Gemigliptin ameliorates Western-diet-induced metabolic syndrome in mice
Bibliographic record
Abstract
Dipeptidyl peptidase 4 (DPP-4) inhibitors are widely used antihyperglycemic agents for type 2 diabetes mellitus. Recently, increasing attention has been focused on the pleiotropic actions of DPP-4 inhibitors. The aim of the present study was to examine whether gemigliptin, a recently developed DPP-4 inhibitor, could ameliorate features of metabolic syndrome. Mice were fed a Western diet (WD) for 12 weeks and were subsequently divided into 2 groups: mice fed a WD diet alone or mice fed a WD diet supplemented with gemigliptin for an additional 4 weeks. Gemigliptin treatment attenuated WD-induced body mass gain, hypercholesterolemia, adipocyte hypertrophy, and macrophage infiltration into adipose tissue, which were accompanied by an increased expression of uncoupling protein 1 in subcutaneous fat. These events contributed to improved insulin sensitivity, as assessed by the homeostasis model assessment of insulin resistance and intraperitoneal insulin tolerance test. Furthermore, gemigliptin reduced WD-induced hepatic triglyceride accumulation via inhibition of de novo lipogenesis and activation of fatty acid oxidation, which was accompanied by AMP-dependent protein kinase activation. Gemigliptin ameliorated WD-induced hepatic inflammation and fibrosis through suppression of oxidative stress. These results suggest that DPP-4 inhibitors may represent promising therapeutic agents for metabolic syndrome beyond their current role as antihyperglycemic agents.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".