Inhibition of endothelin-converting enzyme for protection against neointimal proliferation following balloon angioplasty of the rat carotid artery
Bibliographic record
Abstract
Clinical success of percutaneous transluminal coronary angioplasty is limited by restenosis within months of the initial intervention. A number of vasoactive mediators and growth factors have been reported to participate in this process. The aim of the present experiments was to examine the effects of nonselective neutral endopeptidase (NEPi)/endothelin-converting enzyme (ECEi) inhibitors against neointimal proliferation (NIP) following balloon angioplasty of the left carotid artery of Sprague-Dawley rats with the right vessel serving as the uninjured control. The rats were divided in several groups: group 1, nontreated (vehicle); group 2, treated with a selective NEPi i.p.; groups 3-7, treated with nonselective NEPi/ECEi either i.p., s.c., i.v., or p.o. at various doses. After 2 weeks, cross-sectional histopathological and morphometrical examination of the left carotids revealed a severe NIP in vehicle-treated angioplastic rats compared with the control uninjured right carotid of the same rats. The selective NEPi CGS 24592 had no significant effect on restenosis, nor did the dual NEPi/ECEi CGS 26303 at 5 mg x kg(-1) x day(-1) i.p. Both s.c and i.v. NEPi/ECEi treatment (10 mg x kg(-1) x day(-1) b.i.d. s.c. or 10 mg x kg(-1) x day(-1) i.v.) reduced NIP by up to 35%. The prodrug CGS 26393 (p.o.) also attenuated NIP by 23%. Plasma concentrations of these compounds correlated with the degree of inhibition. These data support the participation of the endothelin system in the rat model of balloon angioplasty and suggest that selective ECEi may be effective.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.001 | 0.000 |
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".