A combination of genistein and magnesium enhances the vasodilatory effect via an eNOS pathway and BK<sub>Ca</sub> current amplification
Bibliographic record
Abstract
The phytoestrogen genistein (GST) and magnesium have been independently shown to regulate vascular tone; however, their individual vasodilatory effects are limited. The aim of this study was to examine the combined effects of GST plus magnesium on vascular tone in mesenteric arteries. The effects of pretreatment with GST (0-200 μmol/L), MgCl2 (0-4.8 mmol/L) and GST plus MgCl2 on 10 μmol/L phenylephrine (PE) precontracted mesenteric arteries in rats were assessed by measuring isometric force. BK(Ca) currents were detected by the patch clamp method. GST caused concentration- and partial endothelium-dependent relaxation. Magnesium resulted in dual adjustment of vascular tone. Magnesium-free solution eliminated the vasodilatation of GST in both endothelium-intact and denuded rings. GST (50 μmol/L) plus magnesium (4.8 mmol/L) caused stronger relaxation in both endothelium-intact and denuded rings. Pretreatment with the nitric oxide synthase (NOS) inhibitor L-N-nitroarginine methyl ester (L-NAME, 100 μmol/L) significantly inhibited the effects of GST, high magnesium, and the combination of GST and magnesium. BK(Ca) currents were amplified to a greater extent when GST (50 μmol/L) was combined with 4.8 versus 1.2 mmol/L Mg(2+). Our data suggest that GST plus magnesium provides enhanced vasodilatory effects in rat mesenteric arteries compared with that observed when either is used separately, which was related to an eNOS pathway and BK(Ca) current amplification.
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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".