Fuel Selection during Prolonged Arm and Leg Exercise with 13C-Glucose Ingestion
Bibliographic record
Abstract
PURPOSE: To compare fuel selection during prolonged arm (AE) and leg exercise (LE) with water or glucose ingestion. METHODS: Ten subjects (VO2max: 4.77 +/- 0.20 and 3.36 +/- 0.15 L x min(-1) for LE and AE, respectively) completed 120 min of LE and AE at 50% of the mode-specific maximal power output (353 +/- 18 and 160 +/- 9 W, respectively) with ingestion of water (20 mL x kg(-1)) or 13C-glucose (2 g x kg(-1)). Substrate oxidation was measured using indirect respiratory calorimetry corrected for urea excretion and 13CO2 production at the mouth. RESULTS: The contribution of protein oxidation to the energy yield (%En) was higher during AE than LE (approximately 8% vs approximately 4%) because of the lower energy expenditure and was not significantly modified with glucose ingestion. With water ingestion, the %En from CHO oxidation was not significantly different during LE and AE (64 +/- 2% and 66 +/- 2%, respectively). Glucose ingestion significantly increased the %En from total CHO oxidation during AE (78 +/- 3%) but not during LE (71 +/- 2%). Exogenous glucose oxidation was not significantly different in AE and LE (56 +/- 4 and 65 +/- 3 g, respectively), but the %En from exogenous glucose was higher during AE than LE (30 +/- 1% and 24 +/- 1%) because of the lower energy expenditure. When glucose was ingested, the %En from endogenous CHO oxidation was significantly reduced during both AE (66 +/- 2% to 48 +/- 3%) and LE (64 +/- 2% to 47 +/- 3%) and was not significantly different in the two modes of exercise. CONCLUSIONS: The difference in fuel selection between AE and LE when water was ingested was modest with a slightly higher reliance on CHO oxidation during AE. The amount of exogenous glucose oxidized was lower but its %En was higher during AE because of the lower energy expenditure.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".