Estrogen replacement increases matrix metalloproteinase contribution to vasoconstriction in a rat model of menopause
Bibliographic record
Abstract
OBJECTIVE: Estrogen deficiency has been implicated in the pathogenesis of postmenopausal hypertension; yet hormone replacement therapy has controversial effects on the cardiovascular risk. Surprisingly, the effects of estrogen in the aging vascular system have been understudied. Aging is associated with vascular inflammation [elevated tumor necrosis factor (TNF)]. TNF is an activator of matrix metalloproteinases (MMPs) that can have vasoactive properties by specific cleavage of big endothelin-1 (ET-1). We hypothesized that MMPs are downstream mediators of vascular dysfunction in aging/estrogen deficiency. METHODS: Aged rats (12 months) were ovariectomized (to model a menopausal phenotype) and treated with placebo, estrogen or TNF inhibitor (etanercept) for 4 weeks. Reactivity of resistance mesenteric arteries was evaluated on pressure arteriograph and vascular MMP activity measured by gelatin zymography. RESULTS: Vasoconstriction to big ET-1 was greater in menopausal (relative to cycling) phenotype, but attenuated with MMP inhibition. Estrogen replacement reduced sensitivity to big ET-1, whereas further increased the role of MMP in the constriction, which was not mediated by TNF. MMP-2 activity in the mesenteric vascular bed was greater in menopausal compared with cycling females, but returned to control levels after estrogen treatment. CONCLUSIONS: Our study indicates that MMPs are critical modulators of endothelin-mediated vasoconstriction in aging/estrogen deficiency that was not evident in cycling animals. Estrogen replacement is complex: although it reduces MMP expression, estrogen leads to a greater acute MMP modulation of vascular function. Thus, understanding the novel role of estrogen as a regulator of vascular MMPs may provide valuable insights into women's cardiovascular health issues in aging.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".