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Host responses to mouse subcutaneous implantation of Cu-PIAS. ( A ) Representative hematoxylin and eosin staining of the implant site after 7, 14, and 21 days. 25-Cu-PIAS mesh is roughly centered in each image and runs horizontally. Mesh material stains homogenously red and is indicated by arrows in the leftmost image of each timepoint. ( B ) Area of 25-Cu-PIAS mesh at each timepoint. Reduction over time indicates degradation of material. ( C ) Blood vessel density around and within the implant sites (CD31 immunohistochemistry) at each timepoint. ( D ) Total macrophage density around and within the implant sites <t>(F4/80</t> immunohistochemistry) at each timepoint. ( E ) M2 macrophage density around and within the implant sites (CD163 immunohistochemistry) at each timepoint. ( F ) Ratio of macrophages expressing a M2 phenotype at each timepoint. ( G ) Collagen thickness above the implant site of scarring mouse model (CXCR3 −/− ), comparing responses to 15-Cu-PIAS and fibrin gel after 3 and 6 months. Statistics: ∗, ∗∗, ∗∗∗, and ∗∗∗∗ indicate p ≤ 0.05, 0.01, 0.001, and 0.0001, respectively.
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Host responses to mouse subcutaneous implantation of Cu-PIAS. ( A ) Representative hematoxylin and eosin staining of the implant site after 7, 14, and 21 days. 25-Cu-PIAS mesh is roughly centered in each image and runs horizontally. Mesh material stains homogenously red and is indicated by arrows in the leftmost image of each timepoint. ( B ) Area of 25-Cu-PIAS mesh at each timepoint. Reduction over time indicates degradation of material. ( C ) Blood vessel density around and within the implant sites (CD31 immunohistochemistry) at each timepoint. ( D ) Total macrophage density around and within the implant sites <t>(F4/80</t> immunohistochemistry) at each timepoint. ( E ) M2 macrophage density around and within the implant sites (CD163 immunohistochemistry) at each timepoint. ( F ) Ratio of macrophages expressing a M2 phenotype at each timepoint. ( G ) Collagen thickness above the implant site of scarring mouse model (CXCR3 −/− ), comparing responses to 15-Cu-PIAS and fibrin gel after 3 and 6 months. Statistics: ∗, ∗∗, ∗∗∗, and ∗∗∗∗ indicate p ≤ 0.05, 0.01, 0.001, and 0.0001, respectively.
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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 <t>of</t> <t>F4/80</t> 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.
Fitc Anti Mouse F4 80, supplied by Elabscience Biotechnology, used in various techniques. Bioz Stars score: 95/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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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 <t>of</t> <t>F4/80</t> 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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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 <t>of</t> <t>F4/80</t> 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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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 <t>of</t> <t>F4/80</t> 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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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 <t>of</t> <t>F4/80</t> 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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Image Search Results


Host responses to mouse subcutaneous implantation of Cu-PIAS. ( A ) Representative hematoxylin and eosin staining of the implant site after 7, 14, and 21 days. 25-Cu-PIAS mesh is roughly centered in each image and runs horizontally. Mesh material stains homogenously red and is indicated by arrows in the leftmost image of each timepoint. ( B ) Area of 25-Cu-PIAS mesh at each timepoint. Reduction over time indicates degradation of material. ( C ) Blood vessel density around and within the implant sites (CD31 immunohistochemistry) at each timepoint. ( D ) Total macrophage density around and within the implant sites (F4/80 immunohistochemistry) at each timepoint. ( E ) M2 macrophage density around and within the implant sites (CD163 immunohistochemistry) at each timepoint. ( F ) Ratio of macrophages expressing a M2 phenotype at each timepoint. ( G ) Collagen thickness above the implant site of scarring mouse model (CXCR3 −/− ), comparing responses to 15-Cu-PIAS and fibrin gel after 3 and 6 months. Statistics: ∗, ∗∗, ∗∗∗, and ∗∗∗∗ indicate p ≤ 0.05, 0.01, 0.001, and 0.0001, respectively.

Journal: Bioactive Materials

Article Title: A catalytically active and recyclable bioelastomer inspired by metalloenzymes

doi: 10.1016/j.bioactmat.2026.02.053

Figure Lengend Snippet: Host responses to mouse subcutaneous implantation of Cu-PIAS. ( A ) Representative hematoxylin and eosin staining of the implant site after 7, 14, and 21 days. 25-Cu-PIAS mesh is roughly centered in each image and runs horizontally. Mesh material stains homogenously red and is indicated by arrows in the leftmost image of each timepoint. ( B ) Area of 25-Cu-PIAS mesh at each timepoint. Reduction over time indicates degradation of material. ( C ) Blood vessel density around and within the implant sites (CD31 immunohistochemistry) at each timepoint. ( D ) Total macrophage density around and within the implant sites (F4/80 immunohistochemistry) at each timepoint. ( E ) M2 macrophage density around and within the implant sites (CD163 immunohistochemistry) at each timepoint. ( F ) Ratio of macrophages expressing a M2 phenotype at each timepoint. ( G ) Collagen thickness above the implant site of scarring mouse model (CXCR3 −/− ), comparing responses to 15-Cu-PIAS and fibrin gel after 3 and 6 months. Statistics: ∗, ∗∗, ∗∗∗, and ∗∗∗∗ indicate p ≤ 0.05, 0.01, 0.001, and 0.0001, respectively.

Article Snippet: F4/80 antibody was purchased from Cell Signaling Technology (Danvers MA, Cat #: 70076).

Techniques: Staining, Immunohistochemistry, Expressing

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