ET<sub>A</sub>and ET<sub>B</sub>receptors are expressed in vascular adventitial fibroblasts
Bibliographic record
Abstract
The adventitia has been recognized to play important roles in vascular oxidative stress, remodeling, and contraction. We recently demonstrated that adventitial fibroblasts are able to express endothelin (ET)-1 in response to ANG II. However, it is unclear whether ET-1 receptors are expressed in the adventitia. We therefore investigated the expression and roles of both ET(A) and ET(B) receptors in collagen synthesis and ET-1 clearance in adventitial fibroblasts. Adventitial fibroblasts were isolated and cultured from the mouse thoracic aorta by the explant method. Cultured cells were treated with ANG II (100 nmol/l) or ET-1 (10 pM) in the presence or absence of the ANG II type 1 receptor antagonist losartan (100 μM), the ET-1 receptor antagonists BQ-123 (ET(A) receptor, 1 μM) and BQ-788 (ET(B) receptor, 1 μM), and the ET(B) receptor agonist sarafotoxin 6C (100 nM). ET-1 peptide levels were determined by ELISA, whereas ET(A), ET(B), and collagen levels were determined by Western blot analysis. ANG II increased ET-1 peptide levels in a time-dependent manner. ANG II increased ET(A) and ET(B) receptor protein levels as well as collagen in a similar fashion. ANG II-induced collagen was reduced while in the presence of BQ-123, suggesting a role for the ET(A) receptor in the regulation of the extracellular matrix. ANG II treatment in the presence of BQ-788 significantly increased ET-1 peptide levels. Conversely, the ET(B) receptor agonist sarafotoxin 6C significantly decreased ET-1 peptide levels. These data implicate a role for the ET(B) receptor in the clearance of the ET-1 peptide. In conclusion, both ET(A) and ET(B) receptors are expressed in adventitial fibroblasts, which paves the ground for the biological significance of adventitial ET-1. The ET(A) receptor subtype mediates collagen I expression, whereas the ET(B) receptor subtype may play a protective role through increasing the clearance of the ET-1 peptide.
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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 | 0.000 |
| 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".