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mammary epithelial cell basal media  (PromoCell)


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    PromoCell mammary epithelial cell basal media
    Mammary Epithelial Cell Basal Media, supplied by PromoCell, used in various techniques. Bioz Stars score: 94/100, based on 20 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/growth+media+supplementmix/Mammary+Epithelial+Cell+Growth+Medium+SupplementMix/pmc12822652-217-6-5
    Average 94 stars, based on 20 article reviews
    mammary epithelial cell basal media - by Bioz Stars, 2026-09
    94/100 stars

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    a) Dotplot of key marker genes and GO terms in deconvoluted (BayesSpace) fibroblast-rich spots from each niche. b) Heatmap showing alignment of fibroblast clusters from scRNAseq analysis of disaggregated synovial tissue (Zhang et al. 2023) to genes associated with fibroblast-rich spots in each niche and a module of the top 40 genes defining the C11 immune cell (IC)-interacting fibroblasts and C4 <t>endothelial</t> cell (EC)-interacting fibroblasts (Korsunsky et al. 2022). c) Representative IF image showing perivascular localisation of fibrotic marker POSTN. d) Feature plots and spatial gene expression maps demonstrating expression of the immune cell (IC)- and endothelial cell (EC)-interacting gene modules across a synovial tissue section. E) Dotplot showing expression of gene modules of IC-interacting fibroblasts and EC-interacting fibroblasts in fibroblasts from each niche. f) Correlation between Krenn histological score and expression of the IC- and EC-interacting gene program in fibroblast-rich spots. Each dot represents a sample. P value calculated using Pearsons’s correlation in ggpubr::ggscatter. g) Representative spatial gene expression maps of 5 gene modules defined by genes upregulated in human RA fibroblasts stimulated in vitro with indicated cytokines compared to non-stimulated control RA fibroblasts (Tsuchiya et al., 2021). h) Heatmap of average scaled expression of cytokine response gene modules in fibroblast-rich spots in each niche. i) Correlation between expression of cytokine response gene modules in fibroblast-rich spots and Krenn score. Each dot represents a sample. P calculated using Pearsons’s correlation in ggpubr::ggscatter.
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    a) Dotplot of key marker genes and GO terms in deconvoluted (BayesSpace) fibroblast-rich spots from each niche. b) Heatmap showing alignment of fibroblast clusters from scRNAseq analysis of disaggregated synovial tissue (Zhang et al. 2023) to genes associated with fibroblast-rich spots in each niche and a module of the top 40 genes defining the C11 immune cell (IC)-interacting fibroblasts and C4 <t>endothelial</t> cell (EC)-interacting fibroblasts (Korsunsky et al. 2022). c) Representative IF image showing perivascular localisation of fibrotic marker POSTN. d) Feature plots and spatial gene expression maps demonstrating expression of the immune cell (IC)- and endothelial cell (EC)-interacting gene modules across a synovial tissue section. E) Dotplot showing expression of gene modules of IC-interacting fibroblasts and EC-interacting fibroblasts in fibroblasts from each niche. f) Correlation between Krenn histological score and expression of the IC- and EC-interacting gene program in fibroblast-rich spots. Each dot represents a sample. P value calculated using Pearsons’s correlation in ggpubr::ggscatter. g) Representative spatial gene expression maps of 5 gene modules defined by genes upregulated in human RA fibroblasts stimulated in vitro with indicated cytokines compared to non-stimulated control RA fibroblasts (Tsuchiya et al., 2021). h) Heatmap of average scaled expression of cytokine response gene modules in fibroblast-rich spots in each niche. i) Correlation between expression of cytokine response gene modules in fibroblast-rich spots and Krenn score. Each dot represents a sample. P calculated using Pearsons’s correlation in ggpubr::ggscatter.
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    a) Dotplot of key marker genes and GO terms in deconvoluted (BayesSpace) fibroblast-rich spots from each niche. b) Heatmap showing alignment of fibroblast clusters from scRNAseq analysis of disaggregated synovial tissue (Zhang et al. 2023) to genes associated with fibroblast-rich spots in each niche and a module of the top 40 genes defining the C11 immune cell (IC)-interacting fibroblasts and C4 <t>endothelial</t> cell (EC)-interacting fibroblasts (Korsunsky et al. 2022). c) Representative IF image showing perivascular localisation of fibrotic marker POSTN. d) Feature plots and spatial gene expression maps demonstrating expression of the immune cell (IC)- and endothelial cell (EC)-interacting gene modules across a synovial tissue section. E) Dotplot showing expression of gene modules of IC-interacting fibroblasts and EC-interacting fibroblasts in fibroblasts from each niche. f) Correlation between Krenn histological score and expression of the IC- and EC-interacting gene program in fibroblast-rich spots. Each dot represents a sample. P value calculated using Pearsons’s correlation in ggpubr::ggscatter. g) Representative spatial gene expression maps of 5 gene modules defined by genes upregulated in human RA fibroblasts stimulated in vitro with indicated cytokines compared to non-stimulated control RA fibroblasts (Tsuchiya et al., 2021). h) Heatmap of average scaled expression of cytokine response gene modules in fibroblast-rich spots in each niche. i) Correlation between expression of cytokine response gene modules in fibroblast-rich spots and Krenn score. Each dot represents a sample. P calculated using Pearsons’s correlation in ggpubr::ggscatter.
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    PromoCell cell media
    a) Dotplot of key marker genes and GO terms in deconvoluted (BayesSpace) fibroblast-rich spots from each niche. b) Heatmap showing alignment of fibroblast clusters from scRNAseq analysis of disaggregated synovial tissue (Zhang et al. 2023) to genes associated with fibroblast-rich spots in each niche and a module of the top 40 genes defining the C11 immune cell (IC)-interacting fibroblasts and C4 <t>endothelial</t> cell (EC)-interacting fibroblasts (Korsunsky et al. 2022). c) Representative IF image showing perivascular localisation of fibrotic marker POSTN. d) Feature plots and spatial gene expression maps demonstrating expression of the immune cell (IC)- and endothelial cell (EC)-interacting gene modules across a synovial tissue section. E) Dotplot showing expression of gene modules of IC-interacting fibroblasts and EC-interacting fibroblasts in fibroblasts from each niche. f) Correlation between Krenn histological score and expression of the IC- and EC-interacting gene program in fibroblast-rich spots. Each dot represents a sample. P value calculated using Pearsons’s correlation in ggpubr::ggscatter. g) Representative spatial gene expression maps of 5 gene modules defined by genes upregulated in human RA fibroblasts stimulated in vitro with indicated cytokines compared to non-stimulated control RA fibroblasts (Tsuchiya et al., 2021). h) Heatmap of average scaled expression of cytokine response gene modules in fibroblast-rich spots in each niche. i) Correlation between expression of cytokine response gene modules in fibroblast-rich spots and Krenn score. Each dot represents a sample. P calculated using Pearsons’s correlation in ggpubr::ggscatter.
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    PromoCell maecs culture media
    a) Dotplot of key marker genes and GO terms in deconvoluted (BayesSpace) fibroblast-rich spots from each niche. b) Heatmap showing alignment of fibroblast clusters from scRNAseq analysis of disaggregated synovial tissue (Zhang et al. 2023) to genes associated with fibroblast-rich spots in each niche and a module of the top 40 genes defining the C11 immune cell (IC)-interacting fibroblasts and C4 <t>endothelial</t> cell (EC)-interacting fibroblasts (Korsunsky et al. 2022). c) Representative IF image showing perivascular localisation of fibrotic marker POSTN. d) Feature plots and spatial gene expression maps demonstrating expression of the immune cell (IC)- and endothelial cell (EC)-interacting gene modules across a synovial tissue section. E) Dotplot showing expression of gene modules of IC-interacting fibroblasts and EC-interacting fibroblasts in fibroblasts from each niche. f) Correlation between Krenn histological score and expression of the IC- and EC-interacting gene program in fibroblast-rich spots. Each dot represents a sample. P value calculated using Pearsons’s correlation in ggpubr::ggscatter. g) Representative spatial gene expression maps of 5 gene modules defined by genes upregulated in human RA fibroblasts stimulated in vitro with indicated cytokines compared to non-stimulated control RA fibroblasts (Tsuchiya et al., 2021). h) Heatmap of average scaled expression of cytokine response gene modules in fibroblast-rich spots in each niche. i) Correlation between expression of cytokine response gene modules in fibroblast-rich spots and Krenn score. Each dot represents a sample. P calculated using Pearsons’s correlation in ggpubr::ggscatter.
    Maecs Culture Media, supplied by PromoCell, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/growth+media+supplementmix/Endothelial+Cell+Growth+Medium+SupplementMix/pmc08994030__41598_2022_9757_MOESM1_ESM-43-13-35
    Average 96 stars, based on 1 article reviews
    maecs culture media - by Bioz Stars, 2026-09
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    Image Search Results


    a) Dotplot of key marker genes and GO terms in deconvoluted (BayesSpace) fibroblast-rich spots from each niche. b) Heatmap showing alignment of fibroblast clusters from scRNAseq analysis of disaggregated synovial tissue (Zhang et al. 2023) to genes associated with fibroblast-rich spots in each niche and a module of the top 40 genes defining the C11 immune cell (IC)-interacting fibroblasts and C4 endothelial cell (EC)-interacting fibroblasts (Korsunsky et al. 2022). c) Representative IF image showing perivascular localisation of fibrotic marker POSTN. d) Feature plots and spatial gene expression maps demonstrating expression of the immune cell (IC)- and endothelial cell (EC)-interacting gene modules across a synovial tissue section. E) Dotplot showing expression of gene modules of IC-interacting fibroblasts and EC-interacting fibroblasts in fibroblasts from each niche. f) Correlation between Krenn histological score and expression of the IC- and EC-interacting gene program in fibroblast-rich spots. Each dot represents a sample. P value calculated using Pearsons’s correlation in ggpubr::ggscatter. g) Representative spatial gene expression maps of 5 gene modules defined by genes upregulated in human RA fibroblasts stimulated in vitro with indicated cytokines compared to non-stimulated control RA fibroblasts (Tsuchiya et al., 2021). h) Heatmap of average scaled expression of cytokine response gene modules in fibroblast-rich spots in each niche. i) Correlation between expression of cytokine response gene modules in fibroblast-rich spots and Krenn score. Each dot represents a sample. P calculated using Pearsons’s correlation in ggpubr::ggscatter.

    Journal: bioRxiv

    Article Title: Spatial programming of fibroblasts promotes resolution of tissue inflammation through immune cell exclusion

    doi: 10.1101/2024.09.20.614064

    Figure Lengend Snippet: a) Dotplot of key marker genes and GO terms in deconvoluted (BayesSpace) fibroblast-rich spots from each niche. b) Heatmap showing alignment of fibroblast clusters from scRNAseq analysis of disaggregated synovial tissue (Zhang et al. 2023) to genes associated with fibroblast-rich spots in each niche and a module of the top 40 genes defining the C11 immune cell (IC)-interacting fibroblasts and C4 endothelial cell (EC)-interacting fibroblasts (Korsunsky et al. 2022). c) Representative IF image showing perivascular localisation of fibrotic marker POSTN. d) Feature plots and spatial gene expression maps demonstrating expression of the immune cell (IC)- and endothelial cell (EC)-interacting gene modules across a synovial tissue section. E) Dotplot showing expression of gene modules of IC-interacting fibroblasts and EC-interacting fibroblasts in fibroblasts from each niche. f) Correlation between Krenn histological score and expression of the IC- and EC-interacting gene program in fibroblast-rich spots. Each dot represents a sample. P value calculated using Pearsons’s correlation in ggpubr::ggscatter. g) Representative spatial gene expression maps of 5 gene modules defined by genes upregulated in human RA fibroblasts stimulated in vitro with indicated cytokines compared to non-stimulated control RA fibroblasts (Tsuchiya et al., 2021). h) Heatmap of average scaled expression of cytokine response gene modules in fibroblast-rich spots in each niche. i) Correlation between expression of cytokine response gene modules in fibroblast-rich spots and Krenn score. Each dot represents a sample. P calculated using Pearsons’s correlation in ggpubr::ggscatter.

    Article Snippet: The apical and basal surfaces of transwell filters were coated with 50 μl of Collagen Type I (50 μg/mL; CC050, Sigma-Aldrich), 50 μl of Collagen Type IV (50 μg/mL; C6745-1ml, Sigma-Aldrich) and 50 μl of Collagen Type VI (50 μg/mL; 009-001-108, Rockland) and equilibrated with Endothelial Cell Growth media (C-39210, PromoCell) for 24 hours at 37 °C.

    Techniques: Marker, Gene Expression, Expressing, In Vitro, Control

    a) Representative immunofluorescence images of areas around vasculature (around n=6 CD31+ vessels from a single sample) with low or high immune infiltration in synovial tissue. Scale bar: 50 µm. b) Quantification of immunofluorescence staining intensity of immune and collagen markers. N=6 for high/low-immune perivascular, measured from the same sample. ns, p>0.05; ****, p < 0.0001 (determined by Two-Way ANOVA with Tukey’s HSD Post Hoc tests). Data is mean ± standard deviation. c) Annotation of cell types based on marker gene expression in multiplex IF staining (Leica Cell DIVE) of synovial tissue. Scale bar: 100 µm. d) Heatmap showing proximity analysis of annotated cell types in multiplex IF. e) Schematic overview of transwell migration experiment. f) Quantification of transmigrated cells from flow cytometry analysis. N=4 for each condition, across different donors. **, p<0.01; *, p<0.05 (determined by Brown-Forsythe ONE-way ANOVA test with Dunnett’s T3 multiple comparisons test). Data is mean ± SEM. g) Representative multiplex immunofluorescence image of synovial tissue analysed using GeoMx® Digital Spatial Profiler (NanoString) showing masks applied to exclude CD45+ cells and select CD90+ fibroblasts to facilitate of collection of transcripts from fibroblasts in regions of interest. Scale bars: 50 µm. Detection of CD45+ cells (red) within 30µm of the endothelial and non-endothelial cells are in circled in grey (I). Detection of CD90+ fibroblasts area selected for RNA probe assessment (greyed area) (II). h) Heatmap of expression of indicated genes across regions of interests, showing difference in fibroblast gene expression from areas of high collagen versus low collagen expression. N=18 collagen high regions and n=19 collagen low regions from seven donors. i) Correlation between expression of selected genes and number of CD45+ cells x10 /µm within each region of interest of synovial tissue samples. P value calculated using Pearson’s correlation in ggpubr.

    Journal: bioRxiv

    Article Title: Spatial programming of fibroblasts promotes resolution of tissue inflammation through immune cell exclusion

    doi: 10.1101/2024.09.20.614064

    Figure Lengend Snippet: a) Representative immunofluorescence images of areas around vasculature (around n=6 CD31+ vessels from a single sample) with low or high immune infiltration in synovial tissue. Scale bar: 50 µm. b) Quantification of immunofluorescence staining intensity of immune and collagen markers. N=6 for high/low-immune perivascular, measured from the same sample. ns, p>0.05; ****, p < 0.0001 (determined by Two-Way ANOVA with Tukey’s HSD Post Hoc tests). Data is mean ± standard deviation. c) Annotation of cell types based on marker gene expression in multiplex IF staining (Leica Cell DIVE) of synovial tissue. Scale bar: 100 µm. d) Heatmap showing proximity analysis of annotated cell types in multiplex IF. e) Schematic overview of transwell migration experiment. f) Quantification of transmigrated cells from flow cytometry analysis. N=4 for each condition, across different donors. **, p<0.01; *, p<0.05 (determined by Brown-Forsythe ONE-way ANOVA test with Dunnett’s T3 multiple comparisons test). Data is mean ± SEM. g) Representative multiplex immunofluorescence image of synovial tissue analysed using GeoMx® Digital Spatial Profiler (NanoString) showing masks applied to exclude CD45+ cells and select CD90+ fibroblasts to facilitate of collection of transcripts from fibroblasts in regions of interest. Scale bars: 50 µm. Detection of CD45+ cells (red) within 30µm of the endothelial and non-endothelial cells are in circled in grey (I). Detection of CD90+ fibroblasts area selected for RNA probe assessment (greyed area) (II). h) Heatmap of expression of indicated genes across regions of interests, showing difference in fibroblast gene expression from areas of high collagen versus low collagen expression. N=18 collagen high regions and n=19 collagen low regions from seven donors. i) Correlation between expression of selected genes and number of CD45+ cells x10 /µm within each region of interest of synovial tissue samples. P value calculated using Pearson’s correlation in ggpubr.

    Article Snippet: The apical and basal surfaces of transwell filters were coated with 50 μl of Collagen Type I (50 μg/mL; CC050, Sigma-Aldrich), 50 μl of Collagen Type IV (50 μg/mL; C6745-1ml, Sigma-Aldrich) and 50 μl of Collagen Type VI (50 μg/mL; 009-001-108, Rockland) and equilibrated with Endothelial Cell Growth media (C-39210, PromoCell) for 24 hours at 37 °C.

    Techniques: Immunofluorescence, Staining, Standard Deviation, Marker, Gene Expression, Multiplex Assay, Migration, Flow Cytometry, Expressing

    a) Distance analysis showing expression of TGF-β fibroblast response module genes from vasculature towards the lining layer. b) Dotplot showing expression of TGF-β response module and fibrotic fibroblast marker genes in synovial organoid data from Wei et al., 2020. c) Dotplot showing expression of selected collagens in organoid data from Wei et al., 2020 (Fibroblast only: organoid containing fibroblasts only; Fibroblasts+EC: organoids containing fibroblasts and ECs; Fibroblasts+EC+DAPT: organoids containing fibroblasts and ECs treated with a NOTCH inhibitor). d) Immunofluorescence images (I) Scale bars: 20µm, (II) Scale bars: 200µm and e) quantification of POSTN, Col VI or Col I staining in organoids containing fibroblasts only or fibroblasts and ECs, either “close” or “far” in respect to ECs. N=3 for each condition. **, p<0.001; NS, p>0.05, as determined by Kruskal-Wallis test with Dunn’s post-hoc test. EC, endothelial cell.

    Journal: bioRxiv

    Article Title: Spatial programming of fibroblasts promotes resolution of tissue inflammation through immune cell exclusion

    doi: 10.1101/2024.09.20.614064

    Figure Lengend Snippet: a) Distance analysis showing expression of TGF-β fibroblast response module genes from vasculature towards the lining layer. b) Dotplot showing expression of TGF-β response module and fibrotic fibroblast marker genes in synovial organoid data from Wei et al., 2020. c) Dotplot showing expression of selected collagens in organoid data from Wei et al., 2020 (Fibroblast only: organoid containing fibroblasts only; Fibroblasts+EC: organoids containing fibroblasts and ECs; Fibroblasts+EC+DAPT: organoids containing fibroblasts and ECs treated with a NOTCH inhibitor). d) Immunofluorescence images (I) Scale bars: 20µm, (II) Scale bars: 200µm and e) quantification of POSTN, Col VI or Col I staining in organoids containing fibroblasts only or fibroblasts and ECs, either “close” or “far” in respect to ECs. N=3 for each condition. **, p<0.001; NS, p>0.05, as determined by Kruskal-Wallis test with Dunn’s post-hoc test. EC, endothelial cell.

    Article Snippet: The apical and basal surfaces of transwell filters were coated with 50 μl of Collagen Type I (50 μg/mL; CC050, Sigma-Aldrich), 50 μl of Collagen Type IV (50 μg/mL; C6745-1ml, Sigma-Aldrich) and 50 μl of Collagen Type VI (50 μg/mL; 009-001-108, Rockland) and equilibrated with Endothelial Cell Growth media (C-39210, PromoCell) for 24 hours at 37 °C.

    Techniques: Expressing, Marker, Immunofluorescence, Staining