Hydrogen Peroxide Enhances the Expression of Gi Protein in Aortic Vascular Smooth Muscle Cells : Relationship with Adenylyl Cyclase
Bibliographic record
Abstract
Reactive oxygen species (ROS) play a critical role in the pathogenesis of many diseases including hypertension, atherosclerosis, and diabetes. We have recently shown that ROS contribute to enhanced expression of G i α protein in vascular smooth muscle cells (VSMC) from spontaneously hypertensive rats (SHR). The current study was undertaken to investigate the effect of H 2 O 2 , an experimental mimicker of oxidative stress, on G i α protein expression and the implication of extracellular signal‐regulated kinase (ERK1/2), and phosphatidylinositol‐3 kinase (PI3K) signaling in H 2 O 2 ‐induced altered expression of G i α protein. Aortic VSMC were treated with different concentrations of H 2 O 2 (50 μM to 250 μM) for different periods of time (30 min to 4 hr). The protein expression was determined by Western Blotting using specific antibodies. H 2 O 2 enhanced the expression of G i α in a concentration and time‐dependent manner with a maximum increase at 100μM for 1hr, whereas G s α expression remained unchanged. The enhanced expression of G i α was demonstrated by the increased inhibition of adenylyl cyclase by inhibitory hormones such as angiotensin II, oxotremorine, and C‐ANP 4–23 . We also found that H 2 O 2 induced the phosphorylation of the serine/threonine kinases ERK1/2, and AKT/PKB (protein kinase B). Moreover, MEK, and PI3K inhibitors restored the H 2 O 2 –induced enhanced expression of G i α proteins to control levels, suggesting the implication of these proteins kinases in the enhanced level of G i α. In conclusion, the modulation of Gi protein expression by H 2 O 2 in aortic vascular smooth muscle cells involves the ERK1/2, and PI3K signaling pathways. This study was supported by the Canadian Institutes of Health Research grant
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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) | 0.002 | 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".