Inhibition of rat aortic smooth muscle contraction by 2-methoxyestradiol
Bibliographic record
Abstract
Recent studies suggest that 2-methoxyestradiol (2-ME), an estrogen metabolite, has a similar inhibitory effect as 17beta-estradiol (E2) on vascular tone. However, it is not known whether 2-ME mediates the effects of E2 or by what mechanism 2-ME regulates smooth muscle contraction. Therefore, we compared the effects of 2-ME and E2 on rat aortic smooth muscle contraction. A preincubation with 2-ME (10 microM) for 1 h inhibited phenylephrine (PE)-induced tension in endothelium-intact, but not -denuded, tissues, whereas E2 inhibited PE-induced contraction in both preparations. The effects of 2-ME and E2 on endothelium-intact preparations were prevented by L-NAME hydrochloride (a nitric oxide synthase inhibitor). The 2-ME treatment reduced PE-induced phosphorylation of the 20-kDa myosin regulatory light chain. The inhibitory effects of 2-ME and E2 were not affected by ICI-182780 (an estrogen receptor antagonist) or actinomycin D (a gene transcription inhibitor); however, the effect of 2-ME, but not E2, was prevented by cycloheximide (a protein synthesis inhibitor). Furthermore, the effect of E2 was not blocked by 1-aminobenzotriazole (a cytochrome P-450 inhibitor) or Ro 41-0960 (a catechol-O-methyltransferase inhibitor). The effect of 2-ME was not mimicked by microtubule-interfering agents (nocodazole or Taxol). We conclude that 2-ME inhibits smooth muscle contractility through an endothelium- and nitric oxide-dependent mechanism, which does not involve estrogen receptors or microtubule disruption. The effect of 2-ME, but not E2, involves de novo protein synthesis. 2-ME does not mediate the inhibitory effect of E2 on smooth muscle contraction. These results support a potentially important role of 2-ME in the regulation of smooth muscle tone in the vasculature.
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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) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".