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fibroblast apoptosis  (TargetMol)


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    Structured Review

    TargetMol fibroblast apoptosis
    Single‐cell RNA‐sequencing (scRNA‐seq) analysis identifies novel apoptotic‐preferential PROCR + fibroblasts in the early stage of HO. (a) The workflow depicting the collection and processing of specimens of sham and HO tendons for scRNA‐seq. (b) Dimension reduction presentation (via tSNE) of combined single‐cell transcriptome data from Achilles tendons of rats from the sham and HO groups after 1 and 3 weeks ( n = 14402). Each dot represents a single cell and is labelled with corresponding cell categories and is coloured according to its cell type identity. Clusters were generated using a resolution of 0.2 before subclustering into major cell types according to the Methods. The Seurat 3 R‐Package segregation grouped the cells into 6 distinct cell clusters. (c and d) Quantitative analysis of clusters based on the combined single‐cell transcriptome data in (b). (e) tSNE of <t>fibroblast</t> clusters (F1–F5). (f) <t>Apoptosis</t> score analyses of fibroblasts based on (e). (g) Bioinformatic analysis of PROCR + cell populations based on (e). (h) Representation analysis of GO categories showing different functions for PROCR + cells. (i) Representation analysis of KEGG categories showing different functions for PROCR + cells.
    Fibroblast Apoptosis, supplied by TargetMol, used in various techniques. Bioz Stars score: 94/100, based on 19 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/result/fibroblast apoptosis/product/TargetMol
    Average 94 stars, based on 19 article reviews
    fibroblast apoptosis - by Bioz Stars, 2026-03
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    Images

    1) Product Images from "Calcified apoptotic vesicles from PROCR + fibroblasts initiate heterotopic ossification"

    Article Title: Calcified apoptotic vesicles from PROCR + fibroblasts initiate heterotopic ossification

    Journal: Journal of Extracellular Vesicles

    doi: 10.1002/jev2.12425

    Single‐cell RNA‐sequencing (scRNA‐seq) analysis identifies novel apoptotic‐preferential PROCR + fibroblasts in the early stage of HO. (a) The workflow depicting the collection and processing of specimens of sham and HO tendons for scRNA‐seq. (b) Dimension reduction presentation (via tSNE) of combined single‐cell transcriptome data from Achilles tendons of rats from the sham and HO groups after 1 and 3 weeks ( n = 14402). Each dot represents a single cell and is labelled with corresponding cell categories and is coloured according to its cell type identity. Clusters were generated using a resolution of 0.2 before subclustering into major cell types according to the Methods. The Seurat 3 R‐Package segregation grouped the cells into 6 distinct cell clusters. (c and d) Quantitative analysis of clusters based on the combined single‐cell transcriptome data in (b). (e) tSNE of fibroblast clusters (F1–F5). (f) Apoptosis score analyses of fibroblasts based on (e). (g) Bioinformatic analysis of PROCR + cell populations based on (e). (h) Representation analysis of GO categories showing different functions for PROCR + cells. (i) Representation analysis of KEGG categories showing different functions for PROCR + cells.
    Figure Legend Snippet: Single‐cell RNA‐sequencing (scRNA‐seq) analysis identifies novel apoptotic‐preferential PROCR + fibroblasts in the early stage of HO. (a) The workflow depicting the collection and processing of specimens of sham and HO tendons for scRNA‐seq. (b) Dimension reduction presentation (via tSNE) of combined single‐cell transcriptome data from Achilles tendons of rats from the sham and HO groups after 1 and 3 weeks ( n = 14402). Each dot represents a single cell and is labelled with corresponding cell categories and is coloured according to its cell type identity. Clusters were generated using a resolution of 0.2 before subclustering into major cell types according to the Methods. The Seurat 3 R‐Package segregation grouped the cells into 6 distinct cell clusters. (c and d) Quantitative analysis of clusters based on the combined single‐cell transcriptome data in (b). (e) tSNE of fibroblast clusters (F1–F5). (f) Apoptosis score analyses of fibroblasts based on (e). (g) Bioinformatic analysis of PROCR + cell populations based on (e). (h) Representation analysis of GO categories showing different functions for PROCR + cells. (i) Representation analysis of KEGG categories showing different functions for PROCR + cells.

    Techniques Used: Single Cell, RNA Sequencing, Generated



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    Single‐cell RNA‐sequencing (scRNA‐seq) analysis identifies novel apoptotic‐preferential PROCR + fibroblasts in the early stage of HO. (a) The workflow depicting the collection and processing of specimens of sham and HO tendons for scRNA‐seq. (b) Dimension reduction presentation (via tSNE) of combined single‐cell transcriptome data from Achilles tendons of rats from the sham and HO groups after 1 and 3 weeks ( n = 14402). Each dot represents a single cell and is labelled with corresponding cell categories and is coloured according to its cell type identity. Clusters were generated using a resolution of 0.2 before subclustering into major cell types according to the Methods. The Seurat 3 R‐Package segregation grouped the cells into 6 distinct cell clusters. (c and d) Quantitative analysis of clusters based on the combined single‐cell transcriptome data in (b). (e) tSNE of <t>fibroblast</t> clusters (F1–F5). (f) <t>Apoptosis</t> score analyses of fibroblasts based on (e). (g) Bioinformatic analysis of PROCR + cell populations based on (e). (h) Representation analysis of GO categories showing different functions for PROCR + cells. (i) Representation analysis of KEGG categories showing different functions for PROCR + cells.
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    Single‐cell RNA‐sequencing (scRNA‐seq) analysis identifies novel apoptotic‐preferential PROCR + fibroblasts in the early stage of HO. (a) The workflow depicting the collection and processing of specimens of sham and HO tendons for scRNA‐seq. (b) Dimension reduction presentation (via tSNE) of combined single‐cell transcriptome data from Achilles tendons of rats from the sham and HO groups after 1 and 3 weeks ( n = 14402). Each dot represents a single cell and is labelled with corresponding cell categories and is coloured according to its cell type identity. Clusters were generated using a resolution of 0.2 before subclustering into major cell types according to the Methods. The Seurat 3 R‐Package segregation grouped the cells into 6 distinct cell clusters. (c and d) Quantitative analysis of clusters based on the combined single‐cell transcriptome data in (b). (e) tSNE of <t>fibroblast</t> clusters (F1–F5). (f) <t>Apoptosis</t> score analyses of fibroblasts based on (e). (g) Bioinformatic analysis of PROCR + cell populations based on (e). (h) Representation analysis of GO categories showing different functions for PROCR + cells. (i) Representation analysis of KEGG categories showing different functions for PROCR + cells.
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    Single‐cell RNA‐sequencing (scRNA‐seq) analysis identifies novel apoptotic‐preferential PROCR + fibroblasts in the early stage of HO. (a) The workflow depicting the collection and processing of specimens of sham and HO tendons for scRNA‐seq. (b) Dimension reduction presentation (via tSNE) of combined single‐cell transcriptome data from Achilles tendons of rats from the sham and HO groups after 1 and 3 weeks ( n = 14402). Each dot represents a single cell and is labelled with corresponding cell categories and is coloured according to its cell type identity. Clusters were generated using a resolution of 0.2 before subclustering into major cell types according to the Methods. The Seurat 3 R‐Package segregation grouped the cells into 6 distinct cell clusters. (c and d) Quantitative analysis of clusters based on the combined single‐cell transcriptome data in (b). (e) tSNE of <t>fibroblast</t> clusters (F1–F5). (f) <t>Apoptosis</t> score analyses of fibroblasts based on (e). (g) Bioinformatic analysis of PROCR + cell populations based on (e). (h) Representation analysis of GO categories showing different functions for PROCR + cells. (i) Representation analysis of KEGG categories showing different functions for PROCR + cells.
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    a Chord diagram that presents the DEGs linked via ribbons to their assigned GO terms. Color coding indicates logFC of upregulated genes (red) or downregulated genes (blue). b GO circle plot; the inner color indicates the significance of the term ( z -score), where pink represents increasing and purple represents decreasing. The outer ring displays scatterplots of the expression levels (logFC) for the genes in each GO term. c DEX-protein interaction network based on STITCH database. d FGF-2 expression in primary <t>MC3T3-E1</t> cells from control or DEX after 24 h treatment. * P < 0.05, DEX dexamethasone
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    Image Search Results


    Single‐cell RNA‐sequencing (scRNA‐seq) analysis identifies novel apoptotic‐preferential PROCR + fibroblasts in the early stage of HO. (a) The workflow depicting the collection and processing of specimens of sham and HO tendons for scRNA‐seq. (b) Dimension reduction presentation (via tSNE) of combined single‐cell transcriptome data from Achilles tendons of rats from the sham and HO groups after 1 and 3 weeks ( n = 14402). Each dot represents a single cell and is labelled with corresponding cell categories and is coloured according to its cell type identity. Clusters were generated using a resolution of 0.2 before subclustering into major cell types according to the Methods. The Seurat 3 R‐Package segregation grouped the cells into 6 distinct cell clusters. (c and d) Quantitative analysis of clusters based on the combined single‐cell transcriptome data in (b). (e) tSNE of fibroblast clusters (F1–F5). (f) Apoptosis score analyses of fibroblasts based on (e). (g) Bioinformatic analysis of PROCR + cell populations based on (e). (h) Representation analysis of GO categories showing different functions for PROCR + cells. (i) Representation analysis of KEGG categories showing different functions for PROCR + cells.

    Journal: Journal of Extracellular Vesicles

    Article Title: Calcified apoptotic vesicles from PROCR + fibroblasts initiate heterotopic ossification

    doi: 10.1002/jev2.12425

    Figure Lengend Snippet: Single‐cell RNA‐sequencing (scRNA‐seq) analysis identifies novel apoptotic‐preferential PROCR + fibroblasts in the early stage of HO. (a) The workflow depicting the collection and processing of specimens of sham and HO tendons for scRNA‐seq. (b) Dimension reduction presentation (via tSNE) of combined single‐cell transcriptome data from Achilles tendons of rats from the sham and HO groups after 1 and 3 weeks ( n = 14402). Each dot represents a single cell and is labelled with corresponding cell categories and is coloured according to its cell type identity. Clusters were generated using a resolution of 0.2 before subclustering into major cell types according to the Methods. The Seurat 3 R‐Package segregation grouped the cells into 6 distinct cell clusters. (c and d) Quantitative analysis of clusters based on the combined single‐cell transcriptome data in (b). (e) tSNE of fibroblast clusters (F1–F5). (f) Apoptosis score analyses of fibroblasts based on (e). (g) Bioinformatic analysis of PROCR + cell populations based on (e). (h) Representation analysis of GO categories showing different functions for PROCR + cells. (i) Representation analysis of KEGG categories showing different functions for PROCR + cells.

    Article Snippet: To inhibit fibroblast apoptosis in the Achilles tendon, Z‐VAD‐FMK (T7020, TargetMol) dissolved in normal saline was injected into rats at 1 μg/rat, three times a week.

    Techniques: Single Cell, RNA Sequencing, Generated

    a Chord diagram that presents the DEGs linked via ribbons to their assigned GO terms. Color coding indicates logFC of upregulated genes (red) or downregulated genes (blue). b GO circle plot; the inner color indicates the significance of the term ( z -score), where pink represents increasing and purple represents decreasing. The outer ring displays scatterplots of the expression levels (logFC) for the genes in each GO term. c DEX-protein interaction network based on STITCH database. d FGF-2 expression in primary MC3T3-E1 cells from control or DEX after 24 h treatment. * P < 0.05, DEX dexamethasone

    Journal: Journal of Orthopaedic Surgery and Research

    Article Title: Overexpression of FGF2 delays the progression of osteonecrosis of the femoral head activating the PI3K/Akt signaling pathway

    doi: 10.1186/s13018-021-02715-9

    Figure Lengend Snippet: a Chord diagram that presents the DEGs linked via ribbons to their assigned GO terms. Color coding indicates logFC of upregulated genes (red) or downregulated genes (blue). b GO circle plot; the inner color indicates the significance of the term ( z -score), where pink represents increasing and purple represents decreasing. The outer ring displays scatterplots of the expression levels (logFC) for the genes in each GO term. c DEX-protein interaction network based on STITCH database. d FGF-2 expression in primary MC3T3-E1 cells from control or DEX after 24 h treatment. * P < 0.05, DEX dexamethasone

    Article Snippet: To explore the mechanisms of FGF-2-mediated MC3T3-E1 cell apoptosis, the PI3K inhibitor LY294002 was used to pretreat cells (20 μM, MCE, Shanghai, China) for 2 h followed by stimulation with FGF-2-pcDNA3 for 12 h. The choice of inhibitor concentrations and time course was based on a previous study [ ].

    Techniques: Expressing, Control

    The apoptosis assay revealed that DEX promoted cell apoptosis in MC3T3-E1 cells. a Effects of DEX on MC3T3-E1 cell proliferation, as demonstrated by CCK-8 assay. b Protein levels of Bax, Bcl-2, Cleaved caspase-3, Caspase-3 and FGF-2 were detected by western blotting after DEX treatment. c Flow cytometry after Annexin V/PI staining and quantitative analysis of the apoptosis ratio after DEX treatment. d Apoptosis by TUNEL staining after DEX treatment (× 100 magnification); * P < 0.05, DEX dexamethasone

    Journal: Journal of Orthopaedic Surgery and Research

    Article Title: Overexpression of FGF2 delays the progression of osteonecrosis of the femoral head activating the PI3K/Akt signaling pathway

    doi: 10.1186/s13018-021-02715-9

    Figure Lengend Snippet: The apoptosis assay revealed that DEX promoted cell apoptosis in MC3T3-E1 cells. a Effects of DEX on MC3T3-E1 cell proliferation, as demonstrated by CCK-8 assay. b Protein levels of Bax, Bcl-2, Cleaved caspase-3, Caspase-3 and FGF-2 were detected by western blotting after DEX treatment. c Flow cytometry after Annexin V/PI staining and quantitative analysis of the apoptosis ratio after DEX treatment. d Apoptosis by TUNEL staining after DEX treatment (× 100 magnification); * P < 0.05, DEX dexamethasone

    Article Snippet: To explore the mechanisms of FGF-2-mediated MC3T3-E1 cell apoptosis, the PI3K inhibitor LY294002 was used to pretreat cells (20 μM, MCE, Shanghai, China) for 2 h followed by stimulation with FGF-2-pcDNA3 for 12 h. The choice of inhibitor concentrations and time course was based on a previous study [ ].

    Techniques: Apoptosis Assay, CCK-8 Assay, Western Blot, Flow Cytometry, Staining, TUNEL Assay

    The effects of FGF-2 overexpression on DEX-induced apoptosis of MC3T3-E1 cells. MC3T3-E1 cells were pretreated with an FGF-2 expression plasmid and/or PI3K inhibitor (LY294002) 12 h before DEX treatment. Flow cytometry after Annexin V/PI staining ( a ) and TUNEL (× 100 magnification, b ) analysis of apoptosis after DEX (10 −6 M, 24 h), DEX + FGF-2 pcDNA3, and DEX + FGF-2 pcDNA3 + LY294002 treatments. c Western blotting was performed to analyze the expression levels of Bax, Bcl-2, cleaved Caspase-3, Caspase-3, FGF ( c ), PI3K, p-PI3K, AKT and p-AKT ( d ) in MC3T3-E1 cells after DEX (10 −6 M, 24 h), DEX + FGF-2 pcDNA3, and DEX + FGF-2 pcDNA3 + LY294002 treatments. * P < 0.05, DEX dexamethasone

    Journal: Journal of Orthopaedic Surgery and Research

    Article Title: Overexpression of FGF2 delays the progression of osteonecrosis of the femoral head activating the PI3K/Akt signaling pathway

    doi: 10.1186/s13018-021-02715-9

    Figure Lengend Snippet: The effects of FGF-2 overexpression on DEX-induced apoptosis of MC3T3-E1 cells. MC3T3-E1 cells were pretreated with an FGF-2 expression plasmid and/or PI3K inhibitor (LY294002) 12 h before DEX treatment. Flow cytometry after Annexin V/PI staining ( a ) and TUNEL (× 100 magnification, b ) analysis of apoptosis after DEX (10 −6 M, 24 h), DEX + FGF-2 pcDNA3, and DEX + FGF-2 pcDNA3 + LY294002 treatments. c Western blotting was performed to analyze the expression levels of Bax, Bcl-2, cleaved Caspase-3, Caspase-3, FGF ( c ), PI3K, p-PI3K, AKT and p-AKT ( d ) in MC3T3-E1 cells after DEX (10 −6 M, 24 h), DEX + FGF-2 pcDNA3, and DEX + FGF-2 pcDNA3 + LY294002 treatments. * P < 0.05, DEX dexamethasone

    Article Snippet: To explore the mechanisms of FGF-2-mediated MC3T3-E1 cell apoptosis, the PI3K inhibitor LY294002 was used to pretreat cells (20 μM, MCE, Shanghai, China) for 2 h followed by stimulation with FGF-2-pcDNA3 for 12 h. The choice of inhibitor concentrations and time course was based on a previous study [ ].

    Techniques: Over Expression, Expressing, Plasmid Preparation, Flow Cytometry, Staining, TUNEL Assay, Western Blot