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antibodies against creb5  (Proteintech)


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    Structured Review

    Proteintech antibodies against creb5
    Bulk RNA-seq of <t>CREB5</t> KD in patient-derived synovial fibroblasts reveals CREB5-dependent integration of cell density in fibroblast lineage programs. A. Representative immunoblots of pCREB5 (T61) and total CREB5 in synovial fibroblasts after CREB5 knockdown, cultured at low (20 cells/mm²) or high (100 cells/mm²) density, with GAPDH as loading control (top). Densitometric quantification of pCREB5 (T61) and total CREB5 normalized to GAPDH (bottom). B. PCA of the normalized gene expression values after batch correction for individual cell line variability. Each point represents the expression profile of one sample. C. GO terms enrichment analysis showing the functional pathways associated with genes upregulated or downregulated in response to CREB5 KD across different cell densities. D. Expression profiles of synovial lining markers ( PRG4 , PDPN , CLU ) and sublining markers ( POSTN , THBS1 , COL1A1 ) across four cell densities in control and CREB5 KD conditions. E. Fisher’s exact test showing the enrichment of AMP-defined lining genes among diffrerntially expressed genes after CREB5 KD. F. Immunoblot analysis of pCREB (S133) and total CREB5 in synovial fibroblasts cultured at 100 cells/mm² for 3 days and stimulated with forskolin (10 μM, 30 min) or DMSO (0.1%, control) prior to lysis, with β-actin as loading control. G. qRT-PCR analysis of lining markers in Synovial fibroblast cultured at at low (20 cells/mm²) and high (100 cells/mm²) density for 6 hours followed by stimulation with forskolin (7 μM) or 0.1% DMSO control for 72 hours. Data represent biological triplicates, and P values are indicated above the bars.
    Antibodies Against Creb5, supplied by Proteintech, used in various techniques. Bioz Stars score: 93/100, based on 8 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
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    antibodies against creb5 - by Bioz Stars, 2026-03
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    Images

    1) Product Images from "Fibroblasts sense spatial proximity via an EGFR–CREB5 axis to restore quiescent synovial lining in remission rheumatoid arthritis"

    Article Title: Fibroblasts sense spatial proximity via an EGFR–CREB5 axis to restore quiescent synovial lining in remission rheumatoid arthritis

    Journal: bioRxiv

    doi: 10.64898/2025.12.10.693501

    Bulk RNA-seq of CREB5 KD in patient-derived synovial fibroblasts reveals CREB5-dependent integration of cell density in fibroblast lineage programs. A. Representative immunoblots of pCREB5 (T61) and total CREB5 in synovial fibroblasts after CREB5 knockdown, cultured at low (20 cells/mm²) or high (100 cells/mm²) density, with GAPDH as loading control (top). Densitometric quantification of pCREB5 (T61) and total CREB5 normalized to GAPDH (bottom). B. PCA of the normalized gene expression values after batch correction for individual cell line variability. Each point represents the expression profile of one sample. C. GO terms enrichment analysis showing the functional pathways associated with genes upregulated or downregulated in response to CREB5 KD across different cell densities. D. Expression profiles of synovial lining markers ( PRG4 , PDPN , CLU ) and sublining markers ( POSTN , THBS1 , COL1A1 ) across four cell densities in control and CREB5 KD conditions. E. Fisher’s exact test showing the enrichment of AMP-defined lining genes among diffrerntially expressed genes after CREB5 KD. F. Immunoblot analysis of pCREB (S133) and total CREB5 in synovial fibroblasts cultured at 100 cells/mm² for 3 days and stimulated with forskolin (10 μM, 30 min) or DMSO (0.1%, control) prior to lysis, with β-actin as loading control. G. qRT-PCR analysis of lining markers in Synovial fibroblast cultured at at low (20 cells/mm²) and high (100 cells/mm²) density for 6 hours followed by stimulation with forskolin (7 μM) or 0.1% DMSO control for 72 hours. Data represent biological triplicates, and P values are indicated above the bars.
    Figure Legend Snippet: Bulk RNA-seq of CREB5 KD in patient-derived synovial fibroblasts reveals CREB5-dependent integration of cell density in fibroblast lineage programs. A. Representative immunoblots of pCREB5 (T61) and total CREB5 in synovial fibroblasts after CREB5 knockdown, cultured at low (20 cells/mm²) or high (100 cells/mm²) density, with GAPDH as loading control (top). Densitometric quantification of pCREB5 (T61) and total CREB5 normalized to GAPDH (bottom). B. PCA of the normalized gene expression values after batch correction for individual cell line variability. Each point represents the expression profile of one sample. C. GO terms enrichment analysis showing the functional pathways associated with genes upregulated or downregulated in response to CREB5 KD across different cell densities. D. Expression profiles of synovial lining markers ( PRG4 , PDPN , CLU ) and sublining markers ( POSTN , THBS1 , COL1A1 ) across four cell densities in control and CREB5 KD conditions. E. Fisher’s exact test showing the enrichment of AMP-defined lining genes among diffrerntially expressed genes after CREB5 KD. F. Immunoblot analysis of pCREB (S133) and total CREB5 in synovial fibroblasts cultured at 100 cells/mm² for 3 days and stimulated with forskolin (10 μM, 30 min) or DMSO (0.1%, control) prior to lysis, with β-actin as loading control. G. qRT-PCR analysis of lining markers in Synovial fibroblast cultured at at low (20 cells/mm²) and high (100 cells/mm²) density for 6 hours followed by stimulation with forskolin (7 μM) or 0.1% DMSO control for 72 hours. Data represent biological triplicates, and P values are indicated above the bars.

    Techniques Used: RNA Sequencing, Derivative Assay, Western Blot, Knockdown, Cell Culture, Control, Gene Expression, Expressing, Functional Assay, Lysis, Quantitative RT-PCR

    EGFR signaling regulates CREB5 activation and synovial fibroblast lineage identity in a cell density–dependent manner. A. Schematic diagram of the experimental design and timelines. B. UMAP representation of single-cell spatial transcriptomic profiles from synovial fibroblasts colored by condition (control vs. siRNA knockdown). C. UMAP plot of synovial fibroblasts grouped by density and EGFR KD condition. (Left) Cells colored by density state (high vs. low) highlight the separation of lining-like and sublining-like populations. (Right) Cells colored by experimental conditions showing control (high and low density) versus EGFR knockdown ( EGFR _high and EGFR _low). D. Heatmap showing UCell scores for low-density gene signatures across all knockdown conditions at high cell density (600 cells/mm²). Each column represents a different knockdown condition or control. The color gradient indicates the strength of a low-density UCell score. E. Violin plots showing the distribution of CLU and PDPN expression in synovial fibroblasts across control and EGFR KD conditions. The x-axis represents experimental conditions and the y-axis represents normalized gene expression. F. Representative immunoblots of total EGFR, pEGFR (Y1068), pCREB5 (T61), and total CREB5 in synovial fibroblasts following HB-EGF stimulation or EGFR KD, cultured at low (20 cells/mm²) or high (100 cells/mm²) density, with α-tubulin as loading control. G. Quantification of EGFR, pEGFR (Y1068), pCREB5 (T61), and total CREB5 immunoblots, normalized to α-tubulin as a loading control. H. qRT-PCR analysis of lining ( PRG4 and CLU ) and sublining marker ( CD90 and POSTN ) expression in synovial fibroblasts cultured at varying cell densities under control or EGFR KD conditions. Data represent biological triplicates, with P values indicated above the bars.
    Figure Legend Snippet: EGFR signaling regulates CREB5 activation and synovial fibroblast lineage identity in a cell density–dependent manner. A. Schematic diagram of the experimental design and timelines. B. UMAP representation of single-cell spatial transcriptomic profiles from synovial fibroblasts colored by condition (control vs. siRNA knockdown). C. UMAP plot of synovial fibroblasts grouped by density and EGFR KD condition. (Left) Cells colored by density state (high vs. low) highlight the separation of lining-like and sublining-like populations. (Right) Cells colored by experimental conditions showing control (high and low density) versus EGFR knockdown ( EGFR _high and EGFR _low). D. Heatmap showing UCell scores for low-density gene signatures across all knockdown conditions at high cell density (600 cells/mm²). Each column represents a different knockdown condition or control. The color gradient indicates the strength of a low-density UCell score. E. Violin plots showing the distribution of CLU and PDPN expression in synovial fibroblasts across control and EGFR KD conditions. The x-axis represents experimental conditions and the y-axis represents normalized gene expression. F. Representative immunoblots of total EGFR, pEGFR (Y1068), pCREB5 (T61), and total CREB5 in synovial fibroblasts following HB-EGF stimulation or EGFR KD, cultured at low (20 cells/mm²) or high (100 cells/mm²) density, with α-tubulin as loading control. G. Quantification of EGFR, pEGFR (Y1068), pCREB5 (T61), and total CREB5 immunoblots, normalized to α-tubulin as a loading control. H. qRT-PCR analysis of lining ( PRG4 and CLU ) and sublining marker ( CD90 and POSTN ) expression in synovial fibroblasts cultured at varying cell densities under control or EGFR KD conditions. Data represent biological triplicates, with P values indicated above the bars.

    Techniques Used: Activation Assay, Control, Knockdown, Expressing, Gene Expression, Western Blot, Cell Culture, Quantitative RT-PCR, Marker

    HB-EGF–EGFR–CREB5 signaling drives density-dependent lining fibroblast differentiation. A. Representative immunoblots of pCREB5 (T61) and total CREB5 in synovial fibroblasts cultured at high density (100 cells/mm²) following stimulation with EGF, HB-EGF, or TGFα (100 ng/ml, 10 min) or no stimulation (control), with GAPDH as loading control. B. Quantification of pCREB5 (T61) and total CREB5 in immunoblots of ligand stimulation, normalized to GAPDH as a loading control. C. qRT-PCR analysis of lining ( PRG4 and CLU ) and sublining marker ( POSTN and COL1A1 ) expression in synovial fibroblasts cultured at low (20 cells/mm²) and high (100 cells/mm²) densities after stimulation for 72 hours with HB-EGF (100 ng/ml), or without stimulation (control). Data represent biological triplicates, with P values indicated above the bars. D. qRT-PCR analysis of lining ( PRG4 and CLU ) and sublining marker ( POSTN and COL1A1 ) expression in synovial fibroblasts cultured at low (20 cells/mm²) and high (100 cells/mm²) densities after HBEGF KD. Data represent biological triplicates, with P values indicated above the bars. E. Representative immunoblots of pCREB5 (T61) and total CREB5 in synovial fibroblasts cultured at low density (20 cells/mm²) or high density (100 cells/mm²) following HBEGF KD, F. Quantification of pCREB5 (T61) and total CREB5 in immunoblots of HBEGF KD, normalized to α-tubulin as a loading control. G. Spatial distribution of lining and sublining fibroblasts in RA patient tissue, with gene expression mapped for CREB5 , HBEGF , and EGFR . H. Model of density-dependent fibroblast differentiation through HB-EGF/EGFR-CREB5 signaling
    Figure Legend Snippet: HB-EGF–EGFR–CREB5 signaling drives density-dependent lining fibroblast differentiation. A. Representative immunoblots of pCREB5 (T61) and total CREB5 in synovial fibroblasts cultured at high density (100 cells/mm²) following stimulation with EGF, HB-EGF, or TGFα (100 ng/ml, 10 min) or no stimulation (control), with GAPDH as loading control. B. Quantification of pCREB5 (T61) and total CREB5 in immunoblots of ligand stimulation, normalized to GAPDH as a loading control. C. qRT-PCR analysis of lining ( PRG4 and CLU ) and sublining marker ( POSTN and COL1A1 ) expression in synovial fibroblasts cultured at low (20 cells/mm²) and high (100 cells/mm²) densities after stimulation for 72 hours with HB-EGF (100 ng/ml), or without stimulation (control). Data represent biological triplicates, with P values indicated above the bars. D. qRT-PCR analysis of lining ( PRG4 and CLU ) and sublining marker ( POSTN and COL1A1 ) expression in synovial fibroblasts cultured at low (20 cells/mm²) and high (100 cells/mm²) densities after HBEGF KD. Data represent biological triplicates, with P values indicated above the bars. E. Representative immunoblots of pCREB5 (T61) and total CREB5 in synovial fibroblasts cultured at low density (20 cells/mm²) or high density (100 cells/mm²) following HBEGF KD, F. Quantification of pCREB5 (T61) and total CREB5 in immunoblots of HBEGF KD, normalized to α-tubulin as a loading control. G. Spatial distribution of lining and sublining fibroblasts in RA patient tissue, with gene expression mapped for CREB5 , HBEGF , and EGFR . H. Model of density-dependent fibroblast differentiation through HB-EGF/EGFR-CREB5 signaling

    Techniques Used: Western Blot, Cell Culture, Control, Quantitative RT-PCR, Marker, Expressing, Gene Expression



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    Image Search Results


    Bulk RNA-seq of CREB5 KD in patient-derived synovial fibroblasts reveals CREB5-dependent integration of cell density in fibroblast lineage programs. A. Representative immunoblots of pCREB5 (T61) and total CREB5 in synovial fibroblasts after CREB5 knockdown, cultured at low (20 cells/mm²) or high (100 cells/mm²) density, with GAPDH as loading control (top). Densitometric quantification of pCREB5 (T61) and total CREB5 normalized to GAPDH (bottom). B. PCA of the normalized gene expression values after batch correction for individual cell line variability. Each point represents the expression profile of one sample. C. GO terms enrichment analysis showing the functional pathways associated with genes upregulated or downregulated in response to CREB5 KD across different cell densities. D. Expression profiles of synovial lining markers ( PRG4 , PDPN , CLU ) and sublining markers ( POSTN , THBS1 , COL1A1 ) across four cell densities in control and CREB5 KD conditions. E. Fisher’s exact test showing the enrichment of AMP-defined lining genes among diffrerntially expressed genes after CREB5 KD. F. Immunoblot analysis of pCREB (S133) and total CREB5 in synovial fibroblasts cultured at 100 cells/mm² for 3 days and stimulated with forskolin (10 μM, 30 min) or DMSO (0.1%, control) prior to lysis, with β-actin as loading control. G. qRT-PCR analysis of lining markers in Synovial fibroblast cultured at at low (20 cells/mm²) and high (100 cells/mm²) density for 6 hours followed by stimulation with forskolin (7 μM) or 0.1% DMSO control for 72 hours. Data represent biological triplicates, and P values are indicated above the bars.

    Journal: bioRxiv

    Article Title: Fibroblasts sense spatial proximity via an EGFR–CREB5 axis to restore quiescent synovial lining in remission rheumatoid arthritis

    doi: 10.64898/2025.12.10.693501

    Figure Lengend Snippet: Bulk RNA-seq of CREB5 KD in patient-derived synovial fibroblasts reveals CREB5-dependent integration of cell density in fibroblast lineage programs. A. Representative immunoblots of pCREB5 (T61) and total CREB5 in synovial fibroblasts after CREB5 knockdown, cultured at low (20 cells/mm²) or high (100 cells/mm²) density, with GAPDH as loading control (top). Densitometric quantification of pCREB5 (T61) and total CREB5 normalized to GAPDH (bottom). B. PCA of the normalized gene expression values after batch correction for individual cell line variability. Each point represents the expression profile of one sample. C. GO terms enrichment analysis showing the functional pathways associated with genes upregulated or downregulated in response to CREB5 KD across different cell densities. D. Expression profiles of synovial lining markers ( PRG4 , PDPN , CLU ) and sublining markers ( POSTN , THBS1 , COL1A1 ) across four cell densities in control and CREB5 KD conditions. E. Fisher’s exact test showing the enrichment of AMP-defined lining genes among diffrerntially expressed genes after CREB5 KD. F. Immunoblot analysis of pCREB (S133) and total CREB5 in synovial fibroblasts cultured at 100 cells/mm² for 3 days and stimulated with forskolin (10 μM, 30 min) or DMSO (0.1%, control) prior to lysis, with β-actin as loading control. G. qRT-PCR analysis of lining markers in Synovial fibroblast cultured at at low (20 cells/mm²) and high (100 cells/mm²) density for 6 hours followed by stimulation with forskolin (7 μM) or 0.1% DMSO control for 72 hours. Data represent biological triplicates, and P values are indicated above the bars.

    Article Snippet: Membranes were blocked for 15 minutes in Everyblot blocking buffer (Bio-Rad # 12010020) then incubated overnight at 4°C with primary antibodies against CREB5 (Proteintech, #14196-1-AP, 1:500 dilution), p-CREB (Cell Signaling Technology, #9198, 1:500), EGFR (Proteintech, # 66455-1-Ig),p-EGFR (Cell Signaling Technology, #3777), p-ATF2(Cell Signaling Technology, # 24329, 1:300), SOX5 (Proteintech, #13216-1-AP, 1:500), FOXO1 (Proteintech, #18592-1-AP, 1:500), EGFR (Proteintech, #66455-1-Ig), GAPDH (Thermo Fisher Scientific, #MA5-15738), ɑ-tubulin (11224-1-AP), or beta-actin (Cell Signaling Technology, #3700).

    Techniques: RNA Sequencing, Derivative Assay, Western Blot, Knockdown, Cell Culture, Control, Gene Expression, Expressing, Functional Assay, Lysis, Quantitative RT-PCR

    EGFR signaling regulates CREB5 activation and synovial fibroblast lineage identity in a cell density–dependent manner. A. Schematic diagram of the experimental design and timelines. B. UMAP representation of single-cell spatial transcriptomic profiles from synovial fibroblasts colored by condition (control vs. siRNA knockdown). C. UMAP plot of synovial fibroblasts grouped by density and EGFR KD condition. (Left) Cells colored by density state (high vs. low) highlight the separation of lining-like and sublining-like populations. (Right) Cells colored by experimental conditions showing control (high and low density) versus EGFR knockdown ( EGFR _high and EGFR _low). D. Heatmap showing UCell scores for low-density gene signatures across all knockdown conditions at high cell density (600 cells/mm²). Each column represents a different knockdown condition or control. The color gradient indicates the strength of a low-density UCell score. E. Violin plots showing the distribution of CLU and PDPN expression in synovial fibroblasts across control and EGFR KD conditions. The x-axis represents experimental conditions and the y-axis represents normalized gene expression. F. Representative immunoblots of total EGFR, pEGFR (Y1068), pCREB5 (T61), and total CREB5 in synovial fibroblasts following HB-EGF stimulation or EGFR KD, cultured at low (20 cells/mm²) or high (100 cells/mm²) density, with α-tubulin as loading control. G. Quantification of EGFR, pEGFR (Y1068), pCREB5 (T61), and total CREB5 immunoblots, normalized to α-tubulin as a loading control. H. qRT-PCR analysis of lining ( PRG4 and CLU ) and sublining marker ( CD90 and POSTN ) expression in synovial fibroblasts cultured at varying cell densities under control or EGFR KD conditions. Data represent biological triplicates, with P values indicated above the bars.

    Journal: bioRxiv

    Article Title: Fibroblasts sense spatial proximity via an EGFR–CREB5 axis to restore quiescent synovial lining in remission rheumatoid arthritis

    doi: 10.64898/2025.12.10.693501

    Figure Lengend Snippet: EGFR signaling regulates CREB5 activation and synovial fibroblast lineage identity in a cell density–dependent manner. A. Schematic diagram of the experimental design and timelines. B. UMAP representation of single-cell spatial transcriptomic profiles from synovial fibroblasts colored by condition (control vs. siRNA knockdown). C. UMAP plot of synovial fibroblasts grouped by density and EGFR KD condition. (Left) Cells colored by density state (high vs. low) highlight the separation of lining-like and sublining-like populations. (Right) Cells colored by experimental conditions showing control (high and low density) versus EGFR knockdown ( EGFR _high and EGFR _low). D. Heatmap showing UCell scores for low-density gene signatures across all knockdown conditions at high cell density (600 cells/mm²). Each column represents a different knockdown condition or control. The color gradient indicates the strength of a low-density UCell score. E. Violin plots showing the distribution of CLU and PDPN expression in synovial fibroblasts across control and EGFR KD conditions. The x-axis represents experimental conditions and the y-axis represents normalized gene expression. F. Representative immunoblots of total EGFR, pEGFR (Y1068), pCREB5 (T61), and total CREB5 in synovial fibroblasts following HB-EGF stimulation or EGFR KD, cultured at low (20 cells/mm²) or high (100 cells/mm²) density, with α-tubulin as loading control. G. Quantification of EGFR, pEGFR (Y1068), pCREB5 (T61), and total CREB5 immunoblots, normalized to α-tubulin as a loading control. H. qRT-PCR analysis of lining ( PRG4 and CLU ) and sublining marker ( CD90 and POSTN ) expression in synovial fibroblasts cultured at varying cell densities under control or EGFR KD conditions. Data represent biological triplicates, with P values indicated above the bars.

    Article Snippet: Membranes were blocked for 15 minutes in Everyblot blocking buffer (Bio-Rad # 12010020) then incubated overnight at 4°C with primary antibodies against CREB5 (Proteintech, #14196-1-AP, 1:500 dilution), p-CREB (Cell Signaling Technology, #9198, 1:500), EGFR (Proteintech, # 66455-1-Ig),p-EGFR (Cell Signaling Technology, #3777), p-ATF2(Cell Signaling Technology, # 24329, 1:300), SOX5 (Proteintech, #13216-1-AP, 1:500), FOXO1 (Proteintech, #18592-1-AP, 1:500), EGFR (Proteintech, #66455-1-Ig), GAPDH (Thermo Fisher Scientific, #MA5-15738), ɑ-tubulin (11224-1-AP), or beta-actin (Cell Signaling Technology, #3700).

    Techniques: Activation Assay, Control, Knockdown, Expressing, Gene Expression, Western Blot, Cell Culture, Quantitative RT-PCR, Marker

    HB-EGF–EGFR–CREB5 signaling drives density-dependent lining fibroblast differentiation. A. Representative immunoblots of pCREB5 (T61) and total CREB5 in synovial fibroblasts cultured at high density (100 cells/mm²) following stimulation with EGF, HB-EGF, or TGFα (100 ng/ml, 10 min) or no stimulation (control), with GAPDH as loading control. B. Quantification of pCREB5 (T61) and total CREB5 in immunoblots of ligand stimulation, normalized to GAPDH as a loading control. C. qRT-PCR analysis of lining ( PRG4 and CLU ) and sublining marker ( POSTN and COL1A1 ) expression in synovial fibroblasts cultured at low (20 cells/mm²) and high (100 cells/mm²) densities after stimulation for 72 hours with HB-EGF (100 ng/ml), or without stimulation (control). Data represent biological triplicates, with P values indicated above the bars. D. qRT-PCR analysis of lining ( PRG4 and CLU ) and sublining marker ( POSTN and COL1A1 ) expression in synovial fibroblasts cultured at low (20 cells/mm²) and high (100 cells/mm²) densities after HBEGF KD. Data represent biological triplicates, with P values indicated above the bars. E. Representative immunoblots of pCREB5 (T61) and total CREB5 in synovial fibroblasts cultured at low density (20 cells/mm²) or high density (100 cells/mm²) following HBEGF KD, F. Quantification of pCREB5 (T61) and total CREB5 in immunoblots of HBEGF KD, normalized to α-tubulin as a loading control. G. Spatial distribution of lining and sublining fibroblasts in RA patient tissue, with gene expression mapped for CREB5 , HBEGF , and EGFR . H. Model of density-dependent fibroblast differentiation through HB-EGF/EGFR-CREB5 signaling

    Journal: bioRxiv

    Article Title: Fibroblasts sense spatial proximity via an EGFR–CREB5 axis to restore quiescent synovial lining in remission rheumatoid arthritis

    doi: 10.64898/2025.12.10.693501

    Figure Lengend Snippet: HB-EGF–EGFR–CREB5 signaling drives density-dependent lining fibroblast differentiation. A. Representative immunoblots of pCREB5 (T61) and total CREB5 in synovial fibroblasts cultured at high density (100 cells/mm²) following stimulation with EGF, HB-EGF, or TGFα (100 ng/ml, 10 min) or no stimulation (control), with GAPDH as loading control. B. Quantification of pCREB5 (T61) and total CREB5 in immunoblots of ligand stimulation, normalized to GAPDH as a loading control. C. qRT-PCR analysis of lining ( PRG4 and CLU ) and sublining marker ( POSTN and COL1A1 ) expression in synovial fibroblasts cultured at low (20 cells/mm²) and high (100 cells/mm²) densities after stimulation for 72 hours with HB-EGF (100 ng/ml), or without stimulation (control). Data represent biological triplicates, with P values indicated above the bars. D. qRT-PCR analysis of lining ( PRG4 and CLU ) and sublining marker ( POSTN and COL1A1 ) expression in synovial fibroblasts cultured at low (20 cells/mm²) and high (100 cells/mm²) densities after HBEGF KD. Data represent biological triplicates, with P values indicated above the bars. E. Representative immunoblots of pCREB5 (T61) and total CREB5 in synovial fibroblasts cultured at low density (20 cells/mm²) or high density (100 cells/mm²) following HBEGF KD, F. Quantification of pCREB5 (T61) and total CREB5 in immunoblots of HBEGF KD, normalized to α-tubulin as a loading control. G. Spatial distribution of lining and sublining fibroblasts in RA patient tissue, with gene expression mapped for CREB5 , HBEGF , and EGFR . H. Model of density-dependent fibroblast differentiation through HB-EGF/EGFR-CREB5 signaling

    Article Snippet: Membranes were blocked for 15 minutes in Everyblot blocking buffer (Bio-Rad # 12010020) then incubated overnight at 4°C with primary antibodies against CREB5 (Proteintech, #14196-1-AP, 1:500 dilution), p-CREB (Cell Signaling Technology, #9198, 1:500), EGFR (Proteintech, # 66455-1-Ig),p-EGFR (Cell Signaling Technology, #3777), p-ATF2(Cell Signaling Technology, # 24329, 1:300), SOX5 (Proteintech, #13216-1-AP, 1:500), FOXO1 (Proteintech, #18592-1-AP, 1:500), EGFR (Proteintech, #66455-1-Ig), GAPDH (Thermo Fisher Scientific, #MA5-15738), ɑ-tubulin (11224-1-AP), or beta-actin (Cell Signaling Technology, #3700).

    Techniques: Western Blot, Cell Culture, Control, Quantitative RT-PCR, Marker, Expressing, Gene Expression

    CREB5 played a crucial role in the maturation of chicken Sertoli cells. A Statistical analysis of the number of differentially expressed genes between mature and immature Sertoli cells. Red represents the number of upregulated genes, and blue represents the number of downregulated genes. B A dot bubble chart showing representative GO terms enriched in differentially expressed genes. C Expression patterns of representative genes of mature and immature Sertoli cells. D A dot bubble chart showing representative KEGG pathways enriched in differentially expressed genes. E A chord plot showing the subordinate relationship between representative genes (Left) and KEGG pathways (Right). The color of the boxes in front of the gene names from blue to red represents the fold change in gene expression. F Schematic of Sertoli cell extraction and CREB5 interference. G and H The mRNA and protein expression of CREB5. I and J The mRNA and protein expression of ZO-1, and occludin in chicken Sertoli cells ( n = 3). K The mRNA expression of AR , LAMA5 , NOTCH2 in chicken Sertoli cells ( n = 3). * P < 0.05, ** P < 0.01

    Journal: Journal of Animal Science and Biotechnology

    Article Title: Unique Sertoli cell adaptations support enhanced spermatogenesis in chickens

    doi: 10.1186/s40104-025-01304-8

    Figure Lengend Snippet: CREB5 played a crucial role in the maturation of chicken Sertoli cells. A Statistical analysis of the number of differentially expressed genes between mature and immature Sertoli cells. Red represents the number of upregulated genes, and blue represents the number of downregulated genes. B A dot bubble chart showing representative GO terms enriched in differentially expressed genes. C Expression patterns of representative genes of mature and immature Sertoli cells. D A dot bubble chart showing representative KEGG pathways enriched in differentially expressed genes. E A chord plot showing the subordinate relationship between representative genes (Left) and KEGG pathways (Right). The color of the boxes in front of the gene names from blue to red represents the fold change in gene expression. F Schematic of Sertoli cell extraction and CREB5 interference. G and H The mRNA and protein expression of CREB5. I and J The mRNA and protein expression of ZO-1, and occludin in chicken Sertoli cells ( n = 3). K The mRNA expression of AR , LAMA5 , NOTCH2 in chicken Sertoli cells ( n = 3). * P < 0.05, ** P < 0.01

    Article Snippet: After blocked with 5% non-fat milk for 1 h, the membranes were incubated overnight at 4 °C with primary antibodies, including CREB5 (Proteintech, Cat# 14196-1-AP), NPAS2 (Santa cruz, Cat# sc-134404), RORα (Proteintech, Cat# 10616-1-AP), ZO-1 (Proteintech, Cat# 21773-1-AP), occludin (Proteintech, Cat# 27260-1-AP), STAR (OmnimAbs, Cat# OM153513 ), HSD3B1 (abcam, Cat# ab65156), CYP11A1 (CellSignalingTechnology, Cat# 14217).

    Techniques: Expressing, Gene Expression, Extraction

    Identification of Ferroptosis-Related Differentially Expressed Genes (FRDEGs) in Alopecia Areata (AA). ( a ) Volcano plot illustrating differentially expressed genes (DEGs) in the GSE68801 dataset, revealing a total of 711 DEGs between AA patients and normal controls (NC), with 355 genes down-regulated and 356 genes up-regulated. ( b ) Venn diagram depicting the overlap between DEGs and ferroptosis-related genes (FRGs), identifying 6 FRDEGs, of which 4 were down-regulated and 2 were up-regulated. ( c ) Heatmap displaying the expression profiles of FRDEGs, highlighting that ALOX15 and ALOX12B are highly expressed in AA, while LCN2, CREB5, SLC7A11, and SLC40A1 are less expressed in AA. The heatmap was generated using R software (version 4.1.1, https://www.r-project.org/ ). Adjustments to font type and size were made for enhanced clarity. AA, alopecia areata; DEGs, differentially expressed genes; FRGs, ferroptosis-related genes; FRDEGs, ferroptosis-related differentially expressed genes.

    Journal: Scientific Reports

    Article Title: Identification of SLC40A1, LCN2, CREB5, and SLC7A11 as ferroptosis-related biomarkers in alopecia areata through machine learning

    doi: 10.1038/s41598-024-54278-4

    Figure Lengend Snippet: Identification of Ferroptosis-Related Differentially Expressed Genes (FRDEGs) in Alopecia Areata (AA). ( a ) Volcano plot illustrating differentially expressed genes (DEGs) in the GSE68801 dataset, revealing a total of 711 DEGs between AA patients and normal controls (NC), with 355 genes down-regulated and 356 genes up-regulated. ( b ) Venn diagram depicting the overlap between DEGs and ferroptosis-related genes (FRGs), identifying 6 FRDEGs, of which 4 were down-regulated and 2 were up-regulated. ( c ) Heatmap displaying the expression profiles of FRDEGs, highlighting that ALOX15 and ALOX12B are highly expressed in AA, while LCN2, CREB5, SLC7A11, and SLC40A1 are less expressed in AA. The heatmap was generated using R software (version 4.1.1, https://www.r-project.org/ ). Adjustments to font type and size were made for enhanced clarity. AA, alopecia areata; DEGs, differentially expressed genes; FRGs, ferroptosis-related genes; FRDEGs, ferroptosis-related differentially expressed genes.

    Article Snippet: Sections were blocked with bovine serum albumin and incubated overnight at 4 °C with antibodies against SLC40A1 (26601-1-AP, Proteintech), LCN2 (26991-1-AP, Proteintech), CREB5 (14196-1-AP, Proteintech), and SLC7A11 (26864-1-AP, Proteintech).

    Techniques: Expressing, Generated, Software

    Correlation Analysis of FRDEGs with Immune Cells (imc) and Immune Functions (imf) in Alopecia Areata (AA). This figure illustrates the correlation between ferroptosis-related differentially expressed genes (FRDEGs) and immune cell infiltration. Notably, ALOX12B and ALOX15 demonstrated a positive correlation with both imc and imf. In contrast, SLC40A1, LCN2, CREB5, and SLC7A11 showed a predominantly negative correlation with these parameters. AA, alopecia areata; imc, immune cells; imf, immune functions.

    Journal: Scientific Reports

    Article Title: Identification of SLC40A1, LCN2, CREB5, and SLC7A11 as ferroptosis-related biomarkers in alopecia areata through machine learning

    doi: 10.1038/s41598-024-54278-4

    Figure Lengend Snippet: Correlation Analysis of FRDEGs with Immune Cells (imc) and Immune Functions (imf) in Alopecia Areata (AA). This figure illustrates the correlation between ferroptosis-related differentially expressed genes (FRDEGs) and immune cell infiltration. Notably, ALOX12B and ALOX15 demonstrated a positive correlation with both imc and imf. In contrast, SLC40A1, LCN2, CREB5, and SLC7A11 showed a predominantly negative correlation with these parameters. AA, alopecia areata; imc, immune cells; imf, immune functions.

    Article Snippet: Sections were blocked with bovine serum albumin and incubated overnight at 4 °C with antibodies against SLC40A1 (26601-1-AP, Proteintech), LCN2 (26991-1-AP, Proteintech), CREB5 (14196-1-AP, Proteintech), and SLC7A11 (26864-1-AP, Proteintech).

    Techniques:

    Diagnostic Marker Gene Identification for Alopecia Areata (AA). ( a ) Displays ten-fold cross-validation in the LASSO model, with each curve representing an individual gene. ( b ) Shows feature selection in the LASSO model, highlighting optimal lambda values with vertical dashed lines. ( c ) Depicts the process of AA marker gene identification using the SVM-RFE algorithm. ( d ) Venn diagram demonstrates the overlap of genes identified by both SVM-RFE and LASSO methods. Five overlapping genes—ALOX15, SLC40A1, LCN2, CREB5, and SLC7A11—were identified as potential diagnostic markers for AA. AA, alopecia areata, SVM-RFE, support vector machine-recursive feature elimination; LASSO, least absolute shrinkage and selection operator;)

    Journal: Scientific Reports

    Article Title: Identification of SLC40A1, LCN2, CREB5, and SLC7A11 as ferroptosis-related biomarkers in alopecia areata through machine learning

    doi: 10.1038/s41598-024-54278-4

    Figure Lengend Snippet: Diagnostic Marker Gene Identification for Alopecia Areata (AA). ( a ) Displays ten-fold cross-validation in the LASSO model, with each curve representing an individual gene. ( b ) Shows feature selection in the LASSO model, highlighting optimal lambda values with vertical dashed lines. ( c ) Depicts the process of AA marker gene identification using the SVM-RFE algorithm. ( d ) Venn diagram demonstrates the overlap of genes identified by both SVM-RFE and LASSO methods. Five overlapping genes—ALOX15, SLC40A1, LCN2, CREB5, and SLC7A11—were identified as potential diagnostic markers for AA. AA, alopecia areata, SVM-RFE, support vector machine-recursive feature elimination; LASSO, least absolute shrinkage and selection operator;)

    Article Snippet: Sections were blocked with bovine serum albumin and incubated overnight at 4 °C with antibodies against SLC40A1 (26601-1-AP, Proteintech), LCN2 (26991-1-AP, Proteintech), CREB5 (14196-1-AP, Proteintech), and SLC7A11 (26864-1-AP, Proteintech).

    Techniques: Diagnostic Assay, Marker, Biomarker Discovery, Selection, Plasmid Preparation

    Validation of Marker Genes for Alopecia Areata (AA). ( a ) Hierarchical validation in the GSE68801 dataset, with subgroups SAA (32 cases) and NSAA (28 cases) based on clinical parameters. SLC40A1, LCN2, CREB5, and SLC7A11 showed significantly lower expression in the SAA group. ( b ) External validation using the GSE80342 dataset (12 AA lesions, 3 NC scalps) revealed significant differences in gene expression between AA and NC groups, particularly higher expression of SLC40A1, LCN2, CREB5, and SLC7A11 in AA. AA, alopecia areata patients; NC, normal controls.

    Journal: Scientific Reports

    Article Title: Identification of SLC40A1, LCN2, CREB5, and SLC7A11 as ferroptosis-related biomarkers in alopecia areata through machine learning

    doi: 10.1038/s41598-024-54278-4

    Figure Lengend Snippet: Validation of Marker Genes for Alopecia Areata (AA). ( a ) Hierarchical validation in the GSE68801 dataset, with subgroups SAA (32 cases) and NSAA (28 cases) based on clinical parameters. SLC40A1, LCN2, CREB5, and SLC7A11 showed significantly lower expression in the SAA group. ( b ) External validation using the GSE80342 dataset (12 AA lesions, 3 NC scalps) revealed significant differences in gene expression between AA and NC groups, particularly higher expression of SLC40A1, LCN2, CREB5, and SLC7A11 in AA. AA, alopecia areata patients; NC, normal controls.

    Article Snippet: Sections were blocked with bovine serum albumin and incubated overnight at 4 °C with antibodies against SLC40A1 (26601-1-AP, Proteintech), LCN2 (26991-1-AP, Proteintech), CREB5 (14196-1-AP, Proteintech), and SLC7A11 (26864-1-AP, Proteintech).

    Techniques: Biomarker Discovery, Marker, Expressing, Gene Expression

    Differential Expression of SLC40A1, CREB5, LCN2, and SLC7A11 in Scalp Tissues of Alopecia Areata (AA) Patients and Normal Controls (NC). ( a – d ) Fluorescent micrographs depict the staining intensity of SLC40A1, CREB5, LCN2, and SLC7A11 (red), with nuclei counterstained with DAPI (blue). Quantitative analysis demonstrates a notable downregulation of SLC40A1 and CREB5 in the scalp tissues of AA patients relative to NC, as reflected by the diminished fluorescence intensity. In contrast, LCN2 and SLC7A11 show no significant change. Data are expressed as the mean ± S.E.M. Asterisks indicate statistical significance where ** P < 0.01; 'ns' denotes non-significance. Scale bar represents 500 μm. AA, alopecia areata patients; NC, normal controls; DAPI, 4',6-diamidino-2-phenylindole.

    Journal: Scientific Reports

    Article Title: Identification of SLC40A1, LCN2, CREB5, and SLC7A11 as ferroptosis-related biomarkers in alopecia areata through machine learning

    doi: 10.1038/s41598-024-54278-4

    Figure Lengend Snippet: Differential Expression of SLC40A1, CREB5, LCN2, and SLC7A11 in Scalp Tissues of Alopecia Areata (AA) Patients and Normal Controls (NC). ( a – d ) Fluorescent micrographs depict the staining intensity of SLC40A1, CREB5, LCN2, and SLC7A11 (red), with nuclei counterstained with DAPI (blue). Quantitative analysis demonstrates a notable downregulation of SLC40A1 and CREB5 in the scalp tissues of AA patients relative to NC, as reflected by the diminished fluorescence intensity. In contrast, LCN2 and SLC7A11 show no significant change. Data are expressed as the mean ± S.E.M. Asterisks indicate statistical significance where ** P < 0.01; 'ns' denotes non-significance. Scale bar represents 500 μm. AA, alopecia areata patients; NC, normal controls; DAPI, 4',6-diamidino-2-phenylindole.

    Article Snippet: Sections were blocked with bovine serum albumin and incubated overnight at 4 °C with antibodies against SLC40A1 (26601-1-AP, Proteintech), LCN2 (26991-1-AP, Proteintech), CREB5 (14196-1-AP, Proteintech), and SLC7A11 (26864-1-AP, Proteintech).

    Techniques: Quantitative Proteomics, Staining, Fluorescence