract={Immobility is a risk factor for thrombosis due to low blood flow, which may result in activation of the coagulation system, recruitment of platelets and clot formation. Nevertheless, hibernating animals---who endure lengthy periods of immobility---do not show signs of thrombosis throughout or after hibernation. One of the adaptations of hemostasis in hibernators consists of a rapidly reversible reduction of the number of circulating platelets during torpor, i.e., the hibernation phase with reduction of metabolic rate, low blood flow and immobility. It is unknown whether these platelet dynamics in hibernating hamsters originate from storage and release, as suggested for ground squirrel, or from breakdown and de novo synthesis. A reduction in detaching forces due to low blood flow can induce reversible adhesion of platelets to the vessel wall, which is called margination. Here, we hypothesized that storage-and-release by margination to the vessel wall induces reversible thrombocytopenia in torpor. Therefore, we transfused labeled platelets in hibernating Syrian hamster (Mesocricetus auratus) and platelets were analyzed using flow cytometry and electron microscopy. The half-life of labeled platelets was extended from 20 to 30 h in hibernating animals compared to non-hibernating control hamsters. More than 90{\%} of labeled platelets were cleared from the circulation during torpor, followed by emergence during arousal which supports storage-and-release to govern thrombocytopenia in torpor. Furthermore, the low number of immature platelets, plasma level of interleukin-1$\alpha$ and normal numbers of megakaryocytes in bone marrow make platelet synthesis or megakaryocyte rupture via interleukin-1$\alpha$ unlikely to account for the recovery of platelet counts upon arousal. Finally, using large-scale electron microscopy we revealed platelets to accumulate in liver sinusoids, but not in spleen or lung, during torpor. These results thus demonstrate that platelet dynamics in hibernation are caused by storage and release of platelets, most likely by margination to the vessel wall in liver sinusoids. Translating the molecular mechanisms that govern platelet retention in the liver, may be of major relevance for hemostatic management in (accidental) hypothermia and for the development of novel anti-thrombotic strategies.},
issn={1432-136X},
doi={10.1007/s00360-021-01351-3},
url={https://doi.org/10.1007/s00360-021-01351-3}
}

@Article{Siegert2021,
author={Siegert, Elise
and Uruha, Akinori
and Goebel, Hans-Hilmar
and Preu{\ss}e, Corinna
and Casteleyn, Vincent
and Kleefeld, Felix
and Alten, Rieke
and Burmester, Gerd R.
and Schneider, Udo
and H{\"o}ppner, Jakob
and Hahn, Kathrin
and Dittmayer, Carsten
and Stenzel, Werner},
title={Systemic sclerosis-associated myositis features minimal inflammation and characteristic capillary pathology},
journal={Acta Neuropathologica},
year={2021},
month={Jun},
day={01},
volume={141},
number={6},
pages={917-927},
abstract={Systemic sclerosis represents a chronic connective tissue disease featuring fibrosis, vasculopathy and autoimmunity, affecting skin, multiple internal organs, and skeletal muscles. The vasculopathy is considered obliterative, but its pathogenesis is still poorly understood. This may partially be due to limitations of conventional transmission electron microscopy previously being conducted only in single patients. The aim of our study was therefore to precisely characterize immune inflammatory features and capillary morphology of systemic sclerosis patients suffering from muscle weakness. In this study, we identified 18 individuals who underwent muscle biopsy because of muscle weakness and myalgia in a cohort of 367 systemic sclerosis patients. We performed detailed conventional and immunohistochemical analysis and large-scale electron microscopy by digitizing entire sections for in-depth ultrastructural analysis. Muscle biopsies of 12 of these 18 patients (67{\%}) presented minimal features of myositis but clear capillary alteration, which we termed minimal myositis with capillary pathology (MMCP). Our study provides novel findings in systemic sclerosis-associated myositis. First, we identified a characteristic and specific morphological pattern termed MMCP in 67{\%} of the cases, while the other 33{\%} feature alterations characteristic of other overlap syndromes. This is also reflected by a relatively homogeneous clinical picture among MMCP patients. They have milder disease with little muscle weakness and a low prevalence of interstitial lung disease (20{\%}) and diffuse skin involvement (10{\%}) and no cases of either pulmonary arterial hypertension or renal crisis. Second, large-scale electron microscopy, introducing a new level of precision in ultrastructural analysis, revealed a characteristic capillary morphology with basement membrane thickening and reduplications, endothelial activation and pericyte proliferation. We provide open-access pan-and-zoom analysis to our datasets, enabling critical discussion and data mining. We clearly highlight characteristic capillary pathology in skeletal muscles of systemic sclerosis patients.},
issn={1432-0533},
doi={10.1007/s00401-021-02305-3},
url={https://doi.org/10.1007/s00401-021-02305-3}
}

@Article{Dane2013,
author={Dane, Martijn J.C.
and van den Berg, Bernard M.
and Avramut, M. Cristina
and Faas, Frank G.A.
and van der Vlag, Johan
and Rops, Angelique L.W.M.M.
and Ravelli, Raimond B.G.
and Koster, Bram J.
and van Zonneveld, Anton Jan
and Vink, Hans
and Rabelink, Ton J.},
title={Glomerular Endothelial Surface Layer Acts as a Barrier against Albumin Filtration},
journal={The American Journal of Pathology},
year={2013},
month={May},
day={01},
publisher={Elsevier},
volume={182},
number={5},
pages={1532-1540},
issn={0002-9440},
doi={10.1016/j.ajpath.2013.01.049},
url={https://doi.org/10.1016/j.ajpath.2013.01.049}
}

@Article{Nijholt2021,
author={Nijholt, Kirsten T.
and Meems, Laura M. G.
and Ruifrok, Willem P. T.
and Maass, Alexander H.
and Yurista, Salva R.
and Pavez-Giani, Mario G.
and Mahmoud, Belend
and Wolters, Anouk H. G.
and van Veldhuisen, Dirk J.
and van Gilst, Wiek H.
and Sillj{\'e}, Herman H. W.
and de Boer, Rudolf A.
and Westenbrink, B. Daan},
title={The erythropoietin receptor expressed in skeletal muscle is essential for mitochondrial biogenesis and physiological exercise},
journal={Pfl{\"u}gers Archiv - European Journal of Physiology},
year={2021},
month={Aug},
day={01},
volume={473},
number={8},
pages={1301-1313},
abstract={Erythropoietin (EPO) is a haematopoietic hormone that regulates erythropoiesis, but the EPO-receptor (EpoR) is also expressed in non-haematopoietic tissues. Stimulation of the EpoR in cardiac and skeletal muscle provides protection from various forms of pathological stress, but its relevance for normal muscle physiology remains unclear. We aimed to determine the contribution of the tissue-specific EpoR to exercise-induced remodelling of cardiac and skeletal muscle. Baseline phenotyping was performed on left ventricle and m. gastrocnemius of mice that only express the EpoR in haematopoietic tissues (EpoR-tKO). Subsequently, mice were caged in the presence or absence of a running wheel for 4 weeks and exercise performance, cardiac function and histological and molecular markers for physiological adaptation were assessed. While gross morphology of both muscles was normal in EpoR-tKO mice, mitochondrial content in skeletal muscle was decreased by 50{\%}, associated with similar reductions in mitochondrial biogenesis, while mitophagy was unaltered. When subjected to exercise, EpoR-tKO mice ran slower and covered less distance than wild-type (WT) mice (5.5{\thinspace}{\textpm}{\thinspace}0.6 vs. 8.0{\thinspace}{\textpm}{\thinspace}0.4 km/day, p{\thinspace}<{\thinspace}0.01). The impaired exercise performance was paralleled by reductions in myocyte growth and angiogenesis in both muscle types. Our findings indicate that the endogenous EPO-EpoR system controls mitochondrial biogenesis in skeletal muscle. The reductions in mitochondrial content were associated with reduced exercise capacity in response to voluntary exercise, supporting a critical role for the extra-haematopoietic EpoR in exercise performance.},
issn={1432-2013},
doi={10.1007/s00424-021-02577-4},
url={https://doi.org/10.1007/s00424-021-02577-4}
}


@article {King2019,
article_type = {journal},
title = {Meiotic cellular rejuvenation is coupled to nuclear remodeling in budding yeast},
author = {King, Grant A and Goodman, Jay S and Schick, Jennifer G and Chetlapalli, Keerthana and Jorgens, Danielle M and McDonald, Kent L and Ünal, Elçin},
editor = {Mizushima, Noboru and Malhotra, Vivek and Mizushima, Noboru and Haraguchi, Tokuko and Lusk, C Patrick},
volume = 8,
year = 2019,
month = {aug},
pub_date = {2019-08-09},
pages = {e47156},
citation = {eLife 2019;8:e47156},
doi = {10.7554/eLife.47156},
url = {https://doi.org/10.7554/eLife.47156},
abstract = {Production of healthy gametes in meiosis relies on the quality control and proper distribution of both nuclear and cytoplasmic contents. Meiotic differentiation naturally eliminates age-induced cellular damage by an unknown mechanism. Using time-lapse fluorescence microscopy in budding yeast, we found that nuclear senescence factors – including protein aggregates, extrachromosomal ribosomal DNA circles, and abnormal nucleolar material – are sequestered away from chromosomes during meiosis II and subsequently eliminated. A similar sequestration and elimination process occurs for the core subunits of the nuclear pore complex in both young and aged cells. Nuclear envelope remodeling drives the formation of a membranous compartment containing the sequestered material. Importantly, de novo generation of plasma membrane is required for the sequestration event, preventing the inheritance of long-lived nucleoporins and senescence factors into the newly formed gametes. Our study uncovers a new mechanism of nuclear quality control and provides insight into its function in meiotic cellular rejuvenation.},
keywords = {meiosis, aging, nuclear pore complex, nucleolus, protein aggregation, quality control},
journal = {eLife},
issn = {2050-084X},
publisher = {eLife Sciences Publications, Ltd},
}

@article{Paivi2009,
author = {Päivi Ylä-Anttila and Helena Vihinen and Eija Jokitalo and Eeva-Liisa Eskelinen},
title = {3D tomography reveals connections between the phagophore and endoplasmic reticulum},
journal = {Autophagy},
volume = {5},
number = {8},
pages = {1180-1185},
year  = {2009},
publisher = {Taylor & Francis},
doi = {10.4161/auto.5.8.10274},
    note ={PMID: 19855179},
URL = {https://doi.org/10.4161/auto.5.8.10274},
eprint = {https://doi.org/10.4161/auto.5.8.10274}
}


@article{Yamaguchi2009,
    author = {Yamaguchi, Masashi and Okada, Hitoshi and Namiki, Yuichi},
    title = "{Smart specimen preparation for freeze substitution and serial ultrathin sectioning of yeast cells}",
    journal = {Journal of Electron Microscopy},
    volume = {58},
    number = {4},
    pages = {261-266},
    year = {2009},
    month = {03},
    abstract = "{A smart and efficient method for freeze substitution and serial sectioning of yeast cells is described. Yeast cells were placed in a single layer between two copper disks, rapidly frozen, freeze substituted and embedded in an epoxy resin. The cell layer was re-embedded by the same resin, the surface trimmed leaving 1 μm above the cell layer, and serially sectioned. The sections were collected on the two-slit grids and placed on a Formvar film mounted to cover the holes of an aluminum supporting rack. The grids were removed from the rack, stained together using a silicon tube and observed in a transmission electron microscope. The images of yeast cells observed were clear and natural, and would be useful for a detailed 3D structural analysis such as structome.}",
    issn = {0022-0744},
    doi = {10.1093/jmicro/dfp013},
    url = {https://doi.org/10.1093/jmicro/dfp013},
    eprint = {https://academic.oup.com/jmicro/article-pdf/58/4/261/5853312/dfp013.pdf},
}

@article {Joesch2016,
article_type = {journal},
title = {Reconstruction of genetically identified neurons imaged by serial-section electron microscopy},
author = {Joesch, Maximilian and Mankus, David and Yamagata, Masahito and Shahbazi, Ali and Schalek, Richard and Suissa-Peleg, Adi and Meister, Markus and Lichtman, Jeff W and Scheirer, Walter J and Sanes, Joshua R},
editor = {Harris, Kristen M},
volume = 5,
year = 2016,
month = {jul},
pub_date = {2016-07-07},
pages = {e15015},
citation = {eLife 2016;5:e15015},
doi = {10.7554/eLife.15015},
url = {https://doi.org/10.7554/eLife.15015},
abstract = {Resolving patterns of synaptic connectivity in neural circuits currently requires serial section electron microscopy. However, complete circuit reconstruction is prohibitively slow and may not be necessary for many purposes such as comparing neuronal structure and connectivity among multiple animals. Here, we present an alternative strategy, targeted reconstruction of specific neuronal types. We used viral vectors to deliver peroxidase derivatives, which catalyze production of an electron-dense tracer, to genetically identify neurons, and developed a protocol that enhances the electron-density of the labeled cells while retaining the quality of the ultrastructure. The high contrast of the marked neurons enabled two innovations that speed data acquisition: targeted high-resolution reimaging of regions selected from rapidly-acquired lower resolution reconstruction, and an unsupervised segmentation algorithm. This pipeline reduces imaging and reconstruction times by two orders of magnitude, facilitating directed inquiry of circuit motifs.},
keywords = {connectomics, peroxidase, electron microscopy, reconstruction},
journal = {eLife},
issn = {2050-084X},
publisher = {eLife Sciences Publications, Ltd},
}



@article{Schindelin2015,
author = {Schindelin, Johannes and Rueden, Curtis T. and Hiner, Mark C. and Eliceiri, Kevin W.},
title = {The ImageJ ecosystem: An open platform for biomedical image analysis},
journal = {Molecular Reproduction and Development},
volume = {82},
number = {7-8},
pages = {518-529},
doi = {https://doi.org/10.1002/mrd.22489},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/mrd.22489},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrd.22489},
abstract = {SUMMARY Technology in microscopy advances rapidly, enabling increasingly affordable, faster, and more precise quantitative biomedical imaging, which necessitates correspondingly more-advanced image processing and analysis techniques. A wide range of software is available—from commercial to academic, special-purpose to Swiss army knife, small to large—but a key characteristic of software that is suitable for scientific inquiry is its accessibility. Open-source software is ideal for scientific endeavors because it can be freely inspected, modified, and redistributed; in particular, the open-software platform ImageJ has had a huge impact on the life sciences, and continues to do so. From its inception, ImageJ has grown significantly due largely to being freely available and its vibrant and helpful user community. Scientists as diverse as interested hobbyists, technical assistants, students, scientific staff, and advanced biology researchers use ImageJ on a daily basis, and exchange knowledge via its dedicated mailing list. Uses of ImageJ range from data visualization and teaching to advanced image processing and statistical analysis. The software's extensibility continues to attract biologists at all career stages as well as computer scientists who wish to effectively implement specific image-processing algorithms. In this review, we use the ImageJ project as a case study of how open-source software fosters its suites of software tools, making multitudes of image-analysis technology easily accessible to the scientific community. We specifically explore what makes ImageJ so popular, how it impacts the life sciences, how it inspires other projects, and how it is self-influenced by coevolving projects within the ImageJ ecosystem. Mol. Reprod. Dev. 82: 518–529, 2015. © 2015 Wiley Periodicals, Inc.},
year = {2015}
}



@article{LITJENS2017,
title = {A survey on deep learning in medical image analysis},
journal = {Medical Image Analysis},
volume = {42},
pages = {60-88},
year = {2017},
issn = {1361-8415},
doi = {https://doi.org/10.1016/j.media.2017.07.005},
url = {https://www.sciencedirect.com/science/article/pii/S1361841517301135},
author = {Geert Litjens and Thijs Kooi and Babak Ehteshami Bejnordi and Arnaud Arindra Adiyoso Setio and Francesco Ciompi and Mohsen Ghafoorian and Jeroen A.W.M. {van der Laak} and Bram {van Ginneken} and Clara I. Sánchez},
keywords = {Deep learning, Convolutional neural networks, Medical imaging, Survey},
abstract = {Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 contributions to the field, most of which appeared in the last year. We survey the use of deep learning for image classification, object detection, segmentation, registration, and other tasks. Concise overviews are provided of studies per application area: neuro, retinal, pulmonary, digital pathology, breast, cardiac, abdominal, musculoskeletal. We end with a summary of the current state-of-the-art, a critical discussion of open challenges and directions for future research.}
}


@Article{deBoer2015,
author={de Boer, Pascal
and Hoogenboom, Jacob P.
and Giepmans, Ben N. G.},
title={Correlated light and electron microscopy: ultrastructure lights up!},
journal={Nature Methods},
year={2015},
month={Jun},
day={01},
volume={12},
number={6},
pages={503-513},
abstract={Correlated light and electron microscopy (CLEM) gives context to biomolecules studied with fluorescence microscopy. This Review discusses recent improvements and guides readers on probes, instrumentation and sample preparation to implement CLEM.},
issn={1548-7105},
doi={10.1038/nmeth.3400},
url={https://doi.org/10.1038/nmeth.3400}
}



@Article{Win2018,
author={Win, Khin Yadanar
and Choomchuay, Somsak
and Hamamoto, Kazuhiko
and Raveesunthornkiat, Manasanan},
title={Comparative Study on Automated Cell Nuclei Segmentation Methods for Cytology Pleural Effusion Images},
journal={Journal of Healthcare Engineering},
year={2018},
month={Sep},
day={12},
publisher={Hindawi},
volume={2018},
pages={9240389},
abstract={Automated cell nuclei segmentation is the most crucial step toward the implementation of a computer-aided diagnosis system for cancer cells. Studies on the automated analysis of cytology pleural effusion images are few because of the lack of reliable cell nuclei segmentation methods. Therefore, this paper presents a comparative study of twelve nuclei segmentation methods for cytology pleural effusion images. Each method involves three main steps: preprocessing, segmentation, and postprocessing. The preprocessing and segmentation stages help enhancing the image quality and extracting the nuclei regions from the rest of the image, respectively. The postprocessing stage helps in refining the segmented nuclei and removing false findings. The segmentation methods are quantitatively evaluated for 35 cytology images of pleural effusion by computing five performance metrics. The evaluation results show that the segmentation performances of the Otsu, k-means, mean shift, Chan{\&}{\#}x2013;Vese, and graph cut methods are 94, 94, 95, 94, and 93{\&}{\#}x0025;, respectively, with high abnormal nuclei detection rates. The average computational times per image are 1.08, 36.62, 50.18, 330, and 44.03 seconds, respectively. The findings of this study will be useful for current and potential future studies on cytology images of pleural effusion.},
issn={2040-2295},
doi={10.1155/2018/9240389},
url={https://doi.org/10.1155/2018/9240389}
}

@ARTICLE{Serag2019,
AUTHOR={Serag, Ahmed and Ion-Margineanu, Adrian and Qureshi, Hammad and McMillan, Ryan and Saint Martin, Marie-Judith and Diamond, Jim and O'Reilly, Paul and Hamilton, Peter},   
TITLE={Translational AI and Deep Learning in Diagnostic Pathology},      
JOURNAL={Frontiers in Medicine},      
VOLUME={6},      
PAGES={185},     
YEAR={2019},      
URL={https://www.frontiersin.org/article/10.3389/fmed.2019.00185},       
DOI={10.3389/fmed.2019.00185},      
ISSN={2296-858X},   
ABSTRACT={There has been an exponential growth in the application of AI in health and in pathology. This is resulting in the innovation of deep learning technologies that are specifically aimed at cellular imaging and practical applications that could transform diagnostic pathology. This paper reviews the different approaches to deep learning in pathology, the public grand challenges that have driven this innovation and a range of emerging applications in pathology. The translation of AI into clinical practice will require applications to be embedded seamlessly within digital pathology workflows, driving an integrated approach to diagnostics and providing pathologists with new tools that accelerate workflow and improve diagnostic consistency and reduce errors. The clearance of digital pathology for primary diagnosis in the US by some manufacturers provides the platform on which to deliver practical AI. AI and computational pathology will continue to mature as researchers, clinicians, industry, regulatory organizations and patient advocacy groups work together to innovate and deliver new technologies to health care providers: technologies which are better, faster, cheaper, more precise, and safe.}
}

@Article{Sadanandan2017,
author={Sadanandan, Sajith Kecheril
and Ranefall, Petter
and Le Guyader, Sylvie
and W{\"a}hlby, Carolina},
title={Automated Training of Deep Convolutional Neural Networks for Cell Segmentation},
journal={Scientific Reports},
year={2017},
month={Aug},
day={10},
volume={7},
number={1},
pages={7860},
abstract={Deep Convolutional Neural Networks (DCNN) have recently emerged as superior for many image segmentation tasks. The DCNN performance is however heavily dependent on the availability of large amounts of problem-specific training samples. Here we show that DCNNs trained on ground truth created automatically using fluorescently labeled cells, perform similar to manual annotations.},
issn={2045-2322},
doi={10.1038/s41598-017-07599-6},
url={https://doi.org/10.1038/s41598-017-07599-6}
}

@article{Karabag2020,
    doi = {10.1371/journal.pone.0230605},
    author = {Karabağ, Cefa and Jones, Martin L. and Peddie, Christopher J. and Weston, Anne E. and Collinson, Lucy M. and Reyes-Aldasoro, Constantino Carlos},
    journal = {PLOS ONE},
    publisher = {Public Library of Science},
    title = {Semantic segmentation of HeLa cells: An objective comparison between one traditional algorithm and four deep-learning architectures},
    year = {2020},
    month = {10},
    volume = {15},
    url = {https://doi.org/10.1371/journal.pone.0230605},
    pages = {1-21},
    abstract = {The quantitative study of cell morphology is of great importance as the structure and condition of cells and their structures can be related to conditions of health or disease. The first step towards that, is the accurate segmentation of cell structures. In this work, we compare five approaches, one traditional and four deep-learning, for the semantic segmentation of the nuclear envelope of cervical cancer cells commonly known as HeLa cells. Images of a HeLa cancer cell were semantically segmented with one traditional image-processing algorithm and four three deep learning architectures: VGG16, ResNet18, Inception-ResNet-v2, and U-Net. Three hundred slices, each 2000 × 2000 pixels, of a HeLa Cell were acquired with Serial Block Face Scanning Electron Microscopy. The first three deep learning architectures were pre-trained with ImageNet and then fine-tuned with transfer learning. The U-Net architecture was trained from scratch with 36, 000 training images and labels of size 128 × 128. The image-processing algorithm followed a pipeline of several traditional steps like edge detection, dilation and morphological operators. The algorithms were compared by measuring pixel-based segmentation accuracy and Jaccard index against a labelled ground truth. The results indicated a superior performance of the traditional algorithm (Accuracy = 99%, Jaccard = 93%) over the deep learning architectures: VGG16 (93%, 90%), ResNet18 (94%, 88%), Inception-ResNet-v2 (94%, 89%), and U-Net (92%, 56%).},
    number = {10},

}


@Article{Karabag2021,
AUTHOR = {Karabağ, Cefa and Jones, Martin L. and Reyes-Aldasoro, Constantino Carlos},
TITLE = {Volumetric Semantic Instance Segmentation of the Plasma Membrane of HeLa Cells},
JOURNAL = {Journal of Imaging},
VOLUME = {7},
YEAR = {2021},
NUMBER = {6},
ARTICLE-NUMBER = {93},
URL = {https://www.mdpi.com/2313-433X/7/6/93},
ISSN = {2313-433X},
ABSTRACT = {In this work, an unsupervised volumetric semantic instance segmentation of the plasma membrane of HeLa cells as observed with serial block face scanning electron microscopy is described. The resin background of the images was segmented at different slices of a 3D stack of 518 slices with 8192 × 8192 pixels each. The background was used to create a distance map, which helped identify and rank the cells by their size at each slice. The centroids of the cells detected at different slices were linked to identify them as a single cell that spanned a number of slices. A subset of these cells, i.e., the largest ones and those not close to the edges were selected for further processing. The selected cells were then automatically cropped to smaller regions of interest of 2000 × 2000 × 300 voxels that were treated as cell instances. Then, for each of these volumes, the nucleus was segmented, and the cell was separated from any neighbouring cells through a series of traditional image processing steps that followed the plasma membrane. The segmentation process was repeated for all the regions of interest previously selected. For one cell for which the ground truth was available, the algorithm provided excellent results in Accuracy (AC) and the Jaccard similarity Index (JI): nucleus: JI =0.9665, AC =0.9975, cell including nucleus JI =0.8711, AC =0.9655, cell excluding nucleus JI =0.8094, AC =0.9629. A limitation of the algorithm for the plasma membrane segmentation was the presence of background. In samples with tightly packed cells, this may not be available. When tested for these conditions, the segmentation of the nuclear envelope was still possible. All the code and data were released openly through GitHub, Zenodo and EMPIAR.},
DOI = {10.3390/jimaging7060093}
}





@INPROCEEDINGS{Oztel2017, 
 author={Oztel, Ismail and Yolcu, Gozde and Ersoy, Ilker and White, Tommi and Bunyak, Filiz},  booktitle={2017 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)},   title={Mitochondria segmentation in electron microscopy volumes using deep convolutional neural network},   year={2017},  volume={},  number={},  pages={1195-1200},  doi={10.1109/BIBM.2017.8217827}}

@ARTICLE{Xiao2018,
AUTHOR={Xiao, Chi and Chen, Xi and Li, Weifu and Li, Linlin and Wang, Lu and Xie, Qiwei and Han, Hua},   
TITLE={Automatic Mitochondria Segmentation for EM Data Using a 3D Supervised Convolutional Network},      
JOURNAL={Frontiers in Neuroanatomy},      
VOLUME={12},      
PAGES={92},     
YEAR={2018},      
URL={https://www.frontiersin.org/article/10.3389/fnana.2018.00092},       
DOI={10.3389/fnana.2018.00092},      
ISSN={1662-5129},   
   
ABSTRACT={Recent studies have supported the relation between mitochondrial functions and degenerative disorders related to ageing, such as Alzheimer's and Parkinson's diseases. Since these studies have exposed the need for detailed and high-resolution analysis of physical alterations in mitochondria, it is necessary to be able to perform segmentation and 3D reconstruction of mitochondria. However, due to the variety of mitochondrial structures, automated mitochondria segmentation and reconstruction in electron microscopy (EM) images have proven to be a difficult and challenging task. This paper puts forward an effective and automated pipeline based on deep learning to realize mitochondria segmentation in different EM images. The proposed pipeline consists of three parts: (1) utilizing image registration and histogram equalization as image pre-processing steps to maintain the consistency of the dataset; (2) proposing an effective approach for 3D mitochondria segmentation based on a volumetric, residual convolutional and deeply supervised network; and (3) employing a 3D connection method to obtain the relationship of mitochondria and displaying the 3D reconstruction results. To our knowledge, we are the first researchers to utilize a 3D fully residual convolutional network with a deeply supervised strategy to improve the accuracy of mitochondria segmentation. The experimental results on anisotropic and isotropic EM volumes demonstrate the effectiveness of our method, and the Jaccard index of our segmentation (91.8% in anisotropy, 90.0% in isotropy) and F1 score of detection (92.2% in anisotropy, 90.9% in isotropy) suggest that our approach achieved state-of-the-art results. Our fully automated pipeline contributes to the development of neuroscience by providing neurologists with a rapid approach for obtaining rich mitochondria statistics and helping them elucidate the mechanism and function of mitochondria.}
}


@INPROCEEDINGS{Roels2017,  
author={Roels, Joris and De Vylder, Jonas and Aelterman, Jan and Saeys, Yvan and Philips, Wilfried},  booktitle={2017 IEEE 14th International Symposium on Biomedical Imaging (ISBI 2017)},   title={Convolutional neural network pruning to accelerate membrane segmentation in electron microscopy},   year={2017},  volume={},  number={},  pages={633-637},  doi={10.1109/ISBI.2017.7950600}}

@Article{Barisoni2020,
author={Barisoni, Laura
and Lafata, Kyle J.
and Hewitt, Stephen M.
and Madabhushi, Anant
and Balis, Ulysses G. J.},
title={Digital pathology and computational image analysis in nephropathology},
journal={Nature Reviews Nephrology},
year={2020},
month={Nov},
day={01},
volume={16},
number={11},
pages={669-685},
abstract={The emergence of digital pathology --- an image-based environment for the acquisition, management and interpretation of pathology information supported by computational techniques for data extraction and analysis --- is changing the pathology ecosystem. In particular, by virtue of our new-found ability to generate and curate digital libraries, the field of machine vision can now be effectively applied to histopathological subject matter by individuals who do not have deep expertise in machine vision techniques. Although these novel approaches have already advanced the detection, classification, and prognostication of diseases in the fields of radiology and oncology, renal pathology is just entering the digital era, with the establishment of consortia and digital pathology repositories for the collection, analysis and integration of pathology data with other domains. The development of machine-learning approaches for the extraction of information from image data, allows for tissue interrogation in a way that was not previously possible. The application of these novel tools are placing pathology centre stage in the process of defining new, integrated, biologically and clinically homogeneous disease categories, to identify patients at risk of progression, and shifting current paradigms for the treatment and prevention of kidney diseases.},
issn={1759-507X},
doi={10.1038/s41581-020-0321-6},
url={https://doi.org/10.1038/s41581-020-0321-6}
}



@article{Min2016,
    author = {Min, Seonwoo and Lee, Byunghan and Yoon, Sungroh},
    title = "{Deep learning in bioinformatics}",
    journal = {Briefings in Bioinformatics},
    volume = {18},
    number = {5},
    pages = {851-869},
    year = {2016},
    month = {07},
    abstract = "{In the era of big data, transformation of biomedical big data into valuable knowledge has been one of the most important challenges in bioinformatics. Deep learning has advanced rapidly since the early 2000s and now demonstrates state-of-the-art performance in various fields. Accordingly, application of deep learning in bioinformatics to gain insight from data has been emphasized in both academia and industry. Here, we review deep learning in bioinformatics, presenting examples of current research. To provide a useful and comprehensive perspective, we categorize research both by the bioinformatics domain (i.e. omics, biomedical imaging, biomedical signal processing) and deep learning architecture (i.e. deep neural networks, convolutional neural networks, recurrent neural networks, emergent architectures) and present brief descriptions of each study. Additionally, we discuss theoretical and practical issues of deep learning in bioinformatics and suggest future research directions. We believe that this review will provide valuable insights and serve as a starting point for researchers to apply deep learning approaches in their bioinformatics studies.}",
    issn = {1467-5463},
    doi = {10.1093/bib/bbw068},
    url = {https://doi.org/10.1093/bib/bbw068},
    eprint = {https://academic.oup.com/bib/article-pdf/18/5/851/25581102/bbw068.pdf},
}





@article{Goubran2020,
author = {Goubran, Maged and Ntiri, Emmanuel Edward and Akhavein, Hassan and Holmes, Melissa and Nestor, Sean and Ramirez, Joel and Adamo, Sabrina and Ozzoude, Miracle and Scott, Christopher and Gao, Fuqiang and Martel, Anne and Swardfager, Walter and Masellis, Mario and Swartz, Richard and MacIntosh, Bradley and Black, Sandra E.},
title = {Hippocampal segmentation for brains with extensive atrophy using three-dimensional convolutional neural networks},
journal = {Human Brain Mapping},
volume = {41},
number = {2},
pages = {291-308},
keywords = {brain atrophy, convolutional neural networks, deep learning, dementia, hippocampus, image segmentation},
doi = {https://doi.org/10.1002/hbm.24811},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/hbm.24811},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/hbm.24811},
abstract = {Abstract Hippocampal volumetry is a critical biomarker of aging and dementia, and it is widely used as a predictor of cognitive performance; however, automated hippocampal segmentation methods are limited because the algorithms are (a) not publicly available, (b) subject to error with significant brain atrophy, cerebrovascular disease and lesions, and/or (c) computationally expensive or require parameter tuning. In this study, we trained a 3D convolutional neural network using 259 bilateral manually delineated segmentations collected from three studies, acquired at multiple sites on different scanners with variable protocols. Our training dataset consisted of elderly cases difficult to segment due to extensive atrophy, vascular disease, and lesions. Our algorithm, (HippMapp3r), was validated against four other publicly available state-of-the-art techniques (HippoDeep, FreeSurfer, SBHV, volBrain, and FIRST). HippMapp3r outperformed the other techniques on all three metrics, generating an average Dice of 0.89 and a correlation coefficient of 0.95. It was two orders of magnitude faster than some of the tested techniques. Further validation was performed on 200 subjects from two other disease populations (frontotemporal dementia and vascular cognitive impairment), highlighting our method's low outlier rate. We finally tested the methods on real and simulated “clinical adversarial” cases to study their robustness to corrupt, low-quality scans. The pipeline and models are available at: https://hippmapp3r.readthedocs.ioto facilitate the study of the hippocampus in large multisite studies.},
year = {2020}
}



@ARTICLE{Zhao2020,
AUTHOR={Zhao, Peng and Zhang, Jindi and Fang, Weijia and Deng, Shuiguang},   
TITLE={SCAU-Net: Spatial-Channel Attention U-Net for Gland Segmentation},      
JOURNAL={Frontiers in Bioengineering and Biotechnology},      
VOLUME={8},      
PAGES={670},     
YEAR={2020},      
URL={https://www.frontiersin.org/article/10.3389/fbioe.2020.00670},       
DOI={10.3389/fbioe.2020.00670},      
ISSN={2296-4185},   
   
ABSTRACT={With the development of medical technology, image semantic segmentation is of great significance for morphological analysis, quantification, and diagnosis of human tissues. However, manual detection and segmentation is a time-consuming task. Especially for biomedical image, only experts are able to identify tissues and mark their contours. In recent years, the development of deep learning has greatly improved the accuracy of computer automatic segmentation. This paper proposes a deep learning image semantic segmentation network named Spatial-Channel Attention U-Net (SCAU-Net) based on current research status of medical image. SCAU-Net has an encoder-decoder-style symmetrical structure integrated with spatial and channel attention as plug-and-play modules. The main idea is to enhance local related features and restrain irrelevant features at the spatial and channel levels. Experiments on the gland dataset GlaS and CRAG show that the proposed SCAU-Net model is superior to the classic U-Net model in image segmentation task, with 1% improvement on Dice score and 1.5% improvement on Jaccard score.}
}


@article{Liqun2019,
author = {Liqun Lin and Weixing Wang and Bolin Chen},
title ={Leukocyte recognition with convolutional neural network},
journal = {Journal of Algorithms \& Computational Technology},
volume = {13},
number = {},
pages = {1748301818813322},
year = {2019},
doi = {10.1177/1748301818813322},
URL = { 
        https://doi.org/10.1177/1748301818813322
},
eprint = { 
        https://doi.org/10.1177/1748301818813322
}
}

@Article{Datta2021,
author={Datta, Abhik
and Ng, Kian Fong
and Balakrishnan, Deepan
and Ding, Melissa
and Chee, See Wee
and Ban, Yvonne
and Shi, Jian
and Loh, N. Duane},
title={A data reduction and compression description for high throughput time-resolved electron microscopy},
journal={Nature Communications},
year={2021},
month={Jan},
day={28},
volume={12},
number={1},
pages={664},
abstract={Fast, direct electron detectors have significantly improved the spatio-temporal resolution of electron microscopy movies. Preserving both spatial and temporal resolution in extended observations, however, requires storing prohibitively large amounts of data. Here, we describe an efficient and flexible data reduction and compression scheme (ReCoDe) that retains both spatial and temporal resolution by preserving individual electron events. Running ReCoDe on a workstation we demonstrate on-the-fly reduction and compression of raw data streaming off a detector at 3 GB/s, for hours of uninterrupted data collection. The output was 100-fold smaller than the raw data and saved directly onto network-attached storage drives over a 10 GbE connection. We discuss calibration techniques that support electron detection and counting (e.g., estimate electron backscattering rates, false positive rates, and data compressibility), and novel data analysis methods enabled by ReCoDe (e.g., recalibration of data post acquisition, and accurate estimation of coincidence loss).},
issn={2041-1723},
doi={10.1038/s41467-020-20694-z},
url={https://doi.org/10.1038/s41467-020-20694-z}
}

@Article{Orloff2013,
author={Orloff, David N.
and Iwasa, Janet H.
and Martone, Maryann E.
and Ellisman, Mark H.
and Kane, Caroline M.},
title={The cell: an image library-CCDB: a curated repository of microscopy data},
journal={Nucleic Acids Research},
year={2013},
month={Jan},
day={01},
volume={41},
number={D1},
pages={D1241-D1250},
abstract={The cell: an image library-CCDB (CIL-CCDB) (http://www.cellimagelibrary.org) is a searchable database and archive of cellular images. As a repository for microscopy data, it accepts all forms of cell imaging from light and electron microscopy, including multi-dimensional images, Z- and time stacks in a broad variety of raw-data formats, as well as movies and animations. The software design of CIL-CCDB was intentionally designed to allow easy incorporation of new technologies and image formats as they are developed. Currently, CIL-CCDB contains over 9250 images from 358 different species. Images are evaluated for quality and annotated with terms from 14 different ontologies in 16 different fields as well as a basic description and technical details. Since its public launch on 9 August 2010, it has been designed to serve as not only an archive but also an active site for researchers and educators.},
issn={0305-1048},
doi={10.1093/nar/gks1257},
url={https://doi.org/10.1093/nar/gks1257}
}



@Article{Hammer2021,
author={Hammer, Mathias
and Huisman, Maximiliaan
and Rigano, Alessandro
and Boehm, Ulrike
and Chambers, James J.
and Gaudreault, Nathalie
and North, Alison J.
and Pimentel, Jaime A.
and Sudar, Damir
and Bajcsy, Peter
and Brown, Claire M.
and Corbett, Alexander D.
and Faklaris, Orestis
and Lacoste, Judith
and Laude, Alex
and Nelson, Glyn
and Nitschke, Roland
and Farzam, Farzin
and Smith, Carlas S.
and Grunwald, David
and Strambio-De-Castillia, Caterina},
title={Towards community-driven metadata standards for light microscopy: tiered specifications extending the OME model},
journal={Nature Methods},
year={2021},
month={Dec},
day={01},
volume={18},
number={12},
pages={1427-1440},
abstract={Rigorous record-keeping and quality control are required to ensure the quality, reproducibility and value of imaging data. The 4DN Initiative and BINA here propose light Microscopy Metadata Specifications that extend the OME Data Model, scale with experimental intent and complexity, and make it possible for scientists to create comprehensive records of imaging experiments.},
issn={1548-7105},
doi={10.1038/s41592-021-01327-9},
url={https://doi.org/10.1038/s41592-021-01327-9}
}



@Article{Moore2021,
author={Moore, Josh
and Allan, Chris
and Besson, Sebastien
and Burel, Jean-Marie
and Diel, Erin
and Gault, David
and Kozlowski, Kevin
and Lindner, Dominik
and Linkert, Melissa
and Manz, Trevor
and Moore, Will
and Pape, Constantin
and Tischer, Christian
and Swedlow, Jason R.},
title={OME-NGFF: scalable format strategies for interoperable bioimaging data},
journal={bioRxiv},
year={2021},
month={Jan},
day={01},
pages={2021.03.31.437929},
abstract={Biological imaging is one of the most innovative fields in the modern biological sciences. New imaging modalities, probes, and analysis tools appear every few months and often prove decisive for enabling new directions in scientific discovery. One feature of this dynamic field is the need to capture new types of data and data structures. While there is a strong drive to make scientific data Findable, Accessible, Interoperable and Reproducible (FAIR 1), the rapid rate of innovation in imaging impedes the unification and adoption of standardized data formats. Despite this, the opportunities for sharing and integrating bioimaging data and, in particular, linking these data to other ``omics'' datasets have never been greater. Therefore, to every extent possible, increasing ``FAIRness'' of bioimaging data is critical for maximizing scientific value, as well as for promoting openness and integrity.In the absence of a common, FAIR format, two approaches have emerged to provide access to bioimaging data: translation and conversion. On-the-fly translation produces a transient representation of bioimage metadata and binary data but must be repeated on each use. In contrast, conversion produces a permanent copy of the data, ideally in an open format that makes the data more accessible and improves performance and parallelization in reads and writes. Both approaches have been implemented successfully in the bioimaging community but both have limitations. At cloud-scale, those shortcomings limit scientific analysis and the sharing of results. We introduce here next-generation file formats (NGFF) as a solution to these challenges.Competing Interest StatementCA, ED, KK, ML and JRS are all affiliated with Glencoe Software, Inc which builds imaging data management solutions for acadmic and industrial research and development organisations.},
doi={10.1101/2021.03.31.437929},
url={http://biorxiv.org/content/early/2021/04/13/2021.03.31.437929.abstract},
url={https://doi.org/10.1101/2021.03.31.437929}
}



@Article{Jiang2021R,
author={Jiang, Yi
and Li, Linlin
and Chen, Xi
and Liu, Jiazheng
and Yuan, Jingbin
and Xie, Qiwei
and Han, Hua},
title={Three-dimensional ATUM-SEM reconstruction and analysis of hepatic endoplasmic reticulum‒organelle interactions},
journal={Journal of Molecular Cell Biology},
year={2021},
month={Sep},
day={01},
volume={13},
number={9},
pages={636-645},
abstract={The endoplasmic reticulum (ER) is a contiguous and complicated membrane network in eukaryotic cells, and membrane contact sites (MCSs) between the ER and other organelles perform vital cellular functions, including lipid homeostasis, metabolite exchange, calcium level regulation, and organelle division. Here, we establish a whole pipeline to reconstruct all ER, mitochondria, lipid droplets, lysosomes, peroxisomes, and nuclei by automated tape-collecting ultramicrotome scanning electron microscopy and deep learning techniques, which generates an unprecedented 3D model for mapping liver samples. Furthermore, the morphology of various organelles and the MCSs between the ER and other organelles are systematically analyzed. We found that the ER presents with predominantly flat cisternae and is knitted tightly all throughout the intracellular space and around other organelles. In addition, the ER has a smaller volume-to-membrane surface area ratio than other organelles, which suggests that the ER could be more suited for functions that require a large membrane surface area. Our data also indicate that ER‒mitochondria contacts are particularly abundant, especially for branched mitochondria. Our study provides 3D reconstructions of various organelles in liver samples together with important fundamental information for biochemical and functional studies in the liver.},
issn={1759-4685},
doi={10.1093/jmcb/mjab032},
url={https://doi.org/10.1093/jmcb/mjab032}
}



@article{Jiang2021,
    author = {Jiang, Yi and Li, Linlin and Chen, Xi and Liu, Jiazheng and Yuan, Jingbin and Xie, Qiwei and Han, Hua},
    title = "{Three-dimensional ATUM-SEM reconstruction and analysis of hepatic endoplasmic reticulum‒organelle interactions}",
    journal = {Journal of Molecular Cell Biology},
    year = {2021},
    month = {05},
    abstract = "{The endoplasmic reticulum (ER) is a contiguous and complicated membrane network in eukaryotic cells, and membrane contact sites (MCSs) between the ER and other organelles perform vital cellular functions, including lipid homeostasis, metabolite exchange, calcium level regulation, and organelle division. Here, we establish a whole pipeline to reconstruct all ER, mitochondria, lipid droplets, lysosomes, peroxisomes, and nuclei by automated tape-collecting ultramicrotome scanning electron microscopy and deep learning techniques, which generates an unprecedented 3D model for mapping liver samples. Furthermore, the morphology of various organelles and the MCSs between the ER and other organelles are systematically analyzed. We found that the ER presents with predominantly flat cisternae and is knitted tightly all throughout the intracellular space and around other organelles. In addition, the ER has a smaller volume-to-membrane surface area ratio than other organelles, which suggests that the ER could be more suited for functions that require a large membrane surface area. Our data also indicate that ER‒mitochondria contacts are particularly abundant, especially for branched mitochondria. Our study provides 3D reconstructions of various organelles in liver samples together with important fundamental information for biochemical and functional studies in the liver.}",
    issn = {1759-4685},
    doi = {10.1093/jmcb/mjab032},
    url = {https://doi.org/10.1093/jmcb/mjab032},
    note = {mjab032},
    eprint = {https://academic.oup.com/jmcb/advance-article-pdf/doi/10.1093/jmcb/mjab032/40451792/mjab032.pdf},
}


@Article{Heinrich2021,
author={Heinrich, Larissa
and Bennett, Davis
and Ackerman, David
and Park, Woohyun
and Bogovic, John
and Eckstein, Nils
and Petruncio, Alyson
and Clements, Jody
and Pang, Song
and Xu, C. Shan
and Funke, Jan
and Korff, Wyatt
and Hess, Harald F.
and Lippincott-Schwartz, Jennifer
and Saalfeld, Stephan
and Weigel, Aubrey V.
and Ali, Riasat
and Arruda, Rebecca
and Bahtra, Rohit
and Nguyen, Destiny
and Team, COSEM Project},
title={Whole-cell organelle segmentation in volume electron microscopy},
journal={Nature},
year={2021},
month={Oct},
day={06},
abstract={Cells contain hundreds of organelles and macromolecular assemblies. Obtaining a complete understanding of their intricate organization requires the nanometre-level, three-dimensional reconstruction of whole cells, which is only feasible with robust and scalable automatic methods. Here, to support the development of such methods, we annotated up to 35 different cellular organelle classes---ranging from endoplasmic reticulum to microtubules to ribosomes---in diverse sample volumes from multiple cell types imaged at a near-isotropic resolution of 4{\thinspace}nm per voxel with focused ion beam scanning electron microscopy (FIB-SEM)1. We trained deep learning architectures to segment these structures in 4{\thinspace}nm and 8{\thinspace}nm per voxel FIB-SEM volumes, validated their performance and showed that automatic reconstructions can be used to directly quantify previously inaccessible metrics including spatial interactions between cellular components. We also show that such reconstructions can be used to automatically register light and electron microscopy images for correlative studies. We have created an open data and open-source web repository, `OpenOrganelle', to share the data, computer code and trained models, which will enable scientists everywhere to query and further improve automatic reconstruction of these datasets.},
issn={1476-4687},
doi={10.1038/s41586-021-03977-3},
url={https://doi.org/10.1038/s41586-021-03977-3}
}



@article {Conrad2021,
article_type = {journal},
title = {CEM500K, a large-scale heterogeneous unlabeled cellular electron microscopy image dataset for deep learning},
author = {Conrad, Ryan and Narayan, Kedar},
editor = {Grigorieff, Nikolaus and Akhmanova, Anna and Grigorieff, Nikolaus and Saalfeld, Stephan},
volume = 10,
year = 2021,
month = {apr},
pub_date = {2021-04-08},
pages = {e65894},
citation = {eLife 2021;10:e65894},
doi = {10.7554/eLife.65894},
url = {https://doi.org/10.7554/eLife.65894},
abstract = {Automated segmentation of cellular electron microscopy (EM) datasets remains a challenge. Supervised deep learning (DL) methods that rely on region-of-interest (ROI) annotations yield models that fail to generalize to unrelated datasets. Newer unsupervised DL algorithms require relevant pre-training images, however, pre-training on currently available EM datasets is computationally expensive and shows little value for unseen biological contexts, as these datasets are large and homogeneous. To address this issue, we present CEM500K, a nimble 25 GB dataset of 0.5 × 10\textsuperscript{6} unique 2D cellular EM images curated from nearly 600 three-dimensional (3D) and 10,000 two-dimensional (2D) images from >100 unrelated imaging projects. We show that models pre-trained on CEM500K learn features that are biologically relevant and resilient to meaningful image augmentations. Critically, we evaluate transfer learning from these pre-trained models on six publicly available and one newly derived benchmark segmentation task and report state-of-the-art results on each. We release the CEM500K dataset, pre-trained models and curation pipeline for model building and further expansion by the EM community. Data and code are available at https://www.ebi.ac.uk/pdbe/emdb/empiar/entry/10592/ and https://git.io/JLLTz.},
keywords = {electron microscopy, deep learning, segmentation, vEM, neural network, image dataset},
journal = {eLife},
issn = {2050-084X},
publisher = {eLife Sciences Publications, Ltd},
}



@article{Zeng2017,
    author = {Zeng, Tao and Wu, Bian and Ji, Shuiwang},
    title = "{DeepEM3D: approaching human-level performance on 3D anisotropic EM image segmentation}",
    journal = {Bioinformatics},
    volume = {33},
    number = {16},
    pages = {2555-2562},
    year = {2017},
    month = {03},
    abstract = "{Progress in 3D electron microscopy (EM) imaging has greatly facilitated neuroscience research in high-throughput data acquisition. Correspondingly, high-throughput automated image analysis methods are necessary to work on par with the speed of data being produced. One such example is the need for automated EM image segmentation for neurite reconstruction. However, the efficiency and reliability of current methods are still lagging far behind human performance.Here, we propose DeepEM3D, a deep learning method for segmenting 3D anisotropic brain electron microscopy images. In this method, the deep learning model can efficiently build feature representation and incorporate sufficient multi-scale contextual information. We propose employing a combination of novel boundary map generation methods with optimized model ensembles to address the inherent challenges of segmenting anisotropic images. We evaluated our method by participating in the 3D segmentation of neurites in EM images (SNEMI3D) challenge. Our submission is ranked #1 on the current leaderboard as of Oct 15, 2016. More importantly, our result was very close to human-level performance in terms of the challenge evaluation metric: namely, a Rand error of 0.06015 versus the human value of 0.05998.The code is available at https://github.com/divelab/deepem3d/Supplementary data are available at Bioinformatics online.}",
    issn = {1367-4803},
    doi = {10.1093/bioinformatics/btx188},
    url = {https://doi.org/10.1093/bioinformatics/btx188},
    eprint = {https://academic.oup.com/bioinformatics/article-pdf/33/16/2555/25163663/btx188.pdf},
}





@article{Khadangi2021,
    author = {Khadangi, Afshin and Boudier, Thomas and Rajagopal, Vijay},
    title = "{EM-stellar: benchmarking deep learning for electron microscopy image segmentation}",
    journal = {Bioinformatics},
    volume = {37},
    number = {1},
    pages = {97-106},
    year = {2021},
    month = {01},
    abstract = "{The inherent low contrast of electron microscopy (EM) datasets presents a significant challenge for rapid segmentation of cellular ultrastructures from EM data. This challenge is particularly prominent when working with high-resolution big-datasets that are now acquired using electron tomography and serial block-face imaging techniques. Deep learning (DL) methods offer an exciting opportunity to automate the segmentation process by learning from manual annotations of a small sample of EM data. While many DL methods are being rapidly adopted to segment EM data no benchmark analysis has been conducted on these methods to date.We present EM-stellar, a platform that is hosted on Google Colab that can be used to benchmark the performance of a range of state-of-the-art DL methods on user-provided datasets. Using EM-stellar we show that the performance of any DL method is dependent on the properties of the images being segmented. It also follows that no single DL method performs consistently across all performance evaluation metrics.EM-stellar (code and data) is written in Python and is freely available under MIT license on GitHub (https://github.com/cellsmb/em-stellar).Supplementary data are available at Bioinformatics online.}",
    issn = {1367-4803},
    doi = {10.1093/bioinformatics/btaa1094},
    url = {https://doi.org/10.1093/bioinformatics/btaa1094},
    eprint = {https://academic.oup.com/bioinformatics/article-pdf/37/1/97/37005819/btaa1094.pdf},
}





@INPROCEEDINGS{Khadangi2021,  
author={Khadangi, Afshin and Boudier, Thomas and Rajagopal, Vijay},  booktitle={2020 25th International Conference on Pattern Recognition (ICPR)},   title={EM-net: Deep learning for electron microscopy image segmentation},   year={2021},  volume={},  number={},  pages={31-38},  doi={10.1109/ICPR48806.2021.9413098}}

@Article{Wagner2020,
AUTHOR = {Wagner, Fabien H. and Dalagnol, Ricardo and Tarabalka, Yuliya and Segantine, Tassiana Y. F. and Thomé, Rogério and Hirye, Mayumi C. M.},
TITLE = {U-Net-Id, an Instance Segmentation Model for Building Extraction from Satellite Images—Case Study in the Joanópolis City, Brazil},
JOURNAL = {Remote Sensing},
VOLUME = {12},
YEAR = {2020},
NUMBER = {10},
ARTICLE-NUMBER = {1544},
URL = {https://www.mdpi.com/2072-4292/12/10/1544},
ISSN = {2072-4292},
ABSTRACT = {Currently, there exists a growing demand for individual building mapping in regions of rapid urban growth in less-developed countries. Most existing methods can segment buildings but cannot discriminate adjacent buildings. Here, we present a new convolutional neural network architecture (CNN) called U-net-id that performs building instance segmentation. The proposed network is trained with WorldView-3 satellite RGB images (0.3 m) and three different labeled masks. The first is the building mask; the second is the border mask, which is the border of the building segment with 4 pixels added outside and 3 pixels inside; and the third is the inner segment mask, which is the segment of the building diminished by 2 pixels. The architecture consists of three parallel paths, one for each mask, all starting with a U-net model. To accurately capture the overlap between the masks, all activation layers of the U-nets are copied and concatenated on each path and sent to two additional convolutional layers before the output activation layers. The method was tested with a dataset of 7563 manually delineated individual buildings of the city of Joanópolis-SP, Brazil. On this dataset, the semantic segmentation showed an overall accuracy of 97.67% and an F1-Score of 0.937 and the building individual instance segmentation showed good performance with a mean intersection over union (IoU) of 0.582 (median IoU = 0.694).},
DOI = {10.3390/rs12101544}
}





@Article{Zhang2019,
author={Zhang, Kun
and Zhang, Hongbin
and Zhou, Huiyu
and Crookes, Danny
and Li, Ling
and Shao, Yeqin
and Liu, Dong},
title={Zebrafish Embryo Vessel Segmentation Using a Novel Dual ResUNet Model},
journal={Computational Intelligence and Neuroscience},
year={2019},
month={Feb},
day={03},
publisher={Hindawi},
volume={2019},
pages={8214975},
abstract={Zebrafish embryo fluorescent vessel analysis, which aims to automatically investigate the pathogenesis of diseases, has attracted much attention in medical imaging. Zebrafish vessel segmentation is a fairly challenging task, which requires distinguishing foreground and background vessels from the 3D projection images. Recently, there has been a trend to introduce domain knowledge to deep learning algorithms for handling complex environment segmentation problems with accurate achievements. In this paper, a novel dual deep learning framework called Dual ResUNet is developed to conduct zebrafish embryo fluorescent vessel segmentation. To avoid the loss of spatial and identity information, the U-Net model is extended to a dual model with a new residual unit. To achieve stable and robust segmentation performance, our proposed approach merges domain knowledge with a novel contour term and shape constraint. We compare our method qualitatively and quantitatively with several standard segmentation models. Our experimental results show that the proposed method achieves better results than the state-of-art segmentation methods. By investigating the quality of the vessel segmentation, we come to the conclusion that our Dual ResUNet model can learn the characteristic features in those cases where fluorescent protein is deficient or blood vessels are overlapped and achieves robust performance in complicated environments.},
issn={1687-5265},
doi={10.1155/2019/8214975},
url={https://doi.org/10.1155/2019/8214975}
}



@Article{Long2020,
author={Long, Feixiao},
title={Microscopy cell nuclei segmentation with enhanced U-Net},
journal={BMC Bioinformatics},
year={2020},
month={Jan},
day={08},
volume={21},
number={1},
pages={8},
abstract={Cell nuclei segmentation is a fundamental task in microscopy image analysis, based on which multiple biological related analysis can be performed. Although deep learning (DL) based techniques have achieved state-of-the-art performances in image segmentation tasks, these methods are usually complex and require support of powerful computing resources. In addition, it is impractical to allocate advanced computing resources to each dark- or bright-field microscopy, which is widely employed in vast clinical institutions, considering the cost of medical exams. Thus, it is essential to develop accurate DL based segmentation algorithms working with resources-constraint computing.},
issn={1471-2105},
doi={10.1186/s12859-019-3332-1},
url={https://doi.org/10.1186/s12859-019-3332-1}
}



@ARTICLE{Quan2021,
AUTHOR={Quan, Tran Minh and Hildebrand, David Grant Colburn and Jeong, Won-Ki},   
TITLE={FusionNet: A Deep Fully Residual Convolutional Neural Network for Image Segmentation in Connectomics},      
JOURNAL={Frontiers in Computer Science},      
VOLUME={3},      
PAGES={34},     
YEAR={2021},      
URL={https://www.frontiersin.org/article/10.3389/fcomp.2021.613981},       
DOI={10.3389/fcomp.2021.613981},      
ISSN={2624-9898},   
ABSTRACT={Cellular-resolution connectomics is an ambitious research direction with the goal of generating comprehensive brain connectivity maps using high-throughput, nano-scale electron microscopy. One of the main challenges in connectomics research is developing scalable image analysis algorithms that require minimal user intervention. Deep learning has provided exceptional performance in image classification tasks in computer vision, leading to a recent explosion in popularity. Similarly, its application to connectomic analyses holds great promise. Here, we introduce a deep neural network architecture, FusionNet, with a focus on its application to accomplish automatic segmentation of neuronal structures in connectomics data. FusionNet combines recent advances in machine learning, such as semantic segmentation and residual neural networks, with summation-based skip connections. This results in a much deeper network architecture and improves segmentation accuracy. We demonstrate the performance of the proposed method by comparing it with several other popular electron microscopy segmentation methods. We further illustrate its flexibility through segmentation results for two different tasks: cell membrane segmentation and cell nucleus segmentation.}
}


@ARTICLE{Siddique2021, 
 author={Siddique, Nahian and Paheding, Sidike and Elkin, Colin P. and Devabhaktuni, Vijay},  journal={IEEE Access},   title={U-Net and Its Variants for Medical Image Segmentation: A Review of Theory and Applications},   year={2021},  volume={9},  number={},  pages={82031-82057},  doi={10.1109/ACCESS.2021.3086020}}

@InProceedings{Cicek2016,
author="{\c{C}}i{\c{c}}ek, {\"O}zg{\"u}n
and Abdulkadir, Ahmed
and Lienkamp, Soeren S.
and Brox, Thomas
and Ronneberger, Olaf",
editor="Ourselin, Sebastien
and Joskowicz, Leo
and Sabuncu, Mert R.
and Unal, Gozde
and Wells, William",
title="3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation",
booktitle="Medical Image Computing and Computer-Assisted Intervention -- MICCAI 2016",
year="2016",
publisher="Springer International Publishing",
address="Cham",
pages="424--432",
abstract="This paper introduces a network for volumetric segmentation that learns from sparsely annotated volumetric images. We outline two attractive use cases of this method: (1) In a semi-automated setup, the user annotates some slices in the volume to be segmented. The network learns from these sparse annotations and provides a dense 3D segmentation. (2) In a fully-automated setup, we assume that a representative, sparsely annotated training set exists. Trained on this data set, the network densely segments new volumetric images. The proposed network extends the previous u-net architecture from Ronneberger et al. by replacing all 2D operations with their 3D counterparts. The implementation performs on-the-fly elastic deformations for efficient data augmentation during training. It is trained end-to-end from scratch, i.e., no pre-trained network is required. We test the performance of the proposed method on a complex, highly variable 3D structure, the Xenopus kidney, and achieve good results for both use cases.",
isbn="978-3-319-46723-8"
}



@Article{Falk2019,
author={Falk, Thorsten
and Mai, Dominic
and Bensch, Robert
and {\c{C}}i{\c{c}}ek, {\"O}zg{\"u}n
and Abdulkadir, Ahmed
and Marrakchi, Yassine
and B{\"o}hm, Anton
and Deubner, Jan
and J{\"a}ckel, Zoe
and Seiwald, Katharina
and Dovzhenko, Alexander
and Tietz, Olaf
and Dal Bosco, Cristina
and Walsh, Sean
and Saltukoglu, Deniz
and Tay, Tuan Leng
and Prinz, Marco
and Palme, Klaus
and Simons, Matias
and Diester, Ilka
and Brox, Thomas
and Ronneberger, Olaf},
title={U-Net: deep learning for cell counting, detection, and morphometry},
journal={Nature Methods},
year={2019},
month={Jan},
day={01},
volume={16},
number={1},
pages={67-70},
abstract={U-Net is a generic deep-learning solution for frequently occurring quantification tasks such as cell detection and shape measurements in biomedical image data. We present an ImageJ plugin that enables non-machine-learning experts to analyze their data with U-Net on either a local computer or a remote server/cloud service. The plugin comes with pretrained models for single-cell segmentation and allows for U-Net to be adapted to new tasks on the basis of a few annotated samples.},
issn={1548-7105},
doi={10.1038/s41592-018-0261-2},
url={https://doi.org/10.1038/s41592-018-0261-2}
}



@article{Ignacio2017,
    author = {Arganda-Carreras, Ignacio and Kaynig, Verena and Rueden, Curtis and Eliceiri, Kevin W and Schindelin, Johannes and Cardona, Albert and Sebastian Seung, H},
    title = "{Trainable Weka Segmentation: a machine learning tool for microscopy pixel classification}",
    journal = {Bioinformatics},
    volume = {33},
    number = {15},
    pages = {2424-2426},
    year = {2017},
    month = {03},
    abstract = "{State-of-the-art light and electron microscopes are capable of acquiring large image datasets, but quantitatively evaluating the data often involves manually annotating structures of interest. This process is time-consuming and often a major bottleneck in the evaluation pipeline. To overcome this problem, we have introduced the Trainable Weka Segmentation (TWS), a machine learning tool that leverages a limited number of manual annotations in order to train a classifier and segment the remaining data automatically. In addition, TWS can provide unsupervised segmentation learning schemes (clustering) and can be customized to employ user-designed image features or classifiers.TWS is distributed as open-source software as part of the Fiji image processing distribution of ImageJ at http://imagej.net/Trainable\_Weka\_Segmentation.Supplementary data are available at Bioinformatics online.}",
    issn = {1367-4803},
    doi = {10.1093/bioinformatics/btx180},
    url = {https://doi.org/10.1093/bioinformatics/btx180},
    eprint = {https://academic.oup.com/bioinformatics/article-pdf/33/15/2424/25157856/btx180.pdf},
}





@article {Hoffpauir2006,
	author = {Hoffpauir, Brian K. and Grimes, Janelle L. and Mathers, Peter H. and Spirou, George A.},
	title = {Synaptogenesis of the Calyx of Held: Rapid Onset of Function and One-to-One Morphological Innervation},
	volume = {26},
	number = {20},
	pages = {5511--5523},
	year = {2006},
	doi = {10.1523/JNEUROSCI.5525-05.2006},
	publisher = {Society for Neuroscience},
	abstract = {Synaptogenesis during early development is thought to follow a canonical program whereby synapses increase rapidly in number and individual axons multiply-innervate nearby targets. Typically, a subset of inputs then out-competes all others through experience-driven processes to establish stable, long-lasting contacts. We investigated the formation of the calyx of Held, probably the largest nerve terminal in the mammalian CNS. Many basic functional and morphological features of calyx growth have not been studied previously, including whether mono-innervation, a hallmark of this system in adult animals, is established early in development. Evoked postsynaptic currents, recorded from neonatal mice between postnatal day 1 (P1) and P4, increased dramatically from -0.14 {\textpm} 0.04 nA at P1 to -6.71 {\textpm} 0.65 nA at P4 with sharp jumps between P2 and P4. These are the first functional assays of these nascent synapses for ages less than P3. AMPA and NMDA receptor-mediated currents were prominent across this age range. Electron microscopy (EM) revealed a concomitant increase, beginning at P2, in the prevalence of postsynaptic densities (16-fold) and adhering contacts (73-fold) by P4. Therefore, both functional and structural data showed that young calyces could form within 2 d, well before the onset of hearing around P8. Convergence of developing calyces onto postsynaptic targets, indicative of competitive processes that precede mono-innervation, was rare (4 of 29) at P4 as assessed using minimal stimulation electrophysiology protocols. Serial EM sectioning through 19 P4 cells further established the paucity (2 of 19) of convergence. These data indicate that calyces of Held follow a noncanonical program to establish targeted innervation that occurs over a rapid time course and precedes auditory experience.},
	issn = {0270-6474},
	URL = {https://www.jneurosci.org/content/26/20/5511},
	eprint = {https://www.jneurosci.org/content/26/20/5511.full.pdf},
	journal = {Journal of Neuroscience}
}


​​@article{Miranda2015,
author = {Miranda, Kildare and Girard-Dias, Wendell and Attias, Marcia and de Souza, Wanderley and Ramos, Isabela},
title = {Three dimensional reconstruction by electron microscopy in the life sciences: An introduction for cell and tissue biologists},
journal = {Molecular Reproduction and Development},
volume = {82},
number = {7-8},
pages = {530-547},
doi = {https://doi.org/10.1002/mrd.22455},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/mrd.22455},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/mrd.22455},
abstract = {SUMMARY Early applications of transmission electron microscopy (TEM) in the life sciences have contributed tremendously to our current understanding at the subcellular level. Initially limited to two-dimensional representations of three-dimensional (3D) objects, this approach has revolutionized the fields of cellular and structural biology–being instrumental for determining the fine morpho-functional characterization of most cellular structures. Electron microscopy has progressively evolved towards the development of tools that allow for the 3D characterization of different structures. This was done with the aid of a wide variety of techniques, which have become increasingly diverse and highly sophisticated. We start this review by examining the principles of 3D reconstruction of cells and tissues using classical approaches in TEM, and follow with a discussion of the modern approaches utilizing TEM as well as on new scanning electron microscopy-based techniques. 3D reconstruction techniques from serial sections and (cryo) electron-tomography are examined, and the recent applications of focused ion beam-scanning microscopes and serial-block-face techniques for the 3D reconstruction of large volumes are discussed. Alternative low-cost techniques and more accessible approaches using basic transmission or field emission scanning electron microscopes are also examined. Mol. Reprod. Dev. 82: 530–547, 2015. © 2015 Wiley Periodicals, Inc.},
year = {2015}
}


@article {Lamers2020,
	author = {Lamers, Mart M. and Beumer, Joep and van der Vaart, Jelte and Knoops, K{\`e}vin and Puschhof, Jens and Breugem, Tim I. and Ravelli, Raimond B. G. and Paul van Schayck, J. and Mykytyn, Anna Z. and Duimel, Hans Q. and van Donselaar, Elly and Riesebosch, Samra and Kuijpers, Helma J. H. and Schipper, Debby and van de Wetering, Willine J. and de Graaf, Miranda and Koopmans, Marion and Cuppen, Edwin and Peters, Peter J. and Haagmans, Bart L. and Clevers, Hans},
	title = {SARS-CoV-2 productively infects human gut enterocytes},
	volume = {369},
	number = {6499},
	pages = {50--54},
	year = {2020},
	doi = {10.1126/science.abc1669},
	publisher = {American Association for the Advancement of Science},
	abstract = {Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes an influenza-like disease with a respiratory transmission route; however, patients often present with gastrointestinal symptoms such as diarrhea, vomiting, and abdominal pain. Moreover, the virus has been detected in anal swabs, and cells in the inner-gut lining express the receptor that SARS-CoV-2 uses to gain entry to cells. Lamers et al. used human intestinal organoids, a {\textquotedblleft}mini-gut{\textquotedblright} cultured in a dish, to demonstrate that SARS-CoV-2 readily replicates in an abundant cell type in the gut lining{\textemdash}the enterocyte{\textemdash}resulting in the production of large amounts of infective virus particles in the intestine. This work demonstrates that intestinal organoids can serve as a model to understand SARS-CoV-2 biology and infectivity in the gut.Science, this issue p. 50Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) can cause coronavirus disease 2019 (COVID-19), an influenza-like disease that is primarily thought to infect the lungs with transmission through the respiratory route. However, clinical evidence suggests that the intestine may present another viral target organ. Indeed, the SARS-CoV-2 receptor angiotensin-converting enzyme 2 (ACE2) is highly expressed on differentiated enterocytes. In human small intestinal organoids (hSIOs), enterocytes were readily infected by SARS-CoV and SARS-CoV-2, as demonstrated by confocal and electron microscopy. Enterocytes produced infectious viral particles, whereas messenger RNA expression analysis of hSIOs revealed induction of a generic viral response program. Therefore, the intestinal epithelium supports SARS-CoV-2 replication, and hSIOs serve as an experimental model for coronavirus infection and biology.},
	issn = {0036-8075},
	URL = {https://science.sciencemag.org/content/369/6499/50},
	eprint = {https://science.sciencemag.org/content/369/6499/50.full.pdf},
	journal = {Science}
}


@Article{Dittmayer2020,
author={Dittmayer, Carsten
and Meinhardt, Jenny
and Radbruch, Helena
and Radke, Josefine
and Heppner, Barbara Ingold
and Heppner, Frank L.
and Stenzel, Werner
and Holland, Gudrun
and Laue, Michael},
title={Why misinterpretation of electron micrographs in SARS-CoV-2-infected tissue goes viral},
journal={The Lancet},
year={2020},
month={Oct},
day={31},
publisher={Elsevier},
volume={396},
number={10260},
pages={e64-e65},
issn={0140-6736},
doi={10.1016/S0140-6736(20)32079-1},
url={https://doi.org/10.1016/S0140-6736(20)32079-1}
}


@Article{Williams2017,
author={Williams, Eleanor
and Moore, Josh
and Li, Simon W.
and Rustici, Gabriella
and Tarkowska, Aleksandra
and Chessel, Anatole
and Leo, Simone
and Antal, B{\'a}lint
and Ferguson, Richard K.
and Sarkans, Ugis
and Brazma, Alvis
and Carazo Salas, Rafael E.
and Swedlow, Jason R.},
title={Image Data Resource: a bioimage data integration and publication platform},
journal={Nature Methods},
year={2017},
month={Aug},
day={01},
volume={14},
number={8},
pages={775-781},
abstract={This Resource describes the Image Data Resource (IDR), a prototype online system for biological image data that links experimental and analytic data across multiple data sets and promotes image data sharing and reanalysis.},
issn={1548-7105},
doi={10.1038/nmeth.4326},
url={https://doi.org/10.1038/nmeth.4326}
}



@article{SUGA2014,
title = {Recent progress in scanning electron microscopy for the characterization of fine structural details of nano materials},
journal = {Progress in Solid State Chemistry},
volume = {42},
number = {1},
pages = {1-21},
year = {2014},
issn = {0079-6786},
doi = {https://doi.org/10.1016/j.progsolidstchem.2014.02.001},
url = {https://www.sciencedirect.com/science/article/pii/S0079678614000028},
author = {Mitsuo Suga and Shunsuke Asahina and Yusuke Sakuda and Hiroyoshi Kazumori and Hidetoshi Nishiyama and Takeshi Nokuo and Viveka Alfredsson and Tomas Kjellman and Sam M. Stevens and Hae Sung Cho and Minhyung Cho and Lu Han and Shunai Che and Michael W. Anderson and Ferdi Schüth and Hexiang Deng and Omar M. Yaghi and Zheng Liu and Hu Young Jeong and Andreas Stein and Kazuyuki Sakamoto and Ryong Ryoo and Osamu Terasaki},
keywords = {Scanning electron microscopy, Through-the-lens detection system, Nano-materials, Atmospheric SEM, Metal-organic frameworks, Mesoporous materials},
abstract = {Research concerning nano-materials (metal-organic frameworks (MOFs), zeolites, mesoporous silicas, etc.) and the nano-scale, including potential barriers for the particulates to diffusion to/from is of increasing importance to the understanding of the catalytic utility of porous materials when combined with any potential super structures (such as hierarchically porous materials). However, it is difficult to characterize the structure of for example MOFs via X-ray powder diffraction because of the serious overlapping of reflections caused by their large unit cells, and it is also difficult to directly observe the opening of surface pores using ordinary methods. Electron-microscopic methods including high-resolution scanning electron microscopy (HRSEM) have therefore become imperative for the above challenges. Here, we present the theory and practical application of recent advances such as through-the-lens detection systems, which permit a reduced landing energy and the selection of high-resolution, topographically specific emitted electrons, even from electrically insulating nano-materials.}
}

@article{Cohen2020,
title = {Scanning electron microscopy as a new tool for diagnostic pathology and cell biology},
journal = {Micron},
volume = {130},
pages = {102797},
year = {2020},
issn = {0968-4328},
doi = {https://doi.org/10.1016/j.micron.2019.102797},
url = {https://www.sciencedirect.com/science/article/pii/S0968432819303154},
author = {Tzipi {Cohen Hyams} and Keriya Mam and Murray C. Killingsworth},
keywords = {Scanning Electron microscopy, SEM, Pathology, Diagnosis, Tissue, Cell biology, Ultrastructure, Renal, Prostate, cancer},
abstract = {Scanning electron microscopy (SEM) use in the biomedical sciences has traditionally been used for characterisation of cell and tissue surface topography. This paper demonstrates the utility of high-resolution scanning electron microscopy (HRSEM) to diagnostic pathology and cell biology ultrastructural examinations. New SEM applications based on the production of transmission electron microscopy-like (TEM-like) images are now possible with the recent introduction of new technologies such as low kV scanning transmission electron microscopy (STEM) detectors, automated scan generators and high-resolution column configurations capable of sub-nanometre resolution. Typical specimen types traditionally imaged by TEM have been examined including renal, lung, prostate and brain tissues. The specimen preparation workflow was unchanged from that routinely used to prepare TEM tissue, apart from replacing copper grids for section mounting with a silicon substrate. These instruments feature a small footprint with little in the way of ancillary equipment, such as water chillers, and are more cost-effective than traditional TEM columns. Also, a new generation of benchtop SEMs have recently become available and have also been assessed for its utility in the tissue pathology and cell biology settings.}
}

@article{Tokunaga1969,
  title={Scanning electron microscopy of normal and pathological human erythrocytes.},
  author={Junichi Tokunaga and Tsuneo Fujita and Akira Hattori},
  journal={Archivum histologicum Japonicum = Nihon soshikigaku kiroku},
  year={1969},
  volume={31(1)},
  pages={21-35}
}

@Article{Bouwer2016,
author={Bouwer, James C.
and Deerinck, Thomas J.
and Bushong, Eric
and Astakhov, Vadim
and Ramachandra, Ranjan
and Peltier, Steven T.
and Ellisman, Mark H.},
title={Deceleration of probe beam by stage bias potential improves resolution of serial block-face scanning electron microscopic images},
journal={Advanced Structural and Chemical Imaging},
year={2016},
month={Sep},
day={15},
volume={2},
number={1},
pages={11},
abstract={Serial block-face scanning electron microscopy (SBEM) is quickly becoming an important imaging tool to explore three-dimensional biological structure across spatial scales. At probe-beam-electron energies of 2.0 keV or lower, the axial resolution should improve, because there is less primary electron penetration into the block face. More specifically, at these lower energies, the interaction volume is much smaller, and therefore, surface detail is more highly resolved. However, the backscattered electron yield for metal contrast agents and the backscattered electron detector sensitivity are both sub-optimal at these lower energies, thus negating the gain in axial resolution. We found that the application of a negative voltage (reversal potential) applied to a modified SBEM stage creates a tunable electric field at the sample. This field can be used to decrease the probe-beam-landing energy and, at the same time, alter the trajectory of the signal to increase the signal collected by the detector. With decelerated low landing-energy electrons, we observed that the probe-beam-electron-penetration depth was reduced to less than 30 nm in epoxy-embedded biological specimens. Concurrently, a large increase in recorded signal occurred due to the re-acceleration of BSEs in the bias field towards the objective pole piece where the detector is located. By tuning the bias field, we were able to manipulate the trajectories of the  primary and secondary electrons, enabling the spatial discrimination of these signals using an advanced ring-type BSE detector configuration or a standard monolithic BSE detector coupled with a blocking aperture.},
issn={2198-0926},
doi={10.1186/s40679-016-0025-y},
url={https://doi.org/10.1186/s40679-016-0025-y}
}

@Article{Cesare2019,
author ="De Cesare, Fabrizio and Di Mattia, Elena and Zussman, Eyal and Macagnano, Antonella",
title  ="A study on the dependence of bacteria adhesion on the polymer nanofibre diameter",
journal  ="Environ. Sci.: Nano",
year  ="2019",
volume  ="6",
issue  ="3",
pages  ="778-797",
publisher  ="The Royal Society of Chemistry",
doi  ="10.1039/C8EN01237G",
url  ="http://dx.doi.org/10.1039/C8EN01237G",
abstract  ="Topography nanostructures have been extensively studied to reduce bacterial adhesion in medical{,} food and industrial contexts. Fibres have also been used in energy{,} water and wastewater treatments{,} and medical applications. Nanosized fibres{,} however{,} have rarely been analysed in interactions with bacteria{,} and they have always been found to inhibit bacterial adhesion and proliferation. We discussed here the size effect of polymer nanofibres on the attachment of bacteria. As a model system{,} a 3D self-standing electrospun nanofibrous poly(ε-caprolactone)-based scaffold was fabricated{,} and Burkholderia terricola bacteria cells were used for testing the interactions. The initial reversible adhesion and the subsequent stable irreversible docking of bacteria to nanofibres through various mechanisms{,} the orientation of bacteria along nanofibres{,} and the communication between cells were explored. Bacteria initially attached preferentially to nanofibres with ≈100 nm diameter{,} i.e. an order of magnitude smaller than that of the bacteria{,} resulting in a bacteria-to-nanofibre diameter ratio as large as ≈5. It is worth noting that interactions always occurred between bacteria and nanofibres coated with a conditioning film of organic substances of bacterial origin. The conditioning film{,} the outer membrane vesicles and the bacterial appendages were found to play a remarkable role in facilitating the subsequent adhesion of B. terricola cells to the electrospun poly(ε-caprolactone) nanofibres. They also permitted bacteria to reversibly and then stably attach to the nanofibrous material and connect and communicate with each other to form microcolonies embedded in exopolymeric substances{,} as an early step towards future biofilm formation. No inhibiting effect of the nanosized fibres on the adhesion{,} proliferation and vitality of the bacterial cells was observed."}

@article {Khalaf2017,
	Title = {Surface Coating of Gypsum-Based Molds for Maxillofacial Prosthetic Silicone Elastomeric Material: Evaluating Different Microbial Adhesion},
	Author = {Khalaf, Salah and Ariffin, Zaihan and Husein, Adam and Reza, Fazal},
	DOI = {10.1111/jopr.12460},
	Number = {8},
	Volume = {26},
	Month = {December},
	Year = {2017},
	Journal = {Journal of prosthodontics : official journal of the American College of Prosthodontists},
	ISSN = {1059-941X},
	Pages = {664—669},
	Abstract = {&lt;h4&gt;Purpose&lt;/h4&gt;To compare the adhesion of three microorganisms on modified and unmodified silicone elastomer surfaces with different surface roughnesses and porosities.&lt;h4&gt;Materials and methods&lt;/h4&gt;Candida albicans, Streptococcus mutans, and Staphylococcus aureus were incubated with modified and unmodified silicone groups (N = 35) for 30 days at 37°C. The counts of viable microorganisms in the accumulating biofilm layer were determined and converted to cfu/cm&lt;sup&gt;2&lt;/sup&gt; unit surface area. A scanning electron microscope (SEM) was used to evaluate the microbial adhesion. Statistical analysis was performed using t-test, one-way ANOVA, and post hoc tests as indicated.&lt;h4&gt;Results&lt;/h4&gt;Significant differences in microbial adhesion were observed between modified and unmodified silicone elastomers after the cells were incubated for 30 days (p &lt; 0.001). SEM showed evident differences in microbial adhesion on modified silicone elastomer compared with unmodified silicone elastomer.&lt;h4&gt;Conclusions&lt;/h4&gt;Surface modification of silicone elastomer yielding a smoother and less porous surface showed lower adhesion of different microorganisms than observed on unmodified surfaces.},
	URL = {https://doi.org/10.1111/jopr.12460}
}

@Article{Conti2018,
author={Conti, Sara
and Perico, Norberto
and Novelli, Rubina
and Carrara, Camillo
and Benigni, Ariela
and Remuzzi, Giuseppe},
title={Early and late scanning electron microscopy findings in diabetic kidney disease},
journal={Scientific Reports},
year={2018},
month={Mar},
day={20},
volume={8},
number={1},
pages={4909},
abstract={Diabetic nephropathy (DN), the single strongest predictor of mortality in patients with type 2 diabetes, is characterized by initial glomerular hyperfiltration with subsequent progressive renal function loss with or without albuminuria, greatly accelerated with the onset of overt proteinuria. Experimental and clinical studies have convincingly shown that early interventions retard disease progression, while treatment if started late in the disease course seldom modifies the slope of GFR decline. Here we assessed whether the negligible renoprotection afforded by drugs in patients with proteinuric DN could be due to loss of glomerular structural integrity, explored by scanning electron microscopy (SEM). In diabetic patients with early renal disease, glomerular structural integrity was largely preserved. At variance SEM documented that in the late stage of proteinuric DN, glomerular structure was subverted with nearly complete loss of podocytes and lobular transformation of the glomerular basement membrane. In these circumstances one can reasonably imply that any form of treatment, albeit personalized, is unlikely to reach a given cellular or molecular target. These findings should persuade physicians to start the putative renoprotective therapy soon after the diagnosis of diabetes or in an early phase of the disease before structural integrity of the glomerular filter is irreversibly compromised.},
issn={2045-2322},
doi={10.1038/s41598-018-23244-2},
url={https://doi.org/10.1038/s41598-018-23244-2}
}

@Article{AutioHarmainen1981ScanningEM,
author={Autio-Harmainen, Helena
and V{\"a}{\"a}n{\"a}nen, R.
and Rapola, J.},
title={Scanning electron microscopic study of normal human glomerulogenesis and of fetal glomeruli in congenital nephrotic syndrome of the Finnish type},
journal={Kidney International},
year={1981},
month={Dec},
day={01},
publisher={Elsevier},
volume={20},
number={6},
pages={747-752},
issn={0085-2538},
doi={10.1038/ki.1981.206},
url={https://doi.org/10.1038/ki.1981.206}
}

@article{Burghardt2015,
author = {Burghardt, Tillmann and Hochapfel, Florian and Salecker, Benjamin and Meese, Christine and Gröne, Hermann-Josef and Rachel, Reinhard and Wanner, Gerhard and Krahn, Michael P. and Witzgall, Ralph},
title = {Advanced electron microscopic techniques provide a deeper insight into the peculiar features of podocytes},
journal = {American Journal of Physiology-Renal Physiology},
volume = {309},
number = {12},
pages = {F1082-F1089},
year = {2015},
doi = {10.1152/ajprenal.00338.2015},
note ={PMID: 26400546},
URL = {https://doi.org/10.1152/ajprenal.00338.2015},
eprint = {https://doi.org/10.1152/ajprenal.00338.2015},
abstract = { Podocytes constitute the outer layer of the glomerular filtration barrier, where they form an intricate network of interdigitating foot processes which are connected by slit diaphragms. A hitherto unanswered puzzle concerns the question of whether slit diaphragms are established between foot processes of the same podocyte or between foot processes of different podocytes. By employing focused ion beam-scanning electron microscopy (FIB-SEM), we provide unequivocal evidence that slit diaphragms are formed between foot processes of different podocytes. We extended our investigations of the filtration slit by using dual-axis electron tomography of human and mouse podocytes as well as of Drosophila melanogaster nephrocytes. Using this technique, we not only find a single slit diaphragm which spans the filtration slit around the whole periphery of the foot processes but additional punctate filamentous contacts between adjacent foot processes. Future work will be necessary to determine the proteins constituting the two types of cell-cell contacts. }
}

@Article{Bonsib1985,
author={Bonsib, Stephen M.},
title={Scanning electron microscopy of acellular glomeruli in nephrotic syndrome},
journal={Kidney International},
year={1985},
month={Apr},
day={01},
publisher={Elsevier},
volume={27},
number={4},
pages={678-684},
issn={0085-2538},
doi={10.1038/ki.1985.64},
url={https://doi.org/10.1038/ki.1985.64}
}

@Article{Bonsib1988,
author={Bonsib, Stephen M.},
title={Glomerular basement membrane necrosis and crescent organization},
journal={Kidney International},
year={1988},
month={May},
day={01},
publisher={Elsevier},
volume={33},
number={5},
pages={966-974},
issn={0085-2538},
doi={10.1038/ki.1988.95},
url={https://doi.org/10.1038/ki.1988.95}
}

@Article{Dittmayer2018,
author={Dittmayer, Carsten
and V{\"o}lcker, Eckhard
and Wacker, Irene
and Schr{\"o}der, Rasmus R.
and Bachmann, Sebastian},
title={Modern field emission scanning electron microscopy provides new perspectives for imaging{\&}{\#}xa0;kidney ultrastructure},
journal={Kidney International},
year={2018},
month={Sep},
day={01},
publisher={Elsevier},
volume={94},
number={3},
pages={625-631},
issn={0085-2538},
doi={10.1016/j.kint.2018.05.017},
url={https://doi.org/10.1016/j.kint.2018.05.017}
}

@article{Crewe1968,
author = {Crewe,A. V.  and Eggenberger,D. N.  and Wall,J.  and Welter,L. M. },
title = {Electron Gun Using a Field Emission Source},
journal = {Review of Scientific Instruments},
volume = {39},
number = {4},
pages = {576-583},
year = {1968},
doi = {10.1063/1.1683435},
URL = {https://doi.org/10.1063/1.1683435},
eprint = {https://doi.org/10.1063/1.1683435}
}

@article{Swanson1969,
author = {Swanson,L. W.  and Crouser,L. C. },
title = {Angular Confinement of Field Electron and Ion Emission},
journal = {Journal of Applied Physics},
volume = {40},
number = {12},
pages = {4741-4749},
year = {1969},
doi = {10.1063/1.1657282},
URL = {https://doi.org/10.1063/1.1657282},
eprint = {https://doi.org/10.1063/1.1657282}
}

@inbook{Swanson2008,
author = {Swanson, Lyn and Schwind, Gregory},
year = {2008},
month = {10},
pages = {1-28},
title = {Review of ZrO/W Schottky Cathode In: Orloff Jon, editor. Handbook of charged particle optics. 2nd ed. CRC Press},
isbn = {978-1-4200-4554-3},
doi = {10.1201/9781420045550.ch1}
}

@article{Williams2005,
author = {Williams, Thomas J.},
title = {Scanning electron microscopy and x-ray microanalysis, 3rd edition. By Joseph Goldstein, Dale Newbury, David Joy, Charles Lyman, Patrick Echlin, Eric Lifshin, Linda Sawyer, Joseph Michael Kluwer Academic Publishers, New York (2003)},
journal = {Scanning},
volume = {27},
number = {4},
pages = {215-216},
doi = {https://doi.org/10.1002/sca.4950270410},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/sca.4950270410},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/sca.4950270410},
year = {2005}
}

@article{Ryan2021,
title = {Optimization of negative stage bias potential for faster imaging in large-scale electron microscopy},
journal = {Journal of Structural Biology: X},
volume = {5},
pages = {100046},
year = {2021},
issn = {2590-1524},
doi = {https://doi.org/10.1016/j.yjsbx.2021.100046},
url = {https://www.sciencedirect.com/science/article/pii/S2590152421000039},
author = {Ryan Lane and Yoram Vos and Anouk H.G. Wolters and Luc van Kessel and S. Elisa Chen and Nalan Liv and Judith Klumperman and Ben N.G. Giepmans and Jacob P. Hoogenboom},
keywords = {Electron microscopy, Large-scale electron microscopy, Stage bias, High-throughput imaging, Volume electron microscopy, Correlative light and electron microscopy},
abstract = {Large-scale electron microscopy (EM) allows analysis of both tissues and macromolecules in a semi-automated manner, but acquisition rate forms a bottleneck. We reasoned that a negative bias potential may be used to enhance signal collection, allowing shorter dwell times and thus increasing imaging speed. Negative bias potential has previously been used to tune penetration depth in block-face imaging. However, optimization of negative bias potential for application in thin section imaging will be needed prior to routine use and application in large-scale EM. Here, we present negative bias potential optimized through a combination of simulations and empirical measurements. We find that the use of a negative bias potential generally results in improvement of image quality and signal-to-noise ratio (SNR). The extent of these improvements depends on the presence and strength of a magnetic immersion field. Maintaining other imaging conditions and aiming for the same image quality and SNR, the use of a negative stage bias can allow for a 20-fold decrease in dwell time, thus reducing the time for a week long acquisition to less than 8 h. We further show that negative bias potential can be applied in an integrated correlative light electron microscopy (CLEM) application, allowing fast acquisition of a high precision overlaid LM-EM dataset. Application of negative stage bias potential will thus help to solve the current bottleneck of image acquisition of large fields of view at high resolution in large-scale microscopy.}
}

@article {shapsoncoe2021,
    title={A connectomic study of a petascale fragment of human cerebral cortex},
    author={Shapson-Coe, Alexander and Januszewski, Micha\l and Berger, Daniel R and Pope, Art and Wu, Yuelong and Blakely, Tim and Schalek, Richard L and Li, Peter and Wang, Shuohong and Maitin-Shepard, Jeremy and others},
    journal={bioRxiv},
    year={2021},
    publisher={Cold Spring Harbor Laboratory}
}

@inproceedings{Turaga2009,
title = "Maximin affinity learning of image segmentation",
abstract = "Images can be segmented by first using a classifier to predict an affinity graph that reflects the degree to which image pixels must be grouped together and then partitioning the graph to yield a segmentation. Machine learning has been applied to the affinity classifier to produce affinity graphs that are good in the sense of minimizing edge misclassification rates. However, this error measure is only indirectly related to the quality of segmentations produced by ultimately partitioning the affinity graph. We present the first machine learning algorithm for training a classifier to produce affinity graphs that are good in the sense of producing segmentations that directly minimize the Rand index, a well known segmentation performance measure. The Rand index measures segmentation performance by quantifying the classification of the connectivity of image pixel pairs after segmentation. By using the simple graph partitioning algorithm of finding the connected components of the thresholded affinity graph, we are able to train an affinity classifier to directly minimize the Rand index of segmentations resulting from the graph partitioning. Our learning algorithm corresponds to the learning of maximin affinities between image pixel pairs, which are predictive of the pixel-pair connectivity.",
author = "Turaga, {Srinivas C.} and Briggman, {Kevin L.} and Moritz Helmstaedter and Winfried Denk and Seung, {H. Sebastian}",
year = "2009",
month = dec,
day = "1",
language = "English (US)",
isbn = "9781615679119",
series = "Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference",
pages = "1865--1873",
booktitle = "Advances in Neural Information Processing Systems 22 - Proceedings of the 2009 Conference",
note = "23rd Annual Conference on Neural Information Processing Systems, NIPS 2009 ; Conference date: 07-12-2009 Through 10-12-2009",
}

@article{Turaga2010,
    author = {Turaga, Srinivas C. and Murray, Joseph F. and Jain, Viren and Roth, Fabian and Helmstaedter, Moritz and Briggman, Kevin and Denk, Winfried and Seung, H. Sebastian},
    title = "{Convolutional Networks Can Learn to Generate Affinity Graphs for Image Segmentation}",
    journal = {Neural Computation},
    volume = {22},
    number = {2},
    pages = {511-538},
    year = {2010},
    month = {02},
    abstract = "{Many image segmentation algorithms first generate an affinity graph and then partition it. We present a machine learning approach to computing an affinity graph using a convolutional network (CN) trained using ground truth provided by human experts. The CN affinity graph can be paired with any standard partitioning algorithm and improves segmentation accuracy significantly compared to standard hand-designed affinity functions.We apply our algorithm to the challenging 3D segmentation problem of reconstructing neuronal processes from volumetric electron microscopy (EM) and show that we are able to learn a good affinity graph directly from the raw EM images. Further, we show that our affinity graph improves the segmentation accuracy of both simple and sophisticated graph partitioning algorithms.In contrast to previous work, we do not rely on prior knowledge in the form of hand-designed image features or image preprocessing. Thus, we expect our algorithm to generalize effectively to arbitrary image types.}",
    issn = {0899-7667},
    doi = {10.1162/neco.2009.10-08-881},
    url = {https://doi.org/10.1162/neco.2009.10-08-881},
    eprint = {https://direct.mit.edu/neco/article-pdf/22/2/511/830538/neco.2009.10-08-881.pdf},
}





@article{Konishi2021,
    author = {Konishi, Kohki and Nonaka, Takao and Takei, Shunsuke and Ohta, Keisuke and Nishioka, Hideo and Suga, Mitsuo},
    title = "{Reducing manual operation time to obtain a segmentation learning model for volume electron microscopy using stepwise deep learning with manual correction}",
    journal = {Microscopy},
    year = {2021},
    month = {07},
    abstract = "{Three-dimensional (3D) observation of a biological sample using serial-section electron microscopy is widely used. However, organelle segmentation requires a significant amount of manual time. Therefore, several studies have been conducted to improve organelle segmentation’s efficiency. One such promising method is 3D deep learning (DL), which is highly accurate. However, the creation of training data for 3D DL still requires manual time and effort. In this study, we developed a highly efficient integrated image segmentation tool that includes stepwise DL with manual correction. The tool has four functions: efficient tracers for annotation, model training/inference for organelle segmentation using a lightweight convolutional neural network, efficient proofreading and model refinement. We applied this tool to increase the training data step by step (stepwise annotation method) to segment the mitochondria in the cells of the cerebral cortex. We found that the stepwise annotation method reduced the manual operation time by one-third compared with the fully manual method, where all the training data were created manually. Moreover, we demonstrated that the F1 score, the metric of segmentation accuracy, was 0.9 by training the 3D DL model with these training data. The stepwise annotation method using this tool and the 3D DL model improved the segmentation efficiency of various organelles.}",
    issn = {2050-5701},
    doi = {10.1093/jmicro/dfab025},
    url = {https://doi.org/10.1093/jmicro/dfab025},
    note = {dfab025},
    eprint = {https://academic.oup.com/jmicro/advance-article-pdf/doi/10.1093/jmicro/dfab025/39311626/dfab025.pdf},
}





@article{Konishi2019,
    author = {Konishi, Kohki and Mimura, Masafumi and Nonaka, Takao and Sase, Ichiro and Nishioka, Hideo and Suga, Mitsuo},
    title = "{Practical method of cell segmentation in electron microscope image stack using deep convolutional neural network☆}",
    journal = {Microscopy},
    volume = {68},
    number = {4},
    pages = {338-341},
    year = {2019},
    month = {03},
    abstract = "{Segmentation of three-dimensional (3D) electron microscopy (EM) image stacks is an arduous and tedious task. Deep convolutional neural networks (CNNs) work well to automate the segmentation; however, they require a large training dataset, which is a major impediment. In order to solve this issue, especially for sparse segmentation, we used a CNN with a minimal training dataset. We segmented a Cerebellar Purkinje cell from an image stack of a mouse Cerebellum cortex in less than two working days, which is much shorter than that of the conventional method. We concluded that we can reduce the total labor time for the sparse segmentation by reducing the training dataset.}",
    issn = {2050-5698},
    doi = {10.1093/jmicro/dfz016},
    url = {https://doi.org/10.1093/jmicro/dfz016},
    eprint = {https://academic.oup.com/jmicro/article-pdf/68/4/338/29967423/dfz016.pdf},
}



@Article{Fang2018,
author={Fang, Tao
and Lu, Xiaotang
and Berger, Daniel
and Gmeiner, Christina
and Cho, Julia
and Schalek, Richard
and Ploegh, Hidde
and Lichtman, Jeff},
title={Nanobody immunostaining for correlated light and electron microscopy with preservation of ultrastructure},
journal={Nature Methods},
year={2018},
month={Dec},
day={01},
volume={15},
number={12},
pages={1029-1032},
abstract={Morphological and molecular characteristics determine the function of biological tissues. Attempts to combine immunofluorescence and electron microscopy invariably compromise the quality of the ultrastructure of tissue sections. We developed NATIVE, a correlated light and electron microscopy approach that preserves ultrastructure while showing the locations of multiple molecular moieties, even deep within tissues. This technique allowed the large-scale 3D reconstruction of a volume of mouse hippocampal CA3 tissue at nanometer resolution.},
issn={1548-7105},
doi={10.1038/s41592-018-0177-x},
url={https://doi.org/10.1038/s41592-018-0177-x}
}



@Article{Weinhard2018,
author={Weinhard, Laetitia
and di Bartolomei, Giulia
and Bolasco, Giulia
and Machado, Pedro
and Schieber, Nicole L.
and Neniskyte, Urte
and Exiga, Melanie
and Vadisiute, Auguste
and Raggioli, Angelo
and Schertel, Andreas
and Schwab, Yannick
and Gross, Cornelius T.},
title={Microglia remodel synapses by presynaptic trogocytosis and spine head filopodia induction},
journal={Nature Communications},
year={2018},
month={Mar},
day={26},
volume={9},
number={1},
pages={1228},
abstract={Microglia are highly motile glial cells that are proposed to mediate synaptic pruning during neuronal circuit formation. Disruption of signaling between microglia and neurons leads to an excess of immature synaptic connections, thought to be the result of impaired phagocytosis of synapses by microglia. However, until now the direct phagocytosis of synapses by microglia has not been reported and fundamental questions remain about the precise synaptic structures and phagocytic mechanisms involved. Here we used light sheet fluorescence microscopy to follow microglia--synapse interactions in developing organotypic hippocampal cultures, complemented by a 3D ultrastructural characterization using correlative light and electron microscopy (CLEM). Our findings define a set of dynamic microglia--synapse interactions, including the selective partial phagocytosis, or trogocytosis (trogo-: nibble), of presynaptic structures and the induction of postsynaptic spine head filopodia by microglia. These findings allow us to propose a mechanism for the facilitatory role of microglia in synaptic circuit remodeling and maturation.},
issn={2041-1723},
doi={10.1038/s41467-018-03566-5},
url={https://doi.org/10.1038/s41467-018-03566-5}
}



@article{LUCKNER2018,
title = {Label-free 3D-CLEM Using Endogenous Tissue Landmarks},
journal = {iScience},
volume = {6},
pages = {92-101},
year = {2018},
issn = {2589-0042},
doi = {https://doi.org/10.1016/j.isci.2018.07.012},
url = {https://www.sciencedirect.com/science/article/pii/S2589004218301007},
author = {Manja Luckner and Steffen Burgold and Severin Filser and Maximilian Scheungrab and Yilmaz Niyaz and Eric Hummel and Gerhard Wanner and Jochen Herms},
keywords = {Neuroscience, Techniques in Neuroscience, Biological Sciences Research Methodologies, Biological Sciences Tools},
abstract = {Summary
Emerging 3D correlative light and electron microscopy approaches enable studying neuronal structure-function relations at unprecedented depth and precision. However, established protocols for the correlation of light and electron micrographs rely on the introduction of artificial fiducial markers, such as polymer beads or near-infrared brandings, which might obscure or even damage the structure under investigation. Here, we report a general applicable “flat embedding” preparation, enabling high-precision overlay of light and scanning electron micrographs, using exclusively endogenous landmarks in the brain: blood vessels, nuclei, and myelinated axons. Furthermore, we demonstrate feasibility of the workflow by combining in vivo 2-photon microscopy and focused ion beam scanning electron microscopy to dissect the role of astrocytic coverage in the persistence of dendritic spines.}
}

@Article{Oorschot2021,
author={Oorschot, Viola
and Lindsey, Benjamin W.
and Kaslin, Jan
and Ramm, Georg},
title={TEM, SEM, and STEM-based immuno-CLEM workflows offer complementary advantages},
journal={Scientific Reports},
year={2021},
month={Jan},
day={13},
volume={11},
number={1},
pages={899},
abstract={Identifying endogenous tissue stem cells remains a key challenge in developmental and regenerative biology. To distinguish and molecularly characterise stem cell populations in large heterogeneous tissues, the combination of cytochemical cell markers with ultrastructural morphology is highly beneficial. Here, we realise this through workflows of multi-resolution immuno-correlative light and electron microscopy (iCLEM) methodologies. Taking advantage of the antigenicity preservation of the Tokuyasu technique, we have established robust protocols and workflows and provide a side-by-side comparison of iCLEM used in combination with scanning EM (SEM), scanning TEM (STEM), or transmission EM (TEM). Evaluation of the applications and advantages of each method highlights their practicality for the identification, quantification, and characterization of heterogeneous cell populations in small organisms, organs, or tissues in healthy and diseased states. The iCLEM techniques are broadly applicable and can use either genetically encoded or cytochemical markers on plant, animal and human tissues. We demonstrate how these protocols are particularly suited for investigating neural stem and progenitor cell populations of the vertebrate nervous system.},
issn={2045-2322},
doi={10.1038/s41598-020-79637-9},
url={https://doi.org/10.1038/s41598-020-79637-9}
}


@Article{Miyaki2020,
author={Miyaki, Takayuki
and Kawasaki, Yuto
and Hosoyamada, Yasue
and Amari, Takashi
and Kinoshita, Mui
and Matsuda, Hironori
and Kakuta, Soichiro
and Sakai, Tatsuo
and Ichimura, Koichiro},
title={Three-dimensional imaging of podocyte ultrastructure using FE-SEM and FIB-SEM tomography},
journal={Cell and Tissue Research},
year={2020},
month={Feb},
day={01},
volume={379},
number={2},
pages={245-254},
abstract={Podocytes are specialized epithelial cells used for glomerular filtration in the kidney. They can be divided into the cell body, primary process and foot process. Here, we describe two useful methods for the three-dimensional(3D) visualization of these subcellular compartments in rodent podocytes. The first method, field-emission scanning electron microscopy (FE-SEM) with conductive staining, is used to visualize the luminal surface of numerous podocytes simultaneously. The second method, focused-ion beam SEM (FIB-SEM) tomography, allows the user to obtain serial images from different depths of field, or Z-stacks, of the glomerulus. This allows for the 3D reconstruction of podocyte ultrastructure, which can be viewed from all angles, from a single image set. This is not possible with conventional FE-SEM. The different advantages and disadvantages of FE-SEM and FIB-SEM tomography compensate for the weaknesses of the other. The combination renders a powerful approach for the 3D analysis of podocyte ultrastructure. As a result, we were able to identify a new subcellular compartment of podocytes, ``ridge-like prominences'' (RLPs).},
issn={1432-0878},
doi={10.1007/s00441-019-03118-3},
url={https://doi.org/10.1007/s00441-019-03118-3}
}





@Inbook{Xu2020fib,
author="Xu, C. Shan
and Pang, Song
and Hayworth, Kenneth J.
and Hess, Harald F.",
editor="Wacker, Irene
and Hummel, Eric
and Burgold, Steffen
and Schr{\"o}der, Rasmus",
title="Transforming FIB-SEMFocused Ion Beam Scanning Electron Microscopy (FIB-SEM)Systems for Large-Volume ConnectomicsConnectomics and Cell BiologyCell biology",
bookTitle="Volume Microscopy : Multiscale Imaging with Photons, Electrons, and Ions",
year="2020",
publisher="Springer US",
address="New York, NY",
pages="221--243",
abstract="Isotropic high-resolution imaging of large volumes provides unprecedented opportunities to advance connectomics and cell biology research. Conventional focused ion beam scanning electron microscopy (FIB-SEM) offers unique benefits such as high resolution (<10 nm in x, y, and z), robust image alignment, and minimal artifacts for superior tracing of neurites. However, its prevailing deficiencies in imaging speed and duration cap the maximum possible image volume. We have developed technologies to overcome these limitations, thereby expanding the image volume of FIB-SEM by more than four orders of magnitude from 103 $\mu$m3 to 3 {\texttimes} 107 $\mu$m3 while maintaining an isotropic resolution of 8 {\texttimes} 8 {\texttimes} 8 nm3 voxels. These expanded volumes are now large enough to support connectomic studies, in which the superior z resolution enables automated tracing of fine neurites and reduces the time-consuming human proofreading effort. Moreover, by trading off imaging speed, the system can readily be operated at even higher resolutions achieving voxel sizes of 4 {\texttimes} 4 {\texttimes} 4 nm3, thereby generating ground truth of the smallest organelles for machine learning in connectomics and providing important insights into cell biology. Primarily limited by time, the maximum volume can be greatly extended.",
isbn="978-1-0716-0691-9",
doi="10.1007/978-1-0716-0691-9_12",
url="https://doi.org/10.1007/978-1-0716-0691-9_12"
}


@article{Muller2020,
    author = {Müller, Andreas and Schmidt, Deborah and Xu, C. Shan and Pang, Song and D’Costa, Joyson Verner and Kretschmar, Susanne and Münster, Carla and Kurth, Thomas and Jug, Florian and Weigert, Martin and Hess, Harald F. and Solimena, Michele},
    title = "{3D FIB-SEM reconstruction of microtubule–organelle interaction in whole primary mouse β cells}",
    journal = {Journal of Cell Biology},
    volume = {220},
    number = {2},
    year = {2020},
    month = {12},
    abstract = "{Microtubules play a major role in intracellular trafficking of vesicles in endocrine cells. Detailed knowledge of microtubule organization and their relation to other cell constituents is crucial for understanding cell function. However, their role in insulin transport and secretion is under debate. Here, we use FIB-SEM to image islet β cells in their entirety with unprecedented resolution. We reconstruct mitochondria, Golgi apparati, centrioles, insulin secretory granules, and microtubules of seven β cells, and generate a comprehensive spatial map of microtubule–organelle interactions. We find that microtubules form nonradial networks that are predominantly not connected to either centrioles or endomembranes. Microtubule number and length, but not microtubule polymer density, vary with glucose stimulation. Furthermore, insulin secretory granules are enriched near the plasma membrane, where they associate with microtubules. In summary, we provide the first 3D reconstructions of complete microtubule networks in primary mammalian cells together with evidence regarding their importance for insulin secretory granule positioning and thus their supportive role in insulin secretion.}",
    issn = {0021-9525},
    doi = {10.1083/jcb.202010039},
    url = {https://doi.org/10.1083/jcb.202010039},
    note = {e202010039},
    eprint = {https://rupress.org/jcb/article-pdf/220/2/e202010039/1406548/jcb\_202010039.pdf},
}


@article{Berger2018,
AUTHOR={Berger, Daniel R. and Seung, H. Sebastian and Lichtman, Jeff W.},   
TITLE={VAST (Volume Annotation and Segmentation Tool): Efficient Manual and Semi-Automatic Labeling of Large 3D Image Stacks},      
JOURNAL={Frontiers in Neural Circuits},      
VOLUME={12},           
YEAR={2018},      
URL={https://www.frontiersin.org/articles/10.3389/fncir.2018.00088},       
DOI={10.3389/fncir.2018.00088},      
ISSN={1662-5110},   
ABSTRACT={Recent developments in serial-section electron microscopy allow the efficient generation of very large image data sets but analyzing such data poses challenges for software tools. Here we introduce Volume Annotation and Segmentation Tool (VAST), a freely available utility program for generating and editing annotations and segmentations of large volumetric image (voxel) data sets. It provides a simple yet powerful user interface for real-time exploration and analysis of large data sets even in the Petabyte range.}
}

@Article{Urakubo2019,
author={Urakubo, Hidetoshi
and Bullmann, Torsten
and Kubota, Yoshiyuki
and Oba, Shigeyuki
and Ishii, Shin},
title={UNI-EM: An Environment for Deep Neural Network-Based Automated Segmentation of Neuronal Electron Microscopic Images},
journal={Scientific Reports},
year={2019},
month={Dec},
day={19},
volume={9},
number={1},
pages={19413},
abstract={Recently, there has been rapid expansion in the field of micro-connectomics, which targets the three-dimensional (3D) reconstruction of neuronal networks from stacks of two-dimensional (2D) electron microscopy (EM) images. The spatial scale of the 3D reconstruction increases rapidly owing to deep convolutional neural networks (CNNs) that enable automated image segmentation. Several research teams have developed their own software pipelines for CNN-based segmentation. However, the complexity of such pipelines makes their use difficult even for computer experts and impossible for non-experts. In this study, we developed a new software program, called UNI-EM, for 2D and 3D CNN-based segmentation. UNI-EM is a software collection for CNN-based EM image segmentation, including ground truth generation, training, inference, postprocessing, proofreading, and visualization. UNI-EM incorporates a set of 2D CNNs, i.e., U-Net, ResNet, HighwayNet, and DenseNet. We further wrapped flood-filling networks (FFNs) as a representative 3D CNN-based neuron segmentation algorithm. The 2D- and 3D-CNNs are known to demonstrate state-of-the-art level segmentation performance. We then provided two example workflows: mitochondria segmentation using a 2D CNN and neuron segmentation using FFNs. By following these example workflows, users can benefit from CNN-based segmentation without possessing knowledge of Python programming or CNN frameworks.},
issn={2045-2322},
doi={10.1038/s41598-019-55431-0},
url={https://doi.org/10.1038/s41598-019-55431-0}
}



@article{Ronchi2021,
    author = {Ronchi, Paolo and Mizzon, Giulia and Machado, Pedro and D’Imprima, Edoardo and Best, Benedikt T. and Cassella, Lucia and Schnorrenberg, Sebastian and Montero, Marta G. and Jechlinger, Martin and Ephrussi, Anne and Leptin, Maria and Mahamid, Julia and Schwab, Yannick},
    title = "{High-precision targeting workflow for volume electron microscopy}",
    journal = {Journal of Cell Biology},
    volume = {220},
    number = {9},
    year = {2021},
    month = {06},
    abstract = "{Cells are 3D objects. Therefore, volume EM (vEM) is often crucial for correct interpretation of ultrastructural data. Today, scanning EM (SEM) methods such as focused ion beam (FIB)–SEM are frequently used for vEM analyses. While they allow automated data acquisition, precise targeting of volumes of interest within a large sample remains challenging. Here, we provide a workflow to target FIB-SEM acquisition of fluorescently labeled cells or subcellular structures with micrometer precision. The strategy relies on fluorescence preservation during sample preparation and targeted trimming guided by confocal maps of the fluorescence signal in the resin block. Laser branding is used to create landmarks on the block surface to position the FIB-SEM acquisition. Using this method, we acquired volumes of specific single cells within large tissues such as 3D cultures of mouse mammary gland organoids, tracheal terminal cells in Drosophila melanogaster larvae, and ovarian follicular cells in adult Drosophila, discovering ultrastructural details that could not be appreciated before.}",
    issn = {0021-9525},
    doi = {10.1083/jcb.202104069},
    url = {https://doi.org/10.1083/jcb.202104069},
    note = {e202104069},
    eprint = {https://rupress.org/jcb/article-pdf/220/9/e202104069/1418512/jcb\_202104069.pdf},
}

@Article{Kim2016,
author={Kim, Gyu Hyun
and Gim, Ja Won
and Lee, Kea Joo},
title={Nano-Resolution Connectomics Using Large-Volume Electron Microscopy},
journal={Applied Microscopy},
year={2016},
month={Dec},
edition={2016/12/30},
publisher={Korean Society of Microscopy},
volume={46},
number={4},
pages={171-175},
keywords={Synapse; Neuron; Circuit; Electron microscopy; Brain mapping},
abstract={A distinctive neuronal network in the brain is believed to make us unique individuals. Electron microscopy is a valuable tool for examining ultrastructural characteristics of neurons, synapses, and subcellular organelles. A recent technological breakthrough in volume electron microscopy allows large-scale circuit reconstruction of the nervous system with unprecedented detail. Serial-section electron microscopy?previously the domain of specialists?became automated with the advent of innovative systems such as the focused ion beam and serial block-face scanning electron microscopes and the automated tape-collecting ultramicrotome. Further advances in microscopic design and instrumentation are also available, which allow the reconstruction of unprecedentedly large volumes of brain tissue at high speed. The recent introduction of correlative light and electron microscopy will help to identify specific neural circuits associated with behavioral characteristics and revolutionize our understanding of how the brain works.},
issn={2287-5123},
doi={10.9729/AM.2016.46.4.171},
url={http:///journal/view.html?doi=10.9729/AM.2016.46.4.171},
url={https://doi.org/10.9729/AM.2016.46.4.171},
language={eng}
}

@Article{Xu2021,
author={Xu, C. Shan
and Pang, Song
and Shtengel, Gleb
and M{\"u}ller, Andreas
and Ritter, Alex T.
and Hoffman, Huxley K.
and Takemura, Shin-ya
and Lu, Zhiyuan
and Pasolli, H. Amalia
and Iyer, Nirmala
and Chung, Jeeyun
and Bennett, Davis
and Weigel, Aubrey V.
and Freeman, Melanie
and van Engelenburg, Schuyler B.
and Walther, Tobias C.
and Farese, Robert V.
and Lippincott-Schwartz, Jennifer
and Mellman, Ira
and Solimena, Michele
and Hess, Harald F.},
title={An open-access volume electron microscopy atlas of whole cells and tissues},
journal={Nature},
year={2021},
month={Oct},
day={06},
abstract={Understanding cellular architecture is essential for understanding biology. Electron microscopy (EM) uniquely visualizes cellular structures with nanometre resolution. However, traditional methods, such as thin-section EM or EM tomography, have limitations in that they visualize only a single slice or a relatively small volume of the cell, respectively. Focused ion beam-scanning electron microscopy (FIB-SEM) has demonstrated the ability to image small volumes of cellular samples with 4-nm isotropic voxels1. Owing to advances in the precision and stability of FIB milling, together with enhanced signal detection and faster SEM scanning, we have increased the volume that can be imaged with 4-nm voxels by two orders of magnitude. Here we present a volume EM atlas at such resolution comprising ten three-dimensional datasets for whole cells and tissues, including cancer cells, immune cells, mouse pancreatic islets and Drosophila neural tissues. These open access data (via OpenOrganelle2) represent the foundation of a field of high-resolution whole-cell volume EM and subsequent analyses, and we invite researchers to explore this atlas and pose questions.},
issn={1476-4687},
doi={10.1038/s41586-021-03992-4},
url={https://doi.org/10.1038/s41586-021-03992-4}
}



@article {Xu2017,
article_type = {journal},
title = {Enhanced FIB-SEM systems for large-volume 3D imaging},
author = {Xu, C Shan and Hayworth, Kenneth J and Lu, Zhiyuan and Grob, Patricia and Hassan, Ahmed M and García-Cerdán, José G and Niyogi, Krishna K and Nogales, Eva and Weinberg, Richard J and Hess, Harald F},
editor = {Nathans, Jeremy},
volume = 6,
year = 2017,
month = {may},
pub_date = {2017-05-13},
pages = {e25916},
citation = {eLife 2017;6:e25916},
doi = {10.7554/eLife.25916},
url = {https://doi.org/10.7554/eLife.25916},
abstract = {Focused Ion Beam Scanning Electron Microscopy (FIB-SEM) can automatically generate 3D images with superior z-axis resolution, yielding data that needs minimal image registration and related post-processing. Obstacles blocking wider adoption of FIB-SEM include slow imaging speed and lack of long-term system stability, which caps the maximum possible acquisition volume. Here, we present techniques that accelerate image acquisition while greatly improving FIB-SEM reliability, allowing the system to operate for months and generating continuously imaged volumes > 10\textsuperscript{6} µm\textsuperscript{3}. These volumes are large enough for connectomics, where the excellent z resolution can help in tracing of small neuronal processes and accelerate the tedious and time-consuming human proofreading effort. Even higher resolution can be achieved on smaller volumes. We present example data sets from mammalian neural tissue, \textit{Drosophila} brain, and \textit{Chlamydomonas reinhardtii} to illustrate the power of this novel high-resolution technique to address questions in both connectomics and cell biology.},
keywords = {connectomics, 3D cellular structure, electron microscopy, imaging, FIB},
journal = {eLife},
issn = {2050-084X},
publisher = {eLife Sciences Publications, Ltd},
}


@Article{Schneider2020,
AUTHOR = {Schneider, Jan Philipp and Wrede, Christoph and Mühlfeld, Christian},
TITLE = {The Three-Dimensional Ultrastructure of the Human Alveolar Epithelium Revealed by Focused Ion Beam Electron Microscopy},
JOURNAL = {International Journal of Molecular Sciences},
VOLUME = {21},
YEAR = {2020},
NUMBER = {3},
ARTICLE-NUMBER = {1089},
URL = {https://www.mdpi.com/1422-0067/21/3/1089},
PubMedID = {32041332},
ISSN = {1422-0067},
ABSTRACT = {Thin type 1 alveolar epithelial (AE1) and surfactant producing type 2 alveolar epithelial (AE2) cells line the alveoli in the lung and are essential for normal lung function. Function is intimately interrelated to structure, so that detailed knowledge of the epithelial ultrastructure can significantly enhance our understanding of its function. The basolateral surface of the cells or the epithelial contact sites are of special interest, because they play an important role in intercellular communication or stabilizing the epithelium. The latter is in particular important for the lung with its variable volume. The aim of the present study was to investigate the three-dimensional (3D) ultrastructure of the human alveolar epithelium focusing on contact sites and the basolateral cell membrane of AE2 cells using focused ion beam electron microscopy and subsequent 3D reconstructions. The study provides detailed surface reconstructions of two AE1 cell domains and two AE2 cells, showing AE1/AE1, AE1/AE2 and AE2/AE2 contact sites, basolateral microvilli pits at AE2 cells and small AE1 processes beneath AE2 cells. Furthermore, we show reconstructions of a surfactant secretion pore, enlargements of the apical AE1 cell surface and long folds bordering grooves on the basal AE1 cell surface. The functional implications of our findings are discussed. These findings may lay the structural basis for further molecular investigations.},
DOI = {10.3390/ijms21031089}
}





@article{Miyamoto2020,
author = {Miyamoto, Tatsuo and Hosoba, Kosuke and Itabashi, Takeshi and Iwane, Atsuko H and Akutsu, Silvia Natsuko and Ochiai, Hiroshi and Saito, Yumiko and Yamamoto, Takashi and Matsuura, Shinya},
title = {Insufficiency of ciliary cholesterol in hereditary Zellweger syndrome},
journal = {The EMBO Journal},
volume = {39},
number = {12},
pages = {e103499},
keywords = {cholesterol, ciliopathy, primary cilia, Zellweger syndrome},
doi = {https://doi.org/10.15252/embj.2019103499},
url = {https://www.embopress.org/doi/abs/10.15252/embj.2019103499},
eprint = {https://www.embopress.org/doi/pdf/10.15252/embj.2019103499},
abstract = {Abstract Primary cilia are antenna-like organelles on the surface of most mammalian cells that receive sonic hedgehog (Shh) signaling in embryogenesis and carcinogenesis. Cellular cholesterol functions as a direct activator of a seven-transmembrane oncoprotein called Smoothened (Smo) and thereby induces Smo accumulation on the ciliary membrane where it transduces the Shh signal. However, how cholesterol is supplied to the ciliary membrane remains unclear. Here, we report that peroxisomes are essential for the transport of cholesterol into the ciliary membrane. Zellweger syndrome (ZS) is a peroxisome-deficient hereditary disorder with several ciliopathy-related features and cells from these patients showed a reduced cholesterol level in the ciliary membrane. Reverse genetics approaches revealed that the GTP exchange factor Rabin8, the Rab GTPase Rab10, and the microtubule minus-end-directed kinesin KIFC3 form a peroxisome-associated complex to control the movement of peroxisomes along microtubules, enabling communication between peroxisomes and ciliary pocket membranes. Our findings suggest that insufficient ciliary cholesterol levels may underlie ciliopathies.},
year = {2020}
}



@ARTICLE{Kawasaki2021,
AUTHOR={Kawasaki, Yuto and Hosoyamada, Yasue and Miyaki, Takayuki and Yamaguchi, Junji and Kakuta, Soichiro and Sakai, Tatsuo and Ichimura, Koichiro},   
TITLE={Three-Dimensional Architecture of Glomerular Endothelial Cells Revealed by FIB-SEM Tomography},      
JOURNAL={Frontiers in Cell and Developmental Biology},      
VOLUME={9},      
PAGES={339},     
YEAR={2021},      
URL={https://www.frontiersin.org/article/10.3389/fcell.2021.653472},       
DOI={10.3389/fcell.2021.653472},      
ISSN={2296-634X},   
ABSTRACT={Focused-ion beam-scanning electron microscopic (FIB-SEM) tomography enables easier acquisition of a series of ultrastructural, sectional images directly from resin-embedded biological samples. In this study, to clarify the three-dimensional (3D) architecture of glomerular endothelial cells (GEnCs) in adult rats, we manually extracted GEnCs from serial FIB-SEM images and reconstructed them on an Amira reconstruction software. The luminal and basal surface structures were clearly visualized in the reconstructed GEnCs, although only the luminal surface structures could be observed by conventional SEM. The luminal surface visualized via the reconstructed GEnCs was quite similar to that observed through conventional SEM, indicating that 3D reconstruction could be performed with high accuracy. Thus, we successfully described the 3D architecture of normal GEnCs in adult rats more clearly and precisely than ever before. The GEnCs were found to consist of three major subcellular compartments, namely, the cell body, cytoplasmic ridges, and sieve plates, in addition to two associated subcellular compartments, namely, the globular protrusions and reticular porous structures. Furthermore, most individual GEnCs made up a “seamless” tubular shape, and some of them formed an autocellular junction to make up a tubular shape. FIB-SEM tomography with reconstruction is a powerful approach to better understand the 3D architecture of GEnCs. Moreover, the morphological information revealed in this study will be valuable for the 3D pathologic evaluation of GEnCs in animal and human glomerular diseases and the structural analysis of developmental processes in the glomerular capillary system.}
}

@Article{Hirashima2019,
author={Hirashima, Shingo
and Ohta, Keisuke
and Kanazawa, Tomonoshin
and Togo, Akinobu
and Kakuma, Tatsuyuki
and Kusukawa, Jingo
and Nakamura, Kei-ichiro},
title={Three-dimensional ultrastructural and histomorphological analysis of the periodontal ligament with occlusal hypofunction via focused ion beam/scanning electron microscope tomography},
journal={Scientific Reports},
year={2019},
month={Jul},
day={02},
volume={9},
number={1},
pages={9520},
abstract={The periodontal ligament (PDL) maintains the environment and function of the periodontium. The PDL has been remodelled in accordance with changes in mechanical loading. Three-dimensional (3D) structural data provide essential information regarding PDL function and dysfunction. However, changes in mechanical loading associated with structural changes in the PDL are poorly understood at the mesoscale. This study aimed to investigate 3D ultrastructural and histomorphometric changes in PDL cells and fibres associated with unloading condition (occlusal hypofunction), using focused ion beam/scanning electron microscope tomography, and to quantitatively analyse the structural properties of PDL cells and fibres. PDL cells formed cellular networks upon morphological changes induced via changes in mechanical loading condition. Drastic changes were observed in a horizontal array of cells, with a sparse and disorganised area of collagen bundles. Furthermore, collagen bundles tended to be thinner than those in the control group. FIB/SEM tomography enables easier acquisition of serial ultrastructural images and quantitative 3D data. This method is powerful for revealing 3D architecture in complex tissues. Our results may help elucidate architectural changes in the PDL microenvironment during changes in mechanical loading condition and regeneration, and advance a wide variety of treatments in dentistry.},
issn={2045-2322},
doi={10.1038/s41598-019-45963-w},
url={https://doi.org/10.1038/s41598-019-45963-w}
}



@Article{Hirashima2016,
author={Hirashima, Shingo
and Ohta, Keisuke
and Kanazawa, Tomonoshin
and Okayama, Satoko
and Togo, Akinobu
and Uchimura, Naohisa
and Kusukawa, Jingo
and Nakamura, Kei-ichiro},
title={Three-dimensional ultrastructural analysis of cells in the periodontal ligament using focused ion beam/scanning electron microscope tomography},
journal={Scientific Reports},
year={2016},
month={Dec},
day={20},
volume={6},
number={1},
pages={39435},
abstract={The accurate comprehension of normal tissue provides essential data to analyse abnormalities such as disease and regenerative processes. In addition, understanding the proper structure of the target tissue and its microenvironment may facilitate successful novel treatment strategies. Many studies have examined the nature and structure of periodontal ligaments (PDLs); however, the three-dimensional (3D) structure of cells in normal PDLs remains poorly understood. In this study, we used focused ion beam/scanning electron microscope tomography to investigate the whole 3D ultrastructure of PDL cells along with quantitatively analysing their structural properties and ascertaining their orientation to the direction of the collagen fibre. PDL cells were shown to be in contact with each other, forming a widespread mesh-like network between the cementum and the alveolar bone. The volume of the cells in the horizontal fibre area was significantly larger than in other areas, whereas the anisotropy of these cells was lower than in other areas. Furthermore, the orientation of cells to the PDL fibres was not parallel to the PDL fibres in each area. As similar evaluations are recognized as being challenging using conventional two-dimensional methods, these novel 3D findings may contribute necessary knowledge for the comprehensive understanding and analysis of PDLs.},
issn={2045-2322},
doi={10.1038/srep39435},
url={https://doi.org/10.1038/srep39435}
}



@article{Robles2019,
title = {Characterization of the bone marrow adipocyte niche with three-dimensional electron microscopy},
journal = {Bone},
volume = {118},
pages = {89-98},
year = {2019},
note = {Bone Marrow Adiposity: Form, Function and Relation to Bone Remodeling},
issn = {8756-3282},
doi = {https://doi.org/10.1016/j.bone.2018.01.020},
url = {https://www.sciencedirect.com/science/article/pii/S8756328218300206},
author = {Hero Robles and SungJae Park and Matthew S. Joens and James A.J. Fitzpatrick and Clarissa S. Craft and Erica L. Scheller},
keywords = {Bone marrow, Ultrastructure, Adipocyte, Fat, Hematopoiesis, Erythropoiesis, Anemia, Bone marrow adipose tissue},
abstract = {Unlike white and brown adipose tissues, the bone marrow adipocyte (BMA) exists in a microenvironment containing unique populations of hematopoietic and skeletal cells. To study this microenvironment at the sub-cellular level, we performed a three-dimensional analysis of the ultrastructure of the BMA niche with focused ion beam scanning electron microscopy (FIB-SEM). This revealed that BMAs display hallmarks of metabolically active cells including polarized lipid deposits, a dense mitochondrial network, and areas of endoplasmic reticulum. The distinct orientations of the triacylglycerol droplets suggest that fatty acids are taken up and/or released in three key areas – at the endothelial interface, into the hematopoietic milieu, and at the bone surface. Near the sinusoidal vasculature, endothelial cells send finger-like projections into the surface of the BMA which terminate near regions of lipid within the BMA cytoplasm. In some regions, perivascular cells encase the BMA with their flattened cellular projections, limiting contacts with other cells in the niche. In the hematopoietic milieu, BMAT adipocytes of the proximal tibia interact extensively with maturing cells of the myeloid/granulocyte lineage. Associations with erythroblast islands are also prominent. At the bone surface, the BMA extends organelle and lipid-rich cytoplasmic regions toward areas of active osteoblasts. This suggests that the BMA may serve to partition nutrient utilization between diverse cellular compartments, serving as an energy-rich hub of the stromal-reticular network. Lastly, though immuno-EM, we've identified a subset of bone marrow adipocytes that are innervated by the sympathetic nervous system, providing an additional mechanism for regulation of the BMA. In summary, this work reveals that the bone marrow adipocyte is a dynamic cell with substantial capacity for interactions with the diverse components of its surrounding microenvironment. These local interactions likely contribute to its unique regulation relative to peripheral adipose tissues.}
}

@Article{Murata2019,
author={Murata, Kazuhisa
and Hirata, Akira
and Ohta, Keisuke
and Enaida, Hiroshi
and Nakamura, Kei-ichiro},
title={Morphometric analysis in mouse scleral fibroblasts using focused ion beam/scanning electron microscopy},
journal={Scientific Reports},
year={2019},
month={Apr},
day={19},
volume={9},
number={1},
pages={6329},
abstract={The sclera as well as the cornea forms the principal part of the outer fibrous coat of the eye, with a primary function of protecting the intraocular contents and maintaining the shape of the globe. However, the exact morphometric arrangement of scleral fibroblasts remains unclarified. The aim of this study was to observe the three-dimensional structure of the mouse scleral fibroblasts by focused ion beam/scanning electron microscopy (FIB/SEM). Four eyes from C57BL/6J mice were fixed using a mixture of glutaraldehyde and formaldehyde. The sclera was cut out at the equatorial portion and the posterior pole, and postfixed with potassium ferrocyanide, osmium, thiocarbohydrazide, uranyl acetate and lead aspartate. Specimens were then dehydrated and embedded in an epoxy resin. Serial block face images were obtained using FIB/SEM. Three-dimensional image reconstruction and segmentation of the image stack were created using computer software (Amira v6.0.1, FEI). Scleral fibroblasts were arranged in collagenous layers. The cells frequently showed a cellular junction with the neighboring cells and formed cellular networks. Compared with equatorial fibroblasts, there was a more complicated cellular arrangement of the posterior scleral fibroblasts.},
issn={2045-2322},
doi={10.1038/s41598-019-42758-x},
url={https://doi.org/10.1038/s41598-019-42758-x}
}




@article {Knott2008,
	author = {Knott, Graham and Marchman, Herschel and Wall, David and Lich, Ben},
	title = {Serial Section Scanning Electron Microscopy of Adult Brain Tissue Using Focused Ion Beam Milling},
	volume = {28},
	number = {12},
	pages = {2959--2964},
	year = {2008},
	doi = {10.1523/JNEUROSCI.3189-07.2008},
	publisher = {Society for Neuroscience},
	issn = {0270-6474},
	URL = {https://www.jneurosci.org/content/28/12/2959},
	eprint = {https://www.jneurosci.org/content/28/12/2959.full.pdf},
	journal = {Journal of Neuroscience}
}

@article{Ede2021,
	doi = {10.1088/2632-2153/abd614},
	url = {https://doi.org/10.1088/2632-2153/abd614},
	year = 2021,
	month = {mar},
	publisher = {{IOP} Publishing},
	volume = {2},
	number = {1},
	pages = {011004},
	author = {Jeffrey M Ede},
	title = {Deep learning in electron microscopy},
	journal = {Machine Learning: Science and Technology},
	abstract = {Deep learning is transforming most areas of science and technology, including electron microscopy. This review paper offers a practical perspective aimed at developers with limited familiarity. For context, we review popular applications of deep learning in electron microscopy. Following, we discuss hardware and software needed to get started with deep learning and interface with electron microscopes. We then review neural network components, popular architectures, and their optimization. Finally, we discuss future directions of deep learning in electron microscopy.}
}

@ARTICLE{Brahim2020,  
AUTHOR={Brahim Belhaouari, Djamal and Fontanini, Anthony and Baudoin, Jean-Pierre and Haddad, Gabriel and Le Bideau, Marion and Bou Khalil, Jacques Yaacoub and Raoult, Didier and La Scola, Bernard},   
TITLE={The Strengths of Scanning Electron Microscopy in Deciphering SARS-CoV-2 Infectious Cycle},      
JOURNAL={Frontiers in Microbiology},      
VOLUME={11},     
PAGES={2014},     
YEAR={2020},      
URL={https://www.frontiersin.org/article/10.3389/fmicb.2020.02014},       
DOI={10.3389/fmicb.2020.02014},      
ISSN={1664-302X},   
ABSTRACT={Electron microscopy is a powerful tool in the field of microbiology. It has played a key role in the rapid diagnosis of viruses in patient samples and has contributed significantly to the clarification of virus structure and function, helping to guide the public health response to emerging viral infections. In the present study, we used scanning electron microscopy (SEM) to study the infectious cycle of SARS-CoV-2 in Vero E6 cells and we controlled some key findings by classical transmission electronic microscopy (TEM). The replication cycle of the virus was followed from 1 to 36 h post-infection. Our results revealed that SARS-CoV-2 infected the cells through membrane fusion. Particles are formed in the peri-nuclear region from a budding of the endoplasmic reticulum-Golgi apparatus complex into morphogenesis matrix vesicae. New SARS-CoV-2 particles were expelled from the cells, through cell lysis or by fusion of virus containing vacuoles with the cell plasma membrane. Overall, this cycle is highly comparable to that of SARS-CoV. By providing a detailed and complete SARS-CoV-2 infectious cycle, SEM proves to be a very rapid and efficient tool compared to classical TEM.}
}

@article {Koster2003,
	Title = {Electron microscopy in cell biology: integrating structure and function},
	Author = {Koster, Abraham J and Klumperman, Judith},
	Volume = {Suppl},
	Month = {September},
	Year = {2003},
	Journal = {Nature reviews. Molecular cell biology},
	ISSN = {1471-0072},
	Pages = {SS6—10},
	Abstract = {Electron microscopy (EM) is at the highest-resolution limit of a spectrum of complementary morphological techniques. When combined with molecular detection methods, EM is the only technique with sufficient resolution to localize proteins to small membrane subdomains in the context of the cell. Recent procedural and technical developments have increasingly improved the power of EM as a cell-biological tool.},
	URL = {http://europepmc.org/abstract/MED/14587520}
}

@article {Bozzola2002,
	Title = {Electron Microscopy},
	Author = {Bozzola, John J},
	Year = {2002},
	Journal = {In: Encyclopedia of Life Sciences},
	Pages = {1--10}
}

@article{Satir2005,
author = {Satir, Peter},
title = {Tour of organelles through the electron microscope: A reprinting of Keith R. Porter's classic Harvey Lecture with a new introduction},
journal = {The Anatomical Record Part A: Discoveries in Molecular, Cellular, and Evolutionary Biology},
volume = {287A},
number = {2},
pages = {1184-1204},
doi = {https://doi.org/10.1002/ar.a.20222},
url = {https://anatomypubs.onlinelibrary.wiley.com/doi/abs/10.1002/ar.a.20222},
eprint = {https://anatomypubs.onlinelibrary.wiley.com/doi/pdf/10.1002/ar.a.20222},
year = {2005}
}

@article{Borzunov2019,
title = {3D surface topography imaging in SEM with improved backscattered electron detector: Arrangement and reconstruction algorithm},
journal = {Ultramicroscopy},
volume = {207},
pages = {112830},
year = {2019},
issn = {0304-3991},
doi = {https://doi.org/10.1016/j.ultramic.2019.112830},
url = {https://www.sciencedirect.com/science/article/pii/S0304399119301949},
author = {A.A. Borzunov and V.Y. Karaulov and N.A. Koshev and D.V. Lukyanenko and E.I. Rau and A.G. Yagola and S.V. Zaitsev},
keywords = {Scanning electron microscopy, Backscattered electrons detector, 3D topography, Reconstruction algorithm},
abstract = {We propose a new SFS (shape from shading) technique for improved 3D surface reconstruction and imaging of relatively smooth surface topography using the scanning electron microscope (SEM). The new arrangement of backscattered electrons detector plates allows decreasing the initial energy of the electron probe, which makes this SEM technique to be suitable for usage on radiation-sensitive samples like biological tissues. Experiments show high effectiveness of the method, which improves both the gradient sensitivity of the signal and the signal to noise ratio.}
}

@article{Reimer1985,
author = {Reimer, L. and Riepenhausen, M.},
title = {Detector strategy for secondary and backscattered electrons using multiple detector systems},
journal = {Scanning},
volume = {7},
number = {5},
pages = {221-238},
doi = {https://doi.org/10.1002/sca.4950070503},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1002/sca.4950070503},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/sca.4950070503},
year = {1985}
}

@article{Borzunov2019,
title = {3D surface topography imaging in SEM with improved backscattered electron detector: Arrangement and reconstruction algorithm},
journal = {Ultramicroscopy},
volume = {207},
pages = {112830},
year = {2019},
issn = {0304-3991},
doi = {https://doi.org/10.1016/j.ultramic.2019.112830},
url = {https://www.sciencedirect.com/science/article/pii/S0304399119301949},
author = {A.A. Borzunov and V.Y. Karaulov and N.A. Koshev and D.V. Lukyanenko and E.I. Rau and A.G. Yagola and S.V. Zaitsev},
keywords = {Scanning electron microscopy, Backscattered electrons detector, 3D topography, Reconstruction algorithm},
abstract = {We propose a new SFS (shape from shading) technique for improved 3D surface reconstruction and imaging of relatively smooth surface topography using the scanning electron microscope (SEM). The new arrangement of backscattered electrons detector plates allows decreasing the initial energy of the electron probe, which makes this SEM technique to be suitable for usage on radiation-sensitive samples like biological tissues. Experiments show high effectiveness of the method, which improves both the gradient sensitivity of the signal and the signal to noise ratio.}
}

@article{RICHARDS1995,
author = {RICHARDS, R. G. and GWYNN, I. AP},
title = {Backscattered electron imaging of the undersurface of resin-embedded cells by field-emission scanning electron microscopy},
journal = {Journal of Microscopy},
volume = {177},
number = {1},
pages = {43-52},
keywords = {Field emission, scanning electron microscopy, backscattered electron imaging, atomic number contrast, tissue culture, cell, adhesion, undersurface},
doi = {https://doi.org/10.1111/j.1365-2818.1995.tb03532.x},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-2818.1995.tb03532.x},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2818.1995.tb03532.x},
abstract = {Summary In this study backscattered electron (BSE) imaging was used to display cellular structures stained with heavy metals within an unstained resin by atomic number contrast in successively deeper layers. Balb/c 3T3 fibroblasts were cultured on either 13-mm discs of plastic Thermanox, commercially pure titanium or steel. The cells were fixed, stained and embedded in resin and the disc removed. The resin block containing the cells was sputter coated and examined in a field-emission scanning electron microscope. The technique allowed for the direct visualization of the cell undersurface and immediately overlying areas of cytoplasm through the surrounding embedding resin, with good resolution and contrast to a significant depth of about 2 μm, without the requirement for cutting sections. The fixation protocol was optimized in order to increase heavy metal staining for maximal backscattered electron production. The operation of the microscope was optimized to maximize the number of backscattered electrons produced and to minimize the spot size. BSE images were collected over a wide range of accelerating voltages (keV), from low values to high values to give ‘sections' of information from increasing depths within the sample. At 3–4 keV only structures a very short distance into the material were observed, essentially the areas of cell attachment to the removed substrate. At higher accelerating voltages information on cell morphology, including in particular stress fibres and cell nuclei, where heavy metals were intensely bound became more evident. The technique allowed stepwise ‘sectional’ information to be acquired. The technique should be useful for studies on cell morphology, cycle and adhesion with greater resolution than can be obtained with any light-microscope-based system.},
year = {1995}
}

@article{Walther1991,
  title={Backscattered electron imaging for high resolution surface scanning electron microscopy with a new type YAG-detector.},
  author={P. Walther and R. Autrata and Y. Chen and J. Pawley},
  journal={Scanning microscopy},
  year={1991},
  volume={5 2},
  pages={301-9; discussion 310}
}

@article{Scala1991,
  title={Conventional and high resolution scanning electron microscopy of biological sectioned material.},
  author={Scala, C. and Cenacchi, G. and Preda, P. and Vici, M. and Apkarian, R. P. and Pasquinelli, G.},
  journal={Scanning microscopy},
  year={1991},
  volume={5 1},
  pages={135–145}
}

@article{Boatman1976,
  title={Morphology, morphometry and electron microscopy of HeLa cells infected with bovine Mycoplasma.},
  author={Boatman, E. and Cartwright, F. and Kenny, G.},
  journal={Cell and tissue research},
  year={1976},
  volume={170 1},
  pages={1–16}
}


@article{Miyamoto2016,
	doi = {10.1088/0957-0233/27/2/025407},
	url = {https://doi.org/10.1088/0957-0233/27/2/025407},
	year = 2016,
	month = {jan},
	publisher = {{IOP} Publishing},
	volume = {27},
	number = {2},
	pages = {025407},
	author = {Atsushi Miyamoto and Yutaka Hojyo},
	title = {Generation of large field {SEM} image by panorama composition technology for nano-order measurement},
	journal = {Measurement Science and Technology},
	abstract = {Semiconductor manufacturing has a pressing need for a method to accurately evaluate the global shape deformation of a photomask pattern. We thus propose a novel composition technique for a large field panorama image of scanning electron microscopy (SEM). The proposed method optimises the arrangement of segmented imaging regions (SIRs), which are components of a panorama image, on the basis of the design data of the photomask pattern layout. The quantity of the line pattern segment, which is a clue to the connection in an overlapping region between adjoining SIRs and the connectability of any two SIRs, is evaluated. As a result of the optimisation, it is guaranteed that all SIR images can be connected theoretically. For 30 evaluation points, the maximum connection error of the SIR images was 1.5 nm in a simulation using pseudo-SEM images. The maximum total measurement error, which includes the connection error and CD measurement error from the panorama image, is estimated at 2.5 nm. This error was equivalent to about 1.4% of the photomask line width (target: 3%). The experiments using real SEM images demonstrate the effectiveness of the proposed method. It was visually confirmed that a large field, high-resolution and seamless panorama image can be generated.}
}

@incollection{Stephan2019,
title = {Chapter 12 - Computational methods for stitching, alignment, and artifact correction of serial section data},
editor = {Thomas Müller-Reichert and Gaia Pigino},
series = {Methods in Cell Biology},
publisher = {Academic Press},
volume = {152},
pages = {261-276},
year = {2019},
booktitle = {Three-Dimensional Electron Microscopy},
issn = {0091-679X},
doi = {https://doi.org/10.1016/bs.mcb.2019.04.007},
url = {https://www.sciencedirect.com/science/article/pii/S0091679X19300585},
author = {Stephan Saalfeld},
keywords = {Stitching, Montage, Alignment, Serial section, Lens distortion correction, Contrast correction, Axial distortion correction},
abstract = {Imaging large samples at the resolution offered by electron microscopy is typically achieved by sequentially recording overlapping tiles that are later combined to seamless mosaics. Mosaics of serial sections are aligned to reconstruct three-dimensional volumes. To achieve this, image distortions and artifacts as introduced during sample preparation or imaging need to be removed. In this chapter, we will discuss typical sources of artifacts and distortion, and we will learn how to use the open source software TrakEM2 to correct them.}
}

@Article{Buys2013,
author={Buys, Antoinette V.
and Van Rooy, Mia-Jean
and Soma, Prashilla
and Van Papendorp, Dirk
and Lipinski, Boguslaw
and Pretorius, Etheresia},
title={Changes in red blood cell membrane structure in type 2 diabetes: a scanning electron and atomic force microscopy study},
journal={Cardiovascular Diabetology},
year={2013},
month={Jan},
day={28},
volume={12},
number={1},
pages={25},
abstract={Red blood cells (RBCs) are highly deformable and possess a robust membrane that can withstand shear force. Previous research showed that in diabetic patients, there is a changed RBC ultrastructure, where these cells are elongated and twist around spontaneously formed fibrin fibers. These changes may impact erythrocyte function. Ultrastructural analysis of RBCs in inflammatory and degenerative diseases can no longer be ignored and should form a fundamental research tool in clinical studies. Consequently, we investigated the membrane roughness and ultrastructural changes in type 2 diabetes. Atomic force microscopy (AFM) was used to study membrane roughness and we correlate this with scanning electron microscopy (SEM) to compare results of both the techniques with the RBCs of healthy individuals. We show that the combined AFM and SEM analyses of RBCs give valuable information about the disease status of patients with diabetes. Effectiveness of treatment regimes on the integrity, cell shape and roughness of RBCs may be tracked, as this cell's health status is crucial to the overall wellness of the diabetic patient.},
issn={1475-2840},
doi={10.1186/1475-2840-12-25},
url={https://doi.org/10.1186/1475-2840-12-25}
}

@article{Hattori1972,
  title={Scanning electron microscopy of reticulocytes.},
  author={Hattori, Akira  and Ito, Suiko  and Matsuoka, Matsuzo },
  journal={Archivum histologicum Japonicum = Nihon soshikigaku kiroku},
  year={1972},
  volume={35 1},
  pages={37-49}
}

@article{Grindem1985,
author = {C. B. Grindem},
title ={Ultrastructural Morphology of Leukemic Cells in the Cat},
journal = {Veterinary Pathology},
volume = {22},
number = {2},
pages = {147-155},
year = {1985},
doi = {10.1177/030098588502200209},
note ={PMID: 2984829},
URL = {https://doi.org/10.1177/030098588502200209},
eprint = {https://doi.org/10.1177/030098588502200209},
abstract = { Transmission and scanning electron microscopic characteristics of leukemic cells from eight cats with spontaneous leukemia are described. Nuclear blebs, myelin figures, cytoplasmic microfibrils and C-type virus were seen more frequently in leukemic cells. Surface ridges and ruffles seen with the scanning electron microscopy were helpful in distinguishing myelogenous from lymphogenous leukemia. }
}

@Article{Florian2017,
author={Grahammer, Florian
and Wigge, Christoph
and Schell, Christoph
and Kretz, Oliver
and Patrakka, Jaakko
and Schneider, Simon
and Klose, Martin
and Kind, Julia
and Arnold, Sebastian J.
and Habermann, Anja
and Br{\"a}uniger, Ricarda
and Rinschen, Markus M.
and V{\"o}lker, Linus
and Bregenzer, Andreas
and Rubbenstroth, Dennis
and Boerries, Melanie
and Kerjaschki, Dontscho
and Miner, Jeffrey H.
and Walz, Gerd
and Benzing, Thomas
and Fornoni, Alessia
and Frangakis, Achilleas S.
and Huber, Tobias B.},
title={A flexible, multilayered protein scaffold maintains the slit in between glomerular podocytes},
journal={JCI Insight},
year={2017},
month={Mar},
day={16},
publisher={The American Society for Clinical Investigation},
volume={1},
number={9},
abstract={Vertebrate life critically depends on renal filtration and excretion of low molecular weight waste products. This process is controlled by a specialized cell-cell contact between podocyte foot processes: the slit diaphragm (SD). Using a comprehensive set of targeted KO mice of key SD molecules, we provided genetic, functional, and high-resolution ultrastructural data highlighting a concept of a flexible, dynamic, and multilayered architecture of the SD. Our data indicate that the mammalian SD is composed of NEPHRIN and NEPH1 molecules, while NEPH2 and NEPH3 do not participate in podocyte intercellular junction formation. Unexpectedly, homo- and heteromeric NEPHRIN/NEPH1 complexes are rarely observed. Instead, single NEPH1 molecules appear to form the lower part of the junction close to the glomerular basement membrane with a width of 23 nm, while single NEPHRIN molecules form an adjacent junction more apically with a width of 45 nm. In both cases, the molecules are quasiperiodically spaced 7 nm apart. These structural findings, in combination with the flexibility inherent to the repetitive Ig folds of NEPHRIN and NEPH1, indicate that the SD likely represents a highly dynamic cell-cell contact that forms an adjustable, nonclogging barrier within the renal filtration apparatus.},
issn={2379-3708},
doi={10.1172/jci.insight.86177},
url={https://doi.org/10.1172/jci.insight.86177}
}



abstract = {Vertebrate life critically depends on renal filtration and excretion of low molecular weight waste products. This process is controlled by a specialized cell-cell contact between podocyte foot processes: the slit diaphragm (SD). Using a comprehensive set of targeted KO mice of key SD molecules, we provided genetic, functional, and high-resolution ultrastructural data highlighting a concept of a flexible, dynamic, and multilayered architecture of the SD. Our data indicate that the mammalian SD is composed of NEPHRIN and NEPH1 molecules, while NEPH2 and NEPH3 do not participate in podocyte intercellular junction formation. Unexpectedly, homo- and heteromeric NEPHRIN/NEPH1 complexes are rarely observed. Instead, single NEPH1 molecules appear to form the lower part of the junction close to the glomerular basement membrane with a width of 23 nm, while single NEPHRIN molecules form an adjacent junction more apically with a width of 45 nm. In both cases, the molecules are quasiperiodically spaced 7 nm apart. These structural findings, in combination with the flexibility inherent to the repetitive Ig folds of NEPHRIN and NEPH1, indicate that the SD likely represents a highly dynamic cell-cell contact that forms an adjustable, nonclogging barrier within the renal filtration apparatus.},
number = {9},
doi = {10.1172/jci.insight.86177},
url = {https://doi.org/10.1172/jci.insight.86177},
}

@Manual{R-base,
title = {R: A Language and Environment for Statistical Computing},
author = {{R Core Team}},
organization = {R Foundation for Statistical Computing},
address = {Vienna, Austria},
year = {2016},
url = {https://www.R-project.org/},
}

@article{Bainton1977,
title = {Abnormalities in Granule Formation in Acute Myelogenous Leukemia},
journal = {Blood},
volume = {49},
number = {5},
pages = {693-704},
year = {1977},
issn = {0006-4971},
doi = {https://doi.org/10.1182/blood.V49.5.693.693},
url = {https://www.sciencedirect.com/science/article/pii/S0006497120701473},
author = {Dorothy F. Bainton and Lawrence M. Friedlander and Stephen B. Shohet},
abstract = {Granule formation was investigated in differentiating neutrophils of a patient with acute myelogenous leukemia (AML) by means of the combined techniques of electron microscopy and peroxidase cytochemistry. Two important pathologic features were observed: first, an abnormal concentration and packaging of peroxidase into Auer rods in leukemic promyelocytes, and second, the presence of Auer rods surrounded by single-unit membranes in some mature polymorphonuclear leukocytes (PMN). An additional unexpected finding was the discovery of two distinct populations of PMN circulating concurrently; a minor (<5%) normal one that contained both peroxidase-positive azurophilic and peroxidase-negative specific granules and a major abnormal one characterized by the absence of specific granules. None of these abnormalities was observed during the two remissions of this patient’s disease. During relapse a “hiatus leukemicus” occurred, which also revealed two populations of cells, a majority population of leukemic blasts, and a minority population of a few normal PMN. These findings documented several developmental abnormalities in the differentiating cells of myelogenous leukemia and also suggested that concurrent normal and abnormal populations of PMN may be a helpful diagnostic feature of a leukemic process.}
}


@article{Miyauchi1997,
    author = {Miyauchi, Jun and Ohyashiki, Kazuma and Inatomi, Yuka and Toyama, Keisuke},
    title = "{Neutrophil Secondary-Granule Deficiency as a Hallmark of All-Trans Retinoic Acid–Induced Differentiation of Acute Promyelocytic Leukemia Cells}",
    journal = {Blood},
    volume = {90},
    number = {2},
    pages = {803-813},
    year = {1997},
    month = {07},
    abstract = "{Acute promyelocytic leukemia (APL) is a neoplasm with the unique chromosomal translocation t(15; 17), which involves the retinoic acid receptor α gene. All-trans retinoic acid (ATRA) has been used for APL patients as a potent therapeutic agent to induce differentiation of leukemia cells. Although polymorphonuclear leukocytes (PMNs) appearing in the blood and bone marrow during ATRA treatment often possess Auer rods, indicating their neoplastic origin, other morphological abnormalities of PMNs have not been elucidated. We studied the morphological changes of APL cells during ATRA treatment at the ultrastructural level. Although most aberrant primary granules, including Auer rods, became morphologically normal in response to ATRA therapy and the nuclei showed chromatin condensation and lobulation, resulting in the emergence of PMNs, the lobulated nuclei often had nuclear filamentous connections and/or nuclear blebs, indicating some pathological process. Furthermore, PMNs, particularly early in ATRA treatment, lacked neutrophil secondary granules as did the PMNs appearing in a culture of APL cells incubated with ATRA, findings consistent with previously reported data that acute myeloid leukemia cell lines do not produce secondary granule proteins even after induction of differentiation towards mature neutrophils. The present data indicate that ATRA is incapable of inducing complete morphological maturation of APL cells and that secondary-granule deficiency may be a hallmark of aberrantly differentiated leukemic cells.}",
    issn = {0006-4971},
    doi = {10.1182/blood.V90.2.803},
    url = {https://doi.org/10.1182/blood.V90.2.803},
    eprint = {https://ashpublications.org/blood/article-pdf/90/2/803/1643467/803.pdf},
}

@article {Naito2004,
	Title = {Differentiation and function of Kupffer cells},
	Author = {Naito, Makoto and Hasegawa, Go and Ebe, Yusuke and Yamamoto, Takashi},
	DOI = {10.1007/s00795-003-0228-x},
	Number = {1},
	Volume = {37},
	Month = {March},
	Year = {2004},
	Journal = {Medical electron microscopy : official journal of the Clinical Electron Microscopy Society of Japan},
	ISSN = {0918-4287},
	Pages = {16—28},
	Abstract = {Kupffer cells are the largest population of tissue macrophages. They are predominantly distributed in the lumen of hepatic sinusoids and exhibit endocytic activity against blood-borne materials entering the liver. Macrophage colony-stimulating factor and other growth factors regulate Kupffer cell differentiation in the fetal and adult period. Because of the unique attributes of tissue, Kupffer cells play essential roles not only in host defense but also in the homeostatic responses of tissue. Macrophage scavenger receptors and heme oxygenase are expressed in Kupffer cells from an early stage of ontogeny. Scavenger receptors are involved not only in the lipid metabolism but also in the bactericidal mechanism. Heme oxygenase in Kupffer cells is essential to the production of bilirubin. In this review, the developmental mechanism and functional activities of Kupffer cells are described. Evidence suggests that Kupffer cells represent a distinct cell population with unique differentiation mechanisms, metabolic functions, and responsiveness to inflammatory agents.},
	URL = {https://doi.org/10.1007/s00795-003-0228-x},
}


@Article{Ioannou2013,
author={Ioannou, George N.
and Haigh, W. Geoffrey
and Thorning, David
and Savard, Christopher},
title={Hepatic cholesterol crystals and crown-like structures distinguish NASH from simple steatosis [S]},
journal={Journal of Lipid Research},
year={2013},
month={May},
day={01},
publisher={Elsevier},
volume={54},
number={5},
pages={1326-1334},
issn={0022-2275},
doi={10.1194/jlr.M034876},
url={https://doi.org/10.1194/jlr.M034876}
}

@article{Matey2008,
    author = {Matey, Victoria and Richards, Jeffrey G. and Wang, Yuxiang and Wood, Chris M. and Rogers, Joe and Davies, Rhiannon and Murray, Brent W. and Chen, X.-Q. and Du, Jizeng and Brauner, Colin J.},
    title = "{The effect of hypoxia on gill morphology and ionoregulatory status in the Lake Qinghai scaleless carp, Gymnocypris przewalskii}",
    journal = {Journal of Experimental Biology},
    volume = {211},
    number = {7},
    pages = {1063-1074},
    year = {2008},
    month = {04},
    abstract = "{Goldfish and crucian carp at low temperature exhibit plasticity in gill morphology during exposure to hypoxia to enhance gas exchange. Hypoxia-induced changes in gill morphology and cellular ultrastructure of the high altitude scaleless carp from Lake Qinghai, China, were investigated to determine whether this is a general characteristic of cold water carp species. Fish were exposed to acute hypoxia (0.3 mg O2 l–1) for 24 h followed by 12 h recovery in normoxic water (6 mg O2l–1 at 3200 m altitude), with no mortality. Dramatic alterations in gill structure were initiated within 8 h of hypoxia and almost complete by 24 h, and included a gradual reduction of filament epithelial thickness (\\&gt;50\\%), elongation of respiratory lamellae, expansion of lamellar respiratory surface area (\\&gt;60\\%) and reduction in epithelial water–blood diffusion distance (\\&lt;50\\%). An increase in caspase 3 activity in gills occurred following 24 h exposure to hypoxia, indicating possible involvement of apoptosis in gill remodeling. Extensive gill mucous production during hypoxia may have been part of a general stress response or may have played a role in ion exchange and water balance. The large increase in lamellar surface area and reduction in diffusion distance presumably enhances gas transfer during hypoxia (especially in the presence of increased mucous production) but comes with an ionoregulatory cost, as indicated by a 10 and 15\\% reduction in plasma [Na+] and [Cl–],respectively, within 12–24 h of hypoxia. Within 12 h of hypoxia exposure, `wavy-convex'-mitochondria rich cells (MRCs) with large apical crypts and numerous branched microvilli were transformed into small`shallow-basin' cells with a flattened surface. As the apical membrane of MRCs is the site for active ion uptake from the water, a reduction in apical crypt surface area may have contributed to the progressive reduction in plasma[Na+] and [Cl–] observed during hypoxia. The changes in the macro- and ultra-structure of fish gills, and plasma[Na+] and [Cl–] during hypoxia were reversible,showing partial recovery by 12 h following return to normoxia. Although the large morphological changes in the gill observed in the scaleless carp support the hypothesis that gill remodeling during hypoxia is a general characteristic of cold water carp species, the reduced magnitude of the response in scaleless carp relative to goldfish and crucian carp may be a reflection of their more active lifestyle or because they reside in a moderately hypoxic environment at altitude.}",
    issn = {0022-0949},
    doi = {10.1242/jeb.010181},
    url = {https://doi.org/10.1242/jeb.010181},
    eprint = {https://journals.biologists.com/jeb/article-pdf/211/7/1063/1266360/1063.pdf},
}


@article{Koga2018,
    author = {Koga, Daisuke and Kusumi, Satoshi and Watanabe, Tsuyoshi},
    title = "{Backscattered electron imaging of resin-embedded sections}",
    journal = {Microscopy},
    volume = {67},
    number = {4},
    pages = {196-206},
    year = {2018},
    month = {06},
    abstract = "{Scanning electron microscopes have longer focal depths than transmission electron microscopes and enable visualization of the three-dimensional (3D) surface structures of specimens. While scanning electron microscopy (SEM) in biological research was generally used for the analysis of bulk specimens until around the year 2000, more recent instrumental advances have broadened the application of SEM; for example, backscattered electron (BSE) signals under low accelerating voltages allow block-face and section-face images of tissues embedded in resin to be acquired. This technical breakthrough has led to the development of novel 3D imaging techniques including focused ion beam SEM, serial-block face SEM and serial section SEM. Using these new techniques, the 3D shapes of cells and cell organelles have been revealed clearly through reconstruction of serial tomographic images. In this review, we address two modern SEM techniques: section-face imaging of resin-embedded tissue samples based on BSE observations, and serial section SEM for reconstruction of the 3D structures of cells and organelles from BSE-mode SEM images of consecutive ultrathin sections on solid substrates.}",
    issn = {2050-5698},
    doi = {10.1093/jmicro/dfy028},
    url = {https://doi.org/10.1093/jmicro/dfy028},
    eprint = {https://academic.oup.com/jmicro/article-pdf/67/4/196/25406804/dfy028.pdf},
}

@Article{Tsuji2017a,
author={Tsuji, Kenji
and Suleiman, Hani
and Miner, Jeffrey H.
and Daley, James M.
and Capen, Diane E.
and P{\u{a}}unescu, Teodor G.
and Lu, Hua A. Jenny},
title={Ultrastructural Characterization of the Glomerulopathy in Alport Mice by Helium Ion Scanning Microscopy (HIM)},
journal={Scientific Reports},
year={2017},
month={Sep},
day={15},
volume={7},
number={1},
pages={11696},
abstract={The glomerulus exercises its filtration barrier function by establishing a complex filtration apparatus consisting of podocyte foot processes, glomerular basement membrane and endothelial cells. Disruption of any component of the glomerular filtration barrier leads to glomerular dysfunction, frequently manifested as proteinuria. Ultrastructural studies of the glomerulus by transmission electron microscopy (TEM) and conventional scanning electron microscopy (SEM) have been routinely used to identify and classify various glomerular diseases. Here we report the application of newly developed helium ion scanning microscopy (HIM) to examine the glomerulopathy in a Col4a3 mutant/Alport syndrome mouse model. Our study revealed unprecedented details of glomerular abnormalities in Col4a3 mutants including distorted podocyte cell bodies and disorganized primary processes. Strikingly, we observed abundant filamentous microprojections arising from podocyte cell bodies and processes, and presence of unique bridging processes that connect the primary processes and foot processes in Alport mice. Furthermore, we detected an altered glomerular endothelium with disrupted sub-endothelial integrity. More importantly, we were able to clearly visualize the complex, three-dimensional podocyte and endothelial interface by HIM. Our study demonstrates that HIM provides nanometer resolution to uncover and rediscover critical ultrastructural characteristics of the glomerulopathy in Col4a3 mutant mice.},
issn={2045-2322},
doi={10.1038/s41598-017-12064-5},
url={https://doi.org/10.1038/s41598-017-12064-5}
}

@Article{Tsuji2017b,
author={Tsuji, Kenji
and P{\u{a}}unescu, Teodor G.
and Suleiman, Hani
and Xie, Dongping
and Mamuya, Fahmy A.
and Miner, Jeffrey H.
and Lu, Hua A. Jenny},
title={Re-characterization of the Glomerulopathy in CD2AP Deficient Mice by High-Resolution Helium Ion Scanning Microscopy},
journal={Scientific Reports},
year={2017},
month={Aug},
day={16},
volume={7},
number={1},
pages={8321},
abstract={Helium ion scanning microscopy (HIM) is a novel technology that directly visualizes the cell surface ultrastructure without surface coating. Despite its very high resolution, it has not been applied extensively to study biological or pathology samples. Here we report the application of this powerful technology to examine the three-dimensional ultrastructural characteristics of proteinuric glomerulopathy in mice with CD2-associated protein (CD2AP) deficiency. HIM revealed the serial alteration of glomerular features including effacement and disorganization of the slit diaphragm, followed by foot process disappearance, flattening and fusion of major processes, and eventual transformation into a podocyte sheet as the disease progressed. The number and size of the filtration slit pores decreased. Strikingly, numerous ``bleb'' shaped microprojections were observed extending from podocyte processes and cell body, indicating significant membrane dynamics accompanying CD2AP deficiency. Visualizing the glomerular endothelium and podocyte-endothelium interface revealed the presence of endothelial damage, and disrupted podocyte and endothelial integrity in 6 week-old Cd2ap-KO mice. We used the HIM technology to investigate at nanometer scale resolution the ultrastructural alterations of the glomerular filtration apparatus in mice lacking the critical slit diaphragm-associated protein CD2AP, highlighting the great potential of HIM to provide new insights into the biology and (patho)physiology of glomerular diseases.},
issn={2045-2322},
doi={10.1038/s41598-017-08304-3},
url={https://doi.org/10.1038/s41598-017-08304-3}
}

@article{Rice2013,
    doi = {10.1371/journal.pone.0057051},
    author = {Rice, William L. and Van Hoek, Alfred N. and Păunescu, Teodor G. and Huynh, Chuong and Goetze, Bernhard and Singh, Bipin and Scipioni, Larry and Stern, Lewis A. and Brown, Dennis},
    journal = {PLOS ONE},
    publisher = {Public Library of Science},
    title = {High Resolution Helium Ion Scanning Microscopy of the Rat Kidney},
    year = {2013},
    month = {03},
    volume = {8},
    url = {https://doi.org/10.1371/journal.pone.0057051},
    pages = {1-9},
    abstract = {Helium ion scanning microscopy is a novel imaging technology with the potential to provide sub-nanometer resolution images of uncoated biological tissues. So far, however, it has been used mainly in materials science applications. Here, we took advantage of helium ion microscopy to explore the epithelium of the rat kidney with unsurpassed image quality and detail. In addition, we evaluated different tissue preparation methods for their ability to preserve tissue architecture. We found that high contrast, high resolution imaging of the renal tubule surface is possible with a relatively simple processing procedure that consists of transcardial perfusion with aldehyde fixatives, vibratome tissue sectioning, tissue dehydration with graded methanol solutions and careful critical point drying. Coupled with the helium ion system, fine details such as membrane texture and membranous nanoprojections on the glomerular podocytes were visualized, and pores within the filtration slit diaphragm could be seen in much greater detail than in previous scanning EM studies. In the collecting duct, the extensive and striking apical microplicae of the intercalated cells were imaged without the shrunken or distorted appearance that is typical with conventional sample processing and scanning electron microscopy. Membrane depressions visible on principal cells suggest possible endo- or exocytotic events, and central cilia on these cells were imaged with remarkable preservation and clarity. We also demonstrate the use of colloidal gold probes for highlighting specific cell-surface proteins and find that 15 nm gold labels are practical and easily distinguishable, indicating that external labels of various sizes can be used to detect multiple targets in the same tissue. We conclude that this technology represents a technical breakthrough in imaging the topographical ultrastructure of animal tissues. Its use in future studies should allow the study of fine cellular details and provide significant advances in our understanding of cell surface structures and membrane organization.},
    number = {3},

}

@article{Paunescu2014,
    author = {Păunescu, Teodor G. and Shum, Winnie W.C. and Huynh, Chuong and Lechner, Lorenz and Goetze, Bernhard and Brown, Dennis and Breton, Sylvie},
    title = "{High-resolution helium ion microscopy of epididymal epithelial cells and their interaction with spermatozoa}",
    journal = {Molecular Human Reproduction},
    volume = {20},
    number = {10},
    pages = {929-937},
    year = {2014},
    month = {07},
    abstract = "{We examined the rat and mouse epididymis using helium ion microscopy (HIM), a novel imaging technology that uses a scanning beam of He+ ions to produce nanometer resolution images of uncoated biological samples. Various tissue fixation, sectioning and dehydration methods were evaluated for their ability to preserve tissue architecture. The cauda epididymidis was luminally perfused in vivo to remove most spermatozoa and the apical surface of the epithelial lining was exposed. Fixed epididymis samples were then subjected to critical point drying (CPD) and HIM. Apical stereocilia in principal cells and smaller apical membrane extensions in clear cells were clearly distinguishable in both rat and mouse epididymis using this technology. After perfusion with an activating solution containing CPT-cAMP, a permeant analog of cAMP, clear cells exhibited an increase in the number and size of membrane ruffles or microplicae. In contrast, principal cells did not exhibit detectable structural modifications. High-resolution HIM imaging clearly showed the ultrastructure of residual sperm cells, including the presence of concentric rings on the midpiece, and of cytoplasmic droplets in some spermatozoa. Close epithelium–sperm interactions were also detected. We found a number of sperm cells whose heads were anchored within the epididymal epithelium. In certain cases, the surface of the sperm cytoplasmic droplet was covered with vesicle-like structures whose size is consistent with that of epididymosomes. In conclusion, we describe here the first application of HIM technology to the study of the structure and morphology of the rodent epididymis. HIM technology represents a major imaging breakthrough that can be successfully applied to study the epididymis and spermatozoa, with the goal of advancing our understanding of their structure and function.}",
    issn = {1360-9947},
    doi = {10.1093/molehr/gau052},
    url = {https://doi.org/10.1093/molehr/gau052},
    eprint = {https://academic.oup.com/molehr/article-pdf/20/10/929/3406483/gau052.pdf},
}

@article{Kuwajima2013,
    doi = {10.1371/journal.pone.0059573},
    author = {Kuwajima, Masaaki and Mendenhall, John M. and Lindsey, Laurence F. and Harris, Kristen M.},
    journal = {PLOS ONE},
    publisher = {Public Library of Science},
    title = {Automated Transmission-Mode Scanning Electron Microscopy (tSEM) for Large Volume Analysis at Nanoscale Resolution},
    year = {2013},
    month = {03},
    volume = {8},
    url = {https://doi.org/10.1371/journal.pone.0059573},
    pages = {1-14},
    abstract = {Transmission-mode scanning electron microscopy (tSEM) on a field emission SEM platform was developed for efficient and cost-effective imaging of circuit-scale volumes from brain at nanoscale resolution. Image area was maximized while optimizing the resolution and dynamic range necessary for discriminating key subcellular structures, such as small axonal, dendritic and glial processes, synapses, smooth endoplasmic reticulum, vesicles, microtubules, polyribosomes, and endosomes which are critical for neuronal function. Individual image fields from the tSEM system were up to 4,295 µm2 (65.54 µm per side) at 2 nm pixel size, contrasting with image fields from a modern transmission electron microscope (TEM) system, which were only 66.59 µm2 (8.160 µm per side) at the same pixel size. The tSEM produced outstanding images and had reduced distortion and drift relative to TEM. Automated stage and scan control in tSEM easily provided unattended serial section imaging and montaging. Lens and scan properties on both TEM and SEM platforms revealed no significant nonlinear distortions within a central field of ∼100 µm2 and produced near-perfect image registration across serial sections using the computational elastic alignment tool in Fiji/TrakEM2 software, and reliable geometric measurements from RECONSTRUCT™ or Fiji/TrakEM2 software. Axial resolution limits the analysis of small structures contained within a section (∼45 nm). Since this new tSEM is non-destructive, objects within a section can be explored at finer axial resolution in TEM tomography with current methods. Future development of tSEM tomography promises thinner axial resolution producing nearly isotropic voxels and should provide within-section analyses of structures without changing platforms. Brain was the test system given our interest in synaptic connectivity and plasticity; however, the new tSEM system is readily applicable to other biological systems.},
    number = {3},

}

@article{Suga2011,
title = {The Atmospheric Scanning Electron Microscope with open sample space observes dynamic phenomena in liquid or gas},
journal = {Ultramicroscopy},
volume = {111},
number = {12},
pages = {1650-1658},
year = {2011},
issn = {0304-3991},
doi = {https://doi.org/10.1016/j.ultramic.2011.08.001},
url = {https://www.sciencedirect.com/science/article/pii/S030439911100194X},
author = {Mitsuo Suga and Hidetoshi Nishiyama and Yuji Konyuba and Shinnosuke Iwamatsu and Yoshiyuki Watanabe and Chie Yoshiura and Takumi Ueda and Chikara Sato},
keywords = {SEM, Electrochemistry, Dynamic observation, Self organization, ASEM, Metal paste},
abstract = {Although conventional electron microscopy (EM) requires samples to be in vacuum, most chemical and physical reactions occur in liquid or gas. The Atmospheric Scanning Electron Microscope (ASEM) can observe dynamic phenomena in liquid or gas under atmospheric pressure in real time. An electron-permeable window made of pressure-resistant 100nm-thick silicon nitride (SiN) film, set into the bottom of the open ASEM sample dish, allows an electron beam to be projected from underneath the sample. A detector positioned below captures backscattered electrons. Using the ASEM, we observed the radiation-induced self-organization process of particles, as well as phenomena accompanying volume change, including evaporation-induced crystallization. Using the electrochemical ASEM dish, we observed tree-like electrochemical depositions on the cathode. In silver nitrate solution, we observed silver depositions near the cathode forming incidental internal voids. The heated ASEM dish allowed observation of patterns of contrast in melting and solidifying solder. Finally, to demonstrate its applicability for monitoring and control of industrial processes, silver paste and solder paste were examined at high throughput. High resolution, imaging speed, flexibility, adaptability, and ease of use facilitate the observation of previously difficult-to-image phenomena, and make the ASEM applicable to various fields.}
}


@article{JOY1991,
title = {The theory and practice of high-resolution scanning electron microscopy},
journal = {Ultramicroscopy},
volume = {37},
number = {1},
pages = {216-233},
year = {1991},
issn = {0304-3991},
doi = {https://doi.org/10.1016/0304-3991(91)90020-7},
url = {https://www.sciencedirect.com/science/article/pii/0304399191900207},
author = {David C. Joy},
abstract = {Recent advances in instrumentation have produced the first commercial examples of what can justifiably be called high-resolution scanning electron microscopes. The key components of such instruments are a cold field emission gun, a small-gap immersion probe-forming lens, and a clean dry-pumped vacuum. The performance of these microscopes is characterized by several major features including a spatial resolution, in secondary electron mode on solid specimens, which can exceed 1 nm on a routine basis; an incident probe current density of the order of 106 A/cm2; and the ability to maintain these levels of performance over an accelerating voltage range of from 1 to 30 keV. This combination of high resolution, high probe current, low contamination and flexible electron-optical conditions provides many new opportunities for the application of the SEM to materials science, physics, and the life sciences.}
}

@article{GOLLA1994,
author = {GOLLA, U. and SCHINDLER, B. and REIMER, L.},
title = {Contrast in the transmission mode of a low-voltage scanning electron microscope},
journal = {Journal of Microscopy},
volume = {173},
number = {3},
pages = {219-225},
keywords = {Low-voltage electron microscopy, transmission mode, contrast thickness, biological sections},
doi = {https://doi.org/10.1111/j.1365-2818.1994.tb03444.x},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-2818.1994.tb03444.x},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2818.1994.tb03444.x},
abstract = {Summary The contrast thicknesses (xk) of thin carbon and platinum films have been measured in the transmission mode of a low-voltage scanning electron microscope for apertures of 40 and 100 mrad and electron energies (E) between 1 and 30 keV. The measured values overlap with those previously measured for E (≥ 17keV) in a transmission electron microscope. Differences in the decrease of xk with decreasing E between carbon and platinum agree with Wentzel-Kramer-Brillouin calculations of the elastic cross-sections. Knowing the value of xk allows the exponential decrease ∝ exp(—x/xk) in transmission with increasing mass-thickness (x = ρt) of the specimen and the increasing gain of contrast for stained biological sections with decreasing electron energy to be calculated for brightfield and darkfield modes.},
year = {1994}
}

@article{Bogner2005,
title = {Wet STEM: A new development in environmental SEM for imaging nano-objects included in a liquid phase},
journal = {Ultramicroscopy},
volume = {104},
number = {3},
pages = {290-301},
year = {2005},
issn = {0304-3991},
doi = {https://doi.org/10.1016/j.ultramic.2005.05.005},
url = {https://www.sciencedirect.com/science/article/pii/S0304399105000926},
author = {A. Bogner and G. Thollet and D. Basset and P.-H. Jouneau and C. Gauthier},
keywords = {ESEM, Wet STEM, Water suspension, Nano-objects},
abstract = {Environmental scanning electron microscopy (ESEM) enables wet samples to be observed without potentially damaging sample preparation through the use of partial water vapour pressure in the microscope specimen chamber. However, in the case of latices in colloidal state or microorganisms, samples are not only wet, but made of objects totally submerged in a liquid phase. In this case, under classical ESEM imaging conditions only the top surface of the liquid is imaged, with poor contrast, and possible drifting of objects. The present paper describes experiments using a powerful new Scanning Transmission Electron Microscopy (STEM) imaging system, that allows transmission observations of wet samples in an ESEM. A special device, designed to observe all sorts of objects submerged in a liquid under annular dark-field imaging conditions, is described. Specific features of the device enable to avoid drifting of floating objects which occurs in the case of a large amount of water, thus allowing slow-scan high-definition imaging of particles with a diameter down to few tens of nm. The large potential applications of this new technique are then illustrated, including the imaging of different nano-objects in water. The particular case of grafted latex particles is discussed, showing that it is possible to observe details on their surface when submerged in water. All the examples demonstrate that images acquired in wet STEM mode show particularly good resolution and contrast, without adding enhancing contrast objects, and without staining.}
}

@article{Bogner2007,
title = {A history of scanning electron microscopy developments: Towards “wet-STEM” imaging},
journal = {Micron},
volume = {38},
number = {4},
pages = {390-401},
year = {2007},
note = {Microscopy of Nanostructures},
issn = {0968-4328},
doi = {https://doi.org/10.1016/j.micron.2006.06.008},
url = {https://www.sciencedirect.com/science/article/pii/S0968432806001016},
author = {A. Bogner and P.-H. Jouneau and G. Thollet and D. Basset and C. Gauthier},
keywords = {Electron microscopy, STEM-in-SEM, Transmission mode, Scattered electrons, Environmental scanning electron microscopy, ESEM},
abstract = {A recently developed imaging mode called “wet-STEM” and new developments in environmental scanning electron microscopy (ESEM) allows the observation of nano-objects suspended in a liquid phase, with a few manometers resolution and a good signal to noise ratio. The idea behind this technique is simply to perform STEM-in-SEM, that is SEM in transmission mode, in an environmental SEM. The purpose of the present contribution is to highlight the main advances that contributed to development of the wet-STEM technique. Although simple in principle, the wet-STEM imaging mode would have been limited before high brightness electron sources became available, and needed some progresses and improvements in ESEM. This new technique extends the scope of SEM as a high-resolution microscope, relatively cheap and widely available imaging tool, for a wider variety of samples.}
}

@article{Kislinger2020,
title = {Multiscale ATUM-FIB Microscopy Enables Targeted Ultrastructural Analysis at Isotropic Resolution},
journal = {iScience},
volume = {23},
number = {7},
pages = {101290},
year = {2020},
issn = {2589-0042},
doi = {https://doi.org/10.1016/j.isci.2020.101290},
url = {https://www.sciencedirect.com/science/article/pii/S2589004220304776},
author = {Georg Kislinger and Helmut Gnägi and Martin Kerschensteiner and Mikael Simons and Thomas Misgeld and Martina Schifferer},
keywords = {Imaging Anatomy, Biological Sciences, Cellular Neuroscience, Experimental Systems for Structural Biology},
abstract = {Summary
Volume electron microscopy enables the ultrastructural analysis of biological tissue. Currently, the techniques involving ultramicrotomy (ATUM, ssTEM) allow large fields of view but afford only limited z-resolution, whereas ion beam-milling approaches (FIB-SEM) yield isotropic voxels but are restricted in volume size. Now we present a hybrid method, named ATUM-FIB, which combines the advantages of both approaches. ATUM-FIB is based on serial sectioning of tissue into “semithick” (2–10 μm) sections collected onto tape. Serial light and electron microscopy allows the identification of regions of interest that are then directly accessible for targeted FIB-SEM. The set of semithick sections thus represents a tissue “library” which provides three-dimensional context information that can be probed “on demand” by local high-resolution analysis. We demonstrate the potential of this technique to reveal the ultrastructure of rare but pathologically important events by identifying microglia contact sites with amyloid plaques in a mouse model of familial Alzheimer's disease.}
}


@article{Reichelt2012,
    doi = {10.1371/journal.ppat.1002740},
    author = {Reichelt, Mike and Joubert, Lydia and Perrino, John and Koh, Ai Leen and Phanwar, Ibanri and Arvin, Ann M.},
    journal = {PLOS Pathogens},
    publisher = {Public Library of Science},
    title = {3D Reconstruction of VZV Infected Cell Nuclei and PML Nuclear Cages by Serial Section Array Scanning Electron Microscopy and Electron Tomography},
    year = {2012},
    month = {06},
    volume = {8},
    url = {https://doi.org/10.1371/journal.ppat.1002740},
    pages = {1-17},
    abstract = {Varicella-zoster virus (VZV) is a human alphaherpesvirus that causes varicella (chickenpox) and herpes zoster (shingles). Like all herpesviruses, the VZV DNA genome is replicated in the nucleus and packaged into nucleocapsids that must egress across the nuclear membrane for incorporation into virus particles in the cytoplasm. Our recent work showed that VZV nucleocapsids are sequestered in nuclear cages formed from promyelocytic leukemia protein (PML) in vitro and in human dorsal root ganglia and skin xenografts in vivo. We sought a method to determine the three-dimensional (3D) distribution of nucleocapsids in the nuclei of herpesvirus-infected cells as well as the 3D shape, volume and ultrastructure of these unique PML subnuclear domains. Here we report the development of a novel 3D imaging and reconstruction strategy that we term Serial Section Array-Scanning Electron Microscopy (SSA-SEM) and its application to the analysis of VZV-infected cells and these nuclear PML cages. We show that SSA-SEM permits large volume imaging and 3D reconstruction at a resolution sufficient to localize, count and distinguish different types of VZV nucleocapsids and to visualize complete PML cages. This method allowed a quantitative determination of how many nucleocapsids can be sequestered within individual PML cages (sequestration capacity), what proportion of nucleocapsids are entrapped in single nuclei (sequestration efficiency) and revealed the ultrastructural detail of the PML cages. More than 98% of all nucleocapsids in reconstructed nuclear volumes were contained in PML cages and single PML cages sequestered up to 2,780 nucleocapsids, which were shown by electron tomography to be embedded and cross-linked by an filamentous electron-dense meshwork within these unique subnuclear domains. This SSA-SEM analysis extends our recent characterization of PML cages and provides a proof of concept for this new strategy to investigate events during virion assembly at the single cell level.},
    number = {6}
}

@article{Horstmann2012,
    doi = {10.1371/journal.pone.0035172},
    author = {Horstmann, Heinz and Körber, Christoph and Sätzler, Kurt and Aydin, Daniel and Kuner, Thomas},
    journal = {PLOS ONE},
    publisher = {Public Library of Science},
    title = {Serial Section Scanning Electron Microscopy (S3EM) on Silicon Wafers for Ultra-Structural Volume Imaging of Cells and Tissues},
    year = {2012},
    month = {04},
    volume = {7},
    url = {https://doi.org/10.1371/journal.pone.0035172},
    pages = {1-8},
    abstract = {High resolution, three-dimensional (3D) representations of cellular ultrastructure are essential for structure function studies in all areas of cell biology. While limited subcellular volumes have been routinely examined using serial section transmission electron microscopy (ssTEM), complete ultrastructural reconstructions of large volumes, entire cells or even tissue are difficult to achieve using ssTEM. Here, we introduce a novel approach combining serial sectioning of tissue with scanning electron microscopy (SEM) using a conductive silicon wafer as a support. Ribbons containing hundreds of 35 nm thick sections can be generated and imaged on the wafer at a lateral pixel resolution of 3.7 nm by recording the backscattered electrons with the in-lens detector of the SEM. The resulting electron micrographs are qualitatively comparable to those obtained by conventional TEM. S3EM images of the same region of interest in consecutive sections can be used for 3D reconstructions of large structures. We demonstrate the potential of this approach by reconstructing a 31.7 µm3 volume of a calyx of Held presynaptic terminal. The approach introduced here, Serial Section SEM (S3EM), for the first time provides the possibility to obtain 3D ultrastructure of large volumes with high resolution and to selectively and repetitively home in on structures of interest. S3EM accelerates process duration, is amenable to full automation and can be implemented with standard instrumentation.},
    number = {4}
}

@article{Oho2000,
    author = {Oho, Eisaku and Okugawa, Kenichi and Kawamata, Shigeru},
    title = "{Practical SEM system based on the montage technique applicable to ultralow-magnification observation, while maintaining original functions}",
    journal = {Journal of Electron Microscopy},
    volume = {49},
    number = {1},
    pages = {135-141},
    year = {2000},
    month = {01},
    abstract = "{A newly developed SEM system has been utilized for obtaining ultralow-magnification SEM images. It is a successful combination of the modern SEM equipped with a motor drive stage fully controlled with PC and digital image processing techniques for automatic montage. In order to accomplish a practical system, several problems peculiar to the field of SEM, i.e. raster rotation, peripheral distortion and charging effects, are discussed and solved. The function of ultralow-magnification (whole area) observation is important during a scanning electron microscopy session.}",
    issn = {0022-0744},
    doi = {10.1093/oxfordjournals.jmicro.a023777},
    url = {https://doi.org/10.1093/oxfordjournals.jmicro.a023777},
    eprint = {https://academic.oup.com/jmicro/article-pdf/49/1/135/3934853/49-1-135.pdf},
}

@INPROCEEDINGS{Blattner2014,  
author={Blattner, Timothy and Keyrouz, Walid and Chalfoun, Joe and Stivalet, Bertrand and Brady, Mary and Zhou, Shujia},  
booktitle={2014 43rd International Conference on Parallel Processing},   
title={A Hybrid CPU-GPU System for Stitching Large Scale Optical Microscopy Images},
year={2014},  
volume={}, 
number={},  
pages={1-9}, 
doi={10.1109/ICPP.2014.9}
}

@article{TSAI2011,
author = {TSAI, C.-L. and LISTER, J.P. and BJORNSSON, C.S. and SMITH, K. and SHAIN, W. and BARNES, C.A. and ROYSAM, B.},
title = {Robust, globally consistent and fully automatic multi-image registration and montage synthesis for 3-D multi-channel images},
journal = {Journal of Microscopy},
volume = {243},
number = {2},
pages = {154-171},
keywords = {Image registration, montage synthesis, 3-D microscopy},
doi = {https://doi.org/10.1111/j.1365-2818.2011.03489.x},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/j.1365-2818.2011.03489.x},
eprint = {https://onlinelibrary.wiley.com/doi/pdf/10.1111/j.1365-2818.2011.03489.x},
abstract = {Summary The need to map regions of brain tissue that are much wider than the field of view of the microscope arises frequently. One common approach is to collect a series of overlapping partial views, and align them to synthesize a montage covering the entire region of interest. We present a method that advances this approach in multiple ways. Our method (1) produces a globally consistent joint registration of an unorganized collection of three-dimensional (3-D) multi-channel images with or without stage micrometer data; (2) produces accurate registrations withstanding changes in scale, rotation, translation and shear by using a 3-D affine transformation model; (3) achieves complete automation, and does not require any parameter settings; (4) handles low and variable overlaps (5–15\%) between adjacent images, minimizing the number of images required to cover a tissue region; (5) has the self-diagnostic ability to recognize registration failures instead of delivering incorrect results; (6) can handle a broad range of biological images by exploiting generic alignment cues from multiple fluorescence channels without requiring segmentation and (7) is computationally efficient enough to run on desktop computers regardless of the number of images. The algorithm was tested with several tissue samples of at least 50 image tiles, involving over 5000 image pairs. It correctly registered all image pairs with an overlap greater than 7\%, correctly recognized all failures, and successfully joint-registered all images for all tissue samples studied. This algorithm is disseminated freely to the community as included with the Fluorescence Association Rules for Multi-Dimensional Insight toolkit for microscopy (http://www.farsight-toolkit.org).},
year = {2011}
}

@article{Liu2013,
author = {Dong Liu and Shitong Wang and Pin Cao and Lu Li and Zhongtao Cheng and Xin Gao and Yongying Yang},
journal = {Opt. Express},
keywords = {Image processing; Instrumentation, measurement, and metrology; Optical inspection; Defect understanding ; Imaging systems; Laser fusion; Nanopositioning equipment; Optical components; Scanning electron microscopy; Surface light scattering},
number = {5},
pages = {5974--5987},
publisher = {OSA},
title = {Dark-field microscopic image stitching method for surface defects evaluation of large fine optics},
volume = {21},
month = {Mar},
year = {2013},
url = {http://www.opticsexpress.org/abstract.cfm?URI=oe-21-5-5974},
doi = {10.1364/OE.21.005974},
abstract = {One of the challenges in surface defects evaluation of large fine optics is to detect defects of microns on surfaces of tens or hundreds of millimeters. Sub-aperture scanning and stitching is considered to be a practical and efficient method. But since there are usually few defects on the large aperture fine optics, resulting in no defects or only one run-through line feature in many sub-aperture images, traditional stitching methods encounter with mismatch problem. In this paper, a feature-based multi-cycle image stitching algorithm is proposed to solve the problem. The overlapping areas of sub-apertures are categorized based on the features they contain. Different types of overlapping areas are then stitched in different cycles with different methods. The stitching trace is changed to follow the one that determined by the features. The whole stitching procedure is a region-growing like process. Sub-aperture blocks grow bigger after each cycle and finally the full aperture image is obtained. Comparison experiment shows that the proposed method is very suitable to stitch sub-apertures that very few feature information exists in the overlapping areas and can stitch the dark-field microscopic sub-aperture images very well.},
}

@Article{Hong2013,
author={Hong, Won-Pyo
and Lee, Seok-Woo
and Choi, Hon-Zong},
title={A stitching algorithm for measuring large areas using scanning electron microscopes},
journal={International Journal of Precision Engineering and Manufacturing},
year={2013},
month={Jan},
day={01},
volume={14},
number={1},
pages={147-151},
abstract={SEM is very useful measuring equipment in the micro and nano area. In general, it is not used to accurately measure the size information of a sample, but to measure its shape characteristics. In addition, it has a measuring area that is limited to just several micro-meters, and it is unsuitable for accurate measurements larger than several tens of micro meters. This paper proposed a stitching algorithm for the split electron beam images using an image processing technique to minimize measurement error. Experiments were conducted targeting circular and rectangular shapes 500 nm∼10 $\mu$ in diameter and line length. Finally, stitching accuracy was verified through a comparison with AFM measuring data.},
issn={2005-4602},
doi={10.1007/s12541-013-0020-3},
url={https://doi.org/10.1007/s12541-013-0020-3}
}

@article{Khoonkari2021, 
title={Making the Stitching Process of Montaged SEM Images Automatic Using Fourier Transform Properties}, 
volume={27}, 
DOI={10.1017/S1431927621002208}, 
number={S1}, 
journal={Microscopy and Microanalysis}, 
publisher={Cambridge University Press}, 
author={Khoonkari, Nasim and Anand, Christopher and Bassim, Nabil}, 
year={2021}, pages={478–480}}

@INPROCEEDINGS{Singla2021,  author={Singla, Aayush and Lippmann, Bernhard and Graeb, Helmut},  
booktitle={2020 25th International Conference on Pattern Recognition (ICPR)},  
title={Recovery of 2D and 3D Layout Information through an Advanced Image Stitching Algorithm using Scanning Electron Microscope Images},   
year={2021},  
volume={},  number={},  
pages={3860-3867},  doi={10.1109/ICPR48806.2021.9412334}}

@ARTICLE{Titze2018,
AUTHOR={Titze, Benjamin and Genoud, Christel and Friedrich, Rainer W.},   
TITLE={SBEMimage: Versatile Acquisition Control Software for Serial Block-Face Electron Microscopy},      
JOURNAL={Frontiers in Neural Circuits},      
VOLUME={12},     
PAGES={54},     
YEAR={2018},      
URL={https://www.frontiersin.org/article/10.3389/fncir.2018.00054},       
DOI={10.3389/fncir.2018.00054},      
ISSN={1662-5110},   
ABSTRACT={We present SBEMimage, an open-source Python-based application to operate serial block-face electron microscopy (SBEM) systems. SBEMimage is designed for complex, challenging acquisition tasks, such as large-scale volume imaging of neuronal tissue or other biological ultrastructure. Advanced monitoring, process control, and error handling capabilities improve reliability, speed, and quality of acquisitions. Debris detection, autofocus, real-time image inspection, and various other quality control features minimize the risk of data loss during long-term acquisitions. Adaptive tile selection allows for efficient imaging of large tissue volumes of arbitrary shape. The software’s graphical user interface is optimized for remote operation. In its user-friendly viewport, tile grids covering the region of interest to be acquired are overlaid on previously acquired overview images of the sample surface. Images from other sources, e.g., light microscopes, can be imported and superimposed. SBEMimage complements existing DigitalMicrograph (Gatan Microscopy Suite) installations on 3View systems but permits higher acquisition rates by interacting directly with the microscope’s control software. Its modular architecture and the use of Python/PyQt make SBEMimage highly customizable and extensible, which allows for fast prototyping and will permit adaptation to a wide range of SBEM systems and applications.}
}


@Article{AUTrepout2017,
author={AU - Tr{\'e}pout, Sylvain
and AU - Bastin, Philippe
and AU - Marco, Sergio},
title={Preparation and Observation of Thick Biological Samples by Scanning Transmission Electron Tomography},
journal={JoVE},
year={2017},
month={Mar},
day={12},
publisher={MyJoVE Corp},
number={121},
pages={e55215},
keywords={Cellular Biology; electron tomography; scanning transmission electron microscopy; thick biological sample; <em>Trypanosoma brucei</em>; depth-of-field; through-focal tilt-series},
abstract={This report describes a protocol for preparing thick biological specimens for further observation using a scanning transmission electron microscope. It also describes an imaging method for studying the 3D structure of thick biological specimens by scanning transmission electron tomography. The sample preparation protocol is based on conventional methods in which the sample is fixed using chemical agents, treated with a heavy atom salt contrasting agent, dehydrated in a series of ethanol baths, and embedded in resin. The specific imaging conditions for observing thick samples by scanning transmission electron microscopy are then described. Sections of the sample are observed using a through-focus method involving the collection of several images at various focal planes. This enables the recovery of in-focus information at various heights throughout the sample. This particular collection pattern is performed at each tilt angle during tomography data collection. A single image is then generated, merging the in-focus information from all the different focal planes. A classic tilt-series dataset is then generated. The advantage of the method is that the tilt-series alignment and reconstruction can be performed using standard tools. The collection of through-focal images allows the reconstruction of a 3D volume that contains all of the structural details of the sample in focus.},
issn={1940-087X},
doi={10.3791/55215},
url={https://www.jove.com/t/55215},
url={https://doi.org/10.3791/55215}
}

@article{Brantner2016, 
title={A Reverse Engineering Approach for Imaging Neuronal Architecture – Large-Area, High-Resolution SEM Imaging}, 
volume={24}, DOI={10.1017/S1551929516000730}, 
number={5}, journal={Microscopy Today}, 
publisher={Cambridge University Press}, 
author={Brantner, Christine A. and Rasche, Martin and Burcham, Kevin E. and Klingfus, Joseph and Fridmann, Joel and Sanabia, Jason E. and Korman, Can E. and Popratiloff, Anastas}, 
year={2016}, pages={28–33}
}


@article{Kataoka2019,
author = {Michiyo Kataoka and Kinji Ishida  and Katsutoshi Ogasawara  and Takayuki Nozaki  and Yoh-Ichi Satoh  and Tetsutaro Sata  and Yuko Sato  and Hideki Hasegawa  and Noriko Nakajima  and Adolfo García-Sastre },
title = {Serial Section Array Scanning Electron Microscopy Analysis of Cells from Lung Autopsy Specimens following Fatal A/H1N1 2009 Pandemic Influenza Virus Infection},
journal = {Journal of Virology},
volume = {93},
number = {19},
pages = {e00644-19},
year = {2019},
doi = {10.1128/JVI.00644-19},
URL = {https://journals.asm.org/doi/abs/10.1128/JVI.00644-19},
eprint = {https://journals.asm.org/doi/pdf/10.1128/JVI.00644-19},
    abstract = { Generally, it is difficult to observe IAV particles in postmortem samples from patients with seasonal influenza. In fact, only a few viral antigens are detected in bronchial epithelial cells from autopsied lung sections. Previously, we detected many viral antigens in AEC-IIs from the lung. This was because the majority of A/H1N1/pdm09 in the lung tissue harbored an aspartic acid-to-glycine substitution at position 222 (D222G) of the hemagglutinin protein. A/H1N1/pdm09 harboring the D222G substitution has a receptor-binding preference for α-2,3-linked sialic acids expressed on human AECs and infects them in the same way as H5N1 and H7N9 avian IAVs. Here, we report the first successful observation of virus particles, not only in AEC-IIs, but also in Ms/Mϕs and Neus, using electron microscopy. The finding of a M/Mϕ harboring numerous virus particles within vesicles and at the cell surface suggests that Ms/Mϕs are involved in the pathogenesis of IAV primary pneumonia. A/H1N1 2009 pandemic influenza virus (A/H1N1/pdm09) was first identified as a novel pandemic influenza A virus (IAV) in 2009. Previously, we reported that many viral antigens were detected in type II alveolar epithelial cells (AEC-IIs) within autopsied lung tissue from a patient with A/H1N1/pdm09 pneumonia. It is important to identify the association between the virus and host cells to elucidate the pathogenesis of IAV pneumonia. To investigate the distribution of virus particles and morphological changes in host cells, the autopsied lung specimens from this patient were examined using transmission electron microscopy (TEM) and a novel scanning electron microscopy (SEM) method. We focused on AEC-IIs as viral antigen-positive cells and on monocytes/macrophages (Ms/Mϕs) and neutrophils (Neus) as innate immune cells. We identified virus particles and intranuclear dense tubules, which are associated with matrix 1 (M1) proteins from IAV. Large-scale two-dimensional observation was enabled by digitally “stitching” together contiguous SEM images. A single whole-cell analysis using a serial section array (SSA)-SEM identified virus particles in vesicles within the cytoplasm and/or around the surfaces of AEC-IIs, Ms/Mϕs, and Neus; however, intranuclear dense tubules were found only in AEC-IIs. Computer-assisted processing of SSA-SEM images from each cell type enabled three-dimensional (3D) modeling of the distribution of virus particles within an ACE-II, a M/Mϕ, and a Neu. IMPORTANCE Generally, it is difficult to observe IAV particles in postmortem samples from patients with seasonal influenza. In fact, only a few viral antigens are detected in bronchial epithelial cells from autopsied lung sections. Previously, we detected many viral antigens in AEC-IIs from the lung. This was because the majority of A/H1N1/pdm09 in the lung tissue harbored an aspartic acid-to-glycine substitution at position 222 (D222G) of the hemagglutinin protein. A/H1N1/pdm09 harboring the D222G substitution has a receptor-binding preference for α-2,3-linked sialic acids expressed on human AECs and infects them in the same way as H5N1 and H7N9 avian IAVs. Here, we report the first successful observation of virus particles, not only in AEC-IIs, but also in Ms/Mϕs and Neus, using electron microscopy. The finding of a M/Mϕ harboring numerous virus particles within vesicles and at the cell surface suggests that Ms/Mϕs are involved in the pathogenesis of IAV primary pneumonia. }
}

@article{MORE2011,
title = {A semi-automated method for identifying and measuring myelinated nerve fibers in scanning electron microscope images},
journal = {Journal of Neuroscience Methods},
volume = {201},
number = {1},
pages = {149-158},
year = {2011},
issn = {0165-0270},
doi = {https://doi.org/10.1016/j.jneumeth.2011.07.026},
url = {https://www.sciencedirect.com/science/article/pii/S0165027011004559},
author = {Heather L. More and Jingyun Chen and Eli Gibson and J. Maxwell Donelan and Mirza Faisal Beg},
keywords = {Image segmentation, Axon, Myelin, Nerve, Semi-automated, Scanning electron microscope},
abstract = {Diagnosing illnesses, developing and comparing treatment methods, and conducting research on the organization of the peripheral nervous system often require the analysis of peripheral nerve images to quantify the number, myelination, and size of axons in a nerve. Current methods that require manually labeling each axon can be extremely time-consuming as a single nerve can contain thousands of axons. To improve efficiency, we developed a computer-assisted axon identification and analysis method that is capable of analyzing and measuring sub-images covering the nerve cross-section, acquired using a scanning electron microscope. This algorithm performs three main procedures – it first uses cross-correlation to combine the acquired sub-images into a large image showing the entire nerve cross-section, then identifies and individually labels axons using a series of image intensity and shape criteria, and finally identifies and labels the myelin sheath of each axon using a region growing algorithm with the geometric centers of axons as seeds. To ensure accurate analysis of the image, we incorporated manual supervision to remove mislabeled axons and add missed axons. The typical user-assisted processing time for a two-megapixel image containing over 2000 axons was less than 1h. This speed was almost eight times faster than the time required to manually process the same image. Our method has proven to be well suited for identifying axons and their characteristics, and represents a significant time savings over traditional manual methods.}
}

@Article{Shimizu2021,
author={Shimizu, Yutaro
and Takagi, Junpei
and Ito, Emi
and Ito, Yoko
and Ebine, Kazuo
and Komatsu, Yamato
and Goto, Yumi
and Sato, Mayuko
and Toyooka, Kiminori
and Ueda, Takashi
and Kurokawa, Kazuo
and Uemura, Tomohiro
and Nakano, Akihiko},
title={Cargo sorting zones in the trans-Golgi network visualized by super-resolution confocal live imaging microscopy in plants},
journal={Nature Communications},
year={2021},
month={Mar},
day={26},
volume={12},
number={1},
pages={1901},
abstract={The trans-Golgi network (TGN) has been known as a key platform to sort and transport proteins to their final destinations in post-Golgi membrane trafficking. However, how the TGN sorts proteins with different destinies still remains elusive. Here, we examined 3D localization and 4D dynamics of TGN-localized proteins of Arabidopsis thaliana that are involved in either secretory or vacuolar trafficking from the TGN, by a multicolor high-speed and high-resolution spinning-disk confocal microscopy approach that we developed. We demonstrate that TGN-localized proteins exhibit spatially and temporally distinct distribution. VAMP721 (R-SNARE), AP (adaptor protein complex)−1, and clathrin which are involved in secretory trafficking compose an exclusive subregion, whereas VAMP727 (R-SNARE) and AP-4 involved in vacuolar trafficking compose another subregion on the same TGN. Based on these findings, we propose that the single TGN has at least two subregions, or ``zones'', responsible for distinct cargo sorting: the secretory-trafficking zone and the vacuolar-trafficking zone.},
issn={2041-1723},
doi={10.1038/s41467-021-22267-0},
url={https://doi.org/10.1038/s41467-021-22267-0}
}



@Article{Maeda2019,
AUTHOR = {Maeda, Mitsuyo and Seto, Toshiyuki and Kadono, Chiho and Morimoto, Hideto and Kida, Sachiho and Suga, Mitsuo and Nakamura, Motohiro and Kataoka, Yosky and Hamazaki, Takashi and Shintaku, Haruo},
TITLE = {Autophagy in the Central Nervous System and Effects of Chloroquine in Mucopolysaccharidosis Type II Mice},
JOURNAL = {International Journal of Molecular Sciences},
VOLUME = {20},
YEAR = {2019},
NUMBER = {23},
ARTICLE-NUMBER = {5829},
URL = {https://www.mdpi.com/1422-0067/20/23/5829},
PubMedID = {31757021},
ISSN = {1422-0067},
ABSTRACT = {Mucopolysaccharidosis type II (MPS II) is a rare lysosomal storage disease (LSD) involving a genetic error in iduronic acid-2-sulfatase (IDS) metabolism that leads to accumulation of glycosaminoglycans within intracellular lysosomes. The primary treatment for MPS II, enzyme replacement therapy, is not effective for central nervous system (CNS) symptoms, such as intellectual disability, because the drugs do not cross the blood–brain barrier. Recently, autophagy has been associated with LSDs. In this study, we examined the morphologic relationship between neuronal damage and autophagy in IDS knockout mice using antibodies against subunit c of mitochondrial adenosine triphosphate (ATP) synthetase and p62. Immunohistological changes suggesting autophagy, such as vacuolation, were observed in neurons, microglia, and pericytes throughout the CNS, and the numbers increased over postnatal development. Oral administration of chloroquine, which inhibits autophagy, did not suppress damage to microglia and pericytes, but greatly reduced neuronal vacuolation and eliminated neuronal cells with abnormal inclusions. Thus, decreasing autophagy appears to prevent neuronal degeneration. These results suggest that an autophagy modulator could be used in addition to conventional enzyme replacement therapy to preserve the CNS in patients with MPS II.},
DOI = {10.3390/ijms20235829}
}

@article{Dittmayer2021, 
title={Preparation of Samples for Large-Scale Automated Electron Microscopy of Tissue and Cell Ultrastructure}, 
volume={27}, 
DOI={10.1017/S1431927621011958}, 
number={4}, 
journal={Microscopy and Microanalysis}, 
publisher={Cambridge University Press}, 
author={Dittmayer, Carsten and Goebel, Hans-Hilmar and Heppner, Frank L. and Stenzel, Werner and Bachmann, Sebastian}, 
year={2021}, 
pages={815–827}
}

@article{Knott2013,
    author = {Knott, Graham and Genoud, Christel},
    title = "{Is EM dead?}",
    journal = {Journal of Cell Science},
    volume = {126},
    number = {20},
    pages = {4545-4552},
    year = {2013},
    month = {10},
    abstract = "{Since electron microscopy (EM) first appeared in the 1930s, it has held centre stage as the primary tool for the exploration of biological structure. Yet, with the recent developments of light microscopy techniques that overcome the limitations imposed by the diffraction boundary, the question arises as to whether the importance of EM in on the wane. This Commentary describes some of the pioneering studies that have shaped our understanding of cell structure. These include the development of cryo-EM techniques that have given researchers the ability to capture images of native structures and at the molecular level. It also describes how a number of recent developments significantly increase the ability of EM to visualise biological systems across a range of length scales, and in 3D, ensuring that EM will remain at the forefront of biology research for the foreseeable future.}",
    issn = {0021-9533},
    doi = {10.1242/jcs.124123},
    url = {https://doi.org/10.1242/jcs.124123},
    eprint = {https://journals.biologists.com/jcs/article-pdf/126/20/4545/1984914/jcs-126-20-4545.pdf},
}