Effects of Resveratrol in Pregnancy Using Murine Models with Reduced Blood Supply to the Uterus
Bibliographic record
Abstract
Preeclampsia (PE) and fetal growth restriction (FGR) contribute significantly to fetal and maternal morbidity and mortality. Although the causes of PE and FGR are not fully understood, both conditions are known to be associated with impaired uterine artery blood flow. Resveratrol, a polyphenol found in a number of plants, has been shown to induce relaxation of uterine arteries in vitro as well as improve many pathological conditions associated with PE and FGR. We hypothesized that treatment of endothelial nitric oxide synthase knockout mice (eNOS⁻/⁻) and catechol-O-methyltransferase knockout mice (COMT⁻/⁻) with resveratrol during pregnancy would improve uterine artery blood flow and therefore ameliorate the PE-like phenotype and FGR in these murine models. Pregnant C57BL/6J, eNOS⁻/⁻ and COMT⁻/⁻ mice received either resveratrol supplemented diet (4 g/kg diet) or control diet between gestational day (GD) 0.5 and GD 18.5. Resveratrol supplementation significantly increased uterine artery blood flow velocity and fetal weight in COMT⁻/⁻ but not in eNOS⁻/⁻ mice. There were no effects of resveratrol on litter size and placental weight among the groups. In conclusion, resveratrol increased uterine artery blood flow velocity and fetal weight in COMT⁻/⁻ mice, suggesting potential as a therapeutic strategy for PE and FGR.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".