Estrogen‐mediated nitric oxide (NO) production in cultured human vascular endothelial cells
Bibliographic record
Abstract
Estrogen (E2) is reported to induce the rapid activation of endothelial nitric oxide synthase (eNOS) and NO release, resulting in vasodilation, decreased platelet adhesion and angiogenesis in the vessel wall. In this study, we have used a cell line (EA.hy926) derived from human umbilical vein endothelial cells (HUVECs) to investigate the cellular mechanism underlying E2‐induced NO synthesis. Experimentally, NO production and cytosolic free [Ca 2+ ] were monitored using the NO‐sensitive dye DAF‐FM and Fluo‐3, respectively, and agonist‐induced changes in membrane potential were recorded using patch clamp techniques. E2 dose‐dependently induced rapid increases in NO synthesis, and only modest changes in cytosolic [Ca 2+ ]. The PI3 kinase inhibitor LY294002, the E2 receptor antagonist ICI 182,780, and the eNOS inhibitor L‐NAME all blocked E2‐mediated NO synthesis. Interestingly, removal of extracellular Ca2+, buffering of cytosolic Ca 2+ by BAPTA or inhibition of SK and IK Ca‐activated K + channels by apamin and charybdotoxin did not affect NO production in response to E2, but attenuated ATP‐mediated NO synthesis. Unlike ATP or histamine, E2 did not induce hyperpolarization of endothelial cell membrane potential. These observations indicate that in human vascular endothelial cells, E2 induces rapid NO production via a cellular pathway distinct from that utilized by Ca‐mobilizing stimuli. (Funded by CIHR)
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.002 | 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".