Development of a smartphone-based quantum dot lateral flow immunoassay strip for ultrasensitive detection of anti-SARS-CoV-2 IgG and neutralizing antibodies

  1. Jinfeng Li
  2. Bochao Liu
  3. Xi Tang
  4. Ze Wu
  5. Jinhui Lu
  6. Chaolan Liang
  7. Shuiping Hou
  8. Ling Zhang
  9. Tingting Li
  10. Wei Zhao
  11. Yongshui Fu
  12. Yuebin Ke
  13. Chengyao Li

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Abstract

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  1. Version published to 10.1016/j.ijid.2022.04.042
  2. ScreenIT

    SciScore for 10.1101/2020.07.21.20159392: (What is this?)

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

    Table 1: Rigor

    Institutional Review Board StatementIRB: This study was approved by the Medical Ethics Committees of Shenzhen CDC and Southern Medical University, and followed the ethical guidelines of the 1975 Declaration of Helsinki.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The colloid gold lateral flow immunoassay strip (CG-LFIA; Lvshiyuan Biotechnology Co. Ltd., Shenzhen, China) was used as comparative assay for detection of antibodies to SARS-CoV-2.
    SARS-CoV-2
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Recombinant spike protein receptor binding domain fused with mouse IgG-Fc fragment (S-RBD) and nucleocapsid phosphoprotein (NP) of SARS-CoV-2 were purchased from Bioeast Biotech Co. Ltd (Hangzhou, China) and S-RBD was produced from HEK293 cells and NP was produced in E. coli, respectively.
    HEK293
    suggested: CLS Cat# 300192/p777_HEK293, RRID:CVCL_0045)
    Software and Algorithms
    SentencesResources
    The data were analyzed using the statistical package SPSS v. 16.0.
    SPSS
    suggested: (SPSS, RRID:SCR_002865)

    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 found bar graphs of continuous data. We recommend replacing bar graphs with more informative graphics, as many different datasets can lead to the same bar graph. The actual data may suggest different conclusions from the summary statistics. For more information, please see Weissgerber et al (2015).

    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.

  3. Version published to 10.1101/2020.07.21.20159392 on medRxiv