Angiotensin-(1-7) Through Receptor Mas Mediates Endothelial Nitric Oxide Synthase Activation via Akt-Dependent Pathways
Bibliographic record
Abstract
Angiotensin-(1-7) [Ang-(1-7)] causes endothelial-dependent vasodilation mediated, in part, by NO release. However, the molecular mechanisms involved in endothelial NO synthase (eNOS) activation by Ang-(1-7) remain unknown. Using Chinese hamster ovary cells stably transfected with Mas cDNA (Chinese hamster ovary-Mas), we evaluated the underlying mechanisms related to receptor Mas-mediated posttranslational eNOS activation and NO release. We further examined the Ang-(1-7) profile of eNOS activation in human aortic endothelial cells, which constitutively express the Mas receptor. Chinese hamster ovary-Mas cells and human aortic endothelial cell were stimulated with Ang-(1-7; 10(-7) mol/L; 1 to 30 minutes) in the absence or presence of A-779 (10(-6) mol/L). Additional experiments were performed in the presence of the phosphatidylinositol 3-kinase inhibitor wortmannin (10(-6) mol/L). Changes in eNOS (at Ser1177/Thr495 residues) and Akt phosphorylation were evaluated by Western blotting. NO release was measured using both the fluorochrome 2,3-diaminonaphthalene and an NO analyzer. Ang-(1-7) significantly stimulated eNOS activation (reciprocal phosphorylation/dephosphorylation at Ser1177/Thr495) and induced a sustained Akt phosphorylation (P<0.05). Concomitantly, a significant increase in NO release was observed (2-fold increase in relation to control). These effects were blocked by A-779. Wortmannin suppressed eNOS activation in both Chinese hamster ovary-Mas and human aortic endothelial cells. Our findings demonstrate that Ang-(1-7), through Mas, stimulates eNOS activation and NO production via Akt-dependent pathways. These novel data highlight the importance of the Ang-(1-7)/Mas axis as a putative regulator of endothelial function.
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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 | 0.001 |
| 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".