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primary antibodies panck  (OriGene)


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    OriGene primary antibodies panck
    Transcriptional signatures of lymphoid cells identified by snRNA-seq. (A) UMAP plot of the lymphoid cell landscape, coloured by subcluster. (B) Feature plots showing the normalized expression of specific marker genes in lymphoid cells. (C) Heatmap showing the average expression levels of selected genes across 11 lymphoid subclusters. (D) Monocle pseudotime trajectory analysis of <t>CD8</t> cells during the progression process. (E) Monocle pseudotime trajectory analysis of <t>CD4</t> cells during the progression process. (F) Immunofluorescence assay for PanCK, CD4, <t>FOXP3,</t> and DAPI in PT and LM samples. Scale bars, 50 µm. (G) Statistical analysis of the number of CD4 FOXP3 T cells in PT and LM, statistical testing was performed using the t-test (**, p < 0.01). (H) Heatmap of immune checkpoint genes in lymphoid cells, with annotations of receptor or ligand, inhibitory or stimulatory roles. The bars at the top indicate receptor or ligand type, while the left bars indicate sample source and lymphoid cell type annotations. (I) KEGG pathway enrichment analysis of differentially expressed genes between CD4 FOXP3 T cells from PT and LM, with a significance threshold of p < 0.05 and log 2 (fold change) ≥ 0.5. (J) Box plots showing TIL (tumor-infiltrating lymphocytes), cytotoxic, and Treg scores for lymphoid cells in PT and LM, statistical testing performed using the t-test (****, p < 0.0001). (K) Bar plots showing the proportions of 11 lymphoid subclusters in PT and LM.
    Primary Antibodies Panck, supplied by OriGene, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/primary antibodies panck/product/OriGene
    Average 90 stars, based on 1 article reviews
    primary antibodies panck - by Bioz Stars, 2026-03
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    Images

    1) Product Images from "Single-nucleus RNA sequencing and spatial transcriptomics reveal an immunosuppressive tumor microenvironment related to metastatic dissemination during pancreatic cancer liver metastasis"

    Article Title: Single-nucleus RNA sequencing and spatial transcriptomics reveal an immunosuppressive tumor microenvironment related to metastatic dissemination during pancreatic cancer liver metastasis

    Journal: Theranostics

    doi: 10.7150/thno.108925

    Transcriptional signatures of lymphoid cells identified by snRNA-seq. (A) UMAP plot of the lymphoid cell landscape, coloured by subcluster. (B) Feature plots showing the normalized expression of specific marker genes in lymphoid cells. (C) Heatmap showing the average expression levels of selected genes across 11 lymphoid subclusters. (D) Monocle pseudotime trajectory analysis of CD8 cells during the progression process. (E) Monocle pseudotime trajectory analysis of CD4 cells during the progression process. (F) Immunofluorescence assay for PanCK, CD4, FOXP3, and DAPI in PT and LM samples. Scale bars, 50 µm. (G) Statistical analysis of the number of CD4 FOXP3 T cells in PT and LM, statistical testing was performed using the t-test (**, p < 0.01). (H) Heatmap of immune checkpoint genes in lymphoid cells, with annotations of receptor or ligand, inhibitory or stimulatory roles. The bars at the top indicate receptor or ligand type, while the left bars indicate sample source and lymphoid cell type annotations. (I) KEGG pathway enrichment analysis of differentially expressed genes between CD4 FOXP3 T cells from PT and LM, with a significance threshold of p < 0.05 and log 2 (fold change) ≥ 0.5. (J) Box plots showing TIL (tumor-infiltrating lymphocytes), cytotoxic, and Treg scores for lymphoid cells in PT and LM, statistical testing performed using the t-test (****, p < 0.0001). (K) Bar plots showing the proportions of 11 lymphoid subclusters in PT and LM.
    Figure Legend Snippet: Transcriptional signatures of lymphoid cells identified by snRNA-seq. (A) UMAP plot of the lymphoid cell landscape, coloured by subcluster. (B) Feature plots showing the normalized expression of specific marker genes in lymphoid cells. (C) Heatmap showing the average expression levels of selected genes across 11 lymphoid subclusters. (D) Monocle pseudotime trajectory analysis of CD8 cells during the progression process. (E) Monocle pseudotime trajectory analysis of CD4 cells during the progression process. (F) Immunofluorescence assay for PanCK, CD4, FOXP3, and DAPI in PT and LM samples. Scale bars, 50 µm. (G) Statistical analysis of the number of CD4 FOXP3 T cells in PT and LM, statistical testing was performed using the t-test (**, p < 0.01). (H) Heatmap of immune checkpoint genes in lymphoid cells, with annotations of receptor or ligand, inhibitory or stimulatory roles. The bars at the top indicate receptor or ligand type, while the left bars indicate sample source and lymphoid cell type annotations. (I) KEGG pathway enrichment analysis of differentially expressed genes between CD4 FOXP3 T cells from PT and LM, with a significance threshold of p < 0.05 and log 2 (fold change) ≥ 0.5. (J) Box plots showing TIL (tumor-infiltrating lymphocytes), cytotoxic, and Treg scores for lymphoid cells in PT and LM, statistical testing performed using the t-test (****, p < 0.0001). (K) Bar plots showing the proportions of 11 lymphoid subclusters in PT and LM.

    Techniques Used: Expressing, Marker, Immunofluorescence



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    Transcriptional signatures of lymphoid cells identified by snRNA-seq. (A) UMAP plot of the lymphoid cell landscape, coloured by subcluster. (B) Feature plots showing the normalized expression of specific marker genes in lymphoid cells. (C) Heatmap showing the average expression levels of selected genes across 11 lymphoid subclusters. (D) Monocle pseudotime trajectory analysis of <t>CD8</t> cells during the progression process. (E) Monocle pseudotime trajectory analysis of <t>CD4</t> cells during the progression process. (F) Immunofluorescence assay for PanCK, CD4, <t>FOXP3,</t> and DAPI in PT and LM samples. Scale bars, 50 µm. (G) Statistical analysis of the number of CD4 FOXP3 T cells in PT and LM, statistical testing was performed using the t-test (**, p < 0.01). (H) Heatmap of immune checkpoint genes in lymphoid cells, with annotations of receptor or ligand, inhibitory or stimulatory roles. The bars at the top indicate receptor or ligand type, while the left bars indicate sample source and lymphoid cell type annotations. (I) KEGG pathway enrichment analysis of differentially expressed genes between CD4 FOXP3 T cells from PT and LM, with a significance threshold of p < 0.05 and log 2 (fold change) ≥ 0.5. (J) Box plots showing TIL (tumor-infiltrating lymphocytes), cytotoxic, and Treg scores for lymphoid cells in PT and LM, statistical testing performed using the t-test (****, p < 0.0001). (K) Bar plots showing the proportions of 11 lymphoid subclusters in PT and LM.
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    Transcriptional signatures of lymphoid cells identified by snRNA-seq. (A) UMAP plot of the lymphoid cell landscape, coloured by subcluster. (B) Feature plots showing the normalized expression of specific marker genes in lymphoid cells. (C) Heatmap showing the average expression levels of selected genes across 11 lymphoid subclusters. (D) Monocle pseudotime trajectory analysis of <t>CD8</t> cells during the progression process. (E) Monocle pseudotime trajectory analysis of <t>CD4</t> cells during the progression process. (F) Immunofluorescence assay for PanCK, CD4, <t>FOXP3,</t> and DAPI in PT and LM samples. Scale bars, 50 µm. (G) Statistical analysis of the number of CD4 FOXP3 T cells in PT and LM, statistical testing was performed using the t-test (**, p < 0.01). (H) Heatmap of immune checkpoint genes in lymphoid cells, with annotations of receptor or ligand, inhibitory or stimulatory roles. The bars at the top indicate receptor or ligand type, while the left bars indicate sample source and lymphoid cell type annotations. (I) KEGG pathway enrichment analysis of differentially expressed genes between CD4 FOXP3 T cells from PT and LM, with a significance threshold of p < 0.05 and log 2 (fold change) ≥ 0.5. (J) Box plots showing TIL (tumor-infiltrating lymphocytes), cytotoxic, and Treg scores for lymphoid cells in PT and LM, statistical testing performed using the t-test (****, p < 0.0001). (K) Bar plots showing the proportions of 11 lymphoid subclusters in PT and LM.
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    Image Search Results


    Transcriptional signatures of lymphoid cells identified by snRNA-seq. (A) UMAP plot of the lymphoid cell landscape, coloured by subcluster. (B) Feature plots showing the normalized expression of specific marker genes in lymphoid cells. (C) Heatmap showing the average expression levels of selected genes across 11 lymphoid subclusters. (D) Monocle pseudotime trajectory analysis of CD8 cells during the progression process. (E) Monocle pseudotime trajectory analysis of CD4 cells during the progression process. (F) Immunofluorescence assay for PanCK, CD4, FOXP3, and DAPI in PT and LM samples. Scale bars, 50 µm. (G) Statistical analysis of the number of CD4 FOXP3 T cells in PT and LM, statistical testing was performed using the t-test (**, p < 0.01). (H) Heatmap of immune checkpoint genes in lymphoid cells, with annotations of receptor or ligand, inhibitory or stimulatory roles. The bars at the top indicate receptor or ligand type, while the left bars indicate sample source and lymphoid cell type annotations. (I) KEGG pathway enrichment analysis of differentially expressed genes between CD4 FOXP3 T cells from PT and LM, with a significance threshold of p < 0.05 and log 2 (fold change) ≥ 0.5. (J) Box plots showing TIL (tumor-infiltrating lymphocytes), cytotoxic, and Treg scores for lymphoid cells in PT and LM, statistical testing performed using the t-test (****, p < 0.0001). (K) Bar plots showing the proportions of 11 lymphoid subclusters in PT and LM.

    Journal: Theranostics

    Article Title: Single-nucleus RNA sequencing and spatial transcriptomics reveal an immunosuppressive tumor microenvironment related to metastatic dissemination during pancreatic cancer liver metastasis

    doi: 10.7150/thno.108925

    Figure Lengend Snippet: Transcriptional signatures of lymphoid cells identified by snRNA-seq. (A) UMAP plot of the lymphoid cell landscape, coloured by subcluster. (B) Feature plots showing the normalized expression of specific marker genes in lymphoid cells. (C) Heatmap showing the average expression levels of selected genes across 11 lymphoid subclusters. (D) Monocle pseudotime trajectory analysis of CD8 cells during the progression process. (E) Monocle pseudotime trajectory analysis of CD4 cells during the progression process. (F) Immunofluorescence assay for PanCK, CD4, FOXP3, and DAPI in PT and LM samples. Scale bars, 50 µm. (G) Statistical analysis of the number of CD4 FOXP3 T cells in PT and LM, statistical testing was performed using the t-test (**, p < 0.01). (H) Heatmap of immune checkpoint genes in lymphoid cells, with annotations of receptor or ligand, inhibitory or stimulatory roles. The bars at the top indicate receptor or ligand type, while the left bars indicate sample source and lymphoid cell type annotations. (I) KEGG pathway enrichment analysis of differentially expressed genes between CD4 FOXP3 T cells from PT and LM, with a significance threshold of p < 0.05 and log 2 (fold change) ≥ 0.5. (J) Box plots showing TIL (tumor-infiltrating lymphocytes), cytotoxic, and Treg scores for lymphoid cells in PT and LM, statistical testing performed using the t-test (****, p < 0.0001). (K) Bar plots showing the proportions of 11 lymphoid subclusters in PT and LM.

    Article Snippet: The sections were incubated with primary antibodies (CD4, CD8, FOXP3, CD20, panCK, and VIM from ZSbio or CST) for 30 min at room temperature, followed by a 10 min incubation with PVB tyramide signal amplification fluorophore (PVB 480, PVB 520, PVB 50, PVB 620, PVB 690, and PVB 780).

    Techniques: Expressing, Marker, Immunofluorescence