Genistein supplementation stimulates the oxytocin system in the aorta of ovariectomized rats
Bibliographic record
Abstract
OBJECTIVE: In the present study, we localized oxytocin (OT) and its receptor (OTR) in the rat aorta, and investigated whether genistein, an isoflavonic phytoestrogen, influences their expression in ovariectomized (OVX) rats deficient in estrogen. METHODS AND RESULTS: OVX Sprague-Dawley rats were randomized to the following groups: genistein (from 0.02 to 5 microg/g/day, s.c. for 10 days), estradiol (E(2,) 0.1 microg/g/day, s.c. for 10 days) or their respective vehicles. OT and OTR immunostaining was concentrated in the aortic tunica intima, suggesting their paracrine/autocrine action within endothelial cells. Reverse transcription-polymerase chain reaction analysis showed that 1 and 5 microg/g but not 0.1 microg/g genistein elevated OT mRNA (2-fold P<0.05), OTR mRNA (2.5-fold, P<0.05) and endothelial nitric oxide synthase (eNOS) mRNA (2-fold, P<0.05) in the aorta of OVX rats. In addition, genistein treatment increased estrogen receptor alpha (ERalpha) (2- to 3-fold, P<0.05) but resulted in a 50% decrease of ERbeta (P<0.05). These genistein effects were neutralized by treatment of OVX rats with the ER antagonist ICI 182,780 (1.5 microg/g/day, s.c. for 10 days). Similarly, Western blot analysis revealed an increase of 67-kDa OTR, 140-kDa eNOS, 62-kDa ERalpha and a decrease of 55-kDa ERbeta (P<0.05) in the aorta of OVX rats treated with genistein. In contrast, the treatment of OVX rats with E(2) elevated ERbeta mRNA (1.5 fold, P<0.05) but similarly to genistein increased OT, OTR, eNOS and ERalpha mRNA. CONCLUSION: These results provide the first evidence of OT and OTR co-localization in endothelial cells. The response to genistein via ER activation can be regarded as a recovery from endothelial dysfunction induced by ovariectomy.
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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".