Increased ROS production and DNA damage in monocytes are biomarkers of aging and atherosclerosis
Bibliographic record
Abstract
New evidence demonstrates that aging and dyslipidemia are closely associated with oxidative stress, DNA damage and apoptosis in some cells and extravascular tissues. However, in monocytes, which are naturally involved in progression and/or resolution of plaque in atherosclerosis, this concurrence has not yet been fully investigated. In this study, we evaluated the influence of aging and hypercholesterolemia on serum pro-inflammatory cytokines, oxidative stress, DNA damage and apoptosis in monocytes from apolipoprotein E-deficient (apoE −/− ) mice compared with age-matched wild-type C57BL/6 (WT) mice. Experiments were performed in young (2-months) and in old (18-months) male wild-type (WT) and apoE −/− mice. Besides the expected differences in serum lipid profile and plaque formation, we observed that atherosclerotic mice exhibited a significant increase in monocytosis and in serum levels of pro-inflammatory cytokines compared to WT mice. Moreover, it was observed that the overproduction of ROS, led to an increased DNA fragmentation and, consequently, apoptosis in monocytes from normocholesterolemic old mice, which was aggravated in age-matched atherosclerotic mice. In this study, we demonstrate that a pro-inflammatory systemic status is associated with an impairment of functionality of monocytes during aging and that these parameters are fundamental extra-arterial contributors to the aggravation of atherosclerosis. The present data open new avenues for the development of future strategies with the purpose of treating atherosclerosis.
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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 | 0.001 | 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".