Kinin B<sub>1</sub>receptor upregulation by angiotensin II and endothelin-1 in rat vascular smooth muscle cells: receptors and mechanisms
Bibliographic record
Abstract
Oxidative stress upregulates the kinin B(1) receptor (B(1)R) in diabetes and hypertension. Since angiotensin II (ANG II) and endothelin-1 (ET-1) are increased in these disorders, this study aims at determining the role of these two prooxidative peptides in B(1)R expression in rat vascular smooth muscle cells (VSMC). In the A10 cell line and aortic VSMC, ANG II enhanced B(1)R protein expression in a concentration- and time-dependent manner (maximal at 1 μM and 6 h). In A10 cells, ANG II (1 μM) also increased B(1)R mRNA expression at 3 h and the activation of induced B(1)R with the agonist [Sar-d-Phe(8)]-des-Arg(9)-BK (10 nM, 5 min) significantly enhanced mitogen-activated protein kinase (MAPK1/2) phosphorylation. The enhancing effect of ANG II on B(1)R protein expression in A10 cells was normalized by the AT(1) (losartan) but not by the AT(2) (PD123319) receptor antagonist. Furthermore, it was inhibited by inhibitors of phosphatidylinositol 3-kinase (wortmannin) and NF-κB (MG132) but not of MAPK (PD098059). Whereas the ET(B) receptor antagonist (BQ788) had no effect, the ET(A) receptor antagonist (BQ123) blocked the effect of ANG II at 6-8 h but not at an early time point. BQ123 and BQ788 also blocked the increasing effect of ET-1 on B(1)R protein expression. Antioxidants (N-acetyl-l-cysteine and diphenyleneiodonium) abolished ANG II- and ET-1-increased B(1)R protein expression. In conclusion, B(1)R induction is linked to oxidative stress and activation of phosphatidylinositol 3-kinase and NF-κB. The newly synthesized B(1)R is functional and can activate MAPK signaling in VSMC. The effect of ANG II is mediated by the AT(1) receptor and the subsequent activation of ET(A) through ET-1 release.
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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 | 0.001 |
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".