ap-1 transcription factor Search Results


c jun 24909 1 ap proteintech rabbit  (Proteintech)
96
Proteintech c jun 24909 1 ap proteintech rabbit
C Jun 24909 1 Ap Proteintech Rabbit, supplied by Proteintech, used in various techniques. Bioz Stars score: 96/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/ap-1+transcription+factor/pmc07566007__mmc1-11-58-60?v=Proteintech
Average 96 stars, based on 1 article reviews
c jun 24909 1 ap proteintech rabbit - by Bioz Stars, 2026-07
96/100 stars
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antibodies against phospho c jun n terminal kinase jnk  (Boster Bio)
93
Boster Bio antibodies against phospho c jun n terminal kinase jnk
Antibodies Against Phospho C Jun N Terminal Kinase Jnk, supplied by Boster Bio, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/ap-1+transcription+factor/pmc08784769-44-0-14?v=Boster+Bio
Average 93 stars, based on 1 article reviews
antibodies against phospho c jun n terminal kinase jnk - by Bioz Stars, 2026-07
93/100 stars
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19967s cell signaling technology d2f1e jun 22114 1 ap proteintech poly c jun  (Proteintech)
93
Proteintech 19967s cell signaling technology d2f1e jun 22114 1 ap proteintech poly c jun
19967s Cell Signaling Technology D2f1e Jun 22114 1 Ap Proteintech Poly C Jun, supplied by Proteintech, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/ap-1+transcription+factor/pmc09876972__41467_2023_36116_MOESM1_ESM-8-116-123?v=Proteintech
Average 93 stars, based on 1 article reviews
19967s cell signaling technology d2f1e jun 22114 1 ap proteintech poly c jun - by Bioz Stars, 2026-07
93/100 stars
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anti phospho jun  (Proteintech)
93
Proteintech anti phospho jun
Anti Phospho Jun, supplied by Proteintech, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/ap-1+transcription+factor/pmc13045223-297-27-28?v=Proteintech
Average 93 stars, based on 1 article reviews
anti phospho jun - by Bioz Stars, 2026-07
93/100 stars
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rabbit anti jun  (Boster Bio)
93
Boster Bio rabbit anti jun
Rabbit Anti Jun, supplied by Boster Bio, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/ap-1+transcription+factor/pmc06472107-75-59-65?v=Boster+Bio
Average 93 stars, based on 1 article reviews
rabbit anti jun - by Bioz Stars, 2026-07
93/100 stars
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junb  (Proteintech)
93
Proteintech junb
Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy <t>of</t> <t>FOSB,</t> <t>JUNB,</t> CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability
Junb, supplied by Proteintech, used in various techniques. Bioz Stars score: 93/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/ap-1+transcription+factor/pmc12465141-401-11-16?v=Proteintech
Average 93 stars, based on 1 article reviews
junb - by Bioz Stars, 2026-07
93/100 stars
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ap-1 transcription factor  (Lallemand inc)
90
Lallemand inc ap-1 transcription factor
Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy <t>of</t> <t>FOSB,</t> <t>JUNB,</t> CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability
Ap 1 Transcription Factor, supplied by Lallemand inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/ap-1+transcription+factor/pm10617104-19-2-22?v=Lallemand+inc
Average 90 stars, based on 1 article reviews
ap-1 transcription factor - by Bioz Stars, 2026-07
90/100 stars
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oligonucleotides encoding the consensus sites for the transcription factors ap-1, nf-kb, and creb  (Promega)
90
Promega oligonucleotides encoding the consensus sites for the transcription factors ap-1, nf-kb, and creb
Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy <t>of</t> <t>FOSB,</t> <t>JUNB,</t> CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability
Oligonucleotides Encoding The Consensus Sites For The Transcription Factors Ap 1, Nf Kb, And Creb, supplied by Promega, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/ap-1+transcription+factor/pm09092493-54-12-16?v=Promega
Average 90 stars, based on 1 article reviews
oligonucleotides encoding the consensus sites for the transcription factors ap-1, nf-kb, and creb - by Bioz Stars, 2026-07
90/100 stars
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ap-1 sequence  (TranScrip Partners)
90
TranScrip Partners ap-1 sequence
Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy <t>of</t> <t>FOSB,</t> <t>JUNB,</t> CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability
Ap 1 Sequence, supplied by TranScrip Partners, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/ap-1+transcription+factor/pmc06148260-213-28-31?v=TranScrip+Partners
Average 90 stars, based on 1 article reviews
ap-1 sequence - by Bioz Stars, 2026-07
90/100 stars
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ap-1 transcription factors c-jun, jund, junb, and c-fos  (PubGene Inc)
90
PubGene Inc ap-1 transcription factors c-jun, jund, junb, and c-fos
Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy <t>of</t> <t>FOSB,</t> <t>JUNB,</t> CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability
Ap 1 Transcription Factors C Jun, Jund, Junb, And C Fos, supplied by PubGene Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/ap-1+transcription+factor/pm15507668-1-8-66?v=PubGene+Inc
Average 90 stars, based on 1 article reviews
ap-1 transcription factors c-jun, jund, junb, and c-fos - by Bioz Stars, 2026-07
90/100 stars
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colorimetric ap-1 transcription factor assay kit  (Active Motif)
90
Active Motif colorimetric ap-1 transcription factor assay kit
Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy <t>of</t> <t>FOSB,</t> <t>JUNB,</t> CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability
Colorimetric Ap 1 Transcription Factor Assay Kit, supplied by Active Motif, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/ap-1+transcription+factor/pmc04285806-76-10-18?v=Active+Motif
Average 90 stars, based on 1 article reviews
colorimetric ap-1 transcription factor assay kit - by Bioz Stars, 2026-07
90/100 stars
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jun proto-oncogene, ap-1 transcription factor subunit [gallus gallus (chicken)]  (Gallus BioPharmaceuticals)
90
Gallus BioPharmaceuticals jun proto-oncogene, ap-1 transcription factor subunit [gallus gallus (chicken)]
Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy <t>of</t> <t>FOSB,</t> <t>JUNB,</t> CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability
Jun Proto Oncogene, Ap 1 Transcription Factor Subunit [Gallus Gallus (Chicken)], supplied by Gallus BioPharmaceuticals, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/ap-1+transcription+factor/pm37452378-662-0-6?v=Gallus+BioPharmaceuticals
Average 90 stars, based on 1 article reviews
jun proto-oncogene, ap-1 transcription factor subunit [gallus gallus (chicken)] - by Bioz Stars, 2026-07
90/100 stars
  Buy from Supplier

Image Search Results


Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability

Journal: BMC Biology

Article Title: Machine learning combined with omics-based approaches reveals T-lymphocyte cellular fate imbalance in abdominal aortic aneurysm

doi: 10.1186/s12915-025-02400-x

Figure Lengend Snippet: Identification of TIRS regulatory mechanisms and key biomarkers. A LASSO-based feature selection, with the optimal lambda determined when the partial likelihood deviance reached the minimum value (left). SVM-RFE-based feature selection, with root mean square error (RMSE) reached the minimum value and R -squared reached the max value (mid). Venn diagram presented the intersection of key biomarkers obtained through both algorithms (right). B Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 1 (AAA n = 80 patients, control n = 10 healthy individuals; Student’s t -test). C ROC curve demonstrating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 1. D Clinical impact plot illustrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in Abdominal Aortic Wall Dataset 2 (AAA n = 9 patients, control n = 10 healthy individuals; Student’s t -test). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Abdominal Aortic Wall Dataset 2. G Clinical impact plot demonstrating the clinical utility of key biomarkers. Again, the “Number high risk” curve is closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive power. H Aberrant expression profiles for key biomarkers in Perivascular Adipose Tissue Dataset 3 (dilated n = 30, non-dilated n = 30; Student’s t -test). I ROC curve verifying the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in Perivascular Adipose Tissue Dataset 3. J Impact plots reiterated superior predictive performance probability, indicating outstanding predictive capability

Article Snippet: The primary antibodies against FOSB (1:500, catalog No. ab184938, Abcam) and JUNB (1:50, catalog No. 10486–1-AP, Proteintech) were incubated overnight at 4 °C, followed by incubation with horseradish peroxidase conjugated secondary antibodies.

Techniques: Selection, Expressing, Control, Diagnostic Assay

Verification of key biomarkers. A Abdominal aortic wall and peripheral blood samples obtained from AAA patients. B Aberrant expression profiles for key biomarkers in the abdominal aortic wall (Inhouse Dataset 1; AAA n = 5 patients, control n = 4 healthy individuals). C ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in the abdominal aortic wall (Inhouse Dataset 1). D Clinical impact plot demonstrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in peripheral blood (Inhouse Dataset 2; AAA n = 24 patients, control n = 15 healthy individuals). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in peripheral blood (Inhouse Dataset 2). G Clinical impact plot illustrating the clinical utility of key biomarkers. Again, the “Number high risk” curve remains closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive capability. H Mice were infused with saline or Ang II (1000 ng/kg/min) + BAPN. Gross abdominal aorta images were shown. Scale bar is 1 cm. I Representative images of immunohistochemical stains for elastin fiber (Van Gieson) and representative photomicrographs of hematoxylin and eosin (H&E) staining. Scale bar is 200 μm. J – L Representative immunohistochemical staining of FOSB and JUNB in aortic cross sections. Scale bar is 50 μm. Data are expressed as mean ± SEM (control n = 3 mice, AAA n = 5 or 6 mice). Student’s t -test was utilized to compare continuous variables between the two groups

Journal: BMC Biology

Article Title: Machine learning combined with omics-based approaches reveals T-lymphocyte cellular fate imbalance in abdominal aortic aneurysm

doi: 10.1186/s12915-025-02400-x

Figure Lengend Snippet: Verification of key biomarkers. A Abdominal aortic wall and peripheral blood samples obtained from AAA patients. B Aberrant expression profiles for key biomarkers in the abdominal aortic wall (Inhouse Dataset 1; AAA n = 5 patients, control n = 4 healthy individuals). C ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in the abdominal aortic wall (Inhouse Dataset 1). D Clinical impact plot demonstrating the clinical utility of key biomarkers. The “Number high risk” curve closely aligns with the “Number high risk with the event” curve at each threshold probability, indicating exceptional predictive power. E Aberrant expression profiles for key biomarkers in peripheral blood (Inhouse Dataset 2; AAA n = 24 patients, control n = 15 healthy individuals). F ROC curve validating the diagnostic efficacy of FOSB, JUNB, CST7, and TBC1D4 in peripheral blood (Inhouse Dataset 2). G Clinical impact plot illustrating the clinical utility of key biomarkers. Again, the “Number high risk” curve remains closely aligned with the “Number high risk with the event” curve at each threshold probability, highlighting the biomarkers’ strong predictive capability. H Mice were infused with saline or Ang II (1000 ng/kg/min) + BAPN. Gross abdominal aorta images were shown. Scale bar is 1 cm. I Representative images of immunohistochemical stains for elastin fiber (Van Gieson) and representative photomicrographs of hematoxylin and eosin (H&E) staining. Scale bar is 200 μm. J – L Representative immunohistochemical staining of FOSB and JUNB in aortic cross sections. Scale bar is 50 μm. Data are expressed as mean ± SEM (control n = 3 mice, AAA n = 5 or 6 mice). Student’s t -test was utilized to compare continuous variables between the two groups

Article Snippet: The primary antibodies against FOSB (1:500, catalog No. ab184938, Abcam) and JUNB (1:50, catalog No. 10486–1-AP, Proteintech) were incubated overnight at 4 °C, followed by incubation with horseradish peroxidase conjugated secondary antibodies.

Techniques: Expressing, Control, Diagnostic Assay, Saline, Immunohistochemical staining, Staining