Nitric oxide attenuates endothelin-1-induced activation of ERK1/2, PKB, and Pyk2 in vascular smooth muscle cells by a cGMP-dependent pathway
Bibliographic record
Abstract
Nitric oxide (NO), in addition to its vasodilator action, has also been shown to antagonize the mitogenic and hypertrophic responses of growth factors and vasoactive peptides such as endothelin-1 (ET-1) in vascular smooth muscle cells (VSMCs). However, the mechanism by which NO exerts its antimitogenic and antihypertrophic effect remains unknown. Therefore, the aim of this study was to determine whether NO generation would modify ET-1-induced signaling pathways involved in cellular growth, proliferation, and hypertrophy in A-10 VSMCs. Treatment of A-10 VSMCs with S-nitroso-N-acetylpenicillamine (SNAP) or sodium nitroprusside (SNP), two NO donors, attenuated the ET-1-enhanced phosphorylation of several key components of growth-promoting and hypertrophic signaling pathways such as ERK1/2, PKB, and Pyk2. On the other hand, inhibition of the endogenous NO generation with N(G)-nitro-L-arginine methyl ester, a nitric oxide synthase inhibitor, increased the ET-1-induced phosphorylation of these signaling components. Since NO mediates its effect principally through a cGMP-soluble guanylyl cyclase (sGC) pathway, we investigated the role of these molecules in NO action. 8-Bromoguanosine 3',5'-cyclic monophosphate, a nonmetabolizable and cell-permeant analog of cGMP, exhibited a effect similar to that of SNAP and SNP. Furthermore, 1H-[1,2,4]oxadiazolo[4,3-a]quinoxalin-1-one (ODQ), an inhibitor of sGC, reversed the inhibitory effect of NO on ET-1-induced responses. SNAP treatment also decreased the protein synthesis induced by ET-1. Together, these data demonstrate that NO, in a cGMP-dependent manner, attenuated ET-1-induced phosphorylation of ERK1/2, PKB, and Pyk2 and also antagonized the hypertrophic effects of ET-1. It may be suggested that NO-induced generation of cGMP contributes to the inhibition of ET-1-induced mitogenic and hypertrophic responses in VSMCs.
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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".