PPAR-alpha activation as a preconditioning-like intervention in rats in vivo confers myocardial protection against acute ischaemia–reperfusion injury: involvement of PI3K–Akt
Bibliographic record
Abstract
Peroxisome proliferator-activated receptors (PPAR) regulate the expression of genes involved in lipid metabolism, energy production, and inflammation. Their role in ischaemia-reperfusion (I/R) is less clear, although research indicates involvement of PPARs in some forms of preconditioning. This study aimed to explore the effects of PPAR-α activation on the I/R injury and potential cardioprotective downstream mechanisms involved. Langendorff-perfused hearts of rats pretreated with the selective PPAR-α agonist WY-14643 (WY, pirinixic acid; 3 mg·(kg body mass)·day(-1); 5 days) were subjected to 30 min ischaemia - 2 h reperfusion with or without the phosphatidylinositol 3-kinase (PI3K)-Akt inhibitor wortmannin for the evaluation of functional (left ventricular developed pressure, LVDP) recovery, infarct size (IS), and reperfusion-induced arrhythmias. A 2-fold increase in baseline PPAR-α mRNA levels (qPCR) in the WY-treated group and higher post-I/R PPAR-α levels compared with those in untreated controls were accompanied by similar changes in the expression of PPAR-α target genes PDK4 and mCPT-1, regulating glucose and fatty acid metabolism, and by enhanced Akt phosphorylation. Post-ischaemic LVDP restoration in WY-treated hearts reached 60% ± 9% of the pre-ischaemic values compared with 24% ± 3% in the control hearts (P < 0.05), coupled with reduced IS and incidence of ventricular fibrillation that was blunted by wortmannin. Results indicate that PPAR-α up-regulation may confer preconditioning-like protection via metabolic effects. Downstream mechanisms of PPAR-α-mediated cardioprotection may involve PI3K-Akt activation.
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How this classification was reachedexpand
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) | 0.000 | 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 | 0.001 |
| 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 teacher head, 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".