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      3D imaging of human organs with micrometer resolution - applied to the endocrine pancreas

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          Abstract

          The possibility to quantitatively study specific molecular/cellular features of complete human organs with preserved spatial 3D context would have widespread implications for pre-clinical and clinical medicine. Whereas optical 3D imaging approaches have experienced a formidable revolution, they have remained limited due to current incapacities in obtaining specific labelling within large tissue volumes. We present a simple approach enabling reconstruction of antibody labeled cells within entire human organs with preserved organ context. We demonstrate the utility of the approach by providing volumetric data and 3D distribution of hundreds of thousands of islets of Langerhans within the human pancreas. By assessments of pancreata from non-diabetic and type 2 diabetic individuals, we display previously unrecognized features of the human islet mass distribution and pathology. As such, this method may contribute not only in unraveling new information of the pancreatic anatomy/pathophysiology, but it may be translated to essentially any antibody marker or organ system.

          Abstract

          Hahn et al. present a method to visualize the endocrine human pancreas in 3D and calculate volumetric data. Using immunolabeling to visualize targets of interest and in reconstructing large tissue parts from imaged cm3-sized tissue blocks, they use their method to reveal previously unknown morphological differences in the endocrine pancreas affected with type 2 diabetes.

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          Most cited references38

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          Reconstruction of zebrafish early embryonic development by scanned light sheet microscopy.

          A long-standing goal of biology is to map the behavior of all cells during vertebrate embryogenesis. We developed digital scanned laser light sheet fluorescence microscopy and recorded nuclei localization and movement in entire wild-type and mutant zebrafish embryos over the first 24 hours of development. Multiview in vivo imaging at 1.5 billion voxels per minute provides "digital embryos," that is, comprehensive databases of cell positions, divisions, and migratory tracks. Our analysis of global cell division patterns reveals a maternally defined initial morphodynamic symmetry break, which identifies the embryonic body axis. We further derive a model of germ layer formation and show that the mesendoderm forms from one-third of the embryo's cells in a single event. Our digital embryos, with 55 million nucleus entries, are provided as a resource.
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            Optical sectioning deep inside live embryos by selective plane illumination microscopy.

            Large, living biological specimens present challenges to existing optical imaging techniques because of their absorptive and scattering properties. We developed selective plane illumination microscopy (SPIM) to generate multidimensional images of samples up to a few millimeters in size. The system combines two-dimensional illumination with orthogonal camera-based detection to achieve high-resolution, optically sectioned imaging throughout the sample, with minimal photodamage and at speeds capable of capturing transient biological phenomena. We used SPIM to visualize all muscles in vivo in the transgenic Medaka line Arnie, which expresses green fluorescent protein in muscle tissue. We also demonstrate that SPIM can be applied to visualize the embryogenesis of the relatively opaque Drosophila melanogaster in vivo.
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              Tissue clearing and its applications in neuroscience

              State-of-the-art tissue-clearing methods provide subcellular-level optical access to intact tissues from individual organs and even to some entire mammals. When combined with light-sheet microscopy and automated approaches to image analysis, existing tissue-clearing methods can speed up and may reduce the cost of conventional histology by several orders of magnitude. In addition, tissue-clearing chemistry allows whole-organ antibody labelling, which can be applied even to thick human tissues. By combining the most powerful labelling, clearing, imaging and data-analysis tools, scientists are extracting structural and functional cellular and subcellular information on complex mammalian bodies and large human specimens at an accelerated pace. The rapid generation of terabyte-scale imaging data furthermore creates a high demand for efficient computational approaches that tackle challenges in large-scale data analysis and management. In this Review, we discuss how tissue-clearing methods could provide an unbiased, system-level view of mammalian bodies and human specimens and discuss future opportunities for the use of these methods in human neuroscience.
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                Author and article information

                Contributors
                Ulf.Ahlgren@umu.se
                Journal
                Commun Biol
                Commun Biol
                Communications Biology
                Nature Publishing Group UK (London )
                2399-3642
                10 September 2021
                10 September 2021
                2021
                : 4
                : 1063
                Affiliations
                [1 ]GRID grid.12650.30, ISNI 0000 0001 1034 3451, Umeå Centre for Molecular Medicine, , Umeå University, ; Umeå, Sweden
                [2 ]GRID grid.8993.b, ISNI 0000 0004 1936 9457, Department of Immunology, Genetics and Pathology, , Uppsala University, ; Uppsala, Sweden
                Author information
                http://orcid.org/0000-0002-0712-8256
                http://orcid.org/0000-0001-9401-6844
                http://orcid.org/0000-0001-5923-8572
                Article
                2589
                10.1038/s42003-021-02589-x
                8433206
                34508173
                9aa070e5-0c64-48a1-bd24-954a2252b1d7
                © The Author(s) 2021

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 8 March 2021
                : 23 August 2021
                Funding
                Funded by: FundRef https://doi.org/10.13039/501100004973, Barndiabetesfonden;
                Funded by: FundRef https://doi.org/10.13039/501100004359, Vetenskapsrådet (Swedish Research Council);
                Funded by: FundRef https://doi.org/10.13039/501100009708, Novo Nordisk Fonden (Novo Nordisk Foundation);
                Funded by: FundRef https://doi.org/10.13039/100008871, JDRF;
                Funded by: FundRef https://doi.org/10.13039/501100007067, Kempestiftelserna (Kempe Foundations);
                Funded by: FundRef https://doi.org/10.13039/501100004885, Umeå Universitet (Umeå University);
                Funded by: Diabetes Wellness (Sverige) Swedish national strategic research initiative EXODIAB
                Categories
                Article
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                © The Author(s) 2021

                diabetes,optical imaging,3-d reconstruction,islets of langerhans

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