Expression of ETA and ETB receptor in adventitial fibroblasts
Bibliographic record
Abstract
Objective: The adventitia has been recognized to play important roles in vascular remodeling and contraction. We recently demonstrated that adventitial fibroblasts are able to express endothelin‐1 (ET‐1) in response to angiotensin II (ANG II). However, it is unclear whether the ET‐1 receptors are expressed in the adventitia. We therefore examined the expression of both the ET A/B receptors and the roles of these two types of receptors in collagen synthesis and ET‐1 clearance in adventitial fibroblasts. Methods and Results: Adventitial fibroblasts were isolated and cultured from the thoracic mouse aorta. Cells were treated with ANG II (100 nM), the ET‐1 receptor antagonists (100 uM), BQ123 (ET A receptor) and/or BQ788 (ET B receptor). ET‐1 peptide levels were determined by ELISA, while ET A/B and collagen levels were determined by Western blot. ANG II increased ET A receptor protein as well as collagen in a similar fashion, reaching significance after 4, 6, and 24 hours treatment. ANG II induced collagen was reduced while in the presence of the ET A receptor antagonist suggesting the role of the ET A receptor in the regulation of the extracellular matrix. ANG II treatment also increased ET B receptor protein levels in time dependent manner. ANG II treatment in the presence of the ET B receptor antagonist significantly increased ET‐1 peptide levels, implicating the role of the ET B receptor in the clearance of the ET‐1 peptide. Conclusion: Both the ET A and ET B receptors are expressed in adventitial fibroblasts. The ET A receptor subtype mediates collagen I expression, while the ET B receptor 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 | 0.000 |
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".