Developing RT-LAMP assays for rapid diagnosis of SARS-CoV-2 in saliva

This article has been Reviewed by the following groups

Read the full article See related articles

Discuss this preprint

Start a discussion What are Sciety discussions?

Abstract

No abstract available

Article activity feed

  1. SciScore for 10.1101/2021.04.25.21256085: (What is this?)

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

    Table 1: Rigor

    EthicsIRB: Assay targets for SARS-CoV-2 diagnosis: This COVID-19 research was approved by the Institutional Review Board at the University of Illinois at Chicago.
    Sex as a biological variablenot detected.
    RandomizationEach 10 µL of RT reaction included 1 µL of 10X RT buffer, 0.4 µL of 25X dNTP (100 mM), 1 µL of 10X random primers, 0.5 µL of reverse transcriptase, 1-5 µL of the RNA sample, and water to final volume of 10 µL.
    Blindingnot detected.
    Power Analysisnot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Experimental Models: Cell Lines
    SentencesResources
    HeLa cell RNA: HeLa cells were cultured at 37°C with 5% CO2 in DMEM media supplemented with 10% FBS.
    HeLa
    suggested: None
    Software and Algorithms
    SentencesResources
    The efficacy of LAMP or RT-LAMP amplification was evaluated by detection of fluorescence signals over a threshold readout (i.e., Time to Threshold, or TT).
    LAMP
    suggested: (LAMP, RRID:SCR_001740)
    The library samples were sequenced on MiniSeq (Illumina).
    MiniSeq
    suggested: None
    In addition, BLAST was performed to identify any sequence match to the NCBI GenBank database.
    BLAST
    suggested: (BLASTX, RRID:SCR_001653)

    Results from OddPub: Thank you for sharing your data.


    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.