Endogenous estrogen mediates vascular reactivity and distensibility in pregnant rat mesenteric arteries
Bibliographic record
Abstract
The role of estrogen in the maternal systemic cardiovascular adaptations during pregnancy is still controversial. Female Sprague-Dawley rats were implanted at day 14 of pregnancy with either a 50-mg tamoxifen pellet (estrogen receptor blocker, n = 10) or placebo pellet (n = 10). Virgin female rats were a nonpregnant control (n = 7). At days 20-22 of pregnancy, resistance-sized mesenteric arteries were mounted onto a dual-chamber arteriograph system. Pregnancy significantly blunted the pressor response to phenylephrine [measurement of the effective concentration that yielded 50% maximum response (EC(50)) values were 1.5 +/- 0.22 vs. 0.69 +/- 0.16 microM (P < 0.05)] and enhanced vasodilation to ACh [EC(50) = 1.13 +/- 2.53 vs. 3.13 +/- 6.04 nM (P < 0.05)] compared with nonpregnant rats. However, tamoxifen treatment during pregnancy reversed these effects. Inhibition of nitric oxide (NO) synthase with N(G)-monomethyl-L-arginine (250 microM) shifted only the responses of the placebo-treated pregnant group to both phenylephrine and ACh. Arterial distensibility in the placebo-treated pregnant group was also significantly increased (P < 0.05) compared with nonpregnant and tamoxifen-treated pregnant animals. In summary, endogenous estrogen during pregnancy increases NO-dependent modulation of vessel tone and arterial distensibility.
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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 | 0.000 |
| 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".