Bibliographic record
Abstract
Cardiovascular disease (CVD) is the most prevalent disease worldwide and there is intense interest in pharmaceutical approaches to reduce the burden of this chronic, aging-related condition. The sirtuin (SIRT) family of NAD(+)-dependent protein deacetylases and ADP-ribosyltransferases have emerged as exciting targets for CVD management that can impact the cardiovascular system both directly and indirectly, the latter by modulating whole body metabolism. SIRT1-4 regulate the activities of a variety of transcription factors, coregulators, and enzymes that improve metabolic control in adipose tissue, liver, skeletal muscle, and pancreas, particularly during obesity and aging. SIRT1 and 7 can control myocardial development and resist stress- and aging-associated myocardial dysfunction through the deacetylation of p53 and forkhead box O1 (FoxO1). By modulating the activity of endothelial nitric oxide synthase (eNOS), FoxO1, and p53, and the expression of angiotensin II type 1 receptor (AT1R), SIRT1 also promotes vasodilatory and regenerative functions in endothelial and smooth muscle cells of the vascular wall. Given the array of potentially beneficial effects of SIRT activation on cardiovascular health, interest in developing specific SIRT agonists is well-substantiated. Because SIRT activity depends on cellular NAD+ availability, enzymes involved in NAD+ biosynthesis, including nicotinamide phosphoribosyltransferase (Nampt), may also be valuable pharmaceutical targets for managing CVD. Herein we review the actions of the SIRT proteins on the cardiovascular system and consider the potential of modulating SIRT activity and NAD+ availability to control CVD.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".