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Miltenyi Biotec cd51

Gene expression and protein exposure of cell surface proteins in MCF7 upon stimulation with TGFβ. (A) Heatmap representing normalized gene expression of different genes ( Y ‐axis) in different samples treated or not treated with TGFβ at the different cell densities ( X ‐axis). Normalization was performed by fixing the first replicate of non‐treated cells (NT) at 20 000 cells per cm 2 to 100%. Statistical significance between NT and cells treated with TGFβ inside each plating density condition was considered. Yellow boxes highlight the genes emerged as significantly different between treated and non‐treated cells. (B) Bars representing relative gene expression of ITGAV <t>(Integrin‐αν/CD51)</t> and LGALS3 n = 3 replicates. Δ C t were calculated using GAPDH as housekeeping. (C) Bars representing the mean fluorescence intensity (MFI) of CD51 and Galectin‐3 exposure on MCF7 cells plated at 20 000 and 60 000 cells per cm 2 . n = 3 replicates. (D) Bars representing the % of MCF7 positive to both CD51 and Galectin‐3 (CD51 + /Galectin‐3 + ) of cells plated at 20 000 and 60 000 cells per cm 2 . n = 3 replicates. (E) Representative flow cytometry histograms of CD51 + and Galectin‐3 + with (Blue) and without (Green) TGFβ treatment at 20 000 cells per cm 2 . n = 3 replicates. (F) Representative flow cytometry counter plot of CD51 + and Galectin‐3 + with (Blue) and without (Green) TGFβ treatment in cells plated at 20 000 cells per cm 2 . n = 3 replicates. Data are expressed as mean ± SD. Significance of data differences was established using unpaired two‐way ANOVA test with multiple comparisons, * P < 0.05, ** P < 0.01 and *** P < 0.001.

Cd51, supplied by Miltenyi Biotec, used in various techniques. Bioz Stars score: 93/100, based on 7 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/cd51/pmc12914766-205-15-20?v=Miltenyi+Biotec
Average 93 stars, based on 7 article reviews

cd51 - by Bioz Stars, 2026-07

93/100 stars

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1) Product Images from "TGFβ enhances platelet–breast‐cancer‐cell interaction and promotes platelet aggregation"

Article Title: TGFβ enhances platelet–breast‐cancer‐cell interaction and promotes platelet aggregation

Journal: The Febs Journal

doi: 10.1111/febs.70279

Figure Legend Snippet: Gene expression and protein exposure of cell surface proteins in MCF7 upon stimulation with TGFβ. (A) Heatmap representing normalized gene expression of different genes ( Y ‐axis) in different samples treated or not treated with TGFβ at the different cell densities ( X ‐axis). Normalization was performed by fixing the first replicate of non‐treated cells (NT) at 20 000 cells per cm 2 to 100%. Statistical significance between NT and cells treated with TGFβ inside each plating density condition was considered. Yellow boxes highlight the genes emerged as significantly different between treated and non‐treated cells. (B) Bars representing relative gene expression of ITGAV (Integrin‐αν/CD51) and LGALS3 n = 3 replicates. Δ C t were calculated using GAPDH as housekeeping. (C) Bars representing the mean fluorescence intensity (MFI) of CD51 and Galectin‐3 exposure on MCF7 cells plated at 20 000 and 60 000 cells per cm 2 . n = 3 replicates. (D) Bars representing the % of MCF7 positive to both CD51 and Galectin‐3 (CD51 + /Galectin‐3 + ) of cells plated at 20 000 and 60 000 cells per cm 2 . n = 3 replicates. (E) Representative flow cytometry histograms of CD51 + and Galectin‐3 + with (Blue) and without (Green) TGFβ treatment at 20 000 cells per cm 2 . n = 3 replicates. (F) Representative flow cytometry counter plot of CD51 + and Galectin‐3 + with (Blue) and without (Green) TGFβ treatment in cells plated at 20 000 cells per cm 2 . n = 3 replicates. Data are expressed as mean ± SD. Significance of data differences was established using unpaired two‐way ANOVA test with multiple comparisons, * P < 0.05, ** P < 0.01 and *** P < 0.001.

Techniques Used: Gene Expression, Fluorescence, Flow Cytometry

Inhibition of Integrin‐aν/CD51, but not of Galectin‐3, reversed the increase in PLT‐MCF7 interaction promoted by TGFβ. (A) Schematic representation of PLT‐MCF7 interaction mediated by Integrin‐αν/CD51 and Galectin‐3 and their inhibition through Cilengitide, GB1107 and GLPG0187. Experiments were performed with cells plated at low density, 20 000 cells per cm 2 , before TGFβ treatment. (B) Schematic representation of the experimental design of PLT‐MCF7 interaction in suspension with Integrin‐αν and Galectin‐3 inhibitors, assayed with flow cytometry. (C) Bars of cell viability for MCF7‐PLT interaction treated with different inhibitors, expressed as % of cells negative to Propidium Iodide (PI − ). n = 3 replicates. (D) Bars of MCF7‐PLT interaction expressed as % of cells positive to CFSE fluorescence (CFSE+) for non‐treated NT and TGFβ−treated (TGFβ+): Cilengitide (purple), GB1107 (ochre) or GLPG0187 (gray). n = 3 replicates. Data are expressed as mean ± SD. Significance of data differences was established using unpaired two‐way ANOVA test with multiple comparisons, * P < 0.05.

Figure Legend Snippet: Inhibition of Integrin‐aν/CD51, but not of Galectin‐3, reversed the increase in PLT‐MCF7 interaction promoted by TGFβ. (A) Schematic representation of PLT‐MCF7 interaction mediated by Integrin‐αν/CD51 and Galectin‐3 and their inhibition through Cilengitide, GB1107 and GLPG0187. Experiments were performed with cells plated at low density, 20 000 cells per cm 2 , before TGFβ treatment. (B) Schematic representation of the experimental design of PLT‐MCF7 interaction in suspension with Integrin‐αν and Galectin‐3 inhibitors, assayed with flow cytometry. (C) Bars of cell viability for MCF7‐PLT interaction treated with different inhibitors, expressed as % of cells negative to Propidium Iodide (PI − ). n = 3 replicates. (D) Bars of MCF7‐PLT interaction expressed as % of cells positive to CFSE fluorescence (CFSE+) for non‐treated NT and TGFβ−treated (TGFβ+): Cilengitide (purple), GB1107 (ochre) or GLPG0187 (gray). n = 3 replicates. Data are expressed as mean ± SD. Significance of data differences was established using unpaired two‐way ANOVA test with multiple comparisons, * P < 0.05.

Techniques Used: Inhibition, Suspension, Flow Cytometry, Fluorescence

Inhibitors of Integrin‐α ν /CD51 and Galectin‐3 counteracted the effect of TGFβ pre‐treatment on MCF7‐induced PLT aggregation. (A) Schematic representation of the experimental design of aggregation assay of PLT with Integrin‐αν/CD51 and Galectin‐3 inhibitors. Experiments were performed with cells plated at low density, 20 000 cells per cm 2 , before TGFβ treatment. (B) Aggregation of PLT only (activate or not with Thrombin) or PLT activated with Thrombin and treated with Cilengitide, GB1107, Cilengitide+GB1107 and GLPG0187 activated with Thrombin. Values are expressed as % of the transmitted light over time and each point is the mean of n = 3 replicates. (C) Schematic representation of the experimental design of aggregation assay upon PLT‐MCF7 interaction in suspension with Integrin‐αν/CD51 and Galectin‐3 inhibitors. (D) Aggregation of PLT after incubation with MCF7 non‐treated NT/treated with TGFβ (blue/green) and of TGFβ + inhibitors. NT condition without thrombin (black) is also represented as negative control. Values are expressed as % of the transmitted light over time and each point is the mean of n = 3 replicates. (D) Maximum aggregation at 30 min for the conditions tested in C. n = 3 replicates. (E) Bars of Maximum aggregation at 30 min for NT and TGFβ conditions and for the TGFβ condition in presence of the different inhibitors. n ≥ =3 replicates. Data are expressed as mean ± SD. Significance of data differences was established using unpaired two‐way ANOVA test with multiple comparisons, * P < 0.05, ** P < 0.01.

Figure Legend Snippet: Inhibitors of Integrin‐α ν /CD51 and Galectin‐3 counteracted the effect of TGFβ pre‐treatment on MCF7‐induced PLT aggregation. (A) Schematic representation of the experimental design of aggregation assay of PLT with Integrin‐αν/CD51 and Galectin‐3 inhibitors. Experiments were performed with cells plated at low density, 20 000 cells per cm 2 , before TGFβ treatment. (B) Aggregation of PLT only (activate or not with Thrombin) or PLT activated with Thrombin and treated with Cilengitide, GB1107, Cilengitide+GB1107 and GLPG0187 activated with Thrombin. Values are expressed as % of the transmitted light over time and each point is the mean of n = 3 replicates. (C) Schematic representation of the experimental design of aggregation assay upon PLT‐MCF7 interaction in suspension with Integrin‐αν/CD51 and Galectin‐3 inhibitors. (D) Aggregation of PLT after incubation with MCF7 non‐treated NT/treated with TGFβ (blue/green) and of TGFβ + inhibitors. NT condition without thrombin (black) is also represented as negative control. Values are expressed as % of the transmitted light over time and each point is the mean of n = 3 replicates. (D) Maximum aggregation at 30 min for the conditions tested in C. n = 3 replicates. (E) Bars of Maximum aggregation at 30 min for NT and TGFβ conditions and for the TGFβ condition in presence of the different inhibitors. n ≥ =3 replicates. Data are expressed as mean ± SD. Significance of data differences was established using unpaired two‐way ANOVA test with multiple comparisons, * P < 0.05, ** P < 0.01.

Techniques Used: Suspension, Incubation, Negative Control

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Journal: The Febs Journal

Article Title: TGFβ enhances platelet–breast‐cancer‐cell interaction and promotes platelet aggregation

doi: 10.1111/febs.70279

Figure Lengend Snippet: Gene expression and protein exposure of cell surface proteins in MCF7 upon stimulation with TGFβ. (A) Heatmap representing normalized gene expression of different genes ( Y ‐axis) in different samples treated or not treated with TGFβ at the different cell densities ( X ‐axis). Normalization was performed by fixing the first replicate of non‐treated cells (NT) at 20 000 cells per cm 2 to 100%. Statistical significance between NT and cells treated with TGFβ inside each plating density condition was considered. Yellow boxes highlight the genes emerged as significantly different between treated and non‐treated cells. (B) Bars representing relative gene expression of ITGAV (Integrin‐αν/CD51) and LGALS3 n = 3 replicates. Δ C t were calculated using GAPDH as housekeeping. (C) Bars representing the mean fluorescence intensity (MFI) of CD51 and Galectin‐3 exposure on MCF7 cells plated at 20 000 and 60 000 cells per cm 2 . n = 3 replicates. (D) Bars representing the % of MCF7 positive to both CD51 and Galectin‐3 (CD51 + /Galectin‐3 + ) of cells plated at 20 000 and 60 000 cells per cm 2 . n = 3 replicates. (E) Representative flow cytometry histograms of CD51 + and Galectin‐3 + with (Blue) and without (Green) TGFβ treatment at 20 000 cells per cm 2 . n = 3 replicates. (F) Representative flow cytometry counter plot of CD51 + and Galectin‐3 + with (Blue) and without (Green) TGFβ treatment in cells plated at 20 000 cells per cm 2 . n = 3 replicates. Data are expressed as mean ± SD. Significance of data differences was established using unpaired two‐way ANOVA test with multiple comparisons, * P < 0.05, ** P < 0.01 and *** P < 0.001.

Article Snippet: For each experimental condition, 0.2 × 10 6 cells were labeled with 1 : 50 CD51 (CD51 Antibody, anti‐human, REAfinity, Miltenyi Biotec, Bergisch Gladbach, Germany) and Galectin‐3 (Galectin‐3 Antibody, anti‐human/mouse, REAfinity, Miltenyi Biotec) for 20 min at room temperature in the dark.

Techniques: Gene Expression, Fluorescence, Flow Cytometry

Journal: The Febs Journal

Article Title: TGFβ enhances platelet–breast‐cancer‐cell interaction and promotes platelet aggregation

doi: 10.1111/febs.70279

Figure Lengend Snippet: Inhibition of Integrin‐aν/CD51, but not of Galectin‐3, reversed the increase in PLT‐MCF7 interaction promoted by TGFβ. (A) Schematic representation of PLT‐MCF7 interaction mediated by Integrin‐αν/CD51 and Galectin‐3 and their inhibition through Cilengitide, GB1107 and GLPG0187. Experiments were performed with cells plated at low density, 20 000 cells per cm 2 , before TGFβ treatment. (B) Schematic representation of the experimental design of PLT‐MCF7 interaction in suspension with Integrin‐αν and Galectin‐3 inhibitors, assayed with flow cytometry. (C) Bars of cell viability for MCF7‐PLT interaction treated with different inhibitors, expressed as % of cells negative to Propidium Iodide (PI − ). n = 3 replicates. (D) Bars of MCF7‐PLT interaction expressed as % of cells positive to CFSE fluorescence (CFSE+) for non‐treated NT and TGFβ−treated (TGFβ+): Cilengitide (purple), GB1107 (ochre) or GLPG0187 (gray). n = 3 replicates. Data are expressed as mean ± SD. Significance of data differences was established using unpaired two‐way ANOVA test with multiple comparisons, * P < 0.05.

Techniques: Inhibition, Suspension, Flow Cytometry, Fluorescence

Journal: The Febs Journal

Article Title: TGFβ enhances platelet–breast‐cancer‐cell interaction and promotes platelet aggregation

doi: 10.1111/febs.70279

Figure Lengend Snippet: Inhibitors of Integrin‐α ν /CD51 and Galectin‐3 counteracted the effect of TGFβ pre‐treatment on MCF7‐induced PLT aggregation. (A) Schematic representation of the experimental design of aggregation assay of PLT with Integrin‐αν/CD51 and Galectin‐3 inhibitors. Experiments were performed with cells plated at low density, 20 000 cells per cm 2 , before TGFβ treatment. (B) Aggregation of PLT only (activate or not with Thrombin) or PLT activated with Thrombin and treated with Cilengitide, GB1107, Cilengitide+GB1107 and GLPG0187 activated with Thrombin. Values are expressed as % of the transmitted light over time and each point is the mean of n = 3 replicates. (C) Schematic representation of the experimental design of aggregation assay upon PLT‐MCF7 interaction in suspension with Integrin‐αν/CD51 and Galectin‐3 inhibitors. (D) Aggregation of PLT after incubation with MCF7 non‐treated NT/treated with TGFβ (blue/green) and of TGFβ + inhibitors. NT condition without thrombin (black) is also represented as negative control. Values are expressed as % of the transmitted light over time and each point is the mean of n = 3 replicates. (D) Maximum aggregation at 30 min for the conditions tested in C. n = 3 replicates. (E) Bars of Maximum aggregation at 30 min for NT and TGFβ conditions and for the TGFβ condition in presence of the different inhibitors. n ≥ =3 replicates. Data are expressed as mean ± SD. Significance of data differences was established using unpaired two‐way ANOVA test with multiple comparisons, * P < 0.05, ** P < 0.01.

Techniques: Suspension, Incubation, Negative Control

SLIT3 is mainly derived from osteoclasts. a) Representative images of SLIT3 (green) and CD51/61 (red) co‐stained cells in subchondral bone in the CON and UAC groups. The white dashed line represents the boundary between bone and cartilage. Scale bars: 10 µm. b) Quantitative analysis in panel (a). n = 6. c–e) FACS of the markers of BMSCs (c), osteoblasts (d), osteoclasts (e) and BMMs. f) from the mandible in 6‐week‐old female UAC rats. n = 6. g) The average Ct value and h) qRT‐PCR analysis of the expression of the Slit3 in BMSCs, osteoblasts, osteoclasts, and BMMs. n = 3. Statistical analyses were performed using Student's t ‐test. **** p < 0.0001. ns : no significance.

Journal: Advanced Science

Article Title: Osteoclast‐Derived SLIT3 Mediates Osteoarthritis Pain and Degenerative Changes

doi: 10.1002/advs.202517545

Figure Lengend Snippet: SLIT3 is mainly derived from osteoclasts. a) Representative images of SLIT3 (green) and CD51/61 (red) co‐stained cells in subchondral bone in the CON and UAC groups. The white dashed line represents the boundary between bone and cartilage. Scale bars: 10 µm. b) Quantitative analysis in panel (a). n = 6. c–e) FACS of the markers of BMSCs (c), osteoblasts (d), osteoclasts (e) and BMMs. f) from the mandible in 6‐week‐old female UAC rats. n = 6. g) The average Ct value and h) qRT‐PCR analysis of the expression of the Slit3 in BMSCs, osteoblasts, osteoclasts, and BMMs. n = 3. Statistical analyses were performed using Student's t ‐test. **** p < 0.0001. ns : no significance.

Article Snippet: The antibodies used were Protein gene product 9.5 (PGP9.5, 1:400, ab8189, Abcam, Cambridge, UK), calcitonin gene‐related peptide 1 (CGRP, 1:300, sc‐57053, Santa Cruz Biotechnology, Santa Cruz, CA, USA), SLIT3 (1:300, DF9909, Affinity Biosciences, Cincinnati, OH, USA), TRAP‐α (1:300, sc‐373916, Santa Cruz Biotechnology), Osteocalcin (1:300, sc‐74495, Santa Cruz Biotechnology), β3‐tubulin (1:300, Cell Signaling Technology, Danvers, MA, USA) and CD51/61(1:300, AF5152, Affinity Biosciences, Cincinnati, OH, USA).

Techniques: Derivative Assay, Staining, Quantitative RT-PCR, Expressing

Slit3 is specifically knocked out in osteoclasts of Slit3 ‐CKO mice. a) Schematic diagram of Slit3 ‐CKO mice. b) Immunofluorescence of SLIT3 (green) and CD51/61 (red) in subchondral bone. The white dashed line represents the boundary between subchondral bone and cartilage. Scale bars:10 µm. c) Quantitative analysis in panel (b). n = 6. d) qRT‐PCR analysis of the gene expression of Slit3 in subchondral bone in the two groups. n = 3. e,f) Western blot and its quantitative analysis, g) ELISA, and h,i) immunohistochemical staining and quantitative analysis of SLIT3 expression in subchondral bone in the WT and Slit3 ‐CKO groups. n = 3. Scale bars: 70 µm. Statistical analyses were performed using Student's t ‐test. * p < 0.05. ** p < 0.01. *** p < 0.001. **** p <0.0001. ns : no significance.

Journal: Advanced Science

Article Title: Osteoclast‐Derived SLIT3 Mediates Osteoarthritis Pain and Degenerative Changes

doi: 10.1002/advs.202517545

Figure Lengend Snippet: Slit3 is specifically knocked out in osteoclasts of Slit3 ‐CKO mice. a) Schematic diagram of Slit3 ‐CKO mice. b) Immunofluorescence of SLIT3 (green) and CD51/61 (red) in subchondral bone. The white dashed line represents the boundary between subchondral bone and cartilage. Scale bars:10 µm. c) Quantitative analysis in panel (b). n = 6. d) qRT‐PCR analysis of the gene expression of Slit3 in subchondral bone in the two groups. n = 3. e,f) Western blot and its quantitative analysis, g) ELISA, and h,i) immunohistochemical staining and quantitative analysis of SLIT3 expression in subchondral bone in the WT and Slit3 ‐CKO groups. n = 3. Scale bars: 70 µm. Statistical analyses were performed using Student's t ‐test. * p < 0.05. ** p < 0.01. *** p < 0.001. **** p <0.0001. ns : no significance.

Techniques: Immunofluorescence, Quantitative RT-PCR, Gene Expression, Western Blot, Enzyme-linked Immunosorbent Assay, Immunohistochemical staining, Staining, Expressing

( A ) Immunostaining of CD51, CD63 and CD71 in LBF treated cells at 160 DIV ( n =3). ( B ) Quantification of the percentage of LBF stage cells with CD51, CD63, and CD71 immunostaining and different combinations of co-expression ( n =3). ( C ) Immunostaining of CD51, CD63 and GFAP in LBF treated cells ( n =3). ( D ) Quantification of the percentage of LBF stage cells with CD51, CD63 and GFAP immunostaining and different combination of co-expression ( n =3). ( E ) Histogram of flow cytometry gating strategy for sorting CD51, CD71, and CD63 expressing or co-expressing cells after LBF treatment. ( F ) Proportion of FACS-isolated cells with each possible combination of CD51, CD71, and CD63 co-expression ( n =6). ( G ) Labeling of the four predominant populations identified based on CD51, CD71, and CD63 expression. Population 1 (CD51+CD71+CD63+, green), population 2 (CD51+CD71-CD63-, red), population 3 (CD51+CD71+CD63-, purple), and population 4 (CD51+CD71-CD63+, blue) account for 70% of FACS-isolated cells. ( H ) Principal component analysis (PCA) plot illustrating the overall sample distribution based on transcriptomic profiles of populations 1-4 cells used for RNA-seq. ( I ) Table depicting the number of differentially expressed genes from pairwise and 3 versus 1 comparison analyses based on greater than 1.5-fold difference and false discovery rate of 0.05. ( J ) Heatmap representation of relative expression of fetal and mature astrocyte enriched genes in each population. n represents the number of independent differentiation experiments from one ESC line and two iPSC lines. Scale bar, 50µm.

Journal: bioRxiv

Article Title: Identification of Human Pluripotent Stem Cell Derived Astrocytic Progenitors that Correlate with Glioblastoma Subtypes

doi: 10.1101/2025.08.26.672421

Figure Lengend Snippet: ( A ) Immunostaining of CD51, CD63 and CD71 in LBF treated cells at 160 DIV ( n =3). ( B ) Quantification of the percentage of LBF stage cells with CD51, CD63, and CD71 immunostaining and different combinations of co-expression ( n =3). ( C ) Immunostaining of CD51, CD63 and GFAP in LBF treated cells ( n =3). ( D ) Quantification of the percentage of LBF stage cells with CD51, CD63 and GFAP immunostaining and different combination of co-expression ( n =3). ( E ) Histogram of flow cytometry gating strategy for sorting CD51, CD71, and CD63 expressing or co-expressing cells after LBF treatment. ( F ) Proportion of FACS-isolated cells with each possible combination of CD51, CD71, and CD63 co-expression ( n =6). ( G ) Labeling of the four predominant populations identified based on CD51, CD71, and CD63 expression. Population 1 (CD51+CD71+CD63+, green), population 2 (CD51+CD71-CD63-, red), population 3 (CD51+CD71+CD63-, purple), and population 4 (CD51+CD71-CD63+, blue) account for 70% of FACS-isolated cells. ( H ) Principal component analysis (PCA) plot illustrating the overall sample distribution based on transcriptomic profiles of populations 1-4 cells used for RNA-seq. ( I ) Table depicting the number of differentially expressed genes from pairwise and 3 versus 1 comparison analyses based on greater than 1.5-fold difference and false discovery rate of 0.05. ( J ) Heatmap representation of relative expression of fetal and mature astrocyte enriched genes in each population. n represents the number of independent differentiation experiments from one ESC line and two iPSC lines. Scale bar, 50µm.

Article Snippet: Primary antibodies used in this study are as follow: Acsbg1 (Abcam #ab65154, IHC at 1:100), CD51 (Biolegend #327910, FACS at 1:500), CD51 (Cell Signaling Technology #13208 1CC at 1:1000), CD63 (Millipore Sigma #C7930, FACS and ICC at 1:500), CD71 (Biolegend #334208, FACS and ICC at 1:1000), Doublcortin (Novus Bio.

Techniques: Immunostaining, Expressing, Flow Cytometry, Isolation, Labeling, RNA Sequencing, Comparison

( A ) Heatmap representation of relative expression of GBM subtype-enriched genes in FACS isolated populations 1-4 cells GBM subtype enriched gene list obtained from . ( B ) Pathway analyses of differentially expressed genes identified in populations 1 and 2 highlighted enrichment in TGF-β signaling in population 1 and Notch signaling in population 2. ( C ) Expression of select TGF-β pathway members and associated genes in population 1-4 cells as detected in the RNA-seq analysis (n=3)( D ) Expression of mesenchymal GBM subtype signature genes and proneual GBM subtype signature genes as detected in the RNA-seq of surface marker identified cell populations. ( E ) UMAP feature plot of CD51, CD63, and CD71 expressing cells illustrating the distribution of cells expressing each surface maker. ( F ) Distribution of CD51+CD63+CD71+ population 1 cells and CD51+CD63-CD71-population 2 cells in the UMAP plot illustrating enrichment in of triple positive cells in cluster Ast.3. ( G, H ) Heatmap of population 1 enriched genes ( G ) and population 2 enriched genes ( H ) among the 10 cell clusters identified in the scRNA-seq. One-way ANOVA *p<0.05, **p<0.01, ***p<0.001 followed by Tukey’s post-hoc test.

Journal: bioRxiv

Article Title: Identification of Human Pluripotent Stem Cell Derived Astrocytic Progenitors that Correlate with Glioblastoma Subtypes

doi: 10.1101/2025.08.26.672421

Figure Lengend Snippet: ( A ) Heatmap representation of relative expression of GBM subtype-enriched genes in FACS isolated populations 1-4 cells GBM subtype enriched gene list obtained from . ( B ) Pathway analyses of differentially expressed genes identified in populations 1 and 2 highlighted enrichment in TGF-β signaling in population 1 and Notch signaling in population 2. ( C ) Expression of select TGF-β pathway members and associated genes in population 1-4 cells as detected in the RNA-seq analysis (n=3)( D ) Expression of mesenchymal GBM subtype signature genes and proneual GBM subtype signature genes as detected in the RNA-seq of surface marker identified cell populations. ( E ) UMAP feature plot of CD51, CD63, and CD71 expressing cells illustrating the distribution of cells expressing each surface maker. ( F ) Distribution of CD51+CD63+CD71+ population 1 cells and CD51+CD63-CD71-population 2 cells in the UMAP plot illustrating enrichment in of triple positive cells in cluster Ast.3. ( G, H ) Heatmap of population 1 enriched genes ( G ) and population 2 enriched genes ( H ) among the 10 cell clusters identified in the scRNA-seq. One-way ANOVA *p<0.05, **p<0.01, ***p<0.001 followed by Tukey’s post-hoc test.

Techniques: Expressing, Isolation, RNA Sequencing, Marker

( A ) Schematic of sequential FACS experimental setup and subsequent assays performed on the cell populations isolated based on CD51, CD63, and CD71. ( B ) Phase-contrast images of populations 1 and 2 cells at 1, 3, and 7 days in vitro (DIV) after sorting. ( C ) Quantification of the percentage of cell in populations 1 to 4 after sorted populations 1 and 2 were subsequently FACS isolated on day 3 and 7 ( n =3). ( D, E ) Immunostaining representative images ( D ) and quantifications ( E ) of Nestin, GFAP, Ki67 and DCX-expressing cells in population 1 and population 2 at 1 DIV after FACS. ( F ) Immunostaining representative images and quantifications of cells expressing lineage markers GFAP, Ki67, and DCX after re-sorting populations 1 and 2 cells by FACS after 3 DIV and 7 DIV. n represents the number of independent differentiation experiments from one ESC line and two iPSC lines. Data are represented as means ± s.e.m. Scale bar, 50µm.

Journal: bioRxiv

Article Title: Identification of Human Pluripotent Stem Cell Derived Astrocytic Progenitors that Correlate with Glioblastoma Subtypes

doi: 10.1101/2025.08.26.672421

Figure Lengend Snippet: ( A ) Schematic of sequential FACS experimental setup and subsequent assays performed on the cell populations isolated based on CD51, CD63, and CD71. ( B ) Phase-contrast images of populations 1 and 2 cells at 1, 3, and 7 days in vitro (DIV) after sorting. ( C ) Quantification of the percentage of cell in populations 1 to 4 after sorted populations 1 and 2 were subsequently FACS isolated on day 3 and 7 ( n =3). ( D, E ) Immunostaining representative images ( D ) and quantifications ( E ) of Nestin, GFAP, Ki67 and DCX-expressing cells in population 1 and population 2 at 1 DIV after FACS. ( F ) Immunostaining representative images and quantifications of cells expressing lineage markers GFAP, Ki67, and DCX after re-sorting populations 1 and 2 cells by FACS after 3 DIV and 7 DIV. n represents the number of independent differentiation experiments from one ESC line and two iPSC lines. Data are represented as means ± s.e.m. Scale bar, 50µm.

Techniques: Isolation, In Vitro, Immunostaining, Expressing

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1) Product Images from "TGFβ enhances platelet–breast‐cancer‐cell interaction and promotes platelet aggregation"

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