Role for DNA damage and epigenetic signaling in coronary artery diseases
Bibliographic record
Abstract
Coronary artery disease (CAD) is the most common cause of heart attacks. Evidence demonstrated that coronary artery stenosis have increased inflammation leading to sustained DNA damage. In cancer, through the activation of poly(ADP)ribose‐polymerase 1 (PARP‐1), a critical enzyme acting as a DNA damage sensor, and the epigenetic reader Bromodomain‐containing protein 4 (BRD4), DNA damage promotes mitochondrial/metabolic dysfunction contributing to cell proliferation. Thus, we hypothesized that increased inflammation‐induced DNA damage in remodeled coronary arteries promotes BRD4 and PARP‐1 expression, triggering CoASMC proliferation. Both coronary arteries (n=10) and primary cultured CoASMC (n=4) from patients with stenosis exhibit increased (p<0.05) DNA damage (γ‐H2AX and 53BP1), PARP‐1 and BRD4 protein expression (western blot). This pathological phenotype significantly increased (p<0.05) cell proliferation (Ki67, MTT assay) through a mitochondrial (TMRM) and metabolic dysfunction (Seahorse XF e 24) compared to control cells (n=3). Furthermore, co‐culture of CoASMC with peripheral blood mononuclear cells (PBMC) isolated from symptomatic CAD patients promotes BRD4 expression (qRT‐PCR). Finally, experimental rat model of carotid angioplasty exhibit a similar phenotype that the one seen in CAD patients. Our study suggests an important role for PARP‐1/BRD4 axis in CoASMC proliferation in CAD. A “Fonds de recherche Quebec‐Sante” graduate scholarship to Jolyane Meloche, as well as Canadian Institutes of Health Research grants and a Canadian Research Chair in Vascular Remodeling Diseases to Sebastien Bonnet supported this work.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".