Vasopeptidase Inhibitor Omapatrilat Induces Profound Insulin Sensitization and Increases Myocardial Glucose Uptake in Zucker Fatty Rats
Bibliographic record
Abstract
BACKGROUND: ACE inhibitors (ACEIs) improve insulin resistance and prevent type 2 diabetes, possibly mediated by inhibition of bradykinin (BK) degradation. The vasopeptidase inhibitor omapatrilat (OMA) raises BK to a greater extent than ACEIs by dual enzyme inhibition, whereas its insulin-sensitizing effects and mechanisms have not been investigated. METHODS AND RESULTS: We compared the insulin-sensitizing effects of OMA, ramipril (an ACEI), losartan (an angiotensin II type 1 receptor blocker), and placebo by 2-step euglycemic hyperinsulinemic clamp in insulin-resistant Zucker fatty rats (n=6 to 7 in each group). OMA resulted in a lower rate of endogenous glucose production than placebo at baseline (35+/-5 versus 54+/-4 mmol x kg(-1) x min(-1), P<0.01), greater suppression of endogenous glucose production by low-dose insulin (73+/-11% versus 27+/-18%, P<0.05), and greater glucose disposal at high-dose insulin (135+/-5 versus 92+/-4 mmol x kg(-1) x min(-1), P<0.01). Ramipril tended to improve insulin sensitivity, but losartan did not. OMA significantly increased 2-deoxyglucose uptake by myocardium, fat, and skeletal muscle. Ramipril increased 2-deoxyglucose uptake only by some skeletal muscles, but losartan did not. The insulin-sensitizing effects of OMA were blocked significantly by HOE-140 (a BK, B2 receptor antagonist) and NG-nitro-L-arginine methyl ester (a nitric oxide synthase inhibitor) in all tissues except myocardium. CONCLUSIONS: OMA induces profound insulin sensitization and increases myocardial glucose uptake in Zucker fatty rats. This effect is greater than that of ramipril and probably occurs at least in part via stimulation of the B2 receptor. OMA has the potential for greater type 2 diabetes prevention than ACEI.
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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 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".