Beneficial effects of isometric strength training on endothelial dysfunction in rats
Bibliographic record
Abstract
Using female 4-week-old Sprague-Dawley rats, we investigated the effects of 14 weeks of progressive strength isometric training on endothelium dysfunction after estrogen deficiency. We also proposed possible mechanism(s) by which such training acted on endothelium-dependent vasodilation in thoracic aortic rings. Rats were randomly divided into 4 groups of 8 rats: a sham operated group, an ovariectomized sedentary group receiving 17beta-estradiol vehicle s.c. daily, an ovariectomized sedentary group receiving a daily injection of 20 microg.kg(-1) 17beta-estradiol s.c., and an ovariectomized exercised group receiving daily s.c. vehicle. Vascular reactivity of aortic rings have been evaluated by a cumulative dose of acetylcholine (ACh), in the presence or absence of L-NAME (N-nitro-L-arginine methyl ester), indomethacin, thapsigargin, iberiotoxin, apamin, and tetraethylammonium. Ovariectomy markedly decreased the relaxation caused by ACh, whereas 17beta-estradiol treatment induced a significant increase in the relaxation elicited by ACh. Isometric exercise enhanced relaxation due to ACh. This enhancement was attenuated in the presence of L-NAME, indomethacin, thapsigargin, iberiotoxin, and apamin. Our data indicated, for the first time, that the endothelium-dependent relaxant response to ACh was markedly improved in trained ovariectomized rats. This increased vasodilation is mediated by nitric oxide, cyclooxygenase, sarco-endoplasmic reticulum Ca2+-ATPase pathways, and endothelium-derived hyperpolarizing factor. Finally, this study suggested that resistance training may provide benefits in addressing vascular dysfunction consequent to a decline in estrogen levels after menopause. However, any benefits for age-related vascular dysfunction remain to be demonstrated.
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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".