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The transition from proliferation to senescence is graded at both the population and the single-cell level (A) Population doubling curve for <t>Hs68</t> fibroblasts. Highlighted points indicate PD 13, 25, and 32 used in subsequent sections. (B) Schematic representation of CDK2 activity sensor. The sensor localizes to the nucleus when CDK2 is off in both quiescence and senescence; phosphorylation by CDK2 marks cell-cycle commitment and leads to translocation of the sensor to the cytoplasm. NLS, nuclear localization signal; NES, nuclear export signal; S, CDK consensus phosphorylation sites on serine. (C) Heatmaps of single-cell CDK2 activity traces for Hs68 fibroblasts. Each row represents the CDK2 activity in a single cell over time according to the color map (blue, quiescent or senescent; yellow, cycling). C/N, cytoplasmic/nuclear signal intensity. (D) Stacked bar chart quantifying the number of mitoses per cell lineage during the live-cell movie from (C). (E) 130 single-cell traces of CDK2 activity from (C) computationally aligned to the time of anaphase for Hs68 plotted for each replicative age. Traces were colored blue if CDK2 activity remained CDK2 low (C/N below 0.8) for 10+ hours following anaphase. (F) Left; cumulative distribution function (CDF) quantifying the total number of hours spent CDK2 low per cell during the live-cell movie (C). Middle; violin plots showing cumulative CDK2 low time per cell from (C). Right; violin plots showing the longest continuous CDK2 low period per cell track from (C). Cells that never raised their CDK2 activity above 0.8 during the experiment are not shown. (G) PD 13 cells from (C) were split into fast cycling (<40 cumulative hours CDK2 low ), slow cycling (50–70 h), or non-cycling (72+ h) (N.C.) categories. Each image shows senescence biomarker staining in one cell. Cyto area was measured by staining with succinimidyl ester. Scale bars represent 26 μm. (H) Violin plots showing the distributions of senescence marker intensity staining in PD 13 cells for each cycling speed described in (G). px, pixels. (I) Cells from (H) were grouped based on cumulative CDK2 low time and intensities for each individual senescence marker were normalized internally and averaged for each group to illustrate the graded manner in which senescence biomarker signals decrease (Lamin B1 and Hoechst standard deviation) or increase with CDK2 low time. (J) ROC analysis showing the capacity of senescence markers to predict/identify cells withdrawn from the cell cycle for more than 60 h in PD 13 cells. AUC, area under curve. (K) In a “binary” model (left), a single cell will maintain high levels of proliferative activity during cellular aging as it approaches senescence, at which point it ceases to proliferate. In our “gradual induction” model (right), senescence induction takes place over the entirety of the replicative aging process where proliferative activity in a single cell declines slowly as senescence biomarkers and tumor-suppressive activity slowly change. Proliferative activity over the course of a 72 h live-cell movie indicates a cell’s proximity to senescence. Information on replicates is provided in data .

Hs68, supplied by ATCC, used in various techniques. Bioz Stars score: 95/100, based on 136 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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1) Product Images from "Replicative senescence induction in single cells is not predicted by telomere length, dysfunction, or oxidation"

Article Title: Replicative senescence induction in single cells is not predicted by telomere length, dysfunction, or oxidation

Journal: iScience

doi: 10.1016/j.isci.2026.114801

The transition from proliferation to senescence is graded at both the population and the single-cell level (A) Population doubling curve for Hs68 fibroblasts. Highlighted points indicate PD 13, 25, and 32 used in subsequent sections. (B) Schematic representation of CDK2 activity sensor. The sensor localizes to the nucleus when CDK2 is off in both quiescence and senescence; phosphorylation by CDK2 marks cell-cycle commitment and leads to translocation of the sensor to the cytoplasm. NLS, nuclear localization signal; NES, nuclear export signal; S, CDK consensus phosphorylation sites on serine. (C) Heatmaps of single-cell CDK2 activity traces for Hs68 fibroblasts. Each row represents the CDK2 activity in a single cell over time according to the color map (blue, quiescent or senescent; yellow, cycling). C/N, cytoplasmic/nuclear signal intensity. (D) Stacked bar chart quantifying the number of mitoses per cell lineage during the live-cell movie from (C). (E) 130 single-cell traces of CDK2 activity from (C) computationally aligned to the time of anaphase for Hs68 plotted for each replicative age. Traces were colored blue if CDK2 activity remained CDK2 low (C/N below 0.8) for 10+ hours following anaphase. (F) Left; cumulative distribution function (CDF) quantifying the total number of hours spent CDK2 low per cell during the live-cell movie (C). Middle; violin plots showing cumulative CDK2 low time per cell from (C). Right; violin plots showing the longest continuous CDK2 low period per cell track from (C). Cells that never raised their CDK2 activity above 0.8 during the experiment are not shown. (G) PD 13 cells from (C) were split into fast cycling (<40 cumulative hours CDK2 low ), slow cycling (50–70 h), or non-cycling (72+ h) (N.C.) categories. Each image shows senescence biomarker staining in one cell. Cyto area was measured by staining with succinimidyl ester. Scale bars represent 26 μm. (H) Violin plots showing the distributions of senescence marker intensity staining in PD 13 cells for each cycling speed described in (G). px, pixels. (I) Cells from (H) were grouped based on cumulative CDK2 low time and intensities for each individual senescence marker were normalized internally and averaged for each group to illustrate the graded manner in which senescence biomarker signals decrease (Lamin B1 and Hoechst standard deviation) or increase with CDK2 low time. (J) ROC analysis showing the capacity of senescence markers to predict/identify cells withdrawn from the cell cycle for more than 60 h in PD 13 cells. AUC, area under curve. (K) In a “binary” model (left), a single cell will maintain high levels of proliferative activity during cellular aging as it approaches senescence, at which point it ceases to proliferate. In our “gradual induction” model (right), senescence induction takes place over the entirety of the replicative aging process where proliferative activity in a single cell declines slowly as senescence biomarkers and tumor-suppressive activity slowly change. Proliferative activity over the course of a 72 h live-cell movie indicates a cell’s proximity to senescence. Information on replicates is provided in data .

Figure Legend Snippet: The transition from proliferation to senescence is graded at both the population and the single-cell level (A) Population doubling curve for Hs68 fibroblasts. Highlighted points indicate PD 13, 25, and 32 used in subsequent sections. (B) Schematic representation of CDK2 activity sensor. The sensor localizes to the nucleus when CDK2 is off in both quiescence and senescence; phosphorylation by CDK2 marks cell-cycle commitment and leads to translocation of the sensor to the cytoplasm. NLS, nuclear localization signal; NES, nuclear export signal; S, CDK consensus phosphorylation sites on serine. (C) Heatmaps of single-cell CDK2 activity traces for Hs68 fibroblasts. Each row represents the CDK2 activity in a single cell over time according to the color map (blue, quiescent or senescent; yellow, cycling). C/N, cytoplasmic/nuclear signal intensity. (D) Stacked bar chart quantifying the number of mitoses per cell lineage during the live-cell movie from (C). (E) 130 single-cell traces of CDK2 activity from (C) computationally aligned to the time of anaphase for Hs68 plotted for each replicative age. Traces were colored blue if CDK2 activity remained CDK2 low (C/N below 0.8) for 10+ hours following anaphase. (F) Left; cumulative distribution function (CDF) quantifying the total number of hours spent CDK2 low per cell during the live-cell movie (C). Middle; violin plots showing cumulative CDK2 low time per cell from (C). Right; violin plots showing the longest continuous CDK2 low period per cell track from (C). Cells that never raised their CDK2 activity above 0.8 during the experiment are not shown. (G) PD 13 cells from (C) were split into fast cycling (<40 cumulative hours CDK2 low ), slow cycling (50–70 h), or non-cycling (72+ h) (N.C.) categories. Each image shows senescence biomarker staining in one cell. Cyto area was measured by staining with succinimidyl ester. Scale bars represent 26 μm. (H) Violin plots showing the distributions of senescence marker intensity staining in PD 13 cells for each cycling speed described in (G). px, pixels. (I) Cells from (H) were grouped based on cumulative CDK2 low time and intensities for each individual senescence marker were normalized internally and averaged for each group to illustrate the graded manner in which senescence biomarker signals decrease (Lamin B1 and Hoechst standard deviation) or increase with CDK2 low time. (J) ROC analysis showing the capacity of senescence markers to predict/identify cells withdrawn from the cell cycle for more than 60 h in PD 13 cells. AUC, area under curve. (K) In a “binary” model (left), a single cell will maintain high levels of proliferative activity during cellular aging as it approaches senescence, at which point it ceases to proliferate. In our “gradual induction” model (right), senescence induction takes place over the entirety of the replicative aging process where proliferative activity in a single cell declines slowly as senescence biomarkers and tumor-suppressive activity slowly change. Proliferative activity over the course of a 72 h live-cell movie indicates a cell’s proximity to senescence. Information on replicates is provided in data .

Techniques Used: Single Cell, Activity Assay, Phospho-proteomics, Translocation Assay, Biomarker Discovery, Staining, Marker, Standard Deviation

Q-FISH-based telomere length quantification cannot predict senescence proximity in single cells (A) Top, top-down view of a 3D projection image of a nucleus of a single Hs68 PD 13 cell with telomere Q-FISH staining. Middle, visual representation of computational segmentation of individual telomeres and quantification of integrated fluorescence intensity (IFI) per telomere. Bottom, IFI distribution for the above cell. Black circle marks the median. (B) Histograms showing distributions of telomere length metrics for 2,327 Hs68 PD 13 cells. Note that Confocal images of Hs68 PD 13 cells shown here were captured using a Nikon AXR with tunable photomultiplier tube detectors, whereas Hs68 PD 33 and AG16359 cells ( A) were captured separately using a Nikon NSPARC with single pixel photon counter detector arrays. Thus, the data from the two microscopes cannot be directly compared. (C) Boxplots showing the relative telomere length distributions for cells from (B). Cells are ordered according to the cumulative time spent CDK2 low during the time-lapse imaging experiment, indicated by the color map. N.C., non-cycling cells. (D) Violin plots showing the distributions of telomere length metrics in PD 13 cells for each cycling speed described in G. (E) Scatterplots showing the correlation between telomere length metrics and cumulative CDK2 low time in PD 13 cells with linear regression analysis in red. Overlaid contours are colored by data point density. (F) ROC analysis using telomere length distribution features to predict/identify cells withdrawn from the cell cycle for longer than 60 h for Hs68 PD 13 cells. AUC, area under curve. (G) ROC analysis using telomere length distribution features to predict/identify cells withdrawn from the cell-cycle for 72 h for Hs68 PD 33 cells.

Figure Legend Snippet: Q-FISH-based telomere length quantification cannot predict senescence proximity in single cells (A) Top, top-down view of a 3D projection image of a nucleus of a single Hs68 PD 13 cell with telomere Q-FISH staining. Middle, visual representation of computational segmentation of individual telomeres and quantification of integrated fluorescence intensity (IFI) per telomere. Bottom, IFI distribution for the above cell. Black circle marks the median. (B) Histograms showing distributions of telomere length metrics for 2,327 Hs68 PD 13 cells. Note that Confocal images of Hs68 PD 13 cells shown here were captured using a Nikon AXR with tunable photomultiplier tube detectors, whereas Hs68 PD 33 and AG16359 cells ( A) were captured separately using a Nikon NSPARC with single pixel photon counter detector arrays. Thus, the data from the two microscopes cannot be directly compared. (C) Boxplots showing the relative telomere length distributions for cells from (B). Cells are ordered according to the cumulative time spent CDK2 low during the time-lapse imaging experiment, indicated by the color map. N.C., non-cycling cells. (D) Violin plots showing the distributions of telomere length metrics in PD 13 cells for each cycling speed described in G. (E) Scatterplots showing the correlation between telomere length metrics and cumulative CDK2 low time in PD 13 cells with linear regression analysis in red. Overlaid contours are colored by data point density. (F) ROC analysis using telomere length distribution features to predict/identify cells withdrawn from the cell cycle for longer than 60 h for Hs68 PD 13 cells. AUC, area under curve. (G) ROC analysis using telomere length distribution features to predict/identify cells withdrawn from the cell-cycle for 72 h for Hs68 PD 33 cells.

Techniques Used: Staining, Fluorescence, Imaging

Proximity to replicative senescence is weakly correlated with telomere-associated DDR foci (A) Split violin plots showing the number of telomeric and non-telomeric 53BP1 foci detected in Hs68 cells at PD 13 and PD 33. (B and C) Left, violin plots showing cumulative time spent CDK2 low during the live-cell movie in groups based on the number of 53BP1 foci per cell (C) or the number of telomeric 53BP1 foci per cell (D) in Hs68 PD 13 cells. Right, cells were binned based on cumulative CDK2 low time. Error bars represent the 95% confidence interval for the mean. (D) Left, top-down view of a 3D projection image of a nucleus of a single Hs68 cell with 53BP1 immunofluorescence staining and telomere Q-FISH. Computationally detected telomeric foci are numbered in blue and non-telomeric foci are numbered in yellow. Scale bars represent 5 μm. Middle, close-up 3D view of each computationally segmented 53BP1 focus. Blue arrows indicate colocalized telomeres. Right, split violin plots showing the intensity sums of all colocalized vs. not colocalized 53BP1 foci from all cells. Confocal images of Hs68 PD 13 cells were captured using a Nikon AXR with tunable photomultiplier tube detectors, and Hs68 PD 33 and AG16359 cells were captured separately using a Nikon NSPARC with single pixel photon counter detector arrays. (E) Cells were grouped based on cumulative CDK2 low time and segmented 53BP1 foci intensities per cell were summed. (F) Same as (B and C) but using telomeric 53BP1 intensity sums rather than the number of 53BP1 foci. (G) ROC analysis using segmented 53BP1 foci intensity sums per cell to predict/identify cells withdrawn from the cell cycle for more than 60 h (for Hs68 PD 13 and AG16359 cells) or for 72 h (for Hs68 PD 33 cells). A.U.C., area under curve. (H) ROC analysis using nuclear mean 53BP1 intensity per cell to predict/identify cells withdrawn from the cell cycle for more than 60 h (for Hs68 PD 13 and AG16359 cells) or for 72 h (for Hs68 PD 33 cells). This experiment used confocal imaging with at 100X magnification and a 12-bit sensor, whereas J used 10X magnification with a 2×2 bin and a 16-bit sensor, hence the difference in AUC between the two figures. AUC, area under curve.

Figure Legend Snippet: Proximity to replicative senescence is weakly correlated with telomere-associated DDR foci (A) Split violin plots showing the number of telomeric and non-telomeric 53BP1 foci detected in Hs68 cells at PD 13 and PD 33. (B and C) Left, violin plots showing cumulative time spent CDK2 low during the live-cell movie in groups based on the number of 53BP1 foci per cell (C) or the number of telomeric 53BP1 foci per cell (D) in Hs68 PD 13 cells. Right, cells were binned based on cumulative CDK2 low time. Error bars represent the 95% confidence interval for the mean. (D) Left, top-down view of a 3D projection image of a nucleus of a single Hs68 cell with 53BP1 immunofluorescence staining and telomere Q-FISH. Computationally detected telomeric foci are numbered in blue and non-telomeric foci are numbered in yellow. Scale bars represent 5 μm. Middle, close-up 3D view of each computationally segmented 53BP1 focus. Blue arrows indicate colocalized telomeres. Right, split violin plots showing the intensity sums of all colocalized vs. not colocalized 53BP1 foci from all cells. Confocal images of Hs68 PD 13 cells were captured using a Nikon AXR with tunable photomultiplier tube detectors, and Hs68 PD 33 and AG16359 cells were captured separately using a Nikon NSPARC with single pixel photon counter detector arrays. (E) Cells were grouped based on cumulative CDK2 low time and segmented 53BP1 foci intensities per cell were summed. (F) Same as (B and C) but using telomeric 53BP1 intensity sums rather than the number of 53BP1 foci. (G) ROC analysis using segmented 53BP1 foci intensity sums per cell to predict/identify cells withdrawn from the cell cycle for more than 60 h (for Hs68 PD 13 and AG16359 cells) or for 72 h (for Hs68 PD 33 cells). A.U.C., area under curve. (H) ROC analysis using nuclear mean 53BP1 intensity per cell to predict/identify cells withdrawn from the cell cycle for more than 60 h (for Hs68 PD 13 and AG16359 cells) or for 72 h (for Hs68 PD 33 cells). This experiment used confocal imaging with at 100X magnification and a 12-bit sensor, whereas J used 10X magnification with a 2×2 bin and a 16-bit sensor, hence the difference in AUC between the two figures. AUC, area under curve.

Techniques Used: Immunofluorescence, Staining, Imaging

Telomeric oxidative DNA damage does not increase with cellular aging or senescence (A) Schematic of cell-cycle withdrawal-dependent loss of Ki67 intensity over time. (B) Left, histogram of median Ki67 nuclear intensity in untreated Hs68 PD 28 cells with quintile positions. Middle, multiplexing of Ki67 and 8oxoG immunofluorescence in untreated Hs68 PD 28 cells. Orange arrow indicates a Ki67 high cell (>90 th percentile Ki67 nuclear median), white arrow indicates a Ki67 off cell (<10 th percentile Ki67 nuclear median). Scale bars represent 25 μm. Right, violin plots showing 8oxoG intensity across Ki67 quintiles in PD 28 cells. (C) Population doubling curve for Hs68 with PD 0, 18, 28, 31, and 33 highlighted in blue. (D) Split violins showing the mean 8oxoG intensity in the highlighted ages in (C). (E) Left, top-down view of a 3D projection image of a nucleus of a single Hs68 cell with 8oxoG immunofluorescence and telomere Q-FISH. Right, cartoon depicting 8oxoG centroid-based colocalization quantification strategy. (F) Split violins showing the number of telomeres per cell that colocalize with at least one 8oxoG lesion. (G) Mean fluorescence intensity in the 8oxoG channel within the segmented telomere objects classified as colocalized with at least one 8oxoG lesion. (H) Analyses from (D–G) using Ki67 off cells acquired from the Baltimore Longitudinal Study on Aging repository.

Figure Legend Snippet: Telomeric oxidative DNA damage does not increase with cellular aging or senescence (A) Schematic of cell-cycle withdrawal-dependent loss of Ki67 intensity over time. (B) Left, histogram of median Ki67 nuclear intensity in untreated Hs68 PD 28 cells with quintile positions. Middle, multiplexing of Ki67 and 8oxoG immunofluorescence in untreated Hs68 PD 28 cells. Orange arrow indicates a Ki67 high cell (>90 th percentile Ki67 nuclear median), white arrow indicates a Ki67 off cell (<10 th percentile Ki67 nuclear median). Scale bars represent 25 μm. Right, violin plots showing 8oxoG intensity across Ki67 quintiles in PD 28 cells. (C) Population doubling curve for Hs68 with PD 0, 18, 28, 31, and 33 highlighted in blue. (D) Split violins showing the mean 8oxoG intensity in the highlighted ages in (C). (E) Left, top-down view of a 3D projection image of a nucleus of a single Hs68 cell with 8oxoG immunofluorescence and telomere Q-FISH. Right, cartoon depicting 8oxoG centroid-based colocalization quantification strategy. (F) Split violins showing the number of telomeres per cell that colocalize with at least one 8oxoG lesion. (G) Mean fluorescence intensity in the 8oxoG channel within the segmented telomere objects classified as colocalized with at least one 8oxoG lesion. (H) Analyses from (D–G) using Ki67 off cells acquired from the Baltimore Longitudinal Study on Aging repository.

Techniques Used: Multiplexing, Immunofluorescence, Fluorescence

Image Search Results

Journal: iScience

Article Title: Replicative senescence induction in single cells is not predicted by telomere length, dysfunction, or oxidation

doi: 10.1016/j.isci.2026.114801

Figure Lengend Snippet: The transition from proliferation to senescence is graded at both the population and the single-cell level (A) Population doubling curve for Hs68 fibroblasts. Highlighted points indicate PD 13, 25, and 32 used in subsequent sections. (B) Schematic representation of CDK2 activity sensor. The sensor localizes to the nucleus when CDK2 is off in both quiescence and senescence; phosphorylation by CDK2 marks cell-cycle commitment and leads to translocation of the sensor to the cytoplasm. NLS, nuclear localization signal; NES, nuclear export signal; S, CDK consensus phosphorylation sites on serine. (C) Heatmaps of single-cell CDK2 activity traces for Hs68 fibroblasts. Each row represents the CDK2 activity in a single cell over time according to the color map (blue, quiescent or senescent; yellow, cycling). C/N, cytoplasmic/nuclear signal intensity. (D) Stacked bar chart quantifying the number of mitoses per cell lineage during the live-cell movie from (C). (E) 130 single-cell traces of CDK2 activity from (C) computationally aligned to the time of anaphase for Hs68 plotted for each replicative age. Traces were colored blue if CDK2 activity remained CDK2 low (C/N below 0.8) for 10+ hours following anaphase. (F) Left; cumulative distribution function (CDF) quantifying the total number of hours spent CDK2 low per cell during the live-cell movie (C). Middle; violin plots showing cumulative CDK2 low time per cell from (C). Right; violin plots showing the longest continuous CDK2 low period per cell track from (C). Cells that never raised their CDK2 activity above 0.8 during the experiment are not shown. (G) PD 13 cells from (C) were split into fast cycling (<40 cumulative hours CDK2 low ), slow cycling (50–70 h), or non-cycling (72+ h) (N.C.) categories. Each image shows senescence biomarker staining in one cell. Cyto area was measured by staining with succinimidyl ester. Scale bars represent 26 μm. (H) Violin plots showing the distributions of senescence marker intensity staining in PD 13 cells for each cycling speed described in (G). px, pixels. (I) Cells from (H) were grouped based on cumulative CDK2 low time and intensities for each individual senescence marker were normalized internally and averaged for each group to illustrate the graded manner in which senescence biomarker signals decrease (Lamin B1 and Hoechst standard deviation) or increase with CDK2 low time. (J) ROC analysis showing the capacity of senescence markers to predict/identify cells withdrawn from the cell cycle for more than 60 h in PD 13 cells. AUC, area under curve. (K) In a “binary” model (left), a single cell will maintain high levels of proliferative activity during cellular aging as it approaches senescence, at which point it ceases to proliferate. In our “gradual induction” model (right), senescence induction takes place over the entirety of the replicative aging process where proliferative activity in a single cell declines slowly as senescence biomarkers and tumor-suppressive activity slowly change. Proliferative activity over the course of a 72 h live-cell movie indicates a cell’s proximity to senescence. Information on replicates is provided in data .

Article Snippet: Hs68 , ATCC , CRL−1635.

Techniques: Single Cell, Activity Assay, Phospho-proteomics, Translocation Assay, Biomarker Discovery, Staining, Marker, Standard Deviation

Journal: iScience

Article Title: Replicative senescence induction in single cells is not predicted by telomere length, dysfunction, or oxidation

doi: 10.1016/j.isci.2026.114801

Figure Lengend Snippet: Q-FISH-based telomere length quantification cannot predict senescence proximity in single cells (A) Top, top-down view of a 3D projection image of a nucleus of a single Hs68 PD 13 cell with telomere Q-FISH staining. Middle, visual representation of computational segmentation of individual telomeres and quantification of integrated fluorescence intensity (IFI) per telomere. Bottom, IFI distribution for the above cell. Black circle marks the median. (B) Histograms showing distributions of telomere length metrics for 2,327 Hs68 PD 13 cells. Note that Confocal images of Hs68 PD 13 cells shown here were captured using a Nikon AXR with tunable photomultiplier tube detectors, whereas Hs68 PD 33 and AG16359 cells ( A) were captured separately using a Nikon NSPARC with single pixel photon counter detector arrays. Thus, the data from the two microscopes cannot be directly compared. (C) Boxplots showing the relative telomere length distributions for cells from (B). Cells are ordered according to the cumulative time spent CDK2 low during the time-lapse imaging experiment, indicated by the color map. N.C., non-cycling cells. (D) Violin plots showing the distributions of telomere length metrics in PD 13 cells for each cycling speed described in G. (E) Scatterplots showing the correlation between telomere length metrics and cumulative CDK2 low time in PD 13 cells with linear regression analysis in red. Overlaid contours are colored by data point density. (F) ROC analysis using telomere length distribution features to predict/identify cells withdrawn from the cell cycle for longer than 60 h for Hs68 PD 13 cells. AUC, area under curve. (G) ROC analysis using telomere length distribution features to predict/identify cells withdrawn from the cell-cycle for 72 h for Hs68 PD 33 cells.

Article Snippet: Hs68 , ATCC , CRL−1635.

Techniques: Staining, Fluorescence, Imaging

Journal: iScience

Article Title: Replicative senescence induction in single cells is not predicted by telomere length, dysfunction, or oxidation

doi: 10.1016/j.isci.2026.114801

Figure Lengend Snippet: Proximity to replicative senescence is weakly correlated with telomere-associated DDR foci (A) Split violin plots showing the number of telomeric and non-telomeric 53BP1 foci detected in Hs68 cells at PD 13 and PD 33. (B and C) Left, violin plots showing cumulative time spent CDK2 low during the live-cell movie in groups based on the number of 53BP1 foci per cell (C) or the number of telomeric 53BP1 foci per cell (D) in Hs68 PD 13 cells. Right, cells were binned based on cumulative CDK2 low time. Error bars represent the 95% confidence interval for the mean. (D) Left, top-down view of a 3D projection image of a nucleus of a single Hs68 cell with 53BP1 immunofluorescence staining and telomere Q-FISH. Computationally detected telomeric foci are numbered in blue and non-telomeric foci are numbered in yellow. Scale bars represent 5 μm. Middle, close-up 3D view of each computationally segmented 53BP1 focus. Blue arrows indicate colocalized telomeres. Right, split violin plots showing the intensity sums of all colocalized vs. not colocalized 53BP1 foci from all cells. Confocal images of Hs68 PD 13 cells were captured using a Nikon AXR with tunable photomultiplier tube detectors, and Hs68 PD 33 and AG16359 cells were captured separately using a Nikon NSPARC with single pixel photon counter detector arrays. (E) Cells were grouped based on cumulative CDK2 low time and segmented 53BP1 foci intensities per cell were summed. (F) Same as (B and C) but using telomeric 53BP1 intensity sums rather than the number of 53BP1 foci. (G) ROC analysis using segmented 53BP1 foci intensity sums per cell to predict/identify cells withdrawn from the cell cycle for more than 60 h (for Hs68 PD 13 and AG16359 cells) or for 72 h (for Hs68 PD 33 cells). A.U.C., area under curve. (H) ROC analysis using nuclear mean 53BP1 intensity per cell to predict/identify cells withdrawn from the cell cycle for more than 60 h (for Hs68 PD 13 and AG16359 cells) or for 72 h (for Hs68 PD 33 cells). This experiment used confocal imaging with at 100X magnification and a 12-bit sensor, whereas J used 10X magnification with a 2×2 bin and a 16-bit sensor, hence the difference in AUC between the two figures. AUC, area under curve.

Article Snippet: Hs68 , ATCC , CRL−1635.

Techniques: Immunofluorescence, Staining, Imaging

Journal: iScience

Article Title: Replicative senescence induction in single cells is not predicted by telomere length, dysfunction, or oxidation

doi: 10.1016/j.isci.2026.114801

Figure Lengend Snippet: Telomeric oxidative DNA damage does not increase with cellular aging or senescence (A) Schematic of cell-cycle withdrawal-dependent loss of Ki67 intensity over time. (B) Left, histogram of median Ki67 nuclear intensity in untreated Hs68 PD 28 cells with quintile positions. Middle, multiplexing of Ki67 and 8oxoG immunofluorescence in untreated Hs68 PD 28 cells. Orange arrow indicates a Ki67 high cell (>90 th percentile Ki67 nuclear median), white arrow indicates a Ki67 off cell (<10 th percentile Ki67 nuclear median). Scale bars represent 25 μm. Right, violin plots showing 8oxoG intensity across Ki67 quintiles in PD 28 cells. (C) Population doubling curve for Hs68 with PD 0, 18, 28, 31, and 33 highlighted in blue. (D) Split violins showing the mean 8oxoG intensity in the highlighted ages in (C). (E) Left, top-down view of a 3D projection image of a nucleus of a single Hs68 cell with 8oxoG immunofluorescence and telomere Q-FISH. Right, cartoon depicting 8oxoG centroid-based colocalization quantification strategy. (F) Split violins showing the number of telomeres per cell that colocalize with at least one 8oxoG lesion. (G) Mean fluorescence intensity in the 8oxoG channel within the segmented telomere objects classified as colocalized with at least one 8oxoG lesion. (H) Analyses from (D–G) using Ki67 off cells acquired from the Baltimore Longitudinal Study on Aging repository.

Article Snippet: Hs68 , ATCC , CRL−1635.

Techniques: Multiplexing, Immunofluorescence, Fluorescence

Comparative in-vitro analysis of skin-rejuvenation activities of MSC secretomes. Secretomes from WJ-MSCs, AD-MSCs, and BM-MSCs were compared across multiple functional assays. Unless otherwise stated, the negative control (N.C.) was Vehicle-CM (α-MEM + 5 % human platelet lysate incubated cell-free for 48 h and processed identically). (A) HS68 fibroblast proliferation by CCK-8, normalized to N.C. (=100 %); n = 5. (B) HaCaT keratinocyte scratch-wound closure at 0 h and 18 h; n = 4. (C) Type I procollagen secretion (ELISA) in HS68 fibroblasts; n = 5. (D) ECM-related gene expression ( COL1A1, COL3A1 ) by qPCR ( GAPDH -normalized) in HS68 fibroblasts; n = 5. (E) Suppression of pro-inflammatory transcripts (IL-6/COX-2/IL-1β/TNF-α or equivalent cytokine readouts) in LPS-stimulated RAW 264.7 macrophages; n = 3. (F) HUVEC tube-formation assay (6 h); tube number and total length; n = 5. VEGF (100 ng/mL) served as positive control. (G) Intracellular ROS (DCF-DA) after H 2 O 2 challenge; secretome treatments versus N.C.; n = 3. Ascorbic acid (Vit. C) served as antioxidant control. (H) Total antioxidant capacity (reported as Trolox equivalents, nmol/μL); n = 5. Vit. C served as positive control. Data are mean ± SEM from independent experiments; statistics by one-way ANOVA with Tukey's post hoc test (∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001). Abbreviations: N.C., negative control (Vehicle-CM); AD, Adipose tissue-derived mesenchymal stem cells secretome; BM, bone marrow-derived mesenchymal stem cells secretome; WJ, Wharton's jelly-derived mesenchymal stem cells secretome; LPS, lipopolysaccharide; VEGF, vascular endothelial growth factor; DCF-DA, 2′,7′-dichlorofluorescein diacetate.

Journal: Regenerative Therapy

Article Title: Wharton's jelly mesenchymal stem cell-secretome enhances skin rejuvenation via ApoA4 and SERPINH1

doi: 10.1016/j.reth.2026.101071

Figure Lengend Snippet: Comparative in-vitro analysis of skin-rejuvenation activities of MSC secretomes. Secretomes from WJ-MSCs, AD-MSCs, and BM-MSCs were compared across multiple functional assays. Unless otherwise stated, the negative control (N.C.) was Vehicle-CM (α-MEM + 5 % human platelet lysate incubated cell-free for 48 h and processed identically). (A) HS68 fibroblast proliferation by CCK-8, normalized to N.C. (=100 %); n = 5. (B) HaCaT keratinocyte scratch-wound closure at 0 h and 18 h; n = 4. (C) Type I procollagen secretion (ELISA) in HS68 fibroblasts; n = 5. (D) ECM-related gene expression ( COL1A1, COL3A1 ) by qPCR ( GAPDH -normalized) in HS68 fibroblasts; n = 5. (E) Suppression of pro-inflammatory transcripts (IL-6/COX-2/IL-1β/TNF-α or equivalent cytokine readouts) in LPS-stimulated RAW 264.7 macrophages; n = 3. (F) HUVEC tube-formation assay (6 h); tube number and total length; n = 5. VEGF (100 ng/mL) served as positive control. (G) Intracellular ROS (DCF-DA) after H 2 O 2 challenge; secretome treatments versus N.C.; n = 3. Ascorbic acid (Vit. C) served as antioxidant control. (H) Total antioxidant capacity (reported as Trolox equivalents, nmol/μL); n = 5. Vit. C served as positive control. Data are mean ± SEM from independent experiments; statistics by one-way ANOVA with Tukey's post hoc test (∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001). Abbreviations: N.C., negative control (Vehicle-CM); AD, Adipose tissue-derived mesenchymal stem cells secretome; BM, bone marrow-derived mesenchymal stem cells secretome; WJ, Wharton's jelly-derived mesenchymal stem cells secretome; LPS, lipopolysaccharide; VEGF, vascular endothelial growth factor; DCF-DA, 2′,7′-dichlorofluorescein diacetate.

Article Snippet: HS68 fibroblasts (6 × 10 4 cells/well; ATCC, USA) were seeded in 6-well plates (Corning, USA) overnight and treated with WJ-MSC secretome or recombinant ApoA4/SERPINH1 (R&D Systems, USA) for 24 h. Total RNA was extracted with QIAzol (QIAGEN, Germany) and reverse transcribed using SuperScript III (Invitrogen, USA) COL1A1 and COL3A1 mRNA levels were measured by qPCR (QuantStudio 6 Flex; Thermo Fisher Scientific, USA) with SYBRTM Green Master Mix (Applied Biosystems, USA).

Techniques: In Vitro, Functional Assay, Negative Control, Incubation, CCK-8 Assay, Enzyme-linked Immunosorbent Assay, Gene Expression, HUVEC Tube Formation Assay, Positive Control, Control, Derivative Assay

SERPINH1 in vitro functions relevant to skin rejuvenation. Baseline control: serum-free assay medium (SFM); Vehicle-CM not used. (A) HS68 fibroblast proliferation (CCK-8) after recombinant SERPINH1 treatment. (B) Immunoblot confirming increased cell-associated SERPINH1 after treatment. (C) HaCaT scratch-wound closure at 18 h; EGF (20 ng/mL) as positive control. (D) Immunoblot of ECM proteins (COL1A1, fibronectin). (E) Immunoblot of hydration-related proteins (HAS2, AQP3); retinoic acid as comparator (positive control). (F) siRNA-mediated SERPINH1 knockdown impairs HaCaT migration. (G) Knockdown reduces TGF-β, TGFβR1, p -Smad2/3, COL1A1, COL3A1, and fibronectin, consistent with dampened TGF-β/Smad signaling and ECM remodeling. Data are mean ± SEM; one-way ANOVA with Tukey's post hoc test (∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001).

Journal: Regenerative Therapy

Article Title: Wharton's jelly mesenchymal stem cell-secretome enhances skin rejuvenation via ApoA4 and SERPINH1

doi: 10.1016/j.reth.2026.101071

Figure Lengend Snippet: SERPINH1 in vitro functions relevant to skin rejuvenation. Baseline control: serum-free assay medium (SFM); Vehicle-CM not used. (A) HS68 fibroblast proliferation (CCK-8) after recombinant SERPINH1 treatment. (B) Immunoblot confirming increased cell-associated SERPINH1 after treatment. (C) HaCaT scratch-wound closure at 18 h; EGF (20 ng/mL) as positive control. (D) Immunoblot of ECM proteins (COL1A1, fibronectin). (E) Immunoblot of hydration-related proteins (HAS2, AQP3); retinoic acid as comparator (positive control). (F) siRNA-mediated SERPINH1 knockdown impairs HaCaT migration. (G) Knockdown reduces TGF-β, TGFβR1, p -Smad2/3, COL1A1, COL3A1, and fibronectin, consistent with dampened TGF-β/Smad signaling and ECM remodeling. Data are mean ± SEM; one-way ANOVA with Tukey's post hoc test (∗ p < 0.05, ∗∗ p < 0.01, ∗∗∗ p < 0.001, ∗∗∗∗ p < 0.0001).

Techniques: In Vitro, Control, CCK-8 Assay, Recombinant, Western Blot, Positive Control, Knockdown, Migration

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