Inhibition of dipeptidyl peptidase-4 averts free fatty acids deposition in the hearts of oral estrogen–progestin contraceptive-induced hyperinsulinemic female rats
Bibliographic record
Abstract
Free fatty acid (FFA) deposition in non-adipose tissues such as the heart is a characteristic of insulin resistant states which feature hyperinsulinemia and dipeptidyl peptidase-4 (DPP-4) activation. Estrogen–progestin oral contraceptives (OC) treatment reportedly increased DPP-4 activity in rat tissue, and DPP-4 inhibitors have anti-diabetic and anti-inflammatory properties. This study aims to investigate the effects of DPP-4 inhibition on cardiac FFA deposition in estrogen–progestin-treated female rats. From our data, estrogen–progestin OC exposure in female rats led to elevated plasma insulin, cardiac DPP-4 activity, FFA and triglyceride (TG) accumulation, TG/high-density lipoprotein cholesterol (TG/HDL-C) ratio, adenosine deaminase/xanthine oxidase/uric acid pathway (ADA/XO/UA), lipid peroxidation, glycogen synthase activity, and alanine phosphatase; whereas cardiac glucose-6-phosphate dehydrogenase, Na+/K+-ATPase and nitric oxide (NO) were decreased. However, DPP-4 inhibition resulted in decreased plasma insulin, cardiac DPP-4 activity, FFA, TG, TG/HDL-C ratio, and alkaline phosphatase. These were accompanied by reduced ADA/XO/UA pathway, lipid peroxidation, and augmented NO and Na+/K+-ATPase in estrogen–progestin OC-treated rats. DPP-4 inhibition attenuated cardiac lipid deposition accompanied by reduced activity in the ADA/XO/UA pathway in estrogen–progestin OC-treated female rats. DPP-4 is therefore a plausible therapeutic target in cardiometabolic disorders.
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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) | 0.000 | 0.000 |
| 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 | 0.000 | 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".