Longitudinal analysis of antibody dynamics in COVID-19 convalescents reveals neutralizing responses up to 16 months after infection

  1. Yang Yang
  2. Minghui Yang
  3. Yun Peng
  4. Yanhua Liang
  5. Jinli Wei
  6. Li Xing
  7. Liping Guo
  8. Xiaohe Li
  9. Jie Li
  10. Jun Wang
  11. Mianhuan Li
  12. Zhixiang Xu
  13. Mingxia Zhang
  14. Fuxiang Wang
  15. Yi Shi
  16. Jing Yuan
  17. Yingxia Liu

Reviewed by

Read the full article See related articles

Listed in

Log in to save this article

Abstract

No abstract available

Article activity feed

  1. Version published to 10.1038/s41564-021-01051-2
  2. ScreenIT

    SciScore for 10.1101/2021.09.18.21263550: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: The study protocol was approved by the Ethics Committees of Shenzhen Third People’s Hospital (2020-010).
    Consent: Written informed consents were obtained from all patients.
    Sex as a biological variablenot detected.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    Enzyme-linked immunosorbent assay (ELISA): RBD and nucleocapsid (N) specific binding immunoglobulin G (IgG) antibodies were measured according to the manufacture’s protocols (Sinobio).
    IgG
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    Cell lines and viruses: African green monkey kidney Vero cell (ATCC, CCL-81) were obtained from ATCC, and 293 cells stably expressing ACE-2 (293-ACE-2) were obtained from Vazyme (Vazyme).
    293
    suggested: RRID:CVCL_DR94)
    A total of 4 × 105 ACE2-293T cells (Vazyme) in 100μl complete media were added per well and incubated for 48h at 37°C and 5% CO2.
    ACE2-293T
    suggested: None
    The mixture was added to Vero cells and incubated at 37°C and 5% CO2 for another 96 hours.
    Vero
    suggested: None
    Software and Algorithms
    SentencesResources
    All statistical tests were calculated using SPSS 20.0 for Windows (IBM).
    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 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 10.1101/2021.09.18.21263550v1 on medRxiv