Regular exercise is associated with a protective metabolic phenotype in the rat heart
Bibliographic record
Abstract
Adaptation of myocardial energy substrate utilization may contribute to the cardioprotective effects of regular exercise, a possibility supported by evidence showing that pharmacological metabolic modulation is beneficial to ischemic hearts during reperfusion. Thus we tested the hypothesis that the beneficial effect of regular physical exercise on recovery from ischemia-reperfusion is associated with a protective metabolic phenotype. Function, glycolysis, and oxidation of glucose, lactate, and palmitate were measured in isolated working hearts from sedentary control (C) and treadmill-trained (T: 10 wk, 4 days/wk) female Sprague-Dawley rats submitted to 20 min ischemia and 40 min reperfusion. Training resulted in myocardial hypertrophy (1.65 +/- 0.05 vs. 1.30 +/- 0.03 g heart wet wt, P < 0.001) and improved recovery of function after ischemia by nearly 50% (P < 0.05). Glycolysis was 25-30% lower in T hearts before and after ischemia (P < 0.05), whereas rates of glucose oxidation were 45% higher before ischemia (P < 0.01). As a result, the fraction of glucose oxidized before and after ischemia was, respectively, twofold and 25% greater in T hearts (P < 0.05). Palmitate oxidation was 50-65% greater in T than in C before and after ischemia (P < 0.05), whereas lactate oxidation did not differ between groups. Alteration in content of selected enzymes and proteins, as assessed by immunoblot analysis, could not account for the reduction in glycolysis or increase in glucose and palmitate oxidation observed. Combined with the studies on the beneficial effect of pharmacological modulation of energy metabolism, the present results provide support for a role of metabolic adaptations in protecting the trained heart against ischemia-reperfusion injury.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".