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rabbit anti sv40 t antigen  (MedChemExpress)


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    Structured Review

    MedChemExpress rabbit anti sv40 t antigen
    Rabbit Anti Sv40 T Antigen, supplied by MedChemExpress, used in various techniques. Bioz Stars score: 94/100, based on 15 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/rabbit anti sv40 t antigen/product/MedChemExpress
    Average 94 stars, based on 15 article reviews
    rabbit anti sv40 t antigen - by Bioz Stars, 2026-05
    94/100 stars

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    Intercellular communication networks between melanoma cells and T cells. (A, B) Number (A) and strength (B) of interactions among annotated tumor and T cell types. (C) Scatter plots illustrating the incoming and outgoing interaction strengths of the indicated cell types. (D) Heatmaps displaying representative outgoing (left) and incoming (right) signaling patterns among 14 cell types. (E) Hierarchical plot showing the inferred intracellular communication network of SPP1 signaling between annotated tumor and T cell types. (F) Violin plots comparing SPP1 expression level among five melanoma subtypes; ∗∗∗∗P < 0.0001. (G) Bar plot showing the major ligand-receptor pairs involved in SPP1 signaling. (H) Representative immunofluorescence images showing <t>SPP1-CD44</t> ligand-receptor pairs in UM cohort (n = 7). HMB45 (green), SPP1 (yellow), CD8 (magenta), and <t>CD44</t> (pink). Scale bar, 20 μm.
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    Intercellular communication networks between melanoma cells and T cells. (A, B) Number (A) and strength (B) of interactions among annotated tumor and T cell types. (C) Scatter plots illustrating the incoming and outgoing interaction strengths of the indicated cell types. (D) Heatmaps displaying representative outgoing (left) and incoming (right) signaling patterns among 14 cell types. (E) Hierarchical plot showing the inferred intracellular communication network of SPP1 signaling between annotated tumor and T cell types. (F) Violin plots comparing SPP1 expression level among five melanoma subtypes; ∗∗∗∗P < 0.0001. (G) Bar plot showing the major ligand-receptor pairs involved in SPP1 signaling. (H) Representative immunofluorescence images showing <t>SPP1-CD44</t> ligand-receptor pairs in UM cohort (n = 7). HMB45 (green), SPP1 (yellow), CD8 (magenta), and <t>CD44</t> (pink). Scale bar, 20 μm.
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    Intercellular communication networks between melanoma cells and T cells. (A, B) Number (A) and strength (B) of interactions among annotated tumor and T cell types. (C) Scatter plots illustrating the incoming and outgoing interaction strengths of the indicated cell types. (D) Heatmaps displaying representative outgoing (left) and incoming (right) signaling patterns among 14 cell types. (E) Hierarchical plot showing the inferred intracellular communication network of SPP1 signaling between annotated tumor and T cell types. (F) Violin plots comparing SPP1 expression level among five melanoma subtypes; ∗∗∗∗P < 0.0001. (G) Bar plot showing the major ligand-receptor pairs involved in SPP1 signaling. (H) Representative immunofluorescence images showing <t>SPP1-CD44</t> ligand-receptor pairs in UM cohort (n = 7). HMB45 (green), SPP1 (yellow), CD8 (magenta), and <t>CD44</t> (pink). Scale bar, 20 μm.
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    Intercellular communication networks between melanoma cells and T cells. (A, B) Number (A) and strength (B) of interactions among annotated tumor and T cell types. (C) Scatter plots illustrating the incoming and outgoing interaction strengths of the indicated cell types. (D) Heatmaps displaying representative outgoing (left) and incoming (right) signaling patterns among 14 cell types. (E) Hierarchical plot showing the inferred intracellular communication network of SPP1 signaling between annotated tumor and T cell types. (F) Violin plots comparing SPP1 expression level among five melanoma subtypes; ∗∗∗∗P < 0.0001. (G) Bar plot showing the major ligand-receptor pairs involved in SPP1 signaling. (H) Representative immunofluorescence images showing <t>SPP1-CD44</t> ligand-receptor pairs in UM cohort (n = 7). HMB45 (green), SPP1 (yellow), CD8 (magenta), and <t>CD44</t> (pink). Scale bar, 20 μm.
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    Image Search Results


    Synthesis process and mechanism diagram of HA/CaCO 3 @Ce6 (A) Schematic of the functional pattern of HA/CaCO 3 @Ce6. (B) Tumor microenvironment-responsive calcium-based nanoplatform enables CD44-targeted modulation, improves acidic tumor niche, and amplifies mitochondrial Ca 2+ overload-mediated ROS production to trigger immunogenic cell death, thereby potentiating SDT efficacy.

    Journal: iScience

    Article Title: pH-responsive CaCO 3 nanoplatform amplifies SDT via calcium overload-ROS loop for deep tumor therapy

    doi: 10.1016/j.isci.2026.115082

    Figure Lengend Snippet: Synthesis process and mechanism diagram of HA/CaCO 3 @Ce6 (A) Schematic of the functional pattern of HA/CaCO 3 @Ce6. (B) Tumor microenvironment-responsive calcium-based nanoplatform enables CD44-targeted modulation, improves acidic tumor niche, and amplifies mitochondrial Ca 2+ overload-mediated ROS production to trigger immunogenic cell death, thereby potentiating SDT efficacy.

    Article Snippet: Anti-Mouse CD44 Rabbit Recombinant Antibody , Sanying Biotechnology , Cat No. 15675-1-AP; RRID: AB_2076198.

    Techniques: Functional Assay

    In vitro HA-mediated targeting performance and the antitumor effects of HA/CaCO 3 @Ce6 (A) Flow cytometry analysis of CD44 receptor expression on the membrane surface of the different liver cancer cells. (B) Quantitative analysis of CD44 receptor expression on the membrane surface of the different liver cancer cells. Data are expressed as the mean ± SD ( n = 3), ∗∗∗p < 0.001 by Student’s t test. (C) CLSM images of Hepa1-6 cells stained with Fluo-4 after incubations with PBS, CaCO 3 , CaCO 3 @Ce6, and HA/CaCO 3 @Ce6 for 6 h. Scale bars, 100 μm. (D) Quantitative analysis of fluorescence intensity of Hepa1-6 cells stained with Fluo-4 after incubations with PBS, CaCO 3 , CaCO 3 @Ce6, and HA/CaCO 3 @Ce6 (G1–G4) for 6 h, respectively. Data are expressed as the mean ± SD ( n = 3). ∗∗∗p < 0.001 by Student’s t test. (E) Cell viability of Hepa1-6 cells treated with PBS, CaCO 3 , CaCO 3 @Ce6, and HA/CaCO 3 @Ce6 with different concentrations for 24 h. Data are expressed as the mean ± SD ( n = 3). ∗∗∗p < 0.001 by Student’s t test. (F) Cell viability of Hepa1-6 cells incubated with PBS, CaCO 3 , CaCO 3 @Ce6, and HA/CaCO 3 @Ce6 for 6 h and irradiated with different US intensity for 3 min. Data are expressed as the mean ± SD ( n = 3), ∗∗∗p < 0.001 by Student’s t test. (G) FCM patterns of apoptotic cells in Hepa1-6 cells with different treatments. (H) Quantitative analysis of apoptotic cells in Hepa1-6 cells with different treatments. G1–G6 represent PBS, CaCO 3 , CaCO 3 @Ce6, CaCO 3 @Ce6 + US, HA/CaCO 3 @Ce6 + US, and Ce6 + US, respectively. Data are expressed as the mean ± SD ( n = 3), ∗∗p ˂ 0.05; ∗∗∗p < 0.001 by Student’s t test. CLSM, confocal laser scanning microscopy; US, ultrasound.

    Journal: iScience

    Article Title: pH-responsive CaCO 3 nanoplatform amplifies SDT via calcium overload-ROS loop for deep tumor therapy

    doi: 10.1016/j.isci.2026.115082

    Figure Lengend Snippet: In vitro HA-mediated targeting performance and the antitumor effects of HA/CaCO 3 @Ce6 (A) Flow cytometry analysis of CD44 receptor expression on the membrane surface of the different liver cancer cells. (B) Quantitative analysis of CD44 receptor expression on the membrane surface of the different liver cancer cells. Data are expressed as the mean ± SD ( n = 3), ∗∗∗p < 0.001 by Student’s t test. (C) CLSM images of Hepa1-6 cells stained with Fluo-4 after incubations with PBS, CaCO 3 , CaCO 3 @Ce6, and HA/CaCO 3 @Ce6 for 6 h. Scale bars, 100 μm. (D) Quantitative analysis of fluorescence intensity of Hepa1-6 cells stained with Fluo-4 after incubations with PBS, CaCO 3 , CaCO 3 @Ce6, and HA/CaCO 3 @Ce6 (G1–G4) for 6 h, respectively. Data are expressed as the mean ± SD ( n = 3). ∗∗∗p < 0.001 by Student’s t test. (E) Cell viability of Hepa1-6 cells treated with PBS, CaCO 3 , CaCO 3 @Ce6, and HA/CaCO 3 @Ce6 with different concentrations for 24 h. Data are expressed as the mean ± SD ( n = 3). ∗∗∗p < 0.001 by Student’s t test. (F) Cell viability of Hepa1-6 cells incubated with PBS, CaCO 3 , CaCO 3 @Ce6, and HA/CaCO 3 @Ce6 for 6 h and irradiated with different US intensity for 3 min. Data are expressed as the mean ± SD ( n = 3), ∗∗∗p < 0.001 by Student’s t test. (G) FCM patterns of apoptotic cells in Hepa1-6 cells with different treatments. (H) Quantitative analysis of apoptotic cells in Hepa1-6 cells with different treatments. G1–G6 represent PBS, CaCO 3 , CaCO 3 @Ce6, CaCO 3 @Ce6 + US, HA/CaCO 3 @Ce6 + US, and Ce6 + US, respectively. Data are expressed as the mean ± SD ( n = 3), ∗∗p ˂ 0.05; ∗∗∗p < 0.001 by Student’s t test. CLSM, confocal laser scanning microscopy; US, ultrasound.

    Article Snippet: Anti-Mouse CD44 Rabbit Recombinant Antibody , Sanying Biotechnology , Cat No. 15675-1-AP; RRID: AB_2076198.

    Techniques: In Vitro, Flow Cytometry, Expressing, Membrane, Staining, Fluorescence, Incubation, Irradiation, Confocal Laser Scanning Microscopy

    Intercellular communication networks between melanoma cells and T cells. (A, B) Number (A) and strength (B) of interactions among annotated tumor and T cell types. (C) Scatter plots illustrating the incoming and outgoing interaction strengths of the indicated cell types. (D) Heatmaps displaying representative outgoing (left) and incoming (right) signaling patterns among 14 cell types. (E) Hierarchical plot showing the inferred intracellular communication network of SPP1 signaling between annotated tumor and T cell types. (F) Violin plots comparing SPP1 expression level among five melanoma subtypes; ∗∗∗∗P < 0.0001. (G) Bar plot showing the major ligand-receptor pairs involved in SPP1 signaling. (H) Representative immunofluorescence images showing SPP1-CD44 ligand-receptor pairs in UM cohort (n = 7). HMB45 (green), SPP1 (yellow), CD8 (magenta), and CD44 (pink). Scale bar, 20 μm.

    Journal: Redox Biology

    Article Title: Tumor-intrinsic redox programming drives an SPP1-CD44 axis of immune suppression in uveal melanoma

    doi: 10.1016/j.redox.2026.104011

    Figure Lengend Snippet: Intercellular communication networks between melanoma cells and T cells. (A, B) Number (A) and strength (B) of interactions among annotated tumor and T cell types. (C) Scatter plots illustrating the incoming and outgoing interaction strengths of the indicated cell types. (D) Heatmaps displaying representative outgoing (left) and incoming (right) signaling patterns among 14 cell types. (E) Hierarchical plot showing the inferred intracellular communication network of SPP1 signaling between annotated tumor and T cell types. (F) Violin plots comparing SPP1 expression level among five melanoma subtypes; ∗∗∗∗P < 0.0001. (G) Bar plot showing the major ligand-receptor pairs involved in SPP1 signaling. (H) Representative immunofluorescence images showing SPP1-CD44 ligand-receptor pairs in UM cohort (n = 7). HMB45 (green), SPP1 (yellow), CD8 (magenta), and CD44 (pink). Scale bar, 20 μm.

    Article Snippet: After blocked with 3 % BSA, the 4 μm serial sections were incubated with primary antibody at 4 °C overnight: SPP1 (Proteintech, 22952-1-AP), HMB45 (Abcam, ab787), CD8 (CST, 98941), and CD44 (CST, 37259).

    Techniques: Expressing, Immunofluorescence

    Redox-dependent SPP1 secretion drives immune suppression (A) ELISA measurement of SPP1 levels in conditioned medium from indicated UM cell lines. ∗P < 0.05, ∗∗∗∗P < 0.0001. (B) Immunoblot validation of SPP1 overexpression in UM cells. (C) ELISA analysis of secreted SPP1 following SPP1 overexpression. ∗∗∗∗P < 0.0001. (D) CCK-8 assay measuring proliferation of UM cells upon SPP1 overexpression. (E) Colony formation (top) and trans well assays (bottom) evaluating the clonogenic growth and invasive potential of UM cells upon SPP1 overexpression. (F) Schematic overview of the UM-CD8 + T cell coculture system. (G) Flow cytometry analysis of Ki-67 and IFN-γ expression levels in CD8 + T cells under different coculture conditions. ∗P < 0.05, ∗∗P < 0.01. (H) Proposed model of the SPP1-CD44 signaling axis in UM progression. (I) CCK-8 assay showing inhibitory effects of Mito-LND on MP46 cell viability. ∗∗P < 0.01. (J) OCR analysis assessing mitochondrial respiration in MP46 cells following Mito-LND treatment. ∗∗∗P < 0.001, ∗∗∗∗P < 0.0001. (K) ROS levels in UM cells after Mito-LND treatment. Scale bar, 200 μm. ∗P < 0.05. (L) Immunoblot analysis of SPP1 expression under oxidative stress induced by Tert -Butyl hydroperoxide solution (TBHP) or Mito-LND. (M) ELISA quantification of secreted SPP1 levels after Mito-LND treatment. ∗∗P < 0.01. (N) Immunoblot analysis of ER stress markers CHOP in UM cells treated with Mito-LND.

    Journal: Redox Biology

    Article Title: Tumor-intrinsic redox programming drives an SPP1-CD44 axis of immune suppression in uveal melanoma

    doi: 10.1016/j.redox.2026.104011

    Figure Lengend Snippet: Redox-dependent SPP1 secretion drives immune suppression (A) ELISA measurement of SPP1 levels in conditioned medium from indicated UM cell lines. ∗P < 0.05, ∗∗∗∗P < 0.0001. (B) Immunoblot validation of SPP1 overexpression in UM cells. (C) ELISA analysis of secreted SPP1 following SPP1 overexpression. ∗∗∗∗P < 0.0001. (D) CCK-8 assay measuring proliferation of UM cells upon SPP1 overexpression. (E) Colony formation (top) and trans well assays (bottom) evaluating the clonogenic growth and invasive potential of UM cells upon SPP1 overexpression. (F) Schematic overview of the UM-CD8 + T cell coculture system. (G) Flow cytometry analysis of Ki-67 and IFN-γ expression levels in CD8 + T cells under different coculture conditions. ∗P < 0.05, ∗∗P < 0.01. (H) Proposed model of the SPP1-CD44 signaling axis in UM progression. (I) CCK-8 assay showing inhibitory effects of Mito-LND on MP46 cell viability. ∗∗P < 0.01. (J) OCR analysis assessing mitochondrial respiration in MP46 cells following Mito-LND treatment. ∗∗∗P < 0.001, ∗∗∗∗P < 0.0001. (K) ROS levels in UM cells after Mito-LND treatment. Scale bar, 200 μm. ∗P < 0.05. (L) Immunoblot analysis of SPP1 expression under oxidative stress induced by Tert -Butyl hydroperoxide solution (TBHP) or Mito-LND. (M) ELISA quantification of secreted SPP1 levels after Mito-LND treatment. ∗∗P < 0.01. (N) Immunoblot analysis of ER stress markers CHOP in UM cells treated with Mito-LND.

    Article Snippet: After blocked with 3 % BSA, the 4 μm serial sections were incubated with primary antibody at 4 °C overnight: SPP1 (Proteintech, 22952-1-AP), HMB45 (Abcam, ab787), CD8 (CST, 98941), and CD44 (CST, 37259).

    Techniques: Enzyme-linked Immunosorbent Assay, Western Blot, Biomarker Discovery, Over Expression, CCK-8 Assay, Flow Cytometry, Expressing