Activating PPARα Prevents Post–Ischemic Contractile Dysfunction in Hypertrophied Neonatal Hearts
Bibliographic record
Abstract
RATIONALE: Post-ischemic contractile dysfunction is a contributor to morbidity and mortality after the surgical correction of congenital heart defects in neonatal patients. Pre-existing hypertrophy in the newborn heart can exacerbate these ischemic injuries, which may partly be due to a decreased energy supply to the heart resulting from low fatty acid β-oxidation rates. OBJECTIVE: We determined whether stimulating fatty acid β-oxidation with GW7647, a peroxisome proliferator-activated receptor-α (PPARα) activator, would improve cardiac energy production and post-ischemic functional recovery in neonatal rabbit hearts subjected to volume overload-induced cardiac hypertrophy. METHODS AND RESULTS: Volume-overload cardiac hypertrophy was produced in 7-day-old rabbits via an aorto-caval shunt, after which, the rabbits were treated with or without GW7647 (3 mg/kg per day) for 14 days. Biventricular working hearts were subjected to 35 minutes of aerobic perfusion, 25 minutes of global no-flow ischemia, and 30 minutes of aerobic reperfusion. GW7647 treatment did not prevent the development of cardiac hypertrophy, but did prevent the decline in left ventricular ejection fraction in vivo. GW7647 treatment increased cardiac fatty acid β-oxidation rates before and after ischemia, which resulted in a significant increase in overall ATP production and an improved in vitro post-ischemic functional recovery. A decrease in post-ischemic proton production and endoplasmic reticulum stress, as well as an activation of sarcoplasmic reticulum calcium ATPase isoform 2 and citrate synthase, was evident in GW7647-treated hearts. CONCLUSIONS: Stimulating fatty acid β-oxidation in neonatal hearts may present a novel cardioprotective intervention to limit post-ischemic contractile dysfunction.
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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 | 0.000 |
| 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 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".