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. 2020 Jul 15;369(6508):eabc8511. doi: 10.1126/science.abc8511

Fig. 3. CD4 T cell activation in a subset of COVID-19 patients is associated with distinct CD4 T cell subsets.

Fig. 3

(A) Representative flow cytometry plots of the gating strategy for CD4 T cell subsets. (B) Frequencies of CD4 T cell subsets, as indicated. (C) Frequencies of KI67+ cells. The green line in the left panel denotes the upper decile of HDs. Representative flow cytometry plots are shown at right. (D) KI67+ cells from non-naïve CD4 T cells versus non-naïve CD8 T cells. Spearman correlation of COVID-19 patients is shown. (E) Frequencies of HLA-DR+CD38+ cells. The green line in the left panel denotes the upper decile of HDs. Representative flow cytometry plots are shown at right. (F) HLA-DR+CD38+ cells from non-naïve CD4 versus non-naïve CD8 T cells, Spearman correlation of COVID-19 patients is shown. (G) (Top) Global viSNE projection of non-naïve CD4 T cells for all participants pooled, with non-naïve CD4 T cells from HDs, RDs, and COVID-19 patients concatenated and overlaid. (Bottom) viSNE projections of indicated protein expression. (H) viSNE projection of non-naïve CD4 T cell clusters identified by FlowSOM clustering. (I) MFI as indicated (column-scaled z-scores). (J) Percentage of non-naïve CD4 T cells from each cohort in each FlowSOM cluster. Boxes represent IQRs. (B, C, E, and J) Each dot represents an individual HDs (green), RDs (blue), or COVID-19 patient (red). Significance was determined by unpaired Wilcoxon test with BH correction: *P < 0.05, **P < 0.01, ***P < 0.001, and ****P < 0.0001.