Exercise training improves myocardial tolerance to ischemia in male but not in female rats
Bibliographic record
Abstract
Acute exercise increases myocardial tolerance to ischemia-reperfusion (I-R) injury in male but not in female rat hearts, possibly due to a decreased heat shock protein 70 (Hsp70) response in the female hearts. This study examined whether repetitive exercise training would increase Hsp70 and myocardial tolerance to I-R injury in female rat hearts. Adaptations in myocardial manganese superoxide dismutase (MnSOD) and endothelial nitric oxide synthase (eNOS) were also assessed. Ten-week old male (M) and female (F) Sprague-Dawley rats (n = 40 total) exercise-trained for 14 wk; the last 8 wk consisted of running 1 h at 30 m/min (2% incline), 5 days/wk. Following training, left ventricle mechanical function (LVMF) was monitored for 30 min of reperfusion following 30 min of global ischemia (Langendorff procedure). Myocardial Hsp70 content was not different in M and F control groups, while increases were observed in both trained groups (M greater than F; P < 0.05). Although MnSOD content did not differ between groups, endothelial nitric oxide synthase (eNOS) levels were decreased in F, with no change in M, following training (P < 0.05). Hearts from control F demonstrated a greater recuperation of all indices of LVMF following I-R compared with control M hearts (P < 0.05). Hearts of trained M exhibited improved recovery of LVMF (left ventricular diastolic pressure, left ventricular end-diastolic pressure, +dP/dt, -dP/dt) during reperfusion compared with control M hearts (P < 0.05). In contrast, hearts of trained F did not show any change in recovery from I-R. Hence, exercise training is more beneficial to M than F in improving myocardial function following I-R 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) | 0.001 | 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) | 0.003 | 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".