Multiscale 3-dimensional pathology findings of COVID-19 diseased lung using high-resolution cleared tissue microscopy

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Abstract

The study of pulmonary samples from individuals who have died as a direct result of COVID-19 infection is vital to our understanding of the pathogenesis of this disease. Histopathologic studies of lung tissue from autopsy of patients with COVID-19 specific mortality are only just emerging. All existing reports have relied on traditional 2-dimensional slide-based histological methods for specimen preparation. However, emerging methods for high-resolution, massively multiscale imaging of tissue microstructure using fluorescence labeling and tissue clearing methods enable the acquisition of tissue histology in 3-dimensions, that could open new insights into the nature of SARS-Cov-2 infection and COVID-19 disease processes. In this article, we present the first 3-dimensional images of lung autopsy tissues taken from a COVID-19 patient, including 3D “virtual histology” of cubic-millimeter volumes of the diseased lung, providing unique insights into disease processes contributing to mortality that could inform frontline treatment decisions.

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  1. SciScore for 10.1101/2020.04.11.037473: (What is this?)

    Please note, not all rigor criteria are appropriate for all manuscripts.

    Table 1: Rigor

    Institutional Review Board StatementIACUC: All experiments were conducted in accordance with SARS-CoV-2 (Risk Factor 3)-specific protocols approved by the Tulane University Institutional Biosafety Committee.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysis8 The system is fitted with a 488-nm laser source (Omicron, PhoxX; maximum power = 200 mW) for fluorescence excitation of Eosin and a 647-nm laser source (Omicron, PhoxX; maximum power = 140 mW) for fluorescence excitation of TO-PRO-3 iodide.
    Sex as a biological variablenot detected.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    After regions of interest were identified, sub-volumes were loaded at full resolution into Amira and the OpenViSUS17 interactive framework for further visualization.
    Amira
    suggested: None

    Results from OddPub: We did not detect open data. We also did not detect open code. Researchers are encouraged to share open data when possible (see Nature blog).


    Results from LimitationRecognizer: An explicit section about the limitations of the techniques employed in this study was not found. We encourage authors to address study limitations.

    Results from TrialIdentifier: No clinical trial numbers were referenced.


    Results from Barzooka: We did not find any issues relating to the usage of bar graphs.


    Results from JetFighter: We did not find any issues relating to colormaps.


    Results from rtransparent:
    • Thank you for including a conflict of interest statement. Authors are encouraged to include this statement when submitting to a journal.
    • Thank you for including a funding statement. Authors are encouraged to include this statement when submitting to a journal.
    • No protocol registration statement was detected.

    About SciScore

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