Expression of human endothelin-converting enzyme isoforms: role of angiotensin IIThis article is one of a selection of papers published in the special issue (part 1 of 2) on Forefronts in Endothelin.
Bibliographic record
Abstract
A key step in endothelin-1 (ET-1) synthesis is the proteolytic cleavage of big ET-1 by the endothelin-converting enzyme-1 (ECE-1). Four alternatively spliced isoforms, ECE-1a to ECE-1d, have been discovered; however, regulation of the expression of specific ECE-1 isoforms is not well understood. Therefore, we stimulated primary human umbilical vein endothelial cells (HUVECs) with angiotensin II (Ang II). Furthermore, expression of ECE-1 isoforms was determined in internal mammary arteries of patients undergoing coronary artery bypass grafting surgery. Patients had received one of 4 therapies: angiotensin-converting enzyme inhibitors (ACE-I), Ang II type 1 receptor blockers (ARB), HMG-CoA reductase inhibitors (statins), and a control group that had received neither ACE-I, ARB (that is, treatment not interfering in the renin-angiotensin system), nor statins. Under control conditions, ECE-1a is the dominant isoform in HUVECs (4.5+/-2.8 amol/microg RNA), followed by ECE-1c (2.7+/-1.0 amol/microg), ECE-1d (0.49+/-0.17 amol/microg), and ECE-1b (0.17+/-0.04 amol/microg). Stimulation with Ang II did not change the ECE-1 expression pattern or the ET-1 release. We found that ECE-1 mRNA expression was higher in patients treated with statins than in patients treated with ARB therapy (5.8+/-0.76 RU versus 3.0+/-0.4 RU), mainly attributed to ECE-1a. In addition, ECE-1a mRNA expression was higher in patients receiving ACE-I therapy than in patients receiving ARB therapy (1.68+/-0.27 RU versus 0.83+/-0.07 RU). We conclude that ECE-1a is the major ECE-1 isoform in primary human endothelial cells. Its expression in internal mammary arteries can be regulated by statin therapy and differs between patients with ACE-I and ARB therapy.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".