Exercise pretraining attenuates endotoxin-induced hemodynamic alteration in type I diabetic rats
Bibliographic record
Abstract
Higher expression of heat shock protein 72 (HSP72) reduces the mortality rate and organ damage in septic shock and prevents cardiac mitochondrial dysfunction due to lipopolysaccharide (LPS). Our hypothesis is that exercise preconditioning may increase the expression of HSP72 in heart and the nucleus tractus solitarii (NTS) of the brain to alleviate the cardiovascular dysfunction in type I diabetic rats receiving endotoxin. Wistar rats were randomly assigned to the following groups: sedentary normal, sedentary type I diabetic rats, and type I diabetic rats with exercise training. The trained rats ran on a treadmill 5 d.week-1, 30-60 min.d-1, at an intensity of 1.0 mile.h-1 (1 mile = 1.6 km) over a 3 week period. Twenty-four hours after the last training session, we compared the temporal profiles of mean arterial pressure, heart rate, cardiac output, stroke volume, and serum tumor necrosis factor alpha level in rats receiving an injection of LPS. In addition, HSP72 expression in heart and NTS from each group was determined. We found that HSP72 expression in the heart and NTS was significantly increased in diabetic rats with exercise training. After administration of LPS, the survival time was significantly longer in diabetic rats with exercise training. Additionaly, serum tumor necrosis factor alpha levels decreased as compared with those rats not receiving exercise training. Exercise training also diminished cardiovascular dysfunction in diabetic rats during endotoxemia. These data suggest that exercise may increase the expression of HSP72 in the heart and NTS to protect against the high mortality rate and attenuate cardiovascular dysfunction in diabetic rats during endotoxemia.
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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 | 0.000 |
| 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".