Effect of exercise training on cardiac oxytocin and natriuretic peptide systems in ovariectomized rats
Bibliographic record
Abstract
Exercise training results in cardiovascular and metabolic adaptations that may be beneficial in menopausal women by reducing blood pressure, insulin resistance, and cholesterol level. The adaptation of the cardiac hormonal systems oxytocin (OT), natriuretic peptides (NPs), and nitric oxide synthase (NOS) in response to exercise training was investigated in intact and ovariectomized (OVX) rats. Ovariectomy significantly augmented body weight (BW), left ventricle (LV) mass, and intra-abdominal fat pad weight and decreased the expression of oxytocin receptor (OTR), atrial natriuretic peptide (ANP), brain natriuretic peptide (BNP), and guanylyl cyclase-A (GC-A), in the right atrium (RA) and LV, indicating estrogenic control of these genes. These effects of ovariectomy were counteracted by 8-wk-long exercise training which decreased fat pad weight (33.4 +/- 2.3 to 23.4 +/- 3.1 g, n = 8, P < 0.05), plasma free fatty acids (0.124 +/- 0.033 to 0.057 +/- 0.010 mM, n = 8, P < 0.01), and plasma triacylglycerol (0.978 +/- 0.174 to 0.588 +/- 0.115 mM, n = 8, P < 0.05). Chronic exercise tended to decrease BW and stimulated ANP (4- to 5-fold) and OTR gene expression in the LV and RA and BNP and inducible NOS (iNOS) mRNA in the LV. In sham-operated rats, exercise augmented ANP expression in the RA, downregulated GC-A mRNA in the LV and RA, but increased its expression threefold in the RA of OVX animals. Endothelial NOS and iNOS expression was enhanced in the left atrium of sham-operated rats. Altogether, these data indicate that in OVX animals, chronic exercise significantly enhances cardiac OT, NPs, and NOS, thus implicating all three hormonal systems in the beneficial effects of exercise training.
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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".