Biochemical, biophysical, and immunological characterization of respiratory secretions in severe SARS-CoV-2 infections

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Abstract

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  1. SciScore for 10.1101/2022.03.28.22272848: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Study Approval: All secretion samples were obtained under the auspices of research protocols approved the Stanford Institutional Review Board (IRB) (Stanford IRB approval #28205, #53685, #55650, #37232, and #43805).
    Consent: Samples were collected after written informed consent from patients or their surrogates prior to inclusion in the study.
    Sex as a biological variablenot detected.
    RandomizationHistology quantification: 150 500 pixel x 500 pixel regions of interest (ROIs) were randomly sampled from each tissue section imaged with the Aperio (Leica) AT2 Digital Pathology whole slide scanner.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Rabbit anti-versican antibody, clone EPR12277 (ab177480; Abcam) and rabbit anti-TSG-6 antibody (ab204049; Abcam) were used at 1:50 dilution.
    anti-versican
    suggested: (Abcam Cat# ab177480, RRID:AB_2827732)
    anti-TSG-6
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    For figure 3 and supplemental figures, most of the lung tissue samples from healthy, COVID-19 ARDS, and non-COVID-19 ARDS groups were obtained in collaboration with clinical partners at University of Texas Health Science Center at Houston (HSC-MS-15-1049 and HSC-MS-08-0354) and Houston Methodist Hospital (Pro00003392).
    HSC-MS-15-1049
    suggested: None
    HSC-MS-08-0354
    suggested: None
    Software and Algorithms
    SentencesResources
    Slides were scanned in bright-field at a 20× objective and the digital images imported for analysis using the Aperio Imagescope v12.4.3.5008 viewing software.
    Imagescope
    suggested: (ImageScope, RRID:SCR_014311)
    The RGB image was deconvolved into its hematoxylin and DAB components using the algorithm from (77), implemented in the rgb2hed function in the scikit-image Python package.
    Python
    suggested: (IPython, RRID:SCR_001658)

    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: We detected the following sentences addressing limitations in the study:
    These studies have several limitations. Most notable is the small numbers of cases and samples of secretions involved. These findings need to be confirmed in larger, multi-center studies involving individuals with diverse backgrounds and case presentations. The underlying mechanisms that lead to increased HA would also benefit from further research to identify the causative cell types and signalling pathways. In addition, data in SARS-CoV-2 animal models would enable improved understanding of the contribution of HA to pathogenesis in this disease. Finally, to safely acquire the rheology data, the COVID-19 samples were heat treated to render the samples non-infectious. In control CF samples, this same heat treatment was found to decrease the modulus (Supplemental Figure 4A), presumably due to the denaturation of biopolymers in the sample. Since we observed that higher modulus samples had larger responses to enzymatic treatment, the true effect of enzymatic treatment on COVID-19 lung secretion may be larger than that reported here using heat-treated samples. Future studies should further evaluate a range of enzymatic treatment dosages and durations to assess the rheological effects on non-heat-treated COVID-19 lung secretions. Additionally, the necessity of using induction to collect healthy sputum is a limitation. These studies may inform the development of much needed therapeutics for patients with COVID-19. Indeed, a study of oral hymecromone as a potential tool for HA inhib...

    Results from TrialIdentifier: We found the following clinical trial numbers in your paper:

    IdentifierStatusTitle
    NCT04359654CompletedNebulised Dornase Alfa for Treatment of COVID-19
    NCT04541979RecruitingAerosoliserat DNase for Treatment of Respiratory Failure in …
    NCT02780752CompletedA Study of Oral Hymecromone and Hyaluronan Synthesis


    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.

    Results from scite Reference Check: We found no unreliable references.


    About SciScore

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.

  2. SciScore for 10.1101/2020.09.11.20191692: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementConsent: Written informed consent was obtained from patients or their surrogates.
    IRB: The cells were isolated as described previously in accordance with approval from the institution’s human subjects review committee.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variableFive were male, three were female.

    Table 2: Resources

    Software and Algorithms
    SentencesResources
    Image analysis was performed using Image J (NIH), as described previously34.
    Image J
    suggested: (ImageJ, RRID:SCR_003070)

    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: We detected the following sentences addressing limitations in the study:
    These studies have several limitations. Most notable is the small numbers of cases and samples of sputum involved. These findings need to be confirmed in larger, multi-center studies involving individuals with diverse backgrounds and case presentations. The underlying mechanism of the increased HA we found would also benefit from further research of the cell types and signalling pathways that produce HA in the lung. In addition, data in SARS-CoV-2 animal models would enable improved understanding of the contribution of HA to pathogenesis in this disease. That stated, given the evidence supporting low molecule weight HA’s role in respiratory inflammation, including COVID-19-associated respiratory distress and mortality, further investigation of the utility of agents known to reduce HA content, such as hymecromone, is recommended. In summary, these data reveal a novel role for HA in COVID-19 respiratory secretions that have important implications for the development of much needed therapeutics for patients with COVID-19.

    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

    SciScore is an automated tool that is designed to assist expert reviewers by finding and presenting formulaic information scattered throughout a paper in a standard, easy to digest format. SciScore checks for the presence and correctness of RRIDs (research resource identifiers), and for rigor criteria such as sex and investigator blinding. For details on the theoretical underpinning of rigor criteria and the tools shown here, including references cited, please follow this link.