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      Interaction of human keratinocytes and nerve fiber terminals at the neuro-cutaneous unit

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          Abstract

          Traditionally, peripheral sensory neurons are assumed as the exclusive transducers of external stimuli. Current research moves epidermal keratinocytes into focus as sensors and transmitters of nociceptive and non-nociceptive sensations, tightly interacting with intraepidermal nerve fibers at the neuro-cutaneous unit. In animal models, epidermal cells establish close contacts and ensheath sensory neurites. However, ultrastructural morphological and mechanistic data examining the human keratinocyte-nerve fiber interface are sparse. We investigated this exact interface in human skin applying super-resolution array tomography, expansion microscopy, and structured illumination microscopy. We show keratinocyte ensheathment of afferents and adjacent connexin 43 contacts in native skin and have applied a pipeline based on expansion microscopy to quantify these parameter in skin sections of healthy participants versus patients with small fiber neuropathy. We further derived a fully human co-culture system, visualizing ensheathment and connexin 43 plaques in vitro. Unraveling human intraepidermal nerve fiber ensheathment and potential interaction sites advances research at the neuro-cutaneous unit. These findings are crucial on the way to decipher the mechanisms of cutaneous nociception.

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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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            Computer visualization of three-dimensional image data using IMOD.

            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.
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              Cellpose: a generalist algorithm for cellular segmentation

              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.
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                Author and article information

                Contributors
                Role: Reviewing Editor
                Role: Senior Editor
                Journal
                eLife
                Elife
                eLife
                eLife
                eLife Sciences Publications, Ltd
                2050-084X
                16 January 2024
                2024
                : 13
                : e77761
                Affiliations
                [1 ] Department of Neurology, University Hospital of Würzburg ( https://ror.org/03pvr2g57) Würzburg Germany
                [2 ] Imaging Core Facility, Biocenter, University of Würzburg ( https://ror.org/03pvr2g57) Würzburg Germany
                [3 ] Department of Biotechnology and Biophysics, University of Würzburg ( https://ror.org/03pvr2g57) Würzburg Germany
                National Institutes of Health ( https://ror.org/01cwqze88) United States
                National Institute of Neurological Disorders and Stroke, National Institutes of Health ( https://ror.org/01cwqze88) United States
                National Institutes of Health ( https://ror.org/01cwqze88) United States
                National Institutes of Health ( https://ror.org/01cwqze88) United States
                University of Pittsburgh ( https://ror.org/01an3r305) United States
                UT Dallas ( https://ror.org/049emcs32) United States
                Author notes
                [†]

                Institute of Clinical Genetics, Technical University Dresden, Dresden, Germany.

                Author information
                https://orcid.org/0000-0001-5931-6673
                https://orcid.org/0000-0002-2719-9617
                https://orcid.org/0000-0002-1692-3219
                https://orcid.org/0000-0001-6941-2669
                https://orcid.org/0000-0001-6973-6428
                Article
                77761
                10.7554/eLife.77761
                10791129
                38225894
                f52ce1db-86bd-4919-bec4-2a896d2bce73
                © 2024, Erbacher et al

                This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.

                History
                : 09 February 2022
                : 19 December 2023
                Funding
                Funded by: FundRef http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
                Award ID: DFG UE171/4-1
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100001659, Deutsche Forschungsgemeinschaft;
                Award ID: UE171/15-1
                Award Recipient :
                Funded by: FundRef http://dx.doi.org/10.13039/501100000781, European Research Council;
                Award ID: ULTRARESOLUTION
                Award Recipient :
                The funders had no role in study design, data collection, and interpretation, or the decision to submit the work for publication.
                Categories
                Research Article
                Neuroscience
                Custom metadata
                Sensory nerve fiber ending ensheathment and connexin 43 contacts by keratinocytes at the neuro-cutaneous unit can be visualized and quantified at super-resolution in human skin.

                Life sciences
                neuro-cutaneous unit,neuropathic pain,keratinocyte,super-resolution microscopy,sensory neurons,human

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