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mouse anti human cd138  (Santa Cruz Biotechnology)


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    Structured Review

    Santa Cruz Biotechnology mouse anti human cd138
    PRELP + CAFs interact and colocalize with immune cells in the tumor microenvironment. (a) Immunofluorescence staining in four groups showed spatial colocalization of PRELP (green) with aSMA (red), CD3 (red), CD20 (red) and <t>CD138</t> (red) in metastatic liver tumors, respectively. Magnified views of the boxed regions are shown on the right. Scale bars, 200 μm. (b) Bubble plot illustrating the incoming (vertical axis) and outgoing (horizontal axis) interaction strength of each cell subtype across all signaling pathways. Dot size represents the relative abundance of each cell type. (c) Predicted ligand-receptor (L–R) interactions between PRELP + CAFs and six immune cell subtypes in the APP-CD74 axis and the collagen-CD44 axis. Rows indicate specific L-R pairs, and columns represent immune cell subtypes. Dot color denotes the communication probability. (d) Predicted ligand-receptor (L–R) interactions of GALECTIN (top) and NECTIN (bottom) signaling pathways between PRELP + CAFs and TNK cell subtypes. Dot color represents the communication probability. (e) Hierarchical plots of the SEMA7A/(ITGB1+ITGA1) signaling network inferred by CellChat. Line thickness represents interaction strength and the color of line matches the signal sending cell. In the top panel, fibroblasts act as signal receivers, while in the bottom panel, myeloid cells receive the signals. (f) Bubble plot illustrating the incoming (vertical axis) and outgoing (horizontal axis) interaction strength of fibroblast and myeloid cell subtype in SEMA4 signaling pathways. Dot size represents the relative abundance of each cell type.
    Mouse Anti Human Cd138, supplied by Santa Cruz Biotechnology, used in various techniques. Bioz Stars score: 93/100, based on 156 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/mouse+anti+human+cd138/pmc12477005-93-32-35?v=Santa+Cruz+Biotechnology
    Average 93 stars, based on 156 article reviews
    mouse anti human cd138 - by Bioz Stars, 2026-07
    93/100 stars

    Images

    1) Product Images from "Characterization of the phenotype and function of PRELP + fibroblast subtype in liver metastatic colorectal cancer"

    Article Title: Characterization of the phenotype and function of PRELP + fibroblast subtype in liver metastatic colorectal cancer

    Journal: Frontiers in Genetics

    doi: 10.3389/fgene.2025.1615259

    PRELP + CAFs interact and colocalize with immune cells in the tumor microenvironment. (a) Immunofluorescence staining in four groups showed spatial colocalization of PRELP (green) with aSMA (red), CD3 (red), CD20 (red) and CD138 (red) in metastatic liver tumors, respectively. Magnified views of the boxed regions are shown on the right. Scale bars, 200 μm. (b) Bubble plot illustrating the incoming (vertical axis) and outgoing (horizontal axis) interaction strength of each cell subtype across all signaling pathways. Dot size represents the relative abundance of each cell type. (c) Predicted ligand-receptor (L–R) interactions between PRELP + CAFs and six immune cell subtypes in the APP-CD74 axis and the collagen-CD44 axis. Rows indicate specific L-R pairs, and columns represent immune cell subtypes. Dot color denotes the communication probability. (d) Predicted ligand-receptor (L–R) interactions of GALECTIN (top) and NECTIN (bottom) signaling pathways between PRELP + CAFs and TNK cell subtypes. Dot color represents the communication probability. (e) Hierarchical plots of the SEMA7A/(ITGB1+ITGA1) signaling network inferred by CellChat. Line thickness represents interaction strength and the color of line matches the signal sending cell. In the top panel, fibroblasts act as signal receivers, while in the bottom panel, myeloid cells receive the signals. (f) Bubble plot illustrating the incoming (vertical axis) and outgoing (horizontal axis) interaction strength of fibroblast and myeloid cell subtype in SEMA4 signaling pathways. Dot size represents the relative abundance of each cell type.
    Figure Legend Snippet: PRELP + CAFs interact and colocalize with immune cells in the tumor microenvironment. (a) Immunofluorescence staining in four groups showed spatial colocalization of PRELP (green) with aSMA (red), CD3 (red), CD20 (red) and CD138 (red) in metastatic liver tumors, respectively. Magnified views of the boxed regions are shown on the right. Scale bars, 200 μm. (b) Bubble plot illustrating the incoming (vertical axis) and outgoing (horizontal axis) interaction strength of each cell subtype across all signaling pathways. Dot size represents the relative abundance of each cell type. (c) Predicted ligand-receptor (L–R) interactions between PRELP + CAFs and six immune cell subtypes in the APP-CD74 axis and the collagen-CD44 axis. Rows indicate specific L-R pairs, and columns represent immune cell subtypes. Dot color denotes the communication probability. (d) Predicted ligand-receptor (L–R) interactions of GALECTIN (top) and NECTIN (bottom) signaling pathways between PRELP + CAFs and TNK cell subtypes. Dot color represents the communication probability. (e) Hierarchical plots of the SEMA7A/(ITGB1+ITGA1) signaling network inferred by CellChat. Line thickness represents interaction strength and the color of line matches the signal sending cell. In the top panel, fibroblasts act as signal receivers, while in the bottom panel, myeloid cells receive the signals. (f) Bubble plot illustrating the incoming (vertical axis) and outgoing (horizontal axis) interaction strength of fibroblast and myeloid cell subtype in SEMA4 signaling pathways. Dot size represents the relative abundance of each cell type.

    Techniques Used: Immunofluorescence, Staining, Protein-Protein interactions



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    PRELP + CAFs interact and colocalize with immune cells in the tumor microenvironment. (a) Immunofluorescence staining in four groups showed spatial colocalization of PRELP (green) with aSMA (red), CD3 (red), CD20 (red) and <t>CD138</t> (red) in metastatic liver tumors, respectively. Magnified views of the boxed regions are shown on the right. Scale bars, 200 μm. (b) Bubble plot illustrating the incoming (vertical axis) and outgoing (horizontal axis) interaction strength of each cell subtype across all signaling pathways. Dot size represents the relative abundance of each cell type. (c) Predicted ligand-receptor (L–R) interactions between PRELP + CAFs and six immune cell subtypes in the APP-CD74 axis and the collagen-CD44 axis. Rows indicate specific L-R pairs, and columns represent immune cell subtypes. Dot color denotes the communication probability. (d) Predicted ligand-receptor (L–R) interactions of GALECTIN (top) and NECTIN (bottom) signaling pathways between PRELP + CAFs and TNK cell subtypes. Dot color represents the communication probability. (e) Hierarchical plots of the SEMA7A/(ITGB1+ITGA1) signaling network inferred by CellChat. Line thickness represents interaction strength and the color of line matches the signal sending cell. In the top panel, fibroblasts act as signal receivers, while in the bottom panel, myeloid cells receive the signals. (f) Bubble plot illustrating the incoming (vertical axis) and outgoing (horizontal axis) interaction strength of fibroblast and myeloid cell subtype in SEMA4 signaling pathways. Dot size represents the relative abundance of each cell type.
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    PRELP + CAFs interact and colocalize with immune cells in the tumor microenvironment. (a) Immunofluorescence staining in four groups showed spatial colocalization of PRELP (green) with aSMA (red), CD3 (red), CD20 (red) and <t>CD138</t> (red) in metastatic liver tumors, respectively. Magnified views of the boxed regions are shown on the right. Scale bars, 200 μm. (b) Bubble plot illustrating the incoming (vertical axis) and outgoing (horizontal axis) interaction strength of each cell subtype across all signaling pathways. Dot size represents the relative abundance of each cell type. (c) Predicted ligand-receptor (L–R) interactions between PRELP + CAFs and six immune cell subtypes in the APP-CD74 axis and the collagen-CD44 axis. Rows indicate specific L-R pairs, and columns represent immune cell subtypes. Dot color denotes the communication probability. (d) Predicted ligand-receptor (L–R) interactions of GALECTIN (top) and NECTIN (bottom) signaling pathways between PRELP + CAFs and TNK cell subtypes. Dot color represents the communication probability. (e) Hierarchical plots of the SEMA7A/(ITGB1+ITGA1) signaling network inferred by CellChat. Line thickness represents interaction strength and the color of line matches the signal sending cell. In the top panel, fibroblasts act as signal receivers, while in the bottom panel, myeloid cells receive the signals. (f) Bubble plot illustrating the incoming (vertical axis) and outgoing (horizontal axis) interaction strength of fibroblast and myeloid cell subtype in SEMA4 signaling pathways. Dot size represents the relative abundance of each cell type.
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    a Minor salivary gland (mSG) biopsy 10x single cell workflow pipeline, Created in BioRender. NAYAR, S. (2024) https://BioRender.com/l06g537 . b Uniform manifold approximation and projection (UMAP) embedding of 17,011 single cells and gross-cell identities clustering of single-cell gene expression data from n = 7 Sjogren’s syndrome (SjS) salivary gland samples illustrating both immune and stromal cell clusters. c Multiplex immunofluorescence image illustrating major lineages identified in minor salivary gland tissue from Sjogren’s patients ( n = 3) probed with a 6-plex panels for CD146 (green), VE-cadherin or CD20 (yellow), Pan-Cytokeratin/CK (magenta), <t>CD138</t> (orange), and CD68 + CD11c (cyan), CD45 or CD8 (white), Podoplanin/PDPN+CD90 or CD3 (red) and CD4 (blue), Scale bar = 50 µm.
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    a Minor salivary gland (mSG) biopsy 10x single cell workflow pipeline, Created in BioRender. NAYAR, S. (2024) https://BioRender.com/l06g537 . b Uniform manifold approximation and projection (UMAP) embedding of 17,011 single cells and gross-cell identities clustering of single-cell gene expression data from n = 7 Sjogren’s syndrome (SjS) salivary gland samples illustrating both immune and stromal cell clusters. c Multiplex immunofluorescence image illustrating major lineages identified in minor salivary gland tissue from Sjogren’s patients ( n = 3) probed with a 6-plex panels for CD146 (green), VE-cadherin or CD20 (yellow), Pan-Cytokeratin/CK (magenta), <t>CD138</t> (orange), and CD68 + CD11c (cyan), CD45 or CD8 (white), Podoplanin/PDPN+CD90 or CD3 (red) and CD4 (blue), Scale bar = 50 µm.
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    Image Search Results


    PRELP + CAFs interact and colocalize with immune cells in the tumor microenvironment. (a) Immunofluorescence staining in four groups showed spatial colocalization of PRELP (green) with aSMA (red), CD3 (red), CD20 (red) and CD138 (red) in metastatic liver tumors, respectively. Magnified views of the boxed regions are shown on the right. Scale bars, 200 μm. (b) Bubble plot illustrating the incoming (vertical axis) and outgoing (horizontal axis) interaction strength of each cell subtype across all signaling pathways. Dot size represents the relative abundance of each cell type. (c) Predicted ligand-receptor (L–R) interactions between PRELP + CAFs and six immune cell subtypes in the APP-CD74 axis and the collagen-CD44 axis. Rows indicate specific L-R pairs, and columns represent immune cell subtypes. Dot color denotes the communication probability. (d) Predicted ligand-receptor (L–R) interactions of GALECTIN (top) and NECTIN (bottom) signaling pathways between PRELP + CAFs and TNK cell subtypes. Dot color represents the communication probability. (e) Hierarchical plots of the SEMA7A/(ITGB1+ITGA1) signaling network inferred by CellChat. Line thickness represents interaction strength and the color of line matches the signal sending cell. In the top panel, fibroblasts act as signal receivers, while in the bottom panel, myeloid cells receive the signals. (f) Bubble plot illustrating the incoming (vertical axis) and outgoing (horizontal axis) interaction strength of fibroblast and myeloid cell subtype in SEMA4 signaling pathways. Dot size represents the relative abundance of each cell type.

    Journal: Frontiers in Genetics

    Article Title: Characterization of the phenotype and function of PRELP + fibroblast subtype in liver metastatic colorectal cancer

    doi: 10.3389/fgene.2025.1615259

    Figure Lengend Snippet: PRELP + CAFs interact and colocalize with immune cells in the tumor microenvironment. (a) Immunofluorescence staining in four groups showed spatial colocalization of PRELP (green) with aSMA (red), CD3 (red), CD20 (red) and CD138 (red) in metastatic liver tumors, respectively. Magnified views of the boxed regions are shown on the right. Scale bars, 200 μm. (b) Bubble plot illustrating the incoming (vertical axis) and outgoing (horizontal axis) interaction strength of each cell subtype across all signaling pathways. Dot size represents the relative abundance of each cell type. (c) Predicted ligand-receptor (L–R) interactions between PRELP + CAFs and six immune cell subtypes in the APP-CD74 axis and the collagen-CD44 axis. Rows indicate specific L-R pairs, and columns represent immune cell subtypes. Dot color denotes the communication probability. (d) Predicted ligand-receptor (L–R) interactions of GALECTIN (top) and NECTIN (bottom) signaling pathways between PRELP + CAFs and TNK cell subtypes. Dot color represents the communication probability. (e) Hierarchical plots of the SEMA7A/(ITGB1+ITGA1) signaling network inferred by CellChat. Line thickness represents interaction strength and the color of line matches the signal sending cell. In the top panel, fibroblasts act as signal receivers, while in the bottom panel, myeloid cells receive the signals. (f) Bubble plot illustrating the incoming (vertical axis) and outgoing (horizontal axis) interaction strength of fibroblast and myeloid cell subtype in SEMA4 signaling pathways. Dot size represents the relative abundance of each cell type.

    Article Snippet: Rabbit anti-human PRELP (Abcam, ab229719, 1:100) was incubated overnight at 4 °C with mouse anti-human COL1A1 (CST, #6648, 1:200), mouse anti-human aSMA (Fluidgm, 3141017D, 1:200), mouse anti-human CD3 (Santa Cruz, sc-59010, 1:80), mouse anti-human CD138 (Santa Cruz, sc-12765, 1:100), and mouse anti-human CD20 (Servicebio, GB14030-50, 1:150) individually in separate reactions.

    Techniques: Immunofluorescence, Staining, Protein-Protein interactions

    a Minor salivary gland (mSG) biopsy 10x single cell workflow pipeline, Created in BioRender. NAYAR, S. (2024) https://BioRender.com/l06g537 . b Uniform manifold approximation and projection (UMAP) embedding of 17,011 single cells and gross-cell identities clustering of single-cell gene expression data from n = 7 Sjogren’s syndrome (SjS) salivary gland samples illustrating both immune and stromal cell clusters. c Multiplex immunofluorescence image illustrating major lineages identified in minor salivary gland tissue from Sjogren’s patients ( n = 3) probed with a 6-plex panels for CD146 (green), VE-cadherin or CD20 (yellow), Pan-Cytokeratin/CK (magenta), CD138 (orange), and CD68 + CD11c (cyan), CD45 or CD8 (white), Podoplanin/PDPN+CD90 or CD3 (red) and CD4 (blue), Scale bar = 50 µm.

    Journal: Nature Communications

    Article Title: Molecular and spatial analysis of tertiary lymphoid structures in Sjogren’s syndrome

    doi: 10.1038/s41467-024-54686-0

    Figure Lengend Snippet: a Minor salivary gland (mSG) biopsy 10x single cell workflow pipeline, Created in BioRender. NAYAR, S. (2024) https://BioRender.com/l06g537 . b Uniform manifold approximation and projection (UMAP) embedding of 17,011 single cells and gross-cell identities clustering of single-cell gene expression data from n = 7 Sjogren’s syndrome (SjS) salivary gland samples illustrating both immune and stromal cell clusters. c Multiplex immunofluorescence image illustrating major lineages identified in minor salivary gland tissue from Sjogren’s patients ( n = 3) probed with a 6-plex panels for CD146 (green), VE-cadherin or CD20 (yellow), Pan-Cytokeratin/CK (magenta), CD138 (orange), and CD68 + CD11c (cyan), CD45 or CD8 (white), Podoplanin/PDPN+CD90 or CD3 (red) and CD4 (blue), Scale bar = 50 µm.

    Article Snippet: Antibodies used were CD45 (Clone D9M8I, CST, 1:100), VE-cadherin (Clone E6N7A, CST, 1:100), Podoplanin/PDPN (EPR7072, Abcam, 1:100), CD90 (Clone D3V8A, CST, 1:100), CD146 (EPR3208; Abcam, 1:00), CD3 (Clone MRQ-39; Cell Marque, 1:500), CD20 (Clone L20; Cell Marque, 1:100), CD8 (Clone 4B11; Thermofisher, 1:50), CD4 (EPR6855; Abcam, 1:400), CD11c (Clone D3V1E; CST), PNAD (Clone MECA-79, Sigma-Aldrich, 1:50) CD82 (Clone D7G6H; CST, 1:200), Tenascin C (HPA004823; Sigma-Aldrich, 1:50), pan-cytokeratin (Clone AE1/AE3, Dako, 1:50), CD138 (Clone B-A38; Bio-Rad, 1:50), CD21 (Clone SP186; Abcam), Granzyme K (Clone 1C3A4; Proteintech, 1:250), FOXP3 (Clone SP97; Thermofisher, 1:50), ICOS (EPR20560; Abcam, 1:50), PD1 (EPR4877(2); Abcam, 1:500), CXCL13 (AF801; R&D systems, 1:20), CXCR5 (Clone D6L3C; CST, 1:25) and Ki67 (Clone MIB-1, Dako, 1:25).

    Techniques: Gene Expression, Multiplex Assay, Immunofluorescence

    a Uniform manifold approximation and projection (UMAP) dimensional reduction and sub-clustering of fibroblast and mural cell transcriptomic data in Sjogren’s syndrome (SjS) minor salivary glands (mSG). b Expression of current identifying and newly discovered identifying genes across the fibroblast and mural subsets. c Expression of gene cassettes used to spatially identify immunofibroblast and CCL21 CCL19 pericytes in salivary glands. d Multiplex immunofluorescence image illustrating immune cells and pericytes identified in minor salivary gland tissue ( n = 2) probed with a 6-plex panels for CD138 (green), CD20 or TNC (yellow), Pan-Cytokeratin/CK or CD82 (orange), VE-cadherin (cyan), Podoplanin/PDPN (white), CD3 or CD146 (red) and DAPI or CD45 (blue), Scale bar = 20 µm. e Multiplex immunofluorescence image of CD146 (grey) pericytes with ccl21rna (green), ccl19rna (red) and DAPI (blue) in immune aggregate within human salivary glands of patients ( n = 2) with Sjögren’s syndrome, Scale bar = 20 µm. f Representative flow cytometric identification of CD146+TNC+ CD36+CCL21+ pericyte cell population in Sjogren’s syndrome minor salivary glands. g Gene-set overrepresentation analysis (using GO and Kegg gene sets) of the fibroblast and mural populations, the top 5 enriched gene sets for each cell subset are shown.

    Journal: Nature Communications

    Article Title: Molecular and spatial analysis of tertiary lymphoid structures in Sjogren’s syndrome

    doi: 10.1038/s41467-024-54686-0

    Figure Lengend Snippet: a Uniform manifold approximation and projection (UMAP) dimensional reduction and sub-clustering of fibroblast and mural cell transcriptomic data in Sjogren’s syndrome (SjS) minor salivary glands (mSG). b Expression of current identifying and newly discovered identifying genes across the fibroblast and mural subsets. c Expression of gene cassettes used to spatially identify immunofibroblast and CCL21 CCL19 pericytes in salivary glands. d Multiplex immunofluorescence image illustrating immune cells and pericytes identified in minor salivary gland tissue ( n = 2) probed with a 6-plex panels for CD138 (green), CD20 or TNC (yellow), Pan-Cytokeratin/CK or CD82 (orange), VE-cadherin (cyan), Podoplanin/PDPN (white), CD3 or CD146 (red) and DAPI or CD45 (blue), Scale bar = 20 µm. e Multiplex immunofluorescence image of CD146 (grey) pericytes with ccl21rna (green), ccl19rna (red) and DAPI (blue) in immune aggregate within human salivary glands of patients ( n = 2) with Sjögren’s syndrome, Scale bar = 20 µm. f Representative flow cytometric identification of CD146+TNC+ CD36+CCL21+ pericyte cell population in Sjogren’s syndrome minor salivary glands. g Gene-set overrepresentation analysis (using GO and Kegg gene sets) of the fibroblast and mural populations, the top 5 enriched gene sets for each cell subset are shown.

    Article Snippet: Antibodies used were CD45 (Clone D9M8I, CST, 1:100), VE-cadherin (Clone E6N7A, CST, 1:100), Podoplanin/PDPN (EPR7072, Abcam, 1:100), CD90 (Clone D3V8A, CST, 1:100), CD146 (EPR3208; Abcam, 1:00), CD3 (Clone MRQ-39; Cell Marque, 1:500), CD20 (Clone L20; Cell Marque, 1:100), CD8 (Clone 4B11; Thermofisher, 1:50), CD4 (EPR6855; Abcam, 1:400), CD11c (Clone D3V1E; CST), PNAD (Clone MECA-79, Sigma-Aldrich, 1:50) CD82 (Clone D7G6H; CST, 1:200), Tenascin C (HPA004823; Sigma-Aldrich, 1:50), pan-cytokeratin (Clone AE1/AE3, Dako, 1:50), CD138 (Clone B-A38; Bio-Rad, 1:50), CD21 (Clone SP186; Abcam), Granzyme K (Clone 1C3A4; Proteintech, 1:250), FOXP3 (Clone SP97; Thermofisher, 1:50), ICOS (EPR20560; Abcam, 1:50), PD1 (EPR4877(2); Abcam, 1:500), CXCL13 (AF801; R&D systems, 1:20), CXCR5 (Clone D6L3C; CST, 1:25) and Ki67 (Clone MIB-1, Dako, 1:25).

    Techniques: Expressing, Multiplex Assay, Immunofluorescence