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      Observing the cell in its native state: Imaging subcellular dynamics in multicellular organisms

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          Abstract

          True physiological imaging of subcellular dynamics requires studying cells within their parent organisms, where all the environmental cues that drive gene expression, and hence the phenotypes that we actually observe, are present. A complete understanding also requires volumetric imaging of the cell and its surroundings at high spatiotemporal resolution, without inducing undue stress on either. We combined lattice light-sheet microscopy with adaptive optics to achieve, across large multicellular volumes, noninvasive aberration-free imaging of subcellular processes, including endocytosis, organelle remodeling during mitosis, and the migration of axons, immune cells, and metastatic cancer cells in vivo. The technology reveals the phenotypic diversity within cells across different organisms and developmental stages and may offer insights into how cells harness their intrinsic variability to adapt to different physiological environments.

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          Most cited references73

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          Fiji: an open-source platform for biological-image analysis.

          Fiji is a distribution of the popular open-source software ImageJ focused on biological-image analysis. Fiji uses modern software engineering practices to combine powerful software libraries with a broad range of scripting languages to enable rapid prototyping of image-processing algorithms. Fiji facilitates the transformation of new algorithms into ImageJ plugins that can be shared with end users through an integrated update system. We propose Fiji as a platform for productive collaboration between computer science and biology research communities.
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            Enzymatic assembly of DNA molecules up to several hundred kilobases.

            We describe an isothermal, single-reaction method for assembling multiple overlapping DNA molecules by the concerted action of a 5' exonuclease, a DNA polymerase and a DNA ligase. First we recessed DNA fragments, yielding single-stranded DNA overhangs that specifically annealed, and then covalently joined them. This assembly method can be used to seamlessly construct synthetic and natural genes, genetic pathways and entire genomes, and could be a useful molecular engineering tool.
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              User-guided 3D active contour segmentation of anatomical structures: significantly improved efficiency and reliability.

              Active contour segmentation and its robust implementation using level set methods are well-established theoretical approaches that have been studied thoroughly in the image analysis literature. Despite the existence of these powerful segmentation methods, the needs of clinical research continue to be fulfilled, to a large extent, using slice-by-slice manual tracing. To bridge the gap between methodological advances and clinical routine, we developed an open source application called ITK-SNAP, which is intended to make level set segmentation easily accessible to a wide range of users, including those with little or no mathematical expertise. This paper describes the methods and software engineering philosophy behind this new tool and provides the results of validation experiments performed in the context of an ongoing child autism neuroimaging study. The validation establishes SNAP intrarater and interrater reliability and overlap error statistics for the caudate nucleus and finds that SNAP is a highly reliable and efficient alternative to manual tracing. Analogous results for lateral ventricle segmentation are provided.
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                Author and article information

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                Journal
                Science
                Science
                American Association for the Advancement of Science (AAAS)
                0036-8075
                1095-9203
                April 20 2018
                April 20 2018
                : 360
                : 6386
                Affiliations
                [1 ]Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, VA 20147, USA.
                [2 ]Department of Cell Biology, Harvard Medical School, 200 Longwood Avenue, Boston, MA 02115, USA.
                [3 ]Program in Cellular and Molecular Medicine, Boston Children’s Hospital, 200 Longwood Avenue, Boston, MA 02115, USA.
                [4 ]Department of Pediatrics, Harvard Medical School, 200 Longwood Avenue, Boston, MA 02115, USA.
                [5 ]Department of Systems Biology, Harvard Medical School, 200 Longwood Avenue, Boston, MA 02115, USA.
                [6 ]Department of Biochemistry and Cell Biology, Stony Brook University, Stony Brook, NY 11794-5215, USA.
                [7 ]Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, CA 94720, USA.
                [8 ]Howard Hughes Medical Institute and Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA 91125, USA.
                [9 ]Living Systems Institute, College of Life and Environmental Sciences, University of Exeter, Exeter EX4 4QD, UK.
                [10 ]Institute of Toxicology and Genetics, Karlsruhe Institute of Technology, 76021 Karlsruhe, Germany.
                Article
                10.1126/science.aaq1392
                6040645
                29674564
                88ae3f28-7362-4a00-adc0-cd1a4da73291
                © 2018
                History

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