The role of GPR30 in mediating the rapid vascular effects of aldosterone and estrogen
Bibliographic record
Abstract
Aldosterone (ALDO) and estrogen (EST) elicit acute vascular effects through rapid signaling pathways. In vascular smooth muscle cells (VSMC), ALDO and EST mediate contraction. However, the mechanisms underlying this common effect remains unclear. Therefore, we examined the role of MR and GPR30 receptors in mediating ALDO and EST rapid effects in VSMC by assessing contractile response using the silicone wrinkling assay and ERK activation by western blotting. Short term (5min) incubations with ALDO or EST (1–1000 nM) mediated dose‐dependent VSMC contraction (ALDO:EC50=43±2 nM; EST:EC50=73±3 nM) and enhanced phenylephrine (PE)‐mediated contraction. The ALDO‐ and EST‐mediated increases in PE‐induced contraction were further enhanced with expression of either MR or GPR30. In contrast to their common effects mediating contraction, short term exposure to ALDO stimulated ERK activation (146 ±7 % of control), whereas EST inhibited ERK activation (67±3% of control), with further inhibition by expression of ERα. However, expression of GPR30 enhanced ALDO mediated‐ERK activation and reversed the effect of estrogen from ERK inhibition to ERK activation (149±11% of control). In summary, these data demonstrate that estrogen and aldosterone‐mediated vascular effects are mediated both by ER and MR, in part, but suggest an important role of GPR30 in mediating VSMC contraction as well as mediating ERK activation in VSMC.
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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".