Inhibition of Dipeptidyl Peptidase-4 Impairs Ventricular Function and Promotes Cardiac Fibrosis in High Fat–Fed Diabetic Mice
Bibliographic record
Abstract
Dipeptidyl peptidase-4 (DPP4) inhibitors used for the treatment of type 2 diabetes are cardioprotective in preclinical studies; however, some cardiovascular outcome studies revealed increased hospitalization rates for heart failure (HF) among a subset of DPP4 inhibitor-treated subjects with diabetes. We evaluated cardiovascular function in young euglycemic Dpp4(-/-) mice and in older, high fat-fed, diabetic C57BL/6J mice treated with either the glucagon-like peptide 1 receptor (GLP-1R) agonist liraglutide or the highly selective DPP4 inhibitor MK-0626. We assessed glucose metabolism, ventricular function and remodeling, and cardiac gene expression profiles linked to inflammation and fibrosis after transverse aortic constriction (TAC) surgery, a pressure-volume overload model of HF. Young euglycemic Dpp4(-/-) mice exhibited a cardioprotective response after TAC surgery or doxorubicin administration, with reduced fibrosis; however, cardiac mRNA analysis revealed increased expression of inflammation-related transcripts. Older, diabetic, high fat-fed mice treated with the GLP-1R agonist liraglutide exhibited preservation of cardiac function. In contrast, diabetic mice treated with MK-0626 exhibited modest cardiac hypertrophy, impairment of cardiac function, and dysregulated expression of genes and proteins controlling inflammation and cardiac fibrosis. These findings provide a model for the analysis of mechanisms linking fibrosis, inflammation, and impaired ventricular function to DPP4 inhibition in preclinical studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".