Intramuscular triacylglycerol utilization in human skeletal muscle during exercise: is there a controversy?
Bibliographic record
Abstract
Intramuscular triacylglyerols (IMTGs) represent a potentially important energy source for contracting human skeletal muscle. Although the majority of evidence from isotope tracer and (1)H-magnetic resonance spectroscopy (MRS) studies demonstrate IMTG utilization during exercise, controversy regarding the importance of IMTG as a metabolic substrate persists. The controversy stems from studies that measure IMTG in skeletal muscle biopsy samples and report no significant net IMTG degradation during prolonged moderate-intensity (55-70% maximal O(2) consumption) exercise lasting 90-120 min. Although postexercise decrements in IMTG levels are often reported from direct muscle measurements, the marked between-biopsy variability (approximately 23%) that has been reported with this technique in untrained subjects is larger than the expected decrease in IMTG content, effectively precluding significant findings. In contrast, recent data obtained in endurance-trained subjects demonstrated reduced variability between duplicate biopsies (approximately 12%), and significant changes in IMTG were detected after 120 min of moderate-intensity exercise. Therefore, it is our contention that the muscle biopsy, isotope tracer, and (1)H-MRS techniques report significant and energetically important oxidation of free fatty acids derived from IMTGs during prolonged moderate exercise.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.003 |
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".