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Effect of SL disA therapy on T cells and macrophage from tumor samples (A, B) Flow Cytometry analysis of <t>CD3</t> and CD8 surface markers(A) and CD3 + CD8 + cells statistical graph (B). (C, D) Flow cytometry analysis of CD3 and CD4 surface markers (C) and CD3 + CD4 + cells statistical graph (D). (E, F) Flow cytometry analysis of F4/80 and CD86 surface markers (E) and F4/80 + CD86 + cells statistical graph (F). Data are expressed as mean ± SEM, n = 3. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001, one-way ANOVA with Tukey’s multiple comparisons tests.
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PHD-MS analyzes tumor microenvironment morphology (A) Expert annotated tumors from immunofluorescent image, with <t>anti-CD3</t> intensity in pink and DAPI intensity in green. IDC is outlined in yellow, carcinoma in situ is outlined in blue, benign hyperplasia is outlined in red, and unclassified tumor is in green. (B) Prominent multiscale domains identified by PHD-MS, selected from the most persistent domains. Regions are numbered to correspond with the labels in (A). (C) PHD-MS heterogeneity map highlights highly heterogeneous regions. The heterogeneity score approximates the number of persistent domains that contain each spot. (D) Mean normalized immune expression from a set of immune genes (PTPRC, CD4, CD8A, CD14, CD68, and IGHG3). (E) Normalized expression of key oncogenes APOE, PGK1, and MALAT1 in the lower IDC. From DGE analysis, APOE is overexpressed in region 7 relative to 8 and 9, PGK1 is overexpressed in 8, and MALAT1 is overexpressed in 9.
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cd3 antibody  (NSJ Bioreagents)
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PHD-MS analyzes tumor microenvironment morphology (A) Expert annotated tumors from immunofluorescent image, with <t>anti-CD3</t> intensity in pink and DAPI intensity in green. IDC is outlined in yellow, carcinoma in situ is outlined in blue, benign hyperplasia is outlined in red, and unclassified tumor is in green. (B) Prominent multiscale domains identified by PHD-MS, selected from the most persistent domains. Regions are numbered to correspond with the labels in (A). (C) PHD-MS heterogeneity map highlights highly heterogeneous regions. The heterogeneity score approximates the number of persistent domains that contain each spot. (D) Mean normalized immune expression from a set of immune genes (PTPRC, CD4, CD8A, CD14, CD68, and IGHG3). (E) Normalized expression of key oncogenes APOE, PGK1, and MALAT1 in the lower IDC. From DGE analysis, APOE is overexpressed in region 7 relative to 8 and 9, PGK1 is overexpressed in 8, and MALAT1 is overexpressed in 9.
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Image Search Results


Effect of SL disA therapy on T cells and macrophage from tumor samples (A, B) Flow Cytometry analysis of CD3 and CD8 surface markers(A) and CD3 + CD8 + cells statistical graph (B). (C, D) Flow cytometry analysis of CD3 and CD4 surface markers (C) and CD3 + CD4 + cells statistical graph (D). (E, F) Flow cytometry analysis of F4/80 and CD86 surface markers (E) and F4/80 + CD86 + cells statistical graph (F). Data are expressed as mean ± SEM, n = 3. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001, one-way ANOVA with Tukey’s multiple comparisons tests.

Journal: Molecular Therapy Oncology

Article Title: Engineered Salmonella -mediated c-di-AMP delivery activates STING to remodel the tumor microenvironment

doi: 10.1016/j.omton.2026.201185

Figure Lengend Snippet: Effect of SL disA therapy on T cells and macrophage from tumor samples (A, B) Flow Cytometry analysis of CD3 and CD8 surface markers(A) and CD3 + CD8 + cells statistical graph (B). (C, D) Flow cytometry analysis of CD3 and CD4 surface markers (C) and CD3 + CD4 + cells statistical graph (D). (E, F) Flow cytometry analysis of F4/80 and CD86 surface markers (E) and F4/80 + CD86 + cells statistical graph (F). Data are expressed as mean ± SEM, n = 3. ∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001, one-way ANOVA with Tukey’s multiple comparisons tests.

Article Snippet: The following antibodies were used: FITC anti-mouse F4/80 (clone CI: A3-1), APC anti-mouse CD86 (clone GL-1), FITC anti-mouse CD3 (clone 17A2), APC anti-mouse CD4 (clone GK1.5), and APC anti-mouse CD8 (clone YTS-169), all purchased from Elabscience Biotechnology Co., Ltd.

Techniques: Flow Cytometry

PHD-MS analyzes tumor microenvironment morphology (A) Expert annotated tumors from immunofluorescent image, with anti-CD3 intensity in pink and DAPI intensity in green. IDC is outlined in yellow, carcinoma in situ is outlined in blue, benign hyperplasia is outlined in red, and unclassified tumor is in green. (B) Prominent multiscale domains identified by PHD-MS, selected from the most persistent domains. Regions are numbered to correspond with the labels in (A). (C) PHD-MS heterogeneity map highlights highly heterogeneous regions. The heterogeneity score approximates the number of persistent domains that contain each spot. (D) Mean normalized immune expression from a set of immune genes (PTPRC, CD4, CD8A, CD14, CD68, and IGHG3). (E) Normalized expression of key oncogenes APOE, PGK1, and MALAT1 in the lower IDC. From DGE analysis, APOE is overexpressed in region 7 relative to 8 and 9, PGK1 is overexpressed in 8, and MALAT1 is overexpressed in 9.

Journal: Cell Reports Methods

Article Title: Multiscale domain identification for spatial transcriptomics via persistent homology

doi: 10.1016/j.crmeth.2026.101376

Figure Lengend Snippet: PHD-MS analyzes tumor microenvironment morphology (A) Expert annotated tumors from immunofluorescent image, with anti-CD3 intensity in pink and DAPI intensity in green. IDC is outlined in yellow, carcinoma in situ is outlined in blue, benign hyperplasia is outlined in red, and unclassified tumor is in green. (B) Prominent multiscale domains identified by PHD-MS, selected from the most persistent domains. Regions are numbered to correspond with the labels in (A). (C) PHD-MS heterogeneity map highlights highly heterogeneous regions. The heterogeneity score approximates the number of persistent domains that contain each spot. (D) Mean normalized immune expression from a set of immune genes (PTPRC, CD4, CD8A, CD14, CD68, and IGHG3). (E) Normalized expression of key oncogenes APOE, PGK1, and MALAT1 in the lower IDC. From DGE analysis, APOE is overexpressed in region 7 relative to 8 and 9, PGK1 is overexpressed in 8, and MALAT1 is overexpressed in 9.

Article Snippet: Visium Invasive Ductal Carcinoma Stained With Fluorescent CD3 Antibody , Zhao et al. , https://www.10xgenomics.com/datasets/invasive-ductal-carcinoma-stained-with-fluorescent-cd-3-antibody-1-standard-1-2-0.

Techniques: In Situ, Expressing