Pleiotropic preconditioning-like cardioprotective effects of hypolipidemic drugs in acute ischemia–reperfusion in normal and hypertensive rats
Bibliographic record
Abstract
Although pleiotropy, which is defined as multiple effects derived from a single gene, was recognized many years ago, and considerable progress has since been achieved in this field, it is not very clear how much this feature of a drug is clinically relevant. During the last decade, beneficial pleiotropic effects from hypolipidemic drugs (as in, effects that are different from the primary ones) have been associated with reduction of cardiovascular risk. As with statins, the agonists of peroxisome proliferator-activated receptors (PPARs), niacin and fibrates, have been suggested to exhibit pleiotropic activity that could significantly modify the outcome of a cardiovascular ailment. This review examines findings demonstrating the impacts of treatment with hypolipidemic drugs on cardiac response to ischemia in a setting of acute ischemia-reperfusion, in relation to PPAR activation. Specifically, it addresses the issue of susceptibility to ischemia, with particular regard to the preconditioning-like cardioprotection conferred by hypolipidemic drugs, as well as the potential molecular mechanisms behind this cardioprotection. Finally, the involvement of PPAR activation in the mechanisms of non-metabolic cardioprotective effects from hypolipidemic drugs, and their effects on normal and pathologically altered myocardium (in the hearts of hypertensive rats) is also discussed.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".