Bibliographic record
Abstract
Given that circulating ET levels in heart failure, in particular, may reach physiological threshold for coronary constrictor responses, the primary objective of the present review is to consider coronary vessels as an important target for circulating and locally produced endothelin(s). In healthy vessels, ET-1 causes biphasic coronary responses characterized by a transient dilation of large and small arteries followed by a sustained constriction. ETB receptors are pivotal in the early dilation of resistance vessels, whereas dilation of conductance vessels may be a secondary phenomenon triggered by flow increases. Exogenous ET-1 causes coronary constriction almost exclusively through ETA receptor activation. Human and canine large epicardial coronary vessels display significant baseline ET-1 dependent tone in vitro and in vivo, an ETA-dependent process. In contrast, ETB receptors located on smooth muscle cells are apparently less important for producing constrictor responses. NO production may serve as an important counter-regulatory mechanism to limit ET-dependent effects on coronary vessels. Conversely, in a dysfunctional endothelium, the loss of NO may augment ET-1 production and activity. By lifting the ET-dependent burden from coronary vessels, ET receptor blockade should help to ensure a closer match between cardiac metabolic demand and coronary perfusion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".