Obesity and lipid stress inhibit carnitine acetyltransferase activity
Bibliographic record
Abstract
Carnitine acetyltransferase (CrAT) is a mitochondrial matrix enzyme that catalyzes the interconversion of acetyl-CoA and acetylcarnitine. Emerging evidence suggests that this enzyme functions as a positive regulator of total body glucose tolerance and muscle activity of pyruvate dehydrogenase (PDH), a mitochondrial enzyme complex that promotes glucose oxidation and is feedback inhibited by acetyl-CoA. Here, we used tandem mass spectrometry-based metabolic profiling to identify a negative relationship between CrAT activity and muscle content of lipid intermediates. CrAT specific activity was diminished in muscles from obese and diabetic rodents despite increased protein abundance. This reduction in enzyme activity was accompanied by muscle accumulation of long-chain acylcarnitines (LCACs) and acyl-CoAs and a decline in the acetylcarnitine/acetyl-CoA ratio. In vitro assays demonstrated that palmitoyl-CoA acts as a direct mixed-model inhibitor of CrAT. Similarly, in primary human myocytes grown in culture, nutritional and genetic manipulations that promoted mitochondrial influx of fatty acids resulted in accumulation of LCACs but a pronounced decrease of CrAT-derived short-chain acylcarnitines. These results suggest that lipid-induced antagonism of CrAT might contribute to decreased PDH activity and glucose disposal in the context of obesity and diabetes.
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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) | 0.000 | 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) | 0.001 | 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".