Antibody Responses to BNT162b2 Vaccination in Japan: Monitoring Vaccine Efficacy by Measuring IgG Antibodies against the Receptor-Binding Domain of SARS-CoV-2

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Abstract

Mass vaccination campaigns using mRNA vaccines against SARS-CoV-2 have begun in many countries. Serological assays to detect antibody production may be a useful tool to monitor the efficacy of SARS-CoV-2 vaccination in individuals.

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  1. SciScore for 10.1101/2021.07.19.21260728: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Ethics statement, participants, and sample processing: This study was approved by the Ethics Committee for Clinical Research of the Center for Research Promotion and Support at Fujita Health University (authorization number HM20-526 and HM21-167).
    Consent: All participants provided written informed consent before undergoing any study procedure.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The plates were washed three times with PBS containing 0.1% Tween 20 (PBS-T), peroxidase-labelled anti-human IgM or IgA antibody (Midrand Bioproducts) was added as secondary antibody and incubated at room temperature for 60 min.
    anti-human IgM
    suggested: None
    IgA
    suggested: None
    After the bound and free fractions were separated, 50 μL of peroxidase-labelled anti-human IgG antibody was added and incubated at 37°C for 3 min, followed by separation of the bound and free fractions.
    anti-human IgG
    suggested: None
    Software and Algorithms
    SentencesResources
    Statistical analysis: Statistical analysis was performed using GraphPad Prism version 8.4.3 for windows (GraphPad Software).
    GraphPad Prism
    suggested: (GraphPad Prism, RRID:SCR_002798)
    GraphPad
    suggested: (GraphPad Prism, RRID:SCR_002798)

    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.

    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.