Contribution of oxidative stress and growth factor receptor transactivation in natriuretic peptide receptor C-mediated attenuation of hyperproliferation of vascular smooth muscle cells from SHR
Bibliographic record
Abstract
Earlier studies have shown the implication of growth factor receptor activation in angiotensin II (Ang II)-induced hyperproliferation of aortic VSMC as well as in hyperproliferation of VSMC from spontaneously hypertensive rats (SHR). We previously showed that NPR-C specific agonist C-ANP4-23 attenuates the hyperproliferation of VSMC from SHR through the inhibition of MAP kinase, Giα protein signaling and overexpression of cell cycle proteins. The aim of the present study was to investigate if C-ANP4-23- mediated attenuation of hyperproliferation of VSMC from SHR also involves growth factor receptor activation and upstream signaling molecules. For this study, C-ANP 4-23 (10 nmole/kg body weight) was injected intraperitoneally into 2 week-old prehypertensive SHR and Wistar Kyoto (WKY) rats twice per week for 6 weeks. The blood pressure in SHR was significantly attenuated by C-ANP4-23 treatment. In addition, C-ANP4-23 treatment also attenuated the hyperproliferation of VSMC from SHR as well as the enhanced phosphorylation of EGF-R, PDGF-R, IGF-R and c-Src. Furthermore, the enhanced levels of superoxide anion, NADPH oxidase activity, and enhanced expression of Nox4,Nox1,Nox2 and P47phox in SHR compared to WKY rats was also significantly attenuated by C-ANP4-23 treatment. In addition, N-acetyl cysteine (NAC), a scavenger of O2-, inhibitors of growth factor receptors and of c-Src, all inhibited the overexpression of cell cycle proteins cyclin D1 and cdk4 in VSMC from SHR. These results suggest that in vivo treatment of SHR with C-ANP4-23 inhibits the enhanced oxidative stress, c-Src and EGF-R, PDGF-R, IGF-R activation which through the inhibition of overexpression of cell cycle proteins result in the attenuation of hyperproliferation of VSMC.
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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) | 0.001 | 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".