Establishment of human post-vaccination SARS-CoV-2 standard reference sera

  1. Jinhua Xiang
  2. Louis Katz
  3. Patricia L. Winokur
  4. Ashok Chaudhary
  5. Barbara Digmann
  6. Rebecca Bradford
  7. Sujatha Rashid
  8. Sudakshina Ghosh
  9. Angela Robertson
  10. Joseph Menetski
  11. Miao Xu
  12. Peng Gao
  13. Catherine Z. Chen
  14. Taylor Lee
  15. Brittany Poelaert
  16. Richard T. Eastman
  17. Matthew D. Hall
  18. Jack T. Stapleton

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Abstract

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  1. Version published to 10.1016/j.jim.2024.113698
  2. ScreenIT

    SciScore for 10.1101/2022.01.24.22269773: (What is this?)

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

    Table 1: Rigor

    EthicsConsent: Subjects and serum collection: Following written informed consent, 68 individuals participated in the study.
    IRB: The study was approved by the University of Iowa Institutional Review Board (IRB, Committee A).
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Vaccinated subjects with no history of SARS-CoV-2 infection who lacked detectable antibodies to SARS-CoV-2 nucleocapsid but had antibodies to SARS-CoV-2 spike protein were recruited for a study of T cell responses to SARS-CoV-2.
    SARS-CoV-2
    suggested: None
    Laboratory methods: Samples from each study volunteer and each pooled serum preparation were evaluated for spike antibody using the LIASON® SARS-CoV-2 S1/S2 IgG assays (Roche Cobas, Roche Diagnostics, Basel, Switzerland) at the University of Iowa Pathology Laboratory and nucleocapsid antibodies using quantitative ELISA (IEQ-CoVN-IgG, IgM, RayBiotech, Peachtree, GA) as recommended by the manufacturer (10, 11).
    IEQ-CoVN-IgG, IgM
    suggested: None
    Roche anti-S antibody quantification (U/mL) were converted to estimated World Health Organization IU/mL using the formula recommended by Lukaszuk et al. (Roche U/ml / 0.972)(12).
    anti-S
    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.

    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.

  3. Version published to 10.1101/2022.01.24.22269773v1 on medRxiv