Fig 1: Expression of T-bet and GATA3 in clinical samples and PTCL cell lines(A) Representative PTCL cases of negative (−), positive Grade 1 (+) and positive Grade 2 (++) are shown. (B) Quantitative RT-PCR showed overexpression of GATA3 in Hut78 cells in comparison with T cells from healthy donors. For T-bet expression, there was a slight increase in Karpas 299 cells only.
Fig 2: The most prominent CD4+ T cell subsets in SS tissues are Th1 cells and Tfh cells. (a) Representative multi-color immunofluorescence image of CD3 (red), CD19 (green) and DAPI (blue) staining in a pSS lesion (patient number 2). (b) Absolute numbers of CD3+ T cells, CD19+ B cells in pSS (n = 10). Paired t test used to calculate p-value. (c) Representative multi-color staining showing each CD4+ T cell subset. [Th1: CD4+ (red) T-bet+ (light blue)] [Th2: CD4+ (red) GATA3+ (yellow)] [Th17: CD4+ (red) RORγ+ (white)] [Tfh: CD4+ (red) CXCR5+ (green)] [Treg: CD4+ (red) Foxp3+ (orange)] [CD4+ CTLs: CD4+ (red) GZMA+ (green)] (d) Relative proportions of Th1, Th2, Th17, Tfh, Treg and CD4+ CTL subsets in tissues from pSS (n = 13), secondary SS (n = 7) and IgG4-RD patients (n = 6). Error bars represent mean ± SEM. *p < 0.05.
Fig 3: AM cells and their restricted IGHV sequences within kidney allografts of patients with ABMR.(A) Representative multiplex immunofluorescence staining performed on a kidney allograft biopsy from a patient with acute DSA+ABMR+, at the time of ABMR episode. Arrows indicate CD20+CD27+T-bet+ (triple-positive) cells. Scale bars indicate 50 μm. (B) RNA-Seq analysis of kidney allograft biopsies was performed; DSA– (n = 7), DSA+ABMR– (n = 2), and DSA+ABMR+ (n = 12). Violin plots showing the expression levels of selected IGHV genes in kidney allograft biopsies. Kruskal-Wallis with Dunn’s posttest. *P < 0.05; **P < 0.01. Each dot represents 1 subject and horizontal lines are median values ± SEM.
Fig 4: The relativity between different TH cell subtypes and the correlation of different TH cell subtypes and ECM in the TIME. Representative immunofluorescent staining for CD4 (green), T-bet, GATA3, or CD25 (red) and 4,6-diamidino-2-phenylindole (DAPI) (blue) (bar = 20 μm.) and corresponding Masson’s trichrome staining (bar = 10/20 μm.) in TNBC samples with low or high tumor-infiltrating TH1 (A), TH2 (B), and Treg cells (C), which are indicated by arrows. (D) Pearson correlation analysis of the three subtypes of TH cells. The t-test analysis of variance between the collagen area of two groups with low or high tumor-infiltrating TH1 (E), TH2 (F), and Treg cells (G). ***p value < 0.001.
Fig 5: High-dimensional flow cytometry analyses of MBCs in kidney transplant patients.(A) t-SNE projections were generated using a concatenated file of n = 79,200 MBCs from HC (n = 4), DSA– (n = 20), DSA+ABMR– (n = 20), and DSA+ABMR+ (n = 20) patients; panels display expression levels of indicated markers (MFI). (B) t-SNE projections of MBC densities in the 4 groups using n = 19,800 cells from each group shown in panel A. (C) t-SNE map overlaid with 12 MBC clusters delineated by SPADE clustering of the concatenated file, as in panel A. (D) Heatmap showing the expression of markers for each MBC cluster according to transformed MFI ratio. (E) Stacked bar plot showing MBC cluster distribution based on SPADE clustering as in panel C. Clusters 3, 4, 6, 7, 9, 11, and 12 are significantly different in their proportions across the indicated groups. Kruskal-Wallis with Dunn’s posttest. (F) Representative examples of flow cytometry analysis and dot plot of percentages of CD21–T-bet+ cells in CD38lo B cells are displayed; HC (n = 17), DSA– (n = 48), DSA+ABMR– (n = 28), and DSA+ABMR+ (n = 20) patients. Kruskal-Wallis with Dunn’s posttest. **P < 0.01; ***P < 0.001; ****P < 0.0001. Each dot represents 1 subject and horizontal lines are mean values ± SEM. SPADE, spanning-tree progression analysis of density-normalized events; t-SNE, t-distributed stochastic neighbor embedding.
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