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visium spatial transcriptomics st  (Spatial Transcriptomics Inc)

 
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    Spatial Transcriptomics Inc visium spatial transcriptomics st
    Visium Spatial Transcriptomics St, supplied by Spatial Transcriptomics Inc, 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/spatial+transcriptomics+st/data+spatial+transcriptomics+visium/pm41592568-773-7-8
    Average 86 stars, based on 1 article reviews
    visium spatial transcriptomics st - by Bioz Stars, 2026-09
    86/100 stars

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    Spatial Transcriptomics:

    Article Title: Phase Separation Competent TIA1 Couples Glycolytic Shutdown to CD8 + T-Cell Activation and Shapes the Efficacy of Intravesical BCG in Bladder Cancer
    Article Snippet: .. Visium spatial-transcriptomics data (GEO GSE171351 ) were processed in Seurat v4; TIA1, EPCAM, and CD8A spot-level expression was visualized in ggplot2 (RStudio, Version: 2025.09.2+418). ..

    Article Title: A technical comparison of spatial transcriptomics platforms across six cancer types.
    Article Snippet: .. To systematically evaluate the technical performance of current spatial transcriptomics technologies, we profiled six FFPE tumor types using five commercially available platforms: Visium v1, Visium v2 (CytAssist), VisiumHD, Xenium, and CosMx. ..


    Article Title: Integrative transcriptomic analysis reveals microglial metabolic-inflammatory crosstalk of HK2–HSPA5–TNF axis after intracerebral hemorrhage
    Article Snippet: .. Spatial transcriptomics analysis leveraged preprocessed Visium data from lesional (hemorrhage-affected) and contralateral hemispheres across nine timepoints (Naive to D28). ..

    Article Title: Ghent Pathology 2025. 15th Joint Meeting of the BDIAP and The Pathological Society joint with the Belgian Society of Pathology, 24-26 June 2025.
    Article Snippet: .. Additionally, we assessed SEQUOIA’s ability to infer spatially resolved expression by comparing predicted values with ground truth obtained from Visium spatial transcriptomics data. ..

    Article Title: CEBPB expression in tumor cells drives immune evasion in colorectal cancer via CTLA4 upregulation in T cells
    Article Snippet: .. For comparative analyses, we also used the publicly available human colorectal cancer scRNA-seq dataset (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE178341) and a Visium spatial-transcriptomics dataset from Zenodo (https://doi.org/10.5281/zenodo.7551712). .. HJY, DY, JDL, HS, and SMK performed in vitro and in vivo experiments, CHP, KK, D ow nloaded from https://spj.science.org on February 04, 2026 32 and HS analyzed scRNA-seq data, HRS analyzed whole-exome sequencing, immunohistochemistry, and public data, CP analyzed public data, MJK, JWP, SBR, SYJ, KJP, and TYK provided human tumor tissue and analyzed clinical data, YL analyzed Lunit SCOPE IO data, JK supervised scRNA-seq analysis, JKW supervised public data and pathological analysis, and SWH provided concept of the study and supervised in vitro and in vivo experiments.

    Article Title: Hist2Cell: Deciphering fine-grained cellular architectures from histology images.
    Article Snippet: .. 39 We selected slices that included both Visium Spatial Transcriptomics (ST) data and 20× magnification H&E images. ..

    Article Title: Single Cell and Spatial Transcriptomics Define a Proinflammatory and Profibrotic Niche After Kidney Injury.
    Article Snippet: .. Spatial Transcriptomics VisiumData Processing: Mouse kidney samples stored in a frozen state were embedded withOCT compound and stored at −80 °C. .. For the preparation of sections for Visium Spatial Transcriptomics sequencing, samples were equilibrated at−18 °C and a 10 μmthick section was cut onto the active sequencing area (6 mm x 6 mm) of a spatial barcoded slide.

    Expressing:

    Article Title: Phase Separation Competent TIA1 Couples Glycolytic Shutdown to CD8 + T-Cell Activation and Shapes the Efficacy of Intravesical BCG in Bladder Cancer
    Article Snippet: .. Visium spatial-transcriptomics data (GEO GSE171351 ) were processed in Seurat v4; TIA1, EPCAM, and CD8A spot-level expression was visualized in ggplot2 (RStudio, Version: 2025.09.2+418). ..

    Article Title: Ghent Pathology 2025. 15th Joint Meeting of the BDIAP and The Pathological Society joint with the Belgian Society of Pathology, 24-26 June 2025.
    Article Snippet: .. Additionally, we assessed SEQUOIA’s ability to infer spatially resolved expression by comparing predicted values with ground truth obtained from Visium spatial transcriptomics data. ..

    Formalin-fixed Paraffin-Embedded:

    Article Title: A technical comparison of spatial transcriptomics platforms across six cancer types.
    Article Snippet: .. To systematically evaluate the technical performance of current spatial transcriptomics technologies, we profiled six FFPE tumor types using five commercially available platforms: Visium v1, Visium v2 (CytAssist), VisiumHD, Xenium, and CosMx. ..



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    <t>Salus-STS</t> <t>high-resolution</t> spatial <t>transcriptomics</t> enables effective cell identification at the subcellular level. (A) Schematics illustrating of the study. (B) Results of cell segmentation via the Salus Cellbins Algorithm. (C–F) Distributions and medians (red text in the figures) of the area (in pixel 2 ) (C) , UMI counts (D) , gene numbers (E) , and proportions of mitochondrial UMIs (F) of segmented cellbins.
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    Spatial organization and cell-cell communication networks in the tumor microenvironment. (A–C) The developmental trajectories of cell sub-populations from a spatial perspective are investigated. (D, E) Heatmap and network diagrams displaying cell–cell dependency analysis in the colocated, neighboring, and extended neighboring (15-point) regions of the spatial transcriptomics data. (F) The interaction heatmap visualized the intensity of intercellular interactions mediated by the ligand-receptor pairs. (G) The spatial cell communication network diagram illustrates that NUhighepi exhibit a higher intensity of cell communication with other cells. (H) Circos plot summarizing cell-type-specific interaction patterns.

    Journal: Frontiers in Oncology

    Article Title: Spatial transcriptome and single-cell sequencing reveal the role of nucleotide metabolism in breast cancer progression and tumor microenvironment

    doi: 10.3389/fonc.2025.1703778

    Figure Lengend Snippet: Spatial organization and cell-cell communication networks in the tumor microenvironment. (A–C) The developmental trajectories of cell sub-populations from a spatial perspective are investigated. (D, E) Heatmap and network diagrams displaying cell–cell dependency analysis in the colocated, neighboring, and extended neighboring (15-point) regions of the spatial transcriptomics data. (F) The interaction heatmap visualized the intensity of intercellular interactions mediated by the ligand-receptor pairs. (G) The spatial cell communication network diagram illustrates that NUhighepi exhibit a higher intensity of cell communication with other cells. (H) Circos plot summarizing cell-type-specific interaction patterns.

    Article Snippet: Breast cancer spatial transcriptomics (ST) data were acquired from the GEO database ( https://www.ncbi.nlm.nih.gov/geo/ ) and 10x Genomics official website ( https://www.10xgenomics.com/ ).

    Techniques:

    Salus-STS high-resolution spatial transcriptomics enables effective cell identification at the subcellular level. (A) Schematics illustrating of the study. (B) Results of cell segmentation via the Salus Cellbins Algorithm. (C–F) Distributions and medians (red text in the figures) of the area (in pixel 2 ) (C) , UMI counts (D) , gene numbers (E) , and proportions of mitochondrial UMIs (F) of segmented cellbins.

    Journal: Frontiers in Reproductive Health

    Article Title: Spatiotemporal dynamics of spermatogenesis: insights from high-resolution spatial transcriptomics and pseudotime trajectories in mouse testes

    doi: 10.3389/frph.2025.1747902

    Figure Lengend Snippet: Salus-STS high-resolution spatial transcriptomics enables effective cell identification at the subcellular level. (A) Schematics illustrating of the study. (B) Results of cell segmentation via the Salus Cellbins Algorithm. (C–F) Distributions and medians (red text in the figures) of the area (in pixel 2 ) (C) , UMI counts (D) , gene numbers (E) , and proportions of mitochondrial UMIs (F) of segmented cellbins.

    Article Snippet: In this study, we used Salus-STS high-resolution spatial transcriptomics (∼1 μm resolution) and Salus Cellbins Algorithm to characterize the spatial transcriptomic profile of mouse testes at single-cell level.

    Techniques:

    Cellbin-based analysis enables accurate identification of distinct cell types in the mouse testis. (A) RCTD-annotated distinct cell types and their proportions. (B) UMAP visualization of the Salus-STS Cellbin data with scRNA-Seq data. (C) Spatial distribution of distinct cell types in the mouse testis. (D) Integrated distribution map of cell distributions in the mouse testis. (E) Markers of distinct cell types and their expression levels. Scaled expression: the average expression level scaled across genes to eliminate the effect of total expression level differences among genes. Percentage: for each cell type, the percentage of cellbins that express the specific gene out of all cellbins of the same type.

    Journal: Frontiers in Reproductive Health

    Article Title: Spatiotemporal dynamics of spermatogenesis: insights from high-resolution spatial transcriptomics and pseudotime trajectories in mouse testes

    doi: 10.3389/frph.2025.1747902

    Figure Lengend Snippet: Cellbin-based analysis enables accurate identification of distinct cell types in the mouse testis. (A) RCTD-annotated distinct cell types and their proportions. (B) UMAP visualization of the Salus-STS Cellbin data with scRNA-Seq data. (C) Spatial distribution of distinct cell types in the mouse testis. (D) Integrated distribution map of cell distributions in the mouse testis. (E) Markers of distinct cell types and their expression levels. Scaled expression: the average expression level scaled across genes to eliminate the effect of total expression level differences among genes. Percentage: for each cell type, the percentage of cellbins that express the specific gene out of all cellbins of the same type.

    Article Snippet: In this study, we used Salus-STS high-resolution spatial transcriptomics (∼1 μm resolution) and Salus Cellbins Algorithm to characterize the spatial transcriptomic profile of mouse testes at single-cell level.

    Techniques: Expressing

    High-resolution spatial transcriptomics uncovers spatiotemporal markers of spermatogenesis. (A) Pseudotime trajectory analysis. (B) Randomly selected seminiferous tubules. (C,D) Top 6 genes with expression levels positively (C) and negatively (D) correlated with the axis from the tubule basement membrane (epithelium) to the lumen center respectively.

    Journal: Frontiers in Reproductive Health

    Article Title: Spatiotemporal dynamics of spermatogenesis: insights from high-resolution spatial transcriptomics and pseudotime trajectories in mouse testes

    doi: 10.3389/frph.2025.1747902

    Figure Lengend Snippet: High-resolution spatial transcriptomics uncovers spatiotemporal markers of spermatogenesis. (A) Pseudotime trajectory analysis. (B) Randomly selected seminiferous tubules. (C,D) Top 6 genes with expression levels positively (C) and negatively (D) correlated with the axis from the tubule basement membrane (epithelium) to the lumen center respectively.

    Article Snippet: In this study, we used Salus-STS high-resolution spatial transcriptomics (∼1 μm resolution) and Salus Cellbins Algorithm to characterize the spatial transcriptomic profile of mouse testes at single-cell level.

    Techniques: Expressing, Membrane