Role of endothelin receptors on basal and endothelin-1-stimulated lung myofibroblast proliferationThis article is one of a selection of papers published in the special issue (part 1 of 2) on Forefronts in Endothelin.
Bibliographic record
Abstract
Proliferation of myofibroblasts (MYF) contributes to numerous lung disorders. Endothelin-1 (ET-1) production is increased in various lung diseases and could contribute to lung remodelling. The respective roles of ETA and ETB receptors (ETA-R, ETB-R) and the role of endogenous ET-1 production by lung MYF on proliferation of MYF remain uncertain. Rat lung MYF were isolated and 3H-thymidine and 3H-leucine incorporation assays were completed in the presence of a selective ETA-R antagonist, a selective ETB-R antagonist, or a combination of both. Receptor expression was evaluated by confocal imaging, and ET-1 levels were measured by ELISA. Confocal microscopy revealed abundant ETA-R and ETB-R expression on lung MYF. ET-1 (10 nmol/L) stimulated MYF proliferation and protein synthesis through PI3-kinase and p38 pathways. Although neither selective ETA-R blockade (BQ-123, 1 micromol/L) nor selective ETB-R blockade (BQ-788, 1 micromol/L) alone inhibited proliferation or protein synthesis, their combination almost completely abolished ET-1 mitogenic effect. Surprisingly, basal MYF proliferation was increased by selective blockade of either ETA-R or ETB-R alone, but not by dual blockade. ET-1 levels were not affected by the antagonists. Our findings indicate that both the ETA-R and the ETB-R regulate basal and stimulated lung MYF proliferation and suggest possible interactions between the receptors.
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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 | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".