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visium spatial tissue optimisation kit  (10X Genomics)

 
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    10X Genomics visium spatial tissue optimisation kit
    A, Schematic of the integrative analysis pipeline combining single cell RNA-seq, <t>Visium</t> spatial transcriptomics and ligand-receptor-target inference to identify niche-macrophage signalling programmes. B,C, Visium sections from homeostatic (B) and 5 dpi regenerating (C) hearts, with each white spot representing a 55µm capture area. D,D ′ , Spatial maps of key structural cell types identified (smooth muscle cells, cardiomyocytes, fibroblasts, epicardium and macrophages) in homeostatic (D) and regenerating (D ′ ) hearts according to inferred cell type composition after cell2location deconvolution. E, Representative MERFISH image illustrating single molecule transcript detection and cell segmentation. E ′ , Heat map summarising the biological categories included in designing the 500 gene MERFISH panel, grouped into structural cell markers, mpeg1.1 + subpopulation genes, injury-induced signatures, candidate niche-macrophage signalling mediators and other regeneration-related genes. F,G, Marker selection matrices used to distinguish structural cells (F) and mpeg1.1 + immune subpopulations (G) in MERFISH data. Detailed gene panel design included in Table S1. H-J, NicheNet-based prioritisation of ligand-receptor circuits, showing ligands upregulated after injury in structural “sender” populations (H), corresponding receptor activity in mpeg1.1 + “receiver” subsets (I) and predicted downstream target genes in mpeg1.1 + macrophages (J) that together define putative functional communication programmes. Detailed NicheNet output included in Supplementary Information 4.
    Visium Spatial Tissue Optimisation Kit, supplied by 10X Genomics, used in various techniques. Bioz Stars score: 86/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/visium+spatial+tissue+optimisation+kit/bio_rxiv__64898__2026__03__05__709830-245-8-13?v=10X+Genomics
    Average 86 stars, based on 1 article reviews
    visium spatial tissue optimisation kit - by Bioz Stars, 2026-07
    86/100 stars

    Images

    1) Product Images from "Cardiac-immune microniches programme macrophage states in the regenerating heart"

    Article Title: Cardiac-immune microniches programme macrophage states in the regenerating heart

    Journal: bioRxiv

    doi: 10.64898/2026.03.05.709830

    A, Schematic of the integrative analysis pipeline combining single cell RNA-seq, Visium spatial transcriptomics and ligand-receptor-target inference to identify niche-macrophage signalling programmes. B,C, Visium sections from homeostatic (B) and 5 dpi regenerating (C) hearts, with each white spot representing a 55µm capture area. D,D ′ , Spatial maps of key structural cell types identified (smooth muscle cells, cardiomyocytes, fibroblasts, epicardium and macrophages) in homeostatic (D) and regenerating (D ′ ) hearts according to inferred cell type composition after cell2location deconvolution. E, Representative MERFISH image illustrating single molecule transcript detection and cell segmentation. E ′ , Heat map summarising the biological categories included in designing the 500 gene MERFISH panel, grouped into structural cell markers, mpeg1.1 + subpopulation genes, injury-induced signatures, candidate niche-macrophage signalling mediators and other regeneration-related genes. F,G, Marker selection matrices used to distinguish structural cells (F) and mpeg1.1 + immune subpopulations (G) in MERFISH data. Detailed gene panel design included in Table S1. H-J, NicheNet-based prioritisation of ligand-receptor circuits, showing ligands upregulated after injury in structural “sender” populations (H), corresponding receptor activity in mpeg1.1 + “receiver” subsets (I) and predicted downstream target genes in mpeg1.1 + macrophages (J) that together define putative functional communication programmes. Detailed NicheNet output included in Supplementary Information 4.
    Figure Legend Snippet: A, Schematic of the integrative analysis pipeline combining single cell RNA-seq, Visium spatial transcriptomics and ligand-receptor-target inference to identify niche-macrophage signalling programmes. B,C, Visium sections from homeostatic (B) and 5 dpi regenerating (C) hearts, with each white spot representing a 55µm capture area. D,D ′ , Spatial maps of key structural cell types identified (smooth muscle cells, cardiomyocytes, fibroblasts, epicardium and macrophages) in homeostatic (D) and regenerating (D ′ ) hearts according to inferred cell type composition after cell2location deconvolution. E, Representative MERFISH image illustrating single molecule transcript detection and cell segmentation. E ′ , Heat map summarising the biological categories included in designing the 500 gene MERFISH panel, grouped into structural cell markers, mpeg1.1 + subpopulation genes, injury-induced signatures, candidate niche-macrophage signalling mediators and other regeneration-related genes. F,G, Marker selection matrices used to distinguish structural cells (F) and mpeg1.1 + immune subpopulations (G) in MERFISH data. Detailed gene panel design included in Table S1. H-J, NicheNet-based prioritisation of ligand-receptor circuits, showing ligands upregulated after injury in structural “sender” populations (H), corresponding receptor activity in mpeg1.1 + “receiver” subsets (I) and predicted downstream target genes in mpeg1.1 + macrophages (J) that together define putative functional communication programmes. Detailed NicheNet output included in Supplementary Information 4.

    Techniques Used: Single Cell, RNA Sequencing, Spatial Transcriptomics, Marker, Selection, Activity Assay, Functional Assay



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    A, Schematic of the integrative analysis pipeline combining single cell RNA-seq, <t>Visium</t> spatial transcriptomics and ligand-receptor-target inference to identify niche-macrophage signalling programmes. B,C, Visium sections from homeostatic (B) and 5 dpi regenerating (C) hearts, with each white spot representing a 55µm capture area. D,D ′ , Spatial maps of key structural cell types identified (smooth muscle cells, cardiomyocytes, fibroblasts, epicardium and macrophages) in homeostatic (D) and regenerating (D ′ ) hearts according to inferred cell type composition after cell2location deconvolution. E, Representative MERFISH image illustrating single molecule transcript detection and cell segmentation. E ′ , Heat map summarising the biological categories included in designing the 500 gene MERFISH panel, grouped into structural cell markers, mpeg1.1 + subpopulation genes, injury-induced signatures, candidate niche-macrophage signalling mediators and other regeneration-related genes. F,G, Marker selection matrices used to distinguish structural cells (F) and mpeg1.1 + immune subpopulations (G) in MERFISH data. Detailed gene panel design included in Table S1. H-J, NicheNet-based prioritisation of ligand-receptor circuits, showing ligands upregulated after injury in structural “sender” populations (H), corresponding receptor activity in mpeg1.1 + “receiver” subsets (I) and predicted downstream target genes in mpeg1.1 + macrophages (J) that together define putative functional communication programmes. Detailed NicheNet output included in Supplementary Information 4.
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    Image Search Results


    A, Schematic of the integrative analysis pipeline combining single cell RNA-seq, Visium spatial transcriptomics and ligand-receptor-target inference to identify niche-macrophage signalling programmes. B,C, Visium sections from homeostatic (B) and 5 dpi regenerating (C) hearts, with each white spot representing a 55µm capture area. D,D ′ , Spatial maps of key structural cell types identified (smooth muscle cells, cardiomyocytes, fibroblasts, epicardium and macrophages) in homeostatic (D) and regenerating (D ′ ) hearts according to inferred cell type composition after cell2location deconvolution. E, Representative MERFISH image illustrating single molecule transcript detection and cell segmentation. E ′ , Heat map summarising the biological categories included in designing the 500 gene MERFISH panel, grouped into structural cell markers, mpeg1.1 + subpopulation genes, injury-induced signatures, candidate niche-macrophage signalling mediators and other regeneration-related genes. F,G, Marker selection matrices used to distinguish structural cells (F) and mpeg1.1 + immune subpopulations (G) in MERFISH data. Detailed gene panel design included in Table S1. H-J, NicheNet-based prioritisation of ligand-receptor circuits, showing ligands upregulated after injury in structural “sender” populations (H), corresponding receptor activity in mpeg1.1 + “receiver” subsets (I) and predicted downstream target genes in mpeg1.1 + macrophages (J) that together define putative functional communication programmes. Detailed NicheNet output included in Supplementary Information 4.

    Journal: bioRxiv

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    doi: 10.64898/2026.03.05.709830

    Figure Lengend Snippet: A, Schematic of the integrative analysis pipeline combining single cell RNA-seq, Visium spatial transcriptomics and ligand-receptor-target inference to identify niche-macrophage signalling programmes. B,C, Visium sections from homeostatic (B) and 5 dpi regenerating (C) hearts, with each white spot representing a 55µm capture area. D,D ′ , Spatial maps of key structural cell types identified (smooth muscle cells, cardiomyocytes, fibroblasts, epicardium and macrophages) in homeostatic (D) and regenerating (D ′ ) hearts according to inferred cell type composition after cell2location deconvolution. E, Representative MERFISH image illustrating single molecule transcript detection and cell segmentation. E ′ , Heat map summarising the biological categories included in designing the 500 gene MERFISH panel, grouped into structural cell markers, mpeg1.1 + subpopulation genes, injury-induced signatures, candidate niche-macrophage signalling mediators and other regeneration-related genes. F,G, Marker selection matrices used to distinguish structural cells (F) and mpeg1.1 + immune subpopulations (G) in MERFISH data. Detailed gene panel design included in Table S1. H-J, NicheNet-based prioritisation of ligand-receptor circuits, showing ligands upregulated after injury in structural “sender” populations (H), corresponding receptor activity in mpeg1.1 + “receiver” subsets (I) and predicted downstream target genes in mpeg1.1 + macrophages (J) that together define putative functional communication programmes. Detailed NicheNet output included in Supplementary Information 4.

    Article Snippet: The ideal permeabilisation time was determined using the Visium Spatial Tissue Optimisation Kit (10X Genomics).

    Techniques: Single Cell, RNA Sequencing, Spatial Transcriptomics, Marker, Selection, Activity Assay, Functional Assay