Acute Dipeptidyl Peptidase-4 Inhibition Rapidly Enhances Insulin-Mediated Suppression of Endogenous Glucose Production in Mice
Bibliographic record
Abstract
Pharmacological approaches that enhance incretin action for the treatment of type 2 diabetes mellitus have recently been developed, i.e. injectable glucagon-like peptide-1 receptor (GLP-1R) agonists with prolonged plasma half-lives and orally available inhibitors of dipeptidyl peptidase (DPP)-4, the main enzyme responsible for the rapid degradation of circulating glucagon-like peptide-1 and glucose-dependent insulinotropic peptide. The mechanism(s) underlying the glucose-lowering effect of these two pharmacotherapies differs and is not yet fully understood. Here we investigated whether acute GLP-1R activation (exendin-4) or DPP-4 inhibition (des-F-sitagliptin) modulates insulin action in mice using a hyperinsulinemic euglycemic clamp. A single iv bolus of des-F-sitagliptin (11 mg/kg) was administered to mice 15 min after the start of the clamp, and its effect was compared with a 50-ng bolus of exendin-4 or the same volume of saline. Despite matched levels of plasma glucose and insulin, within 15 min the glucose infusion rate required to maintain euglycemia was significantly greater after des-F-sitagliptin compared with saline or exendin-4. This difference was entirely due to enhancement of insulin-mediated suppression of endogenous glucose production by des-F-sitagliptin, with no difference in glucose disposal rate. These findings illustrate that DPP-4 inhibition modulates glucose homeostasis through pathways distinct from those used by GLP-1R agonists in mice.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| 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".