Resveratrol prevents angiotensin II-induced hypertrophy of vascular smooth muscle cells through the transactivation of growth factor receptors
Bibliographic record
Abstract
We previously showed that augmented levels of endogenous angiotensin II (AngII) contribute to vascular smooth muscle cell (VSMC) hypertrophy through the transactivation of growth factor receptors in spontaneously hypertensive rats. Resveratrol (RV), a polyphenolic component of red wine, has also been shown to attenuate AngII-evoked VSMC hypertrophy; however, the molecular mechanism mediating this response is obscure. The present study was therefore undertaken to examine whether RV could prevent AngII-induced VSMC hypertrophy through the transactivation of growth factor receptor and associated signaling pathways. AngII treatment of VSMC enhanced the protein synthesis that was attenuated towards control levels by RV pretreatment as well as by the inhibitors of NADPH oxidase, c-Src, and growth factor receptors. Furthermore, RV pretreatment also inhibited enhanced levels of superoxide anion, NADPH oxidase activity, increased expression of NADPH oxidase subunits, and phosphorylation of c-Src, EGF-R, PDGE-R, ERK1/2, and AKT1/2. In conclusion, these results indicate that RV attenuates AngII-induced VSMC hypertrophy through the inhibition of enhanced oxidative stress and activation of c-Src, growth factor receptors, and MAPK/AKT signaling. We suggest that RV could be used as a therapeutic agent in the treatment of vascular complications associated with hypertension and hypertrophy.
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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".