Plasma from patients with bacterial sepsis or severe COVID-19 induces suppressive myeloid cell production from hematopoietic progenitors in vitro

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Abstract

Cytokines in plasma from sepsis or severe COVID-19 patients induce production of suppressive myeloid cells from hematopoietic progenitors in vitro.

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  1. SciScore for 10.1101/2020.09.02.280180: (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 Partners Healthcare Institutional Review Board under protocol 2017P001681.
    Randomizationnot detected.
    Blindingnot detected.
    Power Analysisnot detected.
    Sex as a biological variablenot detected.
    Cell Line Authenticationnot detected.

    Table 2: Resources

    Antibodies
    SentencesResources
    The permeabilized cells were then stained with a pSTAT3-Y705 antibody (clone 13A3-1, BioLegend) for 30 mins on ice.
    pSTAT3-Y705
    suggested: None
    Experimental Models: Cell Lines
    SentencesResources
    HUVEC and HRE co-culture and flow sorting: Primary HUVECs and HREs were purchased from Lonza and cultured in EGM-2 and REGM, respectively.
    HUVEC
    suggested: KCB Cat# KCB 200648YJ, RRID:CVCL_2959)
    To improve cell viability, HUVECs were cultured in tissue culture plates pre-coated with Matrigel (Corning) diluted 1:100 in EBM-2 (Lonza).
    HUVECs
    suggested: None
    Software and Algorithms
    SentencesResources
    STAR was used to align sequencing reads to the UCSC hg19 transcriptome and RSEM was used to generate an expression matrix for all samples.
    STAR
    suggested: (STAR, RRID:SCR_015899)
    RSEM
    suggested: (RSEM, RRID:SCR_013027)
    Both raw count and transcripts per million data were analyzed using edgeR and custom python scripts.
    edgeR
    suggested: (edgeR, RRID:SCR_012802)
    python
    suggested: (IPython, RRID:SCR_001658)
    RNA velocity analysis was performed using the scVelo package60 using the default parameters.
    scVelo
    suggested: (scVelo, RRID:SCR_018168)
    STAR was used to align sequencing reads to the UCSC hg19 transcriptome and RSEM was used to generate an expression matrix for all samples.
    STAR
    suggested: (STAR, RRID:SCR_015899)
    RSEM
    suggested: (RSEM, RRID:SCR_013027)
    CRISPR-Cas9 editing of CD34+ HSPCs: Cas9 protein, pre-designed guide RNAs targeting IL6ST, IL6R, IL10RA, and IL10RB and non-targeting guide RNAs (from GeCKO v2 library) were purchased from Integrated DNA Technologies.
    GeCKO
    suggested: (Gecko, RRID:SCR_009001)
    Flow cytometry data were acquired on a Cytoflex LX (Beckman Coulter) and analyzed using FlowJo v10.1.
    FlowJo
    suggested: (FlowJo, RRID:SCR_008520)

    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: Please consider improving the rainbow (“jet”) colormap(s) used on pages 32 and 9. At least one figure is not accessible to readers with colorblindness and/or is not true to the data, i.e. not perceptually uniform.


    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.