Stress-induced senescence predominates in endothelial cells isolated from atherosclerotic chronic smokers
Bibliographic record
Abstract
Age-associated telomere shortening leads to replicative senescence of human endothelial cells (EC). Risk factors for cardiovascular disease (CVD) accelerate ageing, while there is a concomitant rise in oxidative stress known to promote stress-induced senescence (SIS) in vitro. Of all risk factors for CVD, smoking is most associated with the development of inflammation and accelerated atherosclerosis due to a prooxidant-antioxidant imbalance. We tested the hypothesis that SIS predominates in EC isolated from chronic smokers with premature atherosclerosis undergoing coronary artery bypass graft surgery (CABG). We isolated and cultured EC from segments of internal mammary arteries from smoker, former smoker, and nonsmoker coronary patients. Senescence of EC was induced by serial passage and quantified by the measurement of telomere length and senescence-associated beta-galactosidase activity. Compared with nonsmokers, smoker patients were 10 years younger at the time of CABG, evidence of premature atherosclerosis. Cellular senescence was independent of telomere length and directly related to oxidative damage. EC exhibited higher expression levels of markers of oxidative stress (lipid peroxydation level and caveolin-1 mRNA), inflammation (angiopoietin-like 2 mRNA), hypoxia (vascular endothelial growth factor (VEGF)-A mRNA), and cell damage (p53 mRNA). In conclusion, a high oxidative stress environment in EC isolated from atherosclerotic chronic smokers predisposes to SIS rather than replicative senescence.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".