Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
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.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| 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) | 0.000 | 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 it