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Spatial Transcriptomics Inc array-based spatial transcriptomics visium 10x
Array Based Spatial Transcriptomics Visium 10x, supplied by Spatial Transcriptomics Inc, 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/product/spatial+transcriptomics+arrays/10x+spatial+transcriptomics/pmc11570551-109-18-19
Average 90 stars, based on 1 article reviews
array-based spatial transcriptomics visium 10x - by Bioz Stars, 2026-11
90/100 stars

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Related Articles

Imaging:

Article Title: Integrative spatial omics reveals distinct tumor-promoting multicellular niches and immunosuppressive mechanisms in Black American and White American patients with TNBC
Article Snippet: .. For each patient core (in the BSW Discovery cohort, 3 mm diameter) analyzed using imaging mass cytometry, 10X spatial transcriptomics or Nanostring Geo Mx Digital Spatial Profiling (DSP), ROIs were selected based on two parameters- tumor location (center vs periphery) and amount of immune infiltration observed in the H&E section (immune rich vs immune poor). ..

Mass Cytometry:

Article Title: Integrative spatial omics reveals distinct tumor-promoting multicellular niches and immunosuppressive mechanisms in Black American and White American patients with TNBC
Article Snippet: .. For each patient core (in the BSW Discovery cohort, 3 mm diameter) analyzed using imaging mass cytometry, 10X spatial transcriptomics or Nanostring Geo Mx Digital Spatial Profiling (DSP), ROIs were selected based on two parameters- tumor location (center vs periphery) and amount of immune infiltration observed in the H&E section (immune rich vs immune poor). ..

Spatial Transcriptomics:

Article Title: Integrative spatial omics reveals distinct tumor-promoting multicellular niches and immunosuppressive mechanisms in Black American and White American patients with TNBC
Article Snippet: .. For each patient core (in the BSW Discovery cohort, 3 mm diameter) analyzed using imaging mass cytometry, 10X spatial transcriptomics or Nanostring Geo Mx Digital Spatial Profiling (DSP), ROIs were selected based on two parameters- tumor location (center vs periphery) and amount of immune infiltration observed in the H&E section (immune rich vs immune poor). ..

Article Title: Uncovering the Regional and Cell Specific Bioactivity of Injectable Extracellular Matrix Biomaterials in Myocardial Infarction through Spatial and Single Nucleus Transcriptomics
Article Snippet: Half of the animal hearts per each model group were used were cut into 6 slices using a stainless-steel rat heart slicer matrix (Zivic Instruments) with 1.0 mm coronal spacing. .. Odd slices were frozen in TissueTek OCT TM and sectioned into 10 μm thick slices and placed onto a 10X Visium Spatial Transcriptomics Slide or a regular histology slide. ..

Article Title: Coevolution of neoplastic and non-neoplastic reactive astrocyte states converges on mesenchymal-like and injury-response programs during murine glioblastoma progression and post-radiotherapy recurrence
Article Snippet: .. Tumor samples intended for 10x Spatial Transcriptomics were immediately snap-frozen in isopentane on dry ice, while the remaining tissues were placed in pre-chilled PBS on ice. .. Whole brain from euthanized animals embedded in Optimal Cutting Temperature Compound (OCT) (Thermo Fisher Scientific) were snap-frozen in ice-cold isopentane.

Article Title: Molecular pathology of acute spinal cord injury in middle-aged mice
Article Snippet: .. Fig. 3 Spatial transcriptomics identifies distinct domains in and around the injury site that are similar between young and middle-aged mice. ( A ) 10X Visium spatial transcriptomic spots were clustered based on gene expression and mapped on the injury site to identify eight distinct spatial domains that were named based on a combination of marker genes, Gene Ontology terms, and spatial location. ( B ) Heatmap of top differentially expressed genes for each spatial domain. ..

Article Title: Molecular pathology of acute spinal cord injury in middle-aged mice.
Article Snippet: .. Fig. 3 Spatial transcriptomics identifies distinct domains in and around the injury site that are similar between young and middle-aged mice. (A) 10X Visium spatial transcriptomic spots were clustered based on gene expression and mapped on the injury site to identify eight distinct spatial domains that were named based on a combination of marker genes, Gene Ontology terms, and spatial location. (B) Heatmap of top differentially expressed genes for each spatial domain. ..

Article Title: Spatial and single cell mapping of castleman disease reveals key stromal cell types and cytokine pathways.
Article Snippet: .. Spatial transcriptomics analysis of a validation cohort of CD We performed 10x Xenium spatial transcriptomics analysis in a validation cohort of 13 CD cases and controls. ..

other:

Article Title: A spatial transcriptomic atlas of the host response to oropharyngeal candidiasis.
Article Snippet: Spatial transcriptomics of resolving OPC identifies four major tissue compart ments in uninfected and infected tongue To analyze the microenvironment during OPC, we employed the 10× Genomics Visium spatial transcriptomics technology on frozen tissue sections (n = 4) from tongues of normal and C. albicans-infected Balb/c mice at 60 h of OPC (hereby referred to as day 2, for ease of representation).

Article Title: Visium Spatial Transcriptomics technology pipeline from 9/10 participants at biopsy 1. Using the ChimericSeq SoftwareTM, HBV-human chimeric reads that are indicative of mRNA transcribed from integrated HBV DNA were moved forward for analysis: all non-chimeric
Article Snippet: To confirm that our 3’ HBV amplicon would exclude iDNA-derived transcripts, we identified viral junctions by performing RNA sequencing on permeabilized liver tissue through the 10x Visium Spatial Transcriptomics technology pipeline from 9/10 participants at biopsy 1.

Mouse Assay:

Article Title: Molecular pathology of acute spinal cord injury in middle-aged mice
Article Snippet: .. Fig. 3 Spatial transcriptomics identifies distinct domains in and around the injury site that are similar between young and middle-aged mice. ( A ) 10X Visium spatial transcriptomic spots were clustered based on gene expression and mapped on the injury site to identify eight distinct spatial domains that were named based on a combination of marker genes, Gene Ontology terms, and spatial location. ( B ) Heatmap of top differentially expressed genes for each spatial domain. ..

Gene Expression:

Article Title: Molecular pathology of acute spinal cord injury in middle-aged mice
Article Snippet: .. Fig. 3 Spatial transcriptomics identifies distinct domains in and around the injury site that are similar between young and middle-aged mice. ( A ) 10X Visium spatial transcriptomic spots were clustered based on gene expression and mapped on the injury site to identify eight distinct spatial domains that were named based on a combination of marker genes, Gene Ontology terms, and spatial location. ( B ) Heatmap of top differentially expressed genes for each spatial domain. ..

Article Title: Molecular pathology of acute spinal cord injury in middle-aged mice.
Article Snippet: .. Fig. 3 Spatial transcriptomics identifies distinct domains in and around the injury site that are similar between young and middle-aged mice. (A) 10X Visium spatial transcriptomic spots were clustered based on gene expression and mapped on the injury site to identify eight distinct spatial domains that were named based on a combination of marker genes, Gene Ontology terms, and spatial location. (B) Heatmap of top differentially expressed genes for each spatial domain. ..

Marker:

Article Title: Molecular pathology of acute spinal cord injury in middle-aged mice
Article Snippet: .. Fig. 3 Spatial transcriptomics identifies distinct domains in and around the injury site that are similar between young and middle-aged mice. ( A ) 10X Visium spatial transcriptomic spots were clustered based on gene expression and mapped on the injury site to identify eight distinct spatial domains that were named based on a combination of marker genes, Gene Ontology terms, and spatial location. ( B ) Heatmap of top differentially expressed genes for each spatial domain. ..

Article Title: Molecular pathology of acute spinal cord injury in middle-aged mice.
Article Snippet: .. Fig. 3 Spatial transcriptomics identifies distinct domains in and around the injury site that are similar between young and middle-aged mice. (A) 10X Visium spatial transcriptomic spots were clustered based on gene expression and mapped on the injury site to identify eight distinct spatial domains that were named based on a combination of marker genes, Gene Ontology terms, and spatial location. (B) Heatmap of top differentially expressed genes for each spatial domain. ..

Biomarker Discovery:

Article Title: Spatial and single cell mapping of castleman disease reveals key stromal cell types and cytokine pathways.
Article Snippet: .. Spatial transcriptomics analysis of a validation cohort of CD We performed 10x Xenium spatial transcriptomics analysis in a validation cohort of 13 CD cases and controls. ..



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a Schematic representation of the experimental design of this study. Livers were collected at 12, 24, or 38 h post infection (hpi) with P. berghei parasites or salivary gland lysate of uninfected mosquitoes (SGC) (left). Immunofluorescence (IF) staining of the parasite, spatial <t>transcriptomics</t> (ST) or 10X visium spatial technology protocols, and droplet-based single-nuclei RNA sequencing (snRNA-seq) were performed (center). Both data were further analyzed computationally (right). IHS stands for immune hotspot. b After dimensionality reduction, the normalized and batch-corrected data were embedded in UMAP space and split by the original condition for visualization. Data from SGC sections are shown on the top from 12 to 38 hpi (left to right) and data from P. berghei - infected sections are shown on the bottom from 12 to 38 hpi (left to right). Clusters with an obvious association to infection conditions are highlighted with gray boxes. c For identified clusters ST10 and ST11, differential gene expression analysis (DGEA) was performed, followed by functional enrichment analysis for each cluster (see Methods for details). Overrepresented pathways of the KEGG database for ST10 are shown in rose and for ST11 in aquamarine. Scales for expression values of overrepresented genes belonging to the individual KEGG pathways are shown for ST11 (left) or ST10 (right), from high expression (dark) to lower expression (light). Selected gene names are shown at the bottom. Enrichment scores for the pathways are shown on the right. d Interaction analysis of clusters was performed to evaluate spatial enrichment expression programs as suggested by clustering analysis in space. Positive enrichment values (orange) indicate spots belonging to these clusters are more likely to be neighboring, while negative enrichment values (blue) indicate spots associated with these expression programs are less likely to be neighboring. Clusters without significant enrichment in each other’s neighborhoods are shown in white. e Visium clusters were imposed on spatial positions and annotated according to spatial expression features. Sections of the investigated conditions are divided for ease of inspection as in ( b ), with the top panel comprising SGC sections across 12–38 hpi and the bottom panel comprising P. berghei infected sections across 12–38 hpi.
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a Schematic representation of the experimental design of this study. Livers were collected at 12, 24, or 38 h post infection (hpi) with P. berghei parasites or salivary gland lysate of uninfected mosquitoes (SGC) (left). Immunofluorescence (IF) staining of the parasite, spatial <t>transcriptomics</t> (ST) or 10X visium spatial technology protocols, and droplet-based single-nuclei RNA sequencing (snRNA-seq) were performed (center). Both data were further analyzed computationally (right). IHS stands for immune hotspot. b After dimensionality reduction, the normalized and batch-corrected data were embedded in UMAP space and split by the original condition for visualization. Data from SGC sections are shown on the top from 12 to 38 hpi (left to right) and data from P. berghei - infected sections are shown on the bottom from 12 to 38 hpi (left to right). Clusters with an obvious association to infection conditions are highlighted with gray boxes. c For identified clusters ST10 and ST11, differential gene expression analysis (DGEA) was performed, followed by functional enrichment analysis for each cluster (see Methods for details). Overrepresented pathways of the KEGG database for ST10 are shown in rose and for ST11 in aquamarine. Scales for expression values of overrepresented genes belonging to the individual KEGG pathways are shown for ST11 (left) or ST10 (right), from high expression (dark) to lower expression (light). Selected gene names are shown at the bottom. Enrichment scores for the pathways are shown on the right. d Interaction analysis of clusters was performed to evaluate spatial enrichment expression programs as suggested by clustering analysis in space. Positive enrichment values (orange) indicate spots belonging to these clusters are more likely to be neighboring, while negative enrichment values (blue) indicate spots associated with these expression programs are less likely to be neighboring. Clusters without significant enrichment in each other’s neighborhoods are shown in white. e Visium clusters were imposed on spatial positions and annotated according to spatial expression features. Sections of the investigated conditions are divided for ease of inspection as in ( b ), with the top panel comprising SGC sections across 12–38 hpi and the bottom panel comprising P. berghei infected sections across 12–38 hpi.
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a Schematic representation of the experimental design of this study. Livers were collected at 12, 24, or 38 h post infection (hpi) with P. berghei parasites or salivary gland lysate of uninfected mosquitoes (SGC) (left). Immunofluorescence (IF) staining of the parasite, spatial <t>transcriptomics</t> (ST) or 10X visium spatial technology protocols, and droplet-based single-nuclei RNA sequencing (snRNA-seq) were performed (center). Both data were further analyzed computationally (right). IHS stands for immune hotspot. b After dimensionality reduction, the normalized and batch-corrected data were embedded in UMAP space and split by the original condition for visualization. Data from SGC sections are shown on the top from 12 to 38 hpi (left to right) and data from P. berghei - infected sections are shown on the bottom from 12 to 38 hpi (left to right). Clusters with an obvious association to infection conditions are highlighted with gray boxes. c For identified clusters ST10 and ST11, differential gene expression analysis (DGEA) was performed, followed by functional enrichment analysis for each cluster (see Methods for details). Overrepresented pathways of the KEGG database for ST10 are shown in rose and for ST11 in aquamarine. Scales for expression values of overrepresented genes belonging to the individual KEGG pathways are shown for ST11 (left) or ST10 (right), from high expression (dark) to lower expression (light). Selected gene names are shown at the bottom. Enrichment scores for the pathways are shown on the right. d Interaction analysis of clusters was performed to evaluate spatial enrichment expression programs as suggested by clustering analysis in space. Positive enrichment values (orange) indicate spots belonging to these clusters are more likely to be neighboring, while negative enrichment values (blue) indicate spots associated with these expression programs are less likely to be neighboring. Clusters without significant enrichment in each other’s neighborhoods are shown in white. e Visium clusters were imposed on spatial positions and annotated according to spatial expression features. Sections of the investigated conditions are divided for ease of inspection as in ( b ), with the top panel comprising SGC sections across 12–38 hpi and the bottom panel comprising P. berghei infected sections across 12–38 hpi.
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a Schematic representation of the experimental design of this study. Livers were collected at 12, 24, or 38 h post infection (hpi) with P. berghei parasites or salivary gland lysate of uninfected mosquitoes (SGC) (left). Immunofluorescence (IF) staining of the parasite, spatial <t>transcriptomics</t> (ST) or 10X visium spatial technology protocols, and droplet-based single-nuclei RNA sequencing (snRNA-seq) were performed (center). Both data were further analyzed computationally (right). IHS stands for immune hotspot. b After dimensionality reduction, the normalized and batch-corrected data were embedded in UMAP space and split by the original condition for visualization. Data from SGC sections are shown on the top from 12 to 38 hpi (left to right) and data from P. berghei - infected sections are shown on the bottom from 12 to 38 hpi (left to right). Clusters with an obvious association to infection conditions are highlighted with gray boxes. c For identified clusters ST10 and ST11, differential gene expression analysis (DGEA) was performed, followed by functional enrichment analysis for each cluster (see Methods for details). Overrepresented pathways of the KEGG database for ST10 are shown in rose and for ST11 in aquamarine. Scales for expression values of overrepresented genes belonging to the individual KEGG pathways are shown for ST11 (left) or ST10 (right), from high expression (dark) to lower expression (light). Selected gene names are shown at the bottom. Enrichment scores for the pathways are shown on the right. d Interaction analysis of clusters was performed to evaluate spatial enrichment expression programs as suggested by clustering analysis in space. Positive enrichment values (orange) indicate spots belonging to these clusters are more likely to be neighboring, while negative enrichment values (blue) indicate spots associated with these expression programs are less likely to be neighboring. Clusters without significant enrichment in each other’s neighborhoods are shown in white. e Visium clusters were imposed on spatial positions and annotated according to spatial expression features. Sections of the investigated conditions are divided for ease of inspection as in ( b ), with the top panel comprising SGC sections across 12–38 hpi and the bottom panel comprising P. berghei infected sections across 12–38 hpi.
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a Schematic representation of the experimental design of this study. Livers were collected at 12, 24, or 38 h post infection (hpi) with P. berghei parasites or salivary gland lysate of uninfected mosquitoes (SGC) (left). Immunofluorescence (IF) staining of the parasite, spatial <t>transcriptomics</t> (ST) or 10X visium spatial technology protocols, and droplet-based single-nuclei RNA sequencing (snRNA-seq) were performed (center). Both data were further analyzed computationally (right). IHS stands for immune hotspot. b After dimensionality reduction, the normalized and batch-corrected data were embedded in UMAP space and split by the original condition for visualization. Data from SGC sections are shown on the top from 12 to 38 hpi (left to right) and data from P. berghei - infected sections are shown on the bottom from 12 to 38 hpi (left to right). Clusters with an obvious association to infection conditions are highlighted with gray boxes. c For identified clusters ST10 and ST11, differential gene expression analysis (DGEA) was performed, followed by functional enrichment analysis for each cluster (see Methods for details). Overrepresented pathways of the KEGG database for ST10 are shown in rose and for ST11 in aquamarine. Scales for expression values of overrepresented genes belonging to the individual KEGG pathways are shown for ST11 (left) or ST10 (right), from high expression (dark) to lower expression (light). Selected gene names are shown at the bottom. Enrichment scores for the pathways are shown on the right. d Interaction analysis of clusters was performed to evaluate spatial enrichment expression programs as suggested by clustering analysis in space. Positive enrichment values (orange) indicate spots belonging to these clusters are more likely to be neighboring, while negative enrichment values (blue) indicate spots associated with these expression programs are less likely to be neighboring. Clusters without significant enrichment in each other’s neighborhoods are shown in white. e Visium clusters were imposed on spatial positions and annotated according to spatial expression features. Sections of the investigated conditions are divided for ease of inspection as in ( b ), with the top panel comprising SGC sections across 12–38 hpi and the bottom panel comprising P. berghei infected sections across 12–38 hpi.
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Image Search Results


a Schematic representation of the experimental design of this study. Livers were collected at 12, 24, or 38 h post infection (hpi) with P. berghei parasites or salivary gland lysate of uninfected mosquitoes (SGC) (left). Immunofluorescence (IF) staining of the parasite, spatial transcriptomics (ST) or 10X visium spatial technology protocols, and droplet-based single-nuclei RNA sequencing (snRNA-seq) were performed (center). Both data were further analyzed computationally (right). IHS stands for immune hotspot. b After dimensionality reduction, the normalized and batch-corrected data were embedded in UMAP space and split by the original condition for visualization. Data from SGC sections are shown on the top from 12 to 38 hpi (left to right) and data from P. berghei - infected sections are shown on the bottom from 12 to 38 hpi (left to right). Clusters with an obvious association to infection conditions are highlighted with gray boxes. c For identified clusters ST10 and ST11, differential gene expression analysis (DGEA) was performed, followed by functional enrichment analysis for each cluster (see Methods for details). Overrepresented pathways of the KEGG database for ST10 are shown in rose and for ST11 in aquamarine. Scales for expression values of overrepresented genes belonging to the individual KEGG pathways are shown for ST11 (left) or ST10 (right), from high expression (dark) to lower expression (light). Selected gene names are shown at the bottom. Enrichment scores for the pathways are shown on the right. d Interaction analysis of clusters was performed to evaluate spatial enrichment expression programs as suggested by clustering analysis in space. Positive enrichment values (orange) indicate spots belonging to these clusters are more likely to be neighboring, while negative enrichment values (blue) indicate spots associated with these expression programs are less likely to be neighboring. Clusters without significant enrichment in each other’s neighborhoods are shown in white. e Visium clusters were imposed on spatial positions and annotated according to spatial expression features. Sections of the investigated conditions are divided for ease of inspection as in ( b ), with the top panel comprising SGC sections across 12–38 hpi and the bottom panel comprising P. berghei infected sections across 12–38 hpi.

Journal: Nature Communications

Article Title: Host-pathogen interactions in the Plasmodium -infected mouse liver at spatial and single-cell resolution

doi: 10.1038/s41467-024-51418-2

Figure Lengend Snippet: a Schematic representation of the experimental design of this study. Livers were collected at 12, 24, or 38 h post infection (hpi) with P. berghei parasites or salivary gland lysate of uninfected mosquitoes (SGC) (left). Immunofluorescence (IF) staining of the parasite, spatial transcriptomics (ST) or 10X visium spatial technology protocols, and droplet-based single-nuclei RNA sequencing (snRNA-seq) were performed (center). Both data were further analyzed computationally (right). IHS stands for immune hotspot. b After dimensionality reduction, the normalized and batch-corrected data were embedded in UMAP space and split by the original condition for visualization. Data from SGC sections are shown on the top from 12 to 38 hpi (left to right) and data from P. berghei - infected sections are shown on the bottom from 12 to 38 hpi (left to right). Clusters with an obvious association to infection conditions are highlighted with gray boxes. c For identified clusters ST10 and ST11, differential gene expression analysis (DGEA) was performed, followed by functional enrichment analysis for each cluster (see Methods for details). Overrepresented pathways of the KEGG database for ST10 are shown in rose and for ST11 in aquamarine. Scales for expression values of overrepresented genes belonging to the individual KEGG pathways are shown for ST11 (left) or ST10 (right), from high expression (dark) to lower expression (light). Selected gene names are shown at the bottom. Enrichment scores for the pathways are shown on the right. d Interaction analysis of clusters was performed to evaluate spatial enrichment expression programs as suggested by clustering analysis in space. Positive enrichment values (orange) indicate spots belonging to these clusters are more likely to be neighboring, while negative enrichment values (blue) indicate spots associated with these expression programs are less likely to be neighboring. Clusters without significant enrichment in each other’s neighborhoods are shown in white. e Visium clusters were imposed on spatial positions and annotated according to spatial expression features. Sections of the investigated conditions are divided for ease of inspection as in ( b ), with the top panel comprising SGC sections across 12–38 hpi and the bottom panel comprising P. berghei infected sections across 12–38 hpi.

Article Snippet: In this study, we use a combination of the original Spatial Transcriptomics 2K arrays , (henceforth referred to as ST) and Visium arrays (10X Genomics Inc.) .

Techniques: Infection, Immunofluorescence, Staining, RNA Sequencing, Gene Expression, Functional Assay, Expressing