cd31  (Bioss)

Journal: Aging Cell

Article Title: uPAR ‐Targeting T Cell Engager Exerts Senolytic Effects in Mice and Non‐Human Primates With Serum Aminotransferase Activity as a Safety Monitor

doi: 10.1111/acel.70742

Figure Lengend Snippet: mGFD‐CD3 induces hepatotoxicity by targeting hepatic endothelial cells in mice. (A) H&E analysis performed at 24 h post‐injection of BiTE in the liver tissues of naturally aged mice. Scale bar, 30 μm (original) and 15 μm (magnified). (B) Immunofluorescence analysis was conducted on liver, lung, and kidney samples from naturally aged mice collected 24 h post‐BiTE injection ( n = 6 view field per each treatment group). Scale bar, 30 μm. (C) Immunofluorescence analysis of liver samples of naturally aged mice taken 4 h post‐injection of BiTE to examine the colocalization of BiTE, CD31, and uPAR. Scale bar, 30 μm (original) and 15 μm (magnified). (D) Immunofluorescence analysis to examine the colocalization of CD31 and uPAR in the liver tissues of wild type mice (WT) and uPAR knockout mice; ( n = 3 mice per treatment group). Scale bar, 30 μm. (E) Levels of AST and ALT in serum samples from mice before and after BiTE injection were determined with a Biochemical Analyzer; ( n = 3 mice per treatment group). Data is presented as mean ± SD and analyzed by unpaired two‐tailed Student's t ‐test with Welch's correction. *** p ≤ 0.001.

Article Snippet: All primary antibodies used in this work were commercially available: uPAR (Proteintech, 10286‐1‐AP, 1:200), CD31 (Proteintech, 28083‐1‐AP, 1:400), F4/80 (CST, 70076S, 1:200), and Fc (Invitrogen, A18818, 1:200).

Techniques: Analysis, Injection, Immunofluorescence, Knock-Out, Blood/Plasma/Serum Samples, Two Tailed Test

Journal: Bioactive Materials

Article Title: LRP-1/CD44-targeted regorafenib nano-delivery system leveraging anti-angiogenesis and synergistic cytotoxicity against peritoneal metastasis of colorectal cancer

doi: 10.1016/j.bioactmat.2025.12.015

Figure Lengend Snippet: Analysis of tumor microenvironment and systemic safety evaluation. (A) Representative immunofluorescence staining of tumor tissues from different treatment groups, showing CD31 + blood vessels (red), CD206 + M2 macrophages (green), and DAPI (blue) for nuclei. Scale bar = 100 μm. (B) Representative H&E-stained histological sections of major organs (heart, liver, spleen, lungs, and kidneys). Scale bar = 200 μm. (C) Quantitative analysis of microvessel density (MVD) based on CD31-positive areas. (D) Quantitative analysis of CD206-positive areas. (E) Statistical summary of the percentage of F4/80 + CD86 + cells within CD45 + cells in tumor tissues, as determined by flow cytometry. (F) Quantitative analysis of the HIF-1α-positive area percentage in tumor tissues from different groups. REG@LF means REG@LFHA NPs, REG@LFHA means REG@LFHA NPs. All statistical data are represented as mean ± SD (n = 3; ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001).

Article Snippet: Rabbit anti-mouse CD31 polyclonal antibody and rabbit anti-mouse CD206 polyclonal antibody were acquired from Servicebio (Wuhan, China).

Techniques: Immunofluorescence, Staining, Flow Cytometry

Journal: iScience

Article Title: Insufficient erythrocyte-derived S1P: A pathogenic driver and diagnostic biolipid for tumor progression

doi: 10.1016/j.isci.2026.115216

Figure Lengend Snippet: Enhanced tumor growth, immunosuppression, and inhibited angiogenesis in the eSphk1 −/− tumor-bearing mouse model of HNSCC (A) Schematic representation of the experimental strategy used for the mEER tumor-bearing mouse model. (Created with BioRender.com ). (B) Tumor growth profiles of eSphk1 −/− and control mice in the mEER tumor model. ( N = 6 per group, data are presented as mean ± SD. ∗∗ p < 0.01). (C) Representative images of tumors collected from mEER tumor-bearing mice in each group. (D) Tumor weights in mEER tumor-bearing mice of each group. ( N = 6 per group, data are presented as mean ± SD. ∗∗ p < 0.01). (E) RBC SPHK1 activity in different groups at the end of the experiment. ( N = 6 per group, data are presented as mean ± SD. ∗∗ p < 0.01). (F) P50 expression levels in different groups at the end of the experiment. ( N = 6 per group, data are presented as mean ± SD. ∗ p < 0.05). (G) Blood cell counts (RBC, hemoglobin (Hb), WBC and platelets (PLTs)) in different groups at the end of the experiment. Data are presented as mean ± SD ( N = 5 per group, data are presented as mean ± SD). (H) Flow cytometric analysis shows the percentage of immune cells in the tumor tissue of eSphk1 −/− and control mice at the experimental endpoint. ( N = 4:5, data are presented as mean ± SD. ∗ p < 0.05). (I) Representative fluorescent images of immunostaining for CD31, indicating tumor angiogenesis in tumor tissue of eSphk1 −/− and control group mice under mEER tumor-bearing conditions. Green fluorescence indicates CD31 expression on tumor vasculature. ( N = 3 per group, data are presented as mean ± SD. ∗ p < 0.05). (J) The tumor-bearing model in eSphk1 −/− demonstrates that erythrocyte Sphk1 deficiency promotes tumor progression via mechanisms including immune suppression and reduced angiogenesis. (Statistical analysis: Unpaired two-tailed Student’s t test was used for comparisons in panels D–I).

Article Snippet: To assess microvessel density, tumor sections were stained with an anti-CD31 antibody (Proteintech, 28083-1-AP).

Techniques: Control, Activity Assay, Expressing, Immunostaining, Fluorescence, Two Tailed Test

Journal: iScience

Article Title: Insufficient erythrocyte-derived S1P: A pathogenic driver and diagnostic biolipid for tumor progression

doi: 10.1016/j.isci.2026.115216

Figure Lengend Snippet: Mouse breast cancer model validation shows that changes in erythrocyte S1P affect tumor angiogenesis and promote immune suppression, collectively driving tumor progression (A) Schematic representation of the strategy used to establish the orthotopic breast cancer (Py8119) model in mice. (Created with BioRender.com ). (B) Growth profiles of Py8119 tumors in eSphk1 −/− and control mice. ( N = 6 per group, data are presented as mean ± SD. ∗∗∗∗ p < 0.0001). (C) Representative images of tumors collected from Py8119 tumor-bearing mice in each group. ( N = 5 per group). (D) Tumor weights of Py8119 tumor-bearing mice in each group. ( N = 5 per group, data are presented as mean ± SD. ∗∗ p < 0.01). (E) Erythrocyte Sphk1 activities in different experimental groups at the conclusion of the study. ( N = 5 per group, data are presented as mean ± SD. ∗∗ p < 0.01). (F) Flow cytometric analysis shows the percentage of immune cells in tumor tissues of eSphk1 −/− and control mice at the experimental endpoints. ( N = 4 per group, data are presented as mean ± SD. ∗ p < 0.05). (G) Fluorescent immunostaining images of tumor tissue, stained with anti-CD31 to detect tumor angiogenesis. Green fluorescence indicates CD31 expression on tumor vasculature. ( N = 3 per group, data are presented as mean ± SD. ∗∗ p < 0.01).

Article Snippet: To assess microvessel density, tumor sections were stained with an anti-CD31 antibody (Proteintech, 28083-1-AP).

Techniques: Biomarker Discovery, Control, Immunostaining, Staining, Fluorescence, Expressing