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human renal epithelial cells  (ATCC)


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    Structured Review

    ATCC human renal epithelial cells
    Transcriptional heterogeneity and lineage‐resolved progression in primary senescence at single‐cell level. (A) Experimental overview. Renal <t>epithelial</t> cells were irradiated (IR; 10 Gy, 10 days) to induce primary senescence, with quiescent controls (QUI; 0.01% serum, 3 days) processed for scRNA‐seq. (B) Expression levels of senescence and SASP‐related genes in senescent relative to the controls (QUI, n = 3; IR, n = 3). (C) Secreted IL‐6 levels in CM measured using ELISA (QUI, n = 6; IR, n = 6). Data are presented as the means ± the standard error of the mean (unpaired two‐tailed t ‐test; * p < 0.05, ** p < 0.01, *** p < 0.001). (D) UMAP of primary dataset showing clusters grouped into non‐senescent (C4 and C9), intermediate (C0, C1, C3, and C7), and fully senescent states (C5, C6, and C8) (left). Each bar represents either IR or QUI, and each colored segment's height indicates the fraction of one of the three senescence states within that group (middle). Stacked bar chart showing the proportions of IR and QUI cells across each cluster (right). (E) Feature plots showing expression levels of proliferation and senescence‐associated genes. (F) Heatmap of pathway activity across clusters scored via gene set variation analysis, with Z ‐score normalization. (G) UMAP trajectory analysis using Slingshot identifying three senescence progression lineages. Trajectory lines overlaid on UMAP. Cell clusters are colored by pseudotime progression. (H, I) Boxplots of normalized pathway scores for DNA repair (H) and SASP‐related gene sets (I) across clusters (Kruskal–Wallis test, with pairwise Wilcoxon rank‐sum test; adjusted p‐values as shown). (J) Enriched pathways of non‐senescent, intermediate, and fully senescent states in the primary SnCs. p‐values were calculated using a hypergeometric distribution. (K) TradeSeq‐based heatmap of temporally regulated top 500 genes along the pseudotime trajectory for lineage 3 ( p < 0.05), with representative late‐pseudotime genes highlighted.
    Human Renal Epithelial Cells, supplied by ATCC, used in various techniques. Bioz Stars score: 94/100, based on 57 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
    https://www.bioz.com/product/cortical+pcs+400+011/pmc13182272-181-0-4?v=ATCC
    Average 94 stars, based on 57 article reviews
    human renal epithelial cells - by Bioz Stars, 2026-07
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    Images

    1) Product Images from "Transcriptional Profiling at Single‐Cell Resolution Reveals Diversity and Regulatory Networks of Primary and Secondary Senescent Cells"

    Article Title: Transcriptional Profiling at Single‐Cell Resolution Reveals Diversity and Regulatory Networks of Primary and Secondary Senescent Cells

    Journal: Aging Cell

    doi: 10.1111/acel.70540

    Transcriptional heterogeneity and lineage‐resolved progression in primary senescence at single‐cell level. (A) Experimental overview. Renal epithelial cells were irradiated (IR; 10 Gy, 10 days) to induce primary senescence, with quiescent controls (QUI; 0.01% serum, 3 days) processed for scRNA‐seq. (B) Expression levels of senescence and SASP‐related genes in senescent relative to the controls (QUI, n = 3; IR, n = 3). (C) Secreted IL‐6 levels in CM measured using ELISA (QUI, n = 6; IR, n = 6). Data are presented as the means ± the standard error of the mean (unpaired two‐tailed t ‐test; * p < 0.05, ** p < 0.01, *** p < 0.001). (D) UMAP of primary dataset showing clusters grouped into non‐senescent (C4 and C9), intermediate (C0, C1, C3, and C7), and fully senescent states (C5, C6, and C8) (left). Each bar represents either IR or QUI, and each colored segment's height indicates the fraction of one of the three senescence states within that group (middle). Stacked bar chart showing the proportions of IR and QUI cells across each cluster (right). (E) Feature plots showing expression levels of proliferation and senescence‐associated genes. (F) Heatmap of pathway activity across clusters scored via gene set variation analysis, with Z ‐score normalization. (G) UMAP trajectory analysis using Slingshot identifying three senescence progression lineages. Trajectory lines overlaid on UMAP. Cell clusters are colored by pseudotime progression. (H, I) Boxplots of normalized pathway scores for DNA repair (H) and SASP‐related gene sets (I) across clusters (Kruskal–Wallis test, with pairwise Wilcoxon rank‐sum test; adjusted p‐values as shown). (J) Enriched pathways of non‐senescent, intermediate, and fully senescent states in the primary SnCs. p‐values were calculated using a hypergeometric distribution. (K) TradeSeq‐based heatmap of temporally regulated top 500 genes along the pseudotime trajectory for lineage 3 ( p < 0.05), with representative late‐pseudotime genes highlighted.
    Figure Legend Snippet: Transcriptional heterogeneity and lineage‐resolved progression in primary senescence at single‐cell level. (A) Experimental overview. Renal epithelial cells were irradiated (IR; 10 Gy, 10 days) to induce primary senescence, with quiescent controls (QUI; 0.01% serum, 3 days) processed for scRNA‐seq. (B) Expression levels of senescence and SASP‐related genes in senescent relative to the controls (QUI, n = 3; IR, n = 3). (C) Secreted IL‐6 levels in CM measured using ELISA (QUI, n = 6; IR, n = 6). Data are presented as the means ± the standard error of the mean (unpaired two‐tailed t ‐test; * p < 0.05, ** p < 0.01, *** p < 0.001). (D) UMAP of primary dataset showing clusters grouped into non‐senescent (C4 and C9), intermediate (C0, C1, C3, and C7), and fully senescent states (C5, C6, and C8) (left). Each bar represents either IR or QUI, and each colored segment's height indicates the fraction of one of the three senescence states within that group (middle). Stacked bar chart showing the proportions of IR and QUI cells across each cluster (right). (E) Feature plots showing expression levels of proliferation and senescence‐associated genes. (F) Heatmap of pathway activity across clusters scored via gene set variation analysis, with Z ‐score normalization. (G) UMAP trajectory analysis using Slingshot identifying three senescence progression lineages. Trajectory lines overlaid on UMAP. Cell clusters are colored by pseudotime progression. (H, I) Boxplots of normalized pathway scores for DNA repair (H) and SASP‐related gene sets (I) across clusters (Kruskal–Wallis test, with pairwise Wilcoxon rank‐sum test; adjusted p‐values as shown). (J) Enriched pathways of non‐senescent, intermediate, and fully senescent states in the primary SnCs. p‐values were calculated using a hypergeometric distribution. (K) TradeSeq‐based heatmap of temporally regulated top 500 genes along the pseudotime trajectory for lineage 3 ( p < 0.05), with representative late‐pseudotime genes highlighted.

    Techniques Used: Single Cell, Irradiation, Expressing, Enzyme-linked Immunosorbent Assay, Two Tailed Test, Activity Assay

    SASP‐driven secondary senescence shows distinct transcriptional states. (A) Experimental overview: Proliferative renal epithelial cells were treated with CM from quiescent cells (QCMT) or primary senescent cells (SCMT) and separately processed for scRNA‐seq. (B) qPCR validation of senescence/SASP‐associated genes and expressed as fold changes in SCMT versus QCMT (QCMT, n = 4; SCMT, n = 3). Data are presented as the mean ± standard error of the mean. * p < 0.05, ** p < 0.01, *** p < 0.001 (two‐tailed unpaired t ‐test) (C) Secreted IL‐6 levels in CM measured by ELISA (QCMT, n = 12; SCMT, n = 8). (D) UMAP of secondary SnCs showing clusters grouped into non‐senescent (C2 and C6), intermediate (C0, C1, and C4), and fully senescent clusters (C3, C5, and C7) (left). Each bar represents either QCMT or SCMT, and each colored segment's height indicates the fraction of one of the three senescence states within that group (middle). Stacked bar chart showing the proportions of QCMT and SCMT cells across each cluster (right). (E) Feature plots of representative proliferation and senescence‐associated genes across clusters. (F) Heatmap of pathway activities across clusters ( Z ‐score normalized). (G) UMAP trajectory analysis using Slingshot identifies four lineages with distinct terminal clusters, including a senescence‐resistant endpoint. Trajectory lines indicate senescence progression, and clusters are colored by pseudotime. (H, I) Boxplots of DNA repair (H) and SASP‐related gene set scores (I) across clusters (Kruskal–Wallis two‐sided test with pairwise Wilcoxon rank‐sum test; adjusted p‐values as shown). (J) Enriched pathways categorized into non‐senescent, intermediate, and fully senescent states. p‐values were calculated using a hypergeometric distribution. (K) Heatmap displaying temporally regulated the top 500 genes identified through tradeSeq along the pseudotime trajectory for lineage 4 in secondary senescence (hypergeometric distribution; p < 0.05).
    Figure Legend Snippet: SASP‐driven secondary senescence shows distinct transcriptional states. (A) Experimental overview: Proliferative renal epithelial cells were treated with CM from quiescent cells (QCMT) or primary senescent cells (SCMT) and separately processed for scRNA‐seq. (B) qPCR validation of senescence/SASP‐associated genes and expressed as fold changes in SCMT versus QCMT (QCMT, n = 4; SCMT, n = 3). Data are presented as the mean ± standard error of the mean. * p < 0.05, ** p < 0.01, *** p < 0.001 (two‐tailed unpaired t ‐test) (C) Secreted IL‐6 levels in CM measured by ELISA (QCMT, n = 12; SCMT, n = 8). (D) UMAP of secondary SnCs showing clusters grouped into non‐senescent (C2 and C6), intermediate (C0, C1, and C4), and fully senescent clusters (C3, C5, and C7) (left). Each bar represents either QCMT or SCMT, and each colored segment's height indicates the fraction of one of the three senescence states within that group (middle). Stacked bar chart showing the proportions of QCMT and SCMT cells across each cluster (right). (E) Feature plots of representative proliferation and senescence‐associated genes across clusters. (F) Heatmap of pathway activities across clusters ( Z ‐score normalized). (G) UMAP trajectory analysis using Slingshot identifies four lineages with distinct terminal clusters, including a senescence‐resistant endpoint. Trajectory lines indicate senescence progression, and clusters are colored by pseudotime. (H, I) Boxplots of DNA repair (H) and SASP‐related gene set scores (I) across clusters (Kruskal–Wallis two‐sided test with pairwise Wilcoxon rank‐sum test; adjusted p‐values as shown). (J) Enriched pathways categorized into non‐senescent, intermediate, and fully senescent states. p‐values were calculated using a hypergeometric distribution. (K) Heatmap displaying temporally regulated the top 500 genes identified through tradeSeq along the pseudotime trajectory for lineage 4 in secondary senescence (hypergeometric distribution; p < 0.05).

    Techniques Used: Biomarker Discovery, Two Tailed Test, Enzyme-linked Immunosorbent Assay



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    ATCC renal cortical epithelial cells hrce atcc
    Transcriptional heterogeneity and lineage‐resolved progression in primary senescence at single‐cell level. (A) Experimental overview. Renal <t>epithelial</t> cells were irradiated (IR; 10 Gy, 10 days) to induce primary senescence, with quiescent controls (QUI; 0.01% serum, 3 days) processed for scRNA‐seq. (B) Expression levels of senescence and SASP‐related genes in senescent relative to the controls (QUI, n = 3; IR, n = 3). (C) Secreted IL‐6 levels in CM measured using ELISA (QUI, n = 6; IR, n = 6). Data are presented as the means ± the standard error of the mean (unpaired two‐tailed t ‐test; * p < 0.05, ** p < 0.01, *** p < 0.001). (D) UMAP of primary dataset showing clusters grouped into non‐senescent (C4 and C9), intermediate (C0, C1, C3, and C7), and fully senescent states (C5, C6, and C8) (left). Each bar represents either IR or QUI, and each colored segment's height indicates the fraction of one of the three senescence states within that group (middle). Stacked bar chart showing the proportions of IR and QUI cells across each cluster (right). (E) Feature plots showing expression levels of proliferation and senescence‐associated genes. (F) Heatmap of pathway activity across clusters scored via gene set variation analysis, with Z ‐score normalization. (G) UMAP trajectory analysis using Slingshot identifying three senescence progression lineages. Trajectory lines overlaid on UMAP. Cell clusters are colored by pseudotime progression. (H, I) Boxplots of normalized pathway scores for DNA repair (H) and SASP‐related gene sets (I) across clusters (Kruskal–Wallis test, with pairwise Wilcoxon rank‐sum test; adjusted p‐values as shown). (J) Enriched pathways of non‐senescent, intermediate, and fully senescent states in the primary SnCs. p‐values were calculated using a hypergeometric distribution. (K) TradeSeq‐based heatmap of temporally regulated top 500 genes along the pseudotime trajectory for lineage 3 ( p < 0.05), with representative late‐pseudotime genes highlighted.
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    Transcriptional heterogeneity and lineage‐resolved progression in primary senescence at single‐cell level. (A) Experimental overview. Renal epithelial cells were irradiated (IR; 10 Gy, 10 days) to induce primary senescence, with quiescent controls (QUI; 0.01% serum, 3 days) processed for scRNA‐seq. (B) Expression levels of senescence and SASP‐related genes in senescent relative to the controls (QUI, n = 3; IR, n = 3). (C) Secreted IL‐6 levels in CM measured using ELISA (QUI, n = 6; IR, n = 6). Data are presented as the means ± the standard error of the mean (unpaired two‐tailed t ‐test; * p < 0.05, ** p < 0.01, *** p < 0.001). (D) UMAP of primary dataset showing clusters grouped into non‐senescent (C4 and C9), intermediate (C0, C1, C3, and C7), and fully senescent states (C5, C6, and C8) (left). Each bar represents either IR or QUI, and each colored segment's height indicates the fraction of one of the three senescence states within that group (middle). Stacked bar chart showing the proportions of IR and QUI cells across each cluster (right). (E) Feature plots showing expression levels of proliferation and senescence‐associated genes. (F) Heatmap of pathway activity across clusters scored via gene set variation analysis, with Z ‐score normalization. (G) UMAP trajectory analysis using Slingshot identifying three senescence progression lineages. Trajectory lines overlaid on UMAP. Cell clusters are colored by pseudotime progression. (H, I) Boxplots of normalized pathway scores for DNA repair (H) and SASP‐related gene sets (I) across clusters (Kruskal–Wallis test, with pairwise Wilcoxon rank‐sum test; adjusted p‐values as shown). (J) Enriched pathways of non‐senescent, intermediate, and fully senescent states in the primary SnCs. p‐values were calculated using a hypergeometric distribution. (K) TradeSeq‐based heatmap of temporally regulated top 500 genes along the pseudotime trajectory for lineage 3 ( p < 0.05), with representative late‐pseudotime genes highlighted.

    Journal: Aging Cell

    Article Title: Transcriptional Profiling at Single‐Cell Resolution Reveals Diversity and Regulatory Networks of Primary and Secondary Senescent Cells

    doi: 10.1111/acel.70540

    Figure Lengend Snippet: Transcriptional heterogeneity and lineage‐resolved progression in primary senescence at single‐cell level. (A) Experimental overview. Renal epithelial cells were irradiated (IR; 10 Gy, 10 days) to induce primary senescence, with quiescent controls (QUI; 0.01% serum, 3 days) processed for scRNA‐seq. (B) Expression levels of senescence and SASP‐related genes in senescent relative to the controls (QUI, n = 3; IR, n = 3). (C) Secreted IL‐6 levels in CM measured using ELISA (QUI, n = 6; IR, n = 6). Data are presented as the means ± the standard error of the mean (unpaired two‐tailed t ‐test; * p < 0.05, ** p < 0.01, *** p < 0.001). (D) UMAP of primary dataset showing clusters grouped into non‐senescent (C4 and C9), intermediate (C0, C1, C3, and C7), and fully senescent states (C5, C6, and C8) (left). Each bar represents either IR or QUI, and each colored segment's height indicates the fraction of one of the three senescence states within that group (middle). Stacked bar chart showing the proportions of IR and QUI cells across each cluster (right). (E) Feature plots showing expression levels of proliferation and senescence‐associated genes. (F) Heatmap of pathway activity across clusters scored via gene set variation analysis, with Z ‐score normalization. (G) UMAP trajectory analysis using Slingshot identifying three senescence progression lineages. Trajectory lines overlaid on UMAP. Cell clusters are colored by pseudotime progression. (H, I) Boxplots of normalized pathway scores for DNA repair (H) and SASP‐related gene sets (I) across clusters (Kruskal–Wallis test, with pairwise Wilcoxon rank‐sum test; adjusted p‐values as shown). (J) Enriched pathways of non‐senescent, intermediate, and fully senescent states in the primary SnCs. p‐values were calculated using a hypergeometric distribution. (K) TradeSeq‐based heatmap of temporally regulated top 500 genes along the pseudotime trajectory for lineage 3 ( p < 0.05), with representative late‐pseudotime genes highlighted.

    Article Snippet: Human renal epithelial cells (ATCC; PCS‐400‐011) were cultured in Renal Epithelial Cell Basal Medium (ATCC; PCS‐400‐030) supplemented with the Renal Epithelial Cell Growth Kit (ATCC; PCS‐400‐040), which maintains the cultures at a final serum concentration of 0.5% and incubated at 37°C in 10% CO 2 and 3% O 2 .

    Techniques: Single Cell, Irradiation, Expressing, Enzyme-linked Immunosorbent Assay, Two Tailed Test, Activity Assay

    SASP‐driven secondary senescence shows distinct transcriptional states. (A) Experimental overview: Proliferative renal epithelial cells were treated with CM from quiescent cells (QCMT) or primary senescent cells (SCMT) and separately processed for scRNA‐seq. (B) qPCR validation of senescence/SASP‐associated genes and expressed as fold changes in SCMT versus QCMT (QCMT, n = 4; SCMT, n = 3). Data are presented as the mean ± standard error of the mean. * p < 0.05, ** p < 0.01, *** p < 0.001 (two‐tailed unpaired t ‐test) (C) Secreted IL‐6 levels in CM measured by ELISA (QCMT, n = 12; SCMT, n = 8). (D) UMAP of secondary SnCs showing clusters grouped into non‐senescent (C2 and C6), intermediate (C0, C1, and C4), and fully senescent clusters (C3, C5, and C7) (left). Each bar represents either QCMT or SCMT, and each colored segment's height indicates the fraction of one of the three senescence states within that group (middle). Stacked bar chart showing the proportions of QCMT and SCMT cells across each cluster (right). (E) Feature plots of representative proliferation and senescence‐associated genes across clusters. (F) Heatmap of pathway activities across clusters ( Z ‐score normalized). (G) UMAP trajectory analysis using Slingshot identifies four lineages with distinct terminal clusters, including a senescence‐resistant endpoint. Trajectory lines indicate senescence progression, and clusters are colored by pseudotime. (H, I) Boxplots of DNA repair (H) and SASP‐related gene set scores (I) across clusters (Kruskal–Wallis two‐sided test with pairwise Wilcoxon rank‐sum test; adjusted p‐values as shown). (J) Enriched pathways categorized into non‐senescent, intermediate, and fully senescent states. p‐values were calculated using a hypergeometric distribution. (K) Heatmap displaying temporally regulated the top 500 genes identified through tradeSeq along the pseudotime trajectory for lineage 4 in secondary senescence (hypergeometric distribution; p < 0.05).

    Journal: Aging Cell

    Article Title: Transcriptional Profiling at Single‐Cell Resolution Reveals Diversity and Regulatory Networks of Primary and Secondary Senescent Cells

    doi: 10.1111/acel.70540

    Figure Lengend Snippet: SASP‐driven secondary senescence shows distinct transcriptional states. (A) Experimental overview: Proliferative renal epithelial cells were treated with CM from quiescent cells (QCMT) or primary senescent cells (SCMT) and separately processed for scRNA‐seq. (B) qPCR validation of senescence/SASP‐associated genes and expressed as fold changes in SCMT versus QCMT (QCMT, n = 4; SCMT, n = 3). Data are presented as the mean ± standard error of the mean. * p < 0.05, ** p < 0.01, *** p < 0.001 (two‐tailed unpaired t ‐test) (C) Secreted IL‐6 levels in CM measured by ELISA (QCMT, n = 12; SCMT, n = 8). (D) UMAP of secondary SnCs showing clusters grouped into non‐senescent (C2 and C6), intermediate (C0, C1, and C4), and fully senescent clusters (C3, C5, and C7) (left). Each bar represents either QCMT or SCMT, and each colored segment's height indicates the fraction of one of the three senescence states within that group (middle). Stacked bar chart showing the proportions of QCMT and SCMT cells across each cluster (right). (E) Feature plots of representative proliferation and senescence‐associated genes across clusters. (F) Heatmap of pathway activities across clusters ( Z ‐score normalized). (G) UMAP trajectory analysis using Slingshot identifies four lineages with distinct terminal clusters, including a senescence‐resistant endpoint. Trajectory lines indicate senescence progression, and clusters are colored by pseudotime. (H, I) Boxplots of DNA repair (H) and SASP‐related gene set scores (I) across clusters (Kruskal–Wallis two‐sided test with pairwise Wilcoxon rank‐sum test; adjusted p‐values as shown). (J) Enriched pathways categorized into non‐senescent, intermediate, and fully senescent states. p‐values were calculated using a hypergeometric distribution. (K) Heatmap displaying temporally regulated the top 500 genes identified through tradeSeq along the pseudotime trajectory for lineage 4 in secondary senescence (hypergeometric distribution; p < 0.05).

    Article Snippet: Human renal epithelial cells (ATCC; PCS‐400‐011) were cultured in Renal Epithelial Cell Basal Medium (ATCC; PCS‐400‐030) supplemented with the Renal Epithelial Cell Growth Kit (ATCC; PCS‐400‐040), which maintains the cultures at a final serum concentration of 0.5% and incubated at 37°C in 10% CO 2 and 3% O 2 .

    Techniques: Biomarker Discovery, Two Tailed Test, Enzyme-linked Immunosorbent Assay