Adipose triglyceride lipase deletion from adipocytes, but not skeletal myocytes, impairs acute exercise performance in mice
Bibliographic record
Abstract
Adipose triglyceride lipase (ATGL) is the rate-limiting enzyme mediating triacylglycerol hydrolysis in virtually all cells, including adipocytes and skeletal myocytes, and hence, plays a critical role in mobilizing fatty acids. Global ATGL deficiency promotes skeletal myopathy and exercise intolerance in mice and humans, and yet the tissue-specific contributions to these phenotypes remain unknown. The goal of this study was to determine the relative contribution of ATGL-mediated triacylglycerol hydrolysis in adipocytes vs. skeletal myocytes to acute exercise performance. To achieve this goal, we generated murine models with adipocyte- and skeletal myocyte-specific targeted deletion of ATGL. We then subjected untrained mice to acute peak and submaximal exercise interventions and assessed exercise performance and energy substrate metabolism. Impaired ATGL-mediated lipolysis within adipocytes reduced peak and submaximal exercise performance, reduced peripheral energy substrate availability, shifted energy substrate preference toward carbohydrate oxidation, and decreased HSL Ser(660) phosphorylation and mitochondrial respiration within skeletal muscle. In contrast, impaired ATGL-mediated lipolysis within skeletal myocytes was not sufficient to reduce peak and submaximal exercise performance or peripheral energy substrate availability and instead tended to enhance metabolic flexibility during peak exercise. Furthermore, the expanded intramyocellular triacylglycerol pool in these mice was reduced following exercise in association with preserved HSL phosphorylation, suggesting that HSL may compensate for impaired ATGL action in skeletal muscle during exercise. These data suggest that adipocyte rather than skeletal myocyte ATGL-mediated lipolysis plays a greater role during acute exercise in part because of compensatory mechanisms that maintain lipolysis in muscle, but not adipose tissue, when ATGL is absent.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".