Role of oxidative stress in high glucose-induced decreased expression of G<sub>i</sub>α proteins and adenylyl cyclase signaling in vascular smooth muscle cells
Bibliographic record
Abstract
We have recently shown that aorta from streptozotocin (STZ)-induced diabetic rats and A10 vascular smooth muscle cells (VSMCs) exposed to high glucose exhibited decreased levels of inhibitory guanine nucleotide regulatory protein (Gi)alpha proteins. In the present studies, we investigated the implication of oxidative stress in the hyperglycemia/diabetes-induced decreased expression of the Gialpha protein and adenylyl cyclase signaling in VSMCs by using antioxidants. The levels of Gialpha proteins were significantly decreased in A10 VSMCs exposed to high glucose and in aortic VSMCs from STZ-diabetic rats compared with control cells and were restored to control levels by antioxidants. In addition, (111)Mn-tetralis(benzoic acid porphyrin) and uric acid, scavengers of peroxynitrite, and NG-nitro-L-arginine methyl ester, an inhibitor of nitric oxide synthase but not catalase, also restored the high glucose-induced decreased expression of Gialpha proteins to the control levels in A10 VSMCs. Furthermore, the enhanced production of superoxide anion (O2-) and increased activity of NADPH oxidase in these cells were also restored to control levels by diphenyleneiodonium, an inhibitor of NADPH oxidase. In addition, the diminished inhibition of adenylyl cyclase activity by inhibitory hormones and forskolin-stimulated adenylyl cyclase activity by low concentrations of GTPgammaS as well as the enhanced stimulation of adenylyl cyclase by stimulatory agonists in hyperglycemic cells were restored to control levels by antioxidant treatments. These results suggest that high glucose-induced decreased levels of Gialpha proteins and associated signaling in A10 VSMCs may be attributed to the enhanced oxidative stress due to augmented levels of peroxynitrite and not to H2O2.
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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".