Endothelin-1 induces pulmonary but not aortic smooth muscle cell migration by activating ERK1/2 MAP kinaseThis article is one of a selection of papers published in the two-part special issue entitled 20 Years of Endothelin Research.
Bibliographic record
Abstract
Endothelin 1 (ET-1) is an endogenous peptide that promotes vasoconstriction, endothelial and smooth muscle cell (SMC) proliferation, and fibrosis. ET-1 receptor antagonists are an important treatment strategy for pulmonary arterial hypertension, but less effective in systemic vascular disease. This observation suggests a special role for ET-1 in the pulmonary circulation. We hypothesized that ET-1 contributes to the pathogenesis of pulmonary arterial hypertension, in part, by promoting pulmonary vascular SMC migration. ET-1 treatment promoted migration in 3 distinct types of cultured pulmonary SMC. Pulmonary SMC migration was blocked by an ETA receptor selective agonist and a combined ETA-ETB antagonist, but not by a selective ETB antagonist. In contrast to the effect on pulmonary SMCs, ET-1 had no effect on migration of aortic SMCs. Flow cytometry showed that the ETA receptor was expressed at comparable levels on pulmonary and aortic SMCs, excluding receptor density as an explanation for the divergent effect. ET-1-induced pulmonary SMC migration was blocked by the structurally distinct MEK inhibitors PD98059 and U0126, consistent with a role for ERK1/2 MAP kinase. By Western blot in cultured cells and immunohistochemistry in ex vivo vessels, ET-1 stimulated phosphorylation of ERK1/2 as efficaciously as platelet-derived growth factor in pulmonary, but not aortic, SMCs. In conclusion, ET-1 induces SMC migration, with the ETA receptor tightly coupled to ERK1/2 phosphorylation only in the pulmonary circulation. This finding may help explain the striking difference in the efficacy of endothelin receptor blockers for pulmonary hypertension as compared to that for systemic cardiovascular disease.
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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) | 0.002 | 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".