Endothelin-1 Signaling in Vascular Physiology and Pathophysiology
Bibliographic record
Abstract
The discovery of endothelin (ET) in 1988 has led to considerable effort to unravel its implication in health and disease and the mechanisms evoked by ET. ET-1 and related signaling aberrancies are believed to be implicated in the pathogenesis of diverse cardiovascular diseases, such as hypertension, atherosclerosis, hypertrophy and diabetes. The endothelin system consists of three potent vasoconstrictive isopeptides, ET-1, ET-2 and ET-3, signaling through two G protein coupled receptors, ETA and ETB, which are linked to multiple signaling pathways. Activated signaling transduction pathways include the modulation of the adenylyl cyclase/cAMP pathway through stimulatory (Gs) and inhibitory (Gi) G proteins, activation of the phosphoinositide pathway through the activation of proteins Gq/11, generation of oxidative stress, growth factor receptor-related mitogenic events, such as the activation of phosphatidylinositol-3 kinase pathway, phosphoinositide pathway and activation of the mitogen-activated protein (MAP) kinase cascade. The levels of ETA and ETB receptors as well as the signaling pathways activated by these receptors are altered in several cardiovascular diseases including hypertension, hypertrophy, atherosclerosis, diabetes, etc. In this review, we provide an overview of the signaling events modulated by ET-1 in vascular smooth muscle cells in both physiological and pathological conditions.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".