Estrogen replacement restores flow-induced vasodilation in coronary arterioles of aged and ovariectomized rats
Bibliographic record
Abstract
The risk for cardiovascular disease (CVD) increases with advancing age; however, the age at which CVD risk increases significantly is delayed by more than a decade in women compared with men. This cardioprotection, which women experience until menopause, is presumably due to the presence of ovarian hormones, in particular, estrogen. The purpose of this study was to determine how age and ovarian hormones affect flow-induced vasodilation in the coronary resistance vasculature. Coronary arterioles were isolated from young (6 mo), middle-aged (14 mo), and old (24 mo) intact, ovariectomized (OVX), and ovariectomized + estrogen replaced (OVE) female Fischer-344 rats to assess flow-induced vasodilation. Advancing age impaired flow-induced dilation of coronary arterioles (young: 50 +/- 4 vs. old: 34 +/- 6; % relaxation). Ovariectomy reduced flow-induced dilation in arterioles from young females, and estrogen replacement restored vasodilation to flow. In aged females, flow-induced vasodilation of arterioles was unaltered by OVX; however, estrogen replacement improved flow-induced dilation by approximately 160%. The contribution of nitric oxide (NO) to flow-induced dilation, assessed by nitric oxide synthase (NOS) inhibition with N(G)-nitro-l-arginine methyl ester (l-NAME), declined with age. l-NAME did not alter flow-induced vasodilation in arterioles from OVX rats, regardless of age. In contrast, l-NAME reduced flow-induced vasodilation of arterioles from estrogen-replaced rats at all ages. These findings indicate that the age-induced decline of flow-induced, NO-mediated dilation in coronary arterioles of female rats is related, in part, to a loss of ovarian estrogen, and estrogen supplementation can improve flow-induced dilation, even at an advanced age.
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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) | 0.000 | 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".