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Image Search Results
Journal: Cell reports
Article Title: Unraveling the phenotypic states of human innate-like T cells: Comparative insights with conventional T cells and mouse models
doi: 10.1016/j.celrep.2024.114705
Figure Lengend Snippet: (A) Heatmap showing MetaNeighbor’s AUROC scores between thymocytes split by donor, lineage, and non-effector (c0–11) versus effector (c12–17) clusters. Barplots indicate thymocyte proportions per lineage. (B) Pseudo-bulk differential expression analysis between CD4 + /iNKT and CD8 + /MAIT thymocytes in naive clusters (3, 9, 10, 11). As a negative control, the only three genes that were differentially expressed between CD4 + /MAIT and CD8 + /iNKT thymocytes are displayed in the center of the heatmap. (C) Pseudo-bulk differential expression analysis between CD4 + /CD8 + and iNKT/MAIT thymocytes in naive clusters (3, 9, 10, 11). For both (B) and (C), heatmap displays the expression level of genes (represented with color scale as a Z score of the average normalized expression) that are significantly differentially expressed ( p adj < 0.01). (D) Clustering of hashtag-separated thymic iNKT cells (top), MAIT cells (middle), and γδ T cells (bottom). Right panel shows the score of type I and type III effector gene signature for the corresponding thymic lineage. (E) Kernel density estimates of the normalized expression level of genes of interest. The expression level distribution varies between genes and lineage. The range of kernel density estimate values also varies between each panel (from 0 to 0.04 for the smallest range and 0 to 0.4 for the largest range). A unique color scale was represented to indicate the direction of the values.
Article Snippet:
Techniques: Quantitative Proteomics, Negative Control, Expressing
Journal: Cell reports
Article Title: Unraveling the phenotypic states of human innate-like T cells: Comparative insights with conventional T cells and mouse models
doi: 10.1016/j.celrep.2024.114705
Figure Lengend Snippet: (A–C) (A) Clustering of hashtag-separated blood iNKT, MAIT, γδ T, CD4, and CD8 T cells, (B) the respective proportion of cells per cluster and donor, and (C) the effector GEP signature scores (as in ) per cell type and cluster. (D) Top GEP usage for each cell type, based on cNMF-derived usage matrix. (E) Pseudo-bulk, pairwise differential gene expression between cell types. (F) Cell-type-specific genes among T inn cells using GEP5. For both (E) and (F), heatmaps depict the expression level of genes (represented with color scale as a Z score of the average normalized expression) that are significantly differentially expressed ( p adj < 0.01). n = 4, 4, 9, 4, and 9 for iNKT, MAIT, γδ, CD4, and CD8 cells, respectively.
Article Snippet:
Techniques: Derivative Assay, Gene Expression, Expressing
Journal: Cell reports
Article Title: Unraveling the phenotypic states of human innate-like T cells: Comparative insights with conventional T cells and mouse models
doi: 10.1016/j.celrep.2024.114705
Figure Lengend Snippet:
Article Snippet:
Techniques: Purification, Plasmid Preparation, Blocking Assay, Multiplexing, Recombinant, Antibody Labeling, Staining, Amplification, Software, Flow Cytometry
Journal: Cell reports
Article Title: Unraveling the phenotypic states of human innate-like T cells: Comparative insights with conventional T cells and mouse models
doi: 10.1016/j.celrep.2024.114705
Figure Lengend Snippet: (A) Heatmap showing MetaNeighbor’s AUROC scores between thymocytes split by donor, lineage, and non-effector (c0–11) versus effector (c12–17) clusters. Barplots indicate thymocyte proportions per lineage. (B) Pseudo-bulk differential expression analysis between CD4 + /iNKT and CD8 + /MAIT thymocytes in naive clusters (3, 9, 10, 11). As a negative control, the only three genes that were differentially expressed between CD4 + /MAIT and CD8 + /iNKT thymocytes are displayed in the center of the heatmap. (C) Pseudo-bulk differential expression analysis between CD4 + /CD8 + and iNKT/MAIT thymocytes in naive clusters (3, 9, 10, 11). For both (B) and (C), heatmap displays the expression level of genes (represented with color scale as a Z score of the average normalized expression) that are significantly differentially expressed ( p adj < 0.01). (D) Clustering of hashtag-separated thymic iNKT cells (top), MAIT cells (middle), and γδ T cells (bottom). Right panel shows the score of type I and type III effector gene signature for the corresponding thymic lineage. (E) Kernel density estimates of the normalized expression level of genes of interest. The expression level distribution varies between genes and lineage. The range of kernel density estimate values also varies between each panel (from 0 to 0.04 for the smallest range and 0 to 0.4 for the largest range). A unique color scale was represented to indicate the direction of the values.
Article Snippet:
Techniques: Quantitative Proteomics, Negative Control, Expressing
Journal: Cell reports
Article Title: Unraveling the phenotypic states of human innate-like T cells: Comparative insights with conventional T cells and mouse models
doi: 10.1016/j.celrep.2024.114705
Figure Lengend Snippet: (A–C) (A) Clustering of hashtag-separated blood iNKT, MAIT, γδ T, CD4, and CD8 T cells, (B) the respective proportion of cells per cluster and donor, and (C) the effector GEP signature scores (as in ) per cell type and cluster. (D) Top GEP usage for each cell type, based on cNMF-derived usage matrix. (E) Pseudo-bulk, pairwise differential gene expression between cell types. (F) Cell-type-specific genes among T inn cells using GEP5. For both (E) and (F), heatmaps depict the expression level of genes (represented with color scale as a Z score of the average normalized expression) that are significantly differentially expressed ( p adj < 0.01). n = 4, 4, 9, 4, and 9 for iNKT, MAIT, γδ, CD4, and CD8 cells, respectively.
Article Snippet:
Techniques: Derivative Assay, Gene Expression, Expressing
Journal: Cell reports
Article Title: Unraveling the phenotypic states of human innate-like T cells: Comparative insights with conventional T cells and mouse models
doi: 10.1016/j.celrep.2024.114705
Figure Lengend Snippet:
Article Snippet:
Techniques: Purification, Plasmid Preparation, Blocking Assay, Multiplexing, Recombinant, Antibody Labeling, Staining, Amplification, Software, Flow Cytometry