New Insights into the Interaction of Carbohydrate and Fat Metabolism During Exercise
Bibliographic record
Abstract
Fat and carbohydrate are important fuels for aerobic exercise and there can be reciprocal shifts in the proportions of carbohydrate and fat that are oxidized. The interaction between carbohydrate and fatty acid oxidation is dependent on the intracellular and extracellular metabolic environments. The availability of substrate, both from inside and outside of the muscle, and exercise intensity and duration will affect these environments. The ability of increasing fat provision to downregulate carbohydrate metabolism in the heart, diaphragm and peripheral skeletal muscle has been well studied. However, the regulation of fat metabolism in human skeletal muscle during exercise in the face of increasing carbohydrate availability and exercise intensity has not been well studied until recently. Research in the past 10 years has demonstrated that the regulation of fat metabolism is complex and involves many sites of control, including the transport of fat into the muscle cell, the binding and transport of fat in the cytoplasm, the regulation of intramuscular triacylglycerol synthesis and breakdown, and the transport of fat into the mitochondria. The discovery of proteins that assist in transporting fat across the plasma and mitochondrial membranes, the ability of these proteins to translocate to the membranes during exercise, and the new roles of adipose triglyceride lipase and hormone-sensitive lipase in regulating skeletal muscle lipolysis are examples of recent discoveries. This information has led to the proposal of mechanisms to explain the downregulation of fat metabolism that occurs in the face of increasing carbohydrate availability and when moving from moderate to intense aerobic 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".