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a Heatmap from <t>bulk</t> <t>RNA-seq</t> of WT and XPC⁻/⁻ Th17 cells showing genes related to transcriptional regulation, cytokine signaling, and chemokine responses, displayed as Z-score–normalized values calculated per gene across samples. b – c Flow cytometry contour plots and histograms showing IL-17A and RORγt expression in CD4⁺ T cells from WT and XPC⁻/⁻ mice, with percentages of IL-17A⁺RORγt⁺ and IL-17A⁻RORγt⁺ populations and mean fluorescence intensity (MFI) values indicated ( n = 5 technical replicates). d – f ) Quantification of CD4⁺IL-17A⁺RORγt⁺ cells, CD4⁺RORγt⁺ cells, and RORγt expression (MFI) in WT and XPC⁻/⁻ mice ( n = 5 technical replicates). Data are presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test, with exact P values indicated. g – i Flow cytometric analysis and quantification of phosphorylated STAT3 (pSTAT3) expression in CD4⁺ T cells from WT and XPC⁻/⁻ mice, shown as percentage of pSTAT3⁺ cells and MFI ( n = 5 technical replicates). Data are presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test, with exact P values shown. j – l Flow cytometry histograms and quantification of IL-23R expression in CD4⁺ T cells from WT and XPC⁻/⁻ mice, shown as percentage of IL-23R⁺ cells and MFI ( n = 5 technical replicates). Data are presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test, with exact P values indicated. ( M – O ) Flow cytometry histograms and quantification of IL-1R1 expression in CD4⁺ T cells from WT and XPC⁻/⁻ mice, shown as percentage of IL-1R1⁺ cells and MFI ( n = 5 technical replicates). Data are presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test, with exact P values shown. p – q ) Flow cytometry contour plots and quantification of CD4⁺IL-17A⁺FoxP3⁺ T cells in WT and XPC⁻/⁻ mice ( n = 5 technical replicates), presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test with exact P values indicated. WT samples are shown in black and XPC⁻/⁻ samples in purple. Data are representative of at least three independent experiments. Statistical significance is indicated as follows (* p < 0.05, ** p < 0.01, *** p < 0.001).
Single Cell Rna Seq Data, supplied by Broad Clinical Labs, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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a Heatmap from <t>bulk</t> <t>RNA-seq</t> of WT and XPC⁻/⁻ Th17 cells showing genes related to transcriptional regulation, cytokine signaling, and chemokine responses, displayed as Z-score–normalized values calculated per gene across samples. b – c Flow cytometry contour plots and histograms showing IL-17A and RORγt expression in CD4⁺ T cells from WT and XPC⁻/⁻ mice, with percentages of IL-17A⁺RORγt⁺ and IL-17A⁻RORγt⁺ populations and mean fluorescence intensity (MFI) values indicated ( n = 5 technical replicates). d – f ) Quantification of CD4⁺IL-17A⁺RORγt⁺ cells, CD4⁺RORγt⁺ cells, and RORγt expression (MFI) in WT and XPC⁻/⁻ mice ( n = 5 technical replicates). Data are presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test, with exact P values indicated. g – i Flow cytometric analysis and quantification of phosphorylated STAT3 (pSTAT3) expression in CD4⁺ T cells from WT and XPC⁻/⁻ mice, shown as percentage of pSTAT3⁺ cells and MFI ( n = 5 technical replicates). Data are presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test, with exact P values shown. j – l Flow cytometry histograms and quantification of IL-23R expression in CD4⁺ T cells from WT and XPC⁻/⁻ mice, shown as percentage of IL-23R⁺ cells and MFI ( n = 5 technical replicates). Data are presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test, with exact P values indicated. ( M – O ) Flow cytometry histograms and quantification of IL-1R1 expression in CD4⁺ T cells from WT and XPC⁻/⁻ mice, shown as percentage of IL-1R1⁺ cells and MFI ( n = 5 technical replicates). Data are presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test, with exact P values shown. p – q ) Flow cytometry contour plots and quantification of CD4⁺IL-17A⁺FoxP3⁺ T cells in WT and XPC⁻/⁻ mice ( n = 5 technical replicates), presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test with exact P values indicated. WT samples are shown in black and XPC⁻/⁻ samples in purple. Data are representative of at least three independent experiments. Statistical significance is indicated as follows (* p < 0.05, ** p < 0.01, *** p < 0.001).
Single Cell Rna Seq Data Fromcrohn, supplied by Broad Clinical Labs, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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a Heatmap from bulk RNA-seq of WT and XPC⁻/⁻ Th17 cells showing genes related to transcriptional regulation, cytokine signaling, and chemokine responses, displayed as Z-score–normalized values calculated per gene across samples. b – c Flow cytometry contour plots and histograms showing IL-17A and RORγt expression in CD4⁺ T cells from WT and XPC⁻/⁻ mice, with percentages of IL-17A⁺RORγt⁺ and IL-17A⁻RORγt⁺ populations and mean fluorescence intensity (MFI) values indicated ( n = 5 technical replicates). d – f ) Quantification of CD4⁺IL-17A⁺RORγt⁺ cells, CD4⁺RORγt⁺ cells, and RORγt expression (MFI) in WT and XPC⁻/⁻ mice ( n = 5 technical replicates). Data are presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test, with exact P values indicated. g – i Flow cytometric analysis and quantification of phosphorylated STAT3 (pSTAT3) expression in CD4⁺ T cells from WT and XPC⁻/⁻ mice, shown as percentage of pSTAT3⁺ cells and MFI ( n = 5 technical replicates). Data are presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test, with exact P values shown. j – l Flow cytometry histograms and quantification of IL-23R expression in CD4⁺ T cells from WT and XPC⁻/⁻ mice, shown as percentage of IL-23R⁺ cells and MFI ( n = 5 technical replicates). Data are presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test, with exact P values indicated. ( M – O ) Flow cytometry histograms and quantification of IL-1R1 expression in CD4⁺ T cells from WT and XPC⁻/⁻ mice, shown as percentage of IL-1R1⁺ cells and MFI ( n = 5 technical replicates). Data are presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test, with exact P values shown. p – q ) Flow cytometry contour plots and quantification of CD4⁺IL-17A⁺FoxP3⁺ T cells in WT and XPC⁻/⁻ mice ( n = 5 technical replicates), presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test with exact P values indicated. WT samples are shown in black and XPC⁻/⁻ samples in purple. Data are representative of at least three independent experiments. Statistical significance is indicated as follows (* p < 0.05, ** p < 0.01, *** p < 0.001).

Journal: Nature Communications

Article Title: Th17 cells require the DNA repair sensor xeroderma pigmentosum complementation Group C to control oxidative DNA damage in a murine model

doi: 10.1038/s41467-026-69914-y

Figure Lengend Snippet: a Heatmap from bulk RNA-seq of WT and XPC⁻/⁻ Th17 cells showing genes related to transcriptional regulation, cytokine signaling, and chemokine responses, displayed as Z-score–normalized values calculated per gene across samples. b – c Flow cytometry contour plots and histograms showing IL-17A and RORγt expression in CD4⁺ T cells from WT and XPC⁻/⁻ mice, with percentages of IL-17A⁺RORγt⁺ and IL-17A⁻RORγt⁺ populations and mean fluorescence intensity (MFI) values indicated ( n = 5 technical replicates). d – f ) Quantification of CD4⁺IL-17A⁺RORγt⁺ cells, CD4⁺RORγt⁺ cells, and RORγt expression (MFI) in WT and XPC⁻/⁻ mice ( n = 5 technical replicates). Data are presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test, with exact P values indicated. g – i Flow cytometric analysis and quantification of phosphorylated STAT3 (pSTAT3) expression in CD4⁺ T cells from WT and XPC⁻/⁻ mice, shown as percentage of pSTAT3⁺ cells and MFI ( n = 5 technical replicates). Data are presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test, with exact P values shown. j – l Flow cytometry histograms and quantification of IL-23R expression in CD4⁺ T cells from WT and XPC⁻/⁻ mice, shown as percentage of IL-23R⁺ cells and MFI ( n = 5 technical replicates). Data are presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test, with exact P values indicated. ( M – O ) Flow cytometry histograms and quantification of IL-1R1 expression in CD4⁺ T cells from WT and XPC⁻/⁻ mice, shown as percentage of IL-1R1⁺ cells and MFI ( n = 5 technical replicates). Data are presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test, with exact P values shown. p – q ) Flow cytometry contour plots and quantification of CD4⁺IL-17A⁺FoxP3⁺ T cells in WT and XPC⁻/⁻ mice ( n = 5 technical replicates), presented as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test with exact P values indicated. WT samples are shown in black and XPC⁻/⁻ samples in purple. Data are representative of at least three independent experiments. Statistical significance is indicated as follows (* p < 0.05, ** p < 0.01, *** p < 0.001).

Article Snippet: Single-cell RNA-seq data were obtained from the Broad Institute Single Cell Portal (SCP1884) and originally published by Kong et al. (2023).

Techniques: RNA Sequencing, Flow Cytometry, Expressing, Fluorescence

a Body weight change, expressed as percentage of initial weight, in Rag1⁻/⁻ mice receiving CD4⁺CD45RB^high T cells from WT or XPC⁻/⁻ donors, monitored weekly for 4 weeks after transfer ( n = 5 per group). Data are presented as mean ± SEM and analyzed using a two-sided two-way ANOVA with repeated measures followed by Tukey’s multiple-comparisons post hoc test. b Colon length measured at the experimental endpoint in Rag1⁻/⁻ mice receiving WT or XPC⁻/⁻ CD4⁺ T cells ( n = 5 per group). Data are shown as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test. c – f Representative colonoscopy images, hematoxylin and eosin–stained histological sections, and quantification of endoscopy and histology scores in Rag1⁻/⁻ mice receiving WT or XPC⁻/⁻ CD4⁺ T cells ( n = 5 per group). Quantitative data are shown as individual data points with mean ± SEM and analyzed using two-sided unpaired Student’s t -tests with exact P values indicated. g – h Flow cytometry contour plots showing IFN-γ, IL-17A, and FoxP3 expression in CD4⁺ T cells isolated from mesenteric lymph nodes (mLNs) and large-intestine lamina propria (LI-LP) of Rag1⁻/⁻ mice receiving WT or XPC⁻/⁻ CD4⁺ T cells. i – j Quantification of CD4⁺CD45⁺ T cell subsets (IL-17A⁺, IFN-γ⁺, and FoxP3⁺) from mLNs and LI-LP ( n = 5 per group). Data are presented as mean ± SEM and analyzed using two-sided unpaired Student’s t-tests with exact P values indicated. k – m t-SNE analysis of immune cell populations from colonic tissue of Crohn’s disease patients, heatmap showing scaled expression of DNA repair genes, transcription factors, and cytokines, and t-SNE plots displaying expression of selected genes (H2AFX, XPC, XPA, RORC, IL17A). Single-cell RNA-seq data were obtained from the Broad Institute Single Cell Portal (SCP1884) and originally published by Kong et al. (2023). WT samples are shown in yellow and XPC⁻/⁻ samples in purple. Data are representative of at least three independent experiments unless otherwise indicated. Statistical significance is indicated as follows (* p < 0.05, ** p < 0.01, *** p < 0.001).

Journal: Nature Communications

Article Title: Th17 cells require the DNA repair sensor xeroderma pigmentosum complementation Group C to control oxidative DNA damage in a murine model

doi: 10.1038/s41467-026-69914-y

Figure Lengend Snippet: a Body weight change, expressed as percentage of initial weight, in Rag1⁻/⁻ mice receiving CD4⁺CD45RB^high T cells from WT or XPC⁻/⁻ donors, monitored weekly for 4 weeks after transfer ( n = 5 per group). Data are presented as mean ± SEM and analyzed using a two-sided two-way ANOVA with repeated measures followed by Tukey’s multiple-comparisons post hoc test. b Colon length measured at the experimental endpoint in Rag1⁻/⁻ mice receiving WT or XPC⁻/⁻ CD4⁺ T cells ( n = 5 per group). Data are shown as mean ± SEM and analyzed using a two-sided unpaired Student’s t -test. c – f Representative colonoscopy images, hematoxylin and eosin–stained histological sections, and quantification of endoscopy and histology scores in Rag1⁻/⁻ mice receiving WT or XPC⁻/⁻ CD4⁺ T cells ( n = 5 per group). Quantitative data are shown as individual data points with mean ± SEM and analyzed using two-sided unpaired Student’s t -tests with exact P values indicated. g – h Flow cytometry contour plots showing IFN-γ, IL-17A, and FoxP3 expression in CD4⁺ T cells isolated from mesenteric lymph nodes (mLNs) and large-intestine lamina propria (LI-LP) of Rag1⁻/⁻ mice receiving WT or XPC⁻/⁻ CD4⁺ T cells. i – j Quantification of CD4⁺CD45⁺ T cell subsets (IL-17A⁺, IFN-γ⁺, and FoxP3⁺) from mLNs and LI-LP ( n = 5 per group). Data are presented as mean ± SEM and analyzed using two-sided unpaired Student’s t-tests with exact P values indicated. k – m t-SNE analysis of immune cell populations from colonic tissue of Crohn’s disease patients, heatmap showing scaled expression of DNA repair genes, transcription factors, and cytokines, and t-SNE plots displaying expression of selected genes (H2AFX, XPC, XPA, RORC, IL17A). Single-cell RNA-seq data were obtained from the Broad Institute Single Cell Portal (SCP1884) and originally published by Kong et al. (2023). WT samples are shown in yellow and XPC⁻/⁻ samples in purple. Data are representative of at least three independent experiments unless otherwise indicated. Statistical significance is indicated as follows (* p < 0.05, ** p < 0.01, *** p < 0.001).

Article Snippet: Single-cell RNA-seq data were obtained from the Broad Institute Single Cell Portal (SCP1884) and originally published by Kong et al. (2023).

Techniques: Staining, Flow Cytometry, Expressing, Isolation, Single Cell, RNA Sequencing