Peroxisome Proliferator-Activated Receptors
Bibliographic record
Abstract
Peroxisome proliferator-activated receptors (PPAR) are nuclear receptors acting as transcription factors on numerous target genes after heterodimerization with the retinoid X receptor. PPAR-alpha and PPAR-gamma may be activated by different agonists, although the endogenous ligands are unknown. Although PPAR-alpha is mainly involved in fatty acid oxidation and expressed in liver, kidney, and skeletal muscle, and PPAR-gamma is mainly involved in fat cell differentiation and insulin sensitivity, both are expressed in smooth muscle cells and myocardium, although PPAR-gamma are scarce in the latter. Activators of PPAR-alpha such as fatty acids and fibrates, and PPAR-gamma such as thiazolidinediones have been shown to exert antiproliferative effects, antagonize angiotensin II actions in vivo and in vitro, and exert antioxidant actions inhibiting generation of reactive oxygen species and activation of inflammatory mediators on blood vessels and the heart. These agents lowered blood pressure in several models of hypertension and corrected endothelial dysfunction. They exerted anti-inflammatory and antifibrotic actions on blood vessels and the heart. With the development of dual alpha/gamma-PPAR activators, these newer agents may become interesting therapeutic agents for prevention of vascular and cardiac complications of hypertension as well as for preventative therapy in other forms of cardiovascular disease.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.045 | 0.049 |
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".