Cardiac diacylglycerol accumulation in high fat-fed mice is associated with impaired insulin-stimulated glucose oxidation
Bibliographic record
Abstract
AIMS: the molecular processes leading to cardiac insulin resistance induced via a high-fat diet (HFD) remain unclear. We examined the changes in cardiac insulin sensitivity and the potential mechanism(s) involved following HFD in mice. METHODS AND RESULTS: C57BL/6 mice were fed either a low-fat diet (LFD, 4% kcal fat) or a HFD (60% kcal fat) for 3 or 10 weeks. Insulin-stimulated glucose oxidation in isolated working hearts was decreased at 10 weeks of HFD compared with mice on LFD (249 ± 19 to 399 ± 46 vs. 551 ± 97 to 1464 ± 243 nmol/g dry wt/min; P < 0.05). The accumulation of myocardial diacylglycerol (DAG; 479 ± 174 vs. 266 ± 29 micromol/g wet wt; P < 0.05), but not long-chain acyl CoA, ceramide, or triacylglycerol, correlated with the development of insulin resistance. The accumulation of DAG occurred concomitantly with an increase in glycerol phosphate acyltransferase activity, a decrease in DAG acyltransferase activity, as well as an increase in the translocation of protein kinase C-α (PKCα) and phosphorylation of p70s6k. Neither HFD-induced accumulation of cardiac DAG nor up-regulation of phosphorylated p70s6k occurred in mice lacking malonyl CoA decarboxylase which are resistant to the development of HFD-induced insulin resistance. CONCLUSION: the activation of myocardial p70s6k and PKCα is closely associated with cardiac insulin resistance in which the accumulation of intra-myocardial DAG could be responsible.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".