Nitric oxide attenuates overexpression of Giα proteins in vascular smooth muscle cells from SHR: Role of ROS and ROS-mediated signaling
Bibliographic record
Abstract
Vascular smooth muscle cells (VSMC) from spontaneously hypertensive rats (SHR) exhibit decreased levels of nitric oxide (NO) that may be responsible for the overexpression of Giα proteins that has been shown as a contributing factor for the pathogenesis of hypertension in SHR. The present study was undertaken to investigate if increasing the intracellular levels of NO by NO donor S-Nitroso-N-acetyl-DL-penicillamine (SNAP) could attenuate the enhanced expression of Giα proteins in VSMC from SHR and explore the underlying mechanisms responsible for this response. The expression of Giα proteins and phosphorylation of ERK1/2, growth factor receptors and c-Src was determined by Western blotting using specific antibodies. Treatment of VSMC from SHR with SNAP for 24 hrs decreased the enhanced expression of Giα-2 and Giα-3 proteins and hyperproliferation that was not reversed by 1H (1, 2, 4) oxadiazole (4, 3-a) quinoxalin-1-one (ODQ), an inhibitor of soluble guanylyl cyclase, however, PD98059, a MEK inhibitor restored the SNAP-induced decreased expression of Giα proteins towards control levels. In addition, the increased production of superoxide anion, NAD(P)H oxidase activity, overexpression of AT1 receptor, Nox4, p22phox and p47phox proteins, enhanced levels of TBARS and protein carbonyl, increased phosphorylation of PDGF-R, EGF-R, c-Src and ERK1/2 in VSMC from SHR were all decreased to control levels by SNAP treatment. These results suggest that NO decreased the enhanced expression of Giα-2/3 proteins and hyperproliferation of VSMC from SHR by cGMP-independent mechanism and involves ROS and ROS-mediated transactivation of EGF-R/PDGF-R and MAP kinase signaling pathways.
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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".