Cardioprotective effect of the PPAR ligand tetradecylthioacetic acid in type 2 diabetic mice
Bibliographic record
Abstract
Tetradecylthioacetic acid (TTA) is a novel peroxisome proliferator-activated receptor (PPAR) ligand with marked hypolipidemic and insulin-sensitizing effects in obese models. TTA has recently been shown to attenuate dyslipidemia in patients with type 2 diabetes, corroborating the potential for TTA in antidiabetic therapy. In a recent study on normal mice, we showed that TTA increased myocardial fatty acid (FA) oxidation, which was associated with decreased cardiac efficiency and impaired postischemic functional recovery. The aim of the present study was, therefore, to elucidate the effects of TTA treatment (0.5%, 8 days) on cardiac metabolism and function in a hyperlipidemic type 2 diabetic model. We found that TTA treatment increased myocardial FA oxidation, not only in nondiabetic (db/+) mice but also in diabetic (db/db) mice, despite a clear lipid-lowering effect. Although TTA had deleterious effects in hearts from nondiabetic mice (decreased efficiency and impaired mitochondrial respiratory capacity), these effects were not observed in db/db hearts. In db/db hearts, TTA improved ischemic tolerance, an effect that is most likely related to the antioxidant property of TTA. The present study strongly advocates the need for investigation of the cardiac effects of PPAR ligands used in antidiabetic/hypolipidemic therapy, because of their pleiotropic properties.
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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 | 0.002 |
| 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".