The Effects of Acute Ingestion of a High-fat Solution, compared to a High-Carbohydrate Solution, on Skeletal Muscle Oxygenation, Fat Oxidation and Performance During a 2-hour Cycling Effort Followed by a Short Time Trial in Cyclists and Triathletes
Bibliographic record
Abstract
This study aimed to determine the effects of consuming a high fat solution (HFS) compared to a high carbohydrate solution (HCS) during a cycling effort on substrate oxidation, muscle oxygenation and performance with cyclists and triathletes. Thirteen men participated in this study (age: 30.4 ± 6.3 y; height: 178.7 ± 6.1 cm; weight: 74.9 ± 6.5 kg; V̇O2 peak: 60.5 ± 7.9 mlO2×kg-1×min-1). The solutions were isocaloric (total of 720 kcal) and were consumed every 20 minutes. Each solution of HFS contained 12.78 g of lipids, 1.33 g of carbohydrates and 0.67 g of proteins, and each solution of HCS contained 28 g of carbohydrates. We measured pulmonary oxygen consumption and skeletal muscle oxygenation, using a Near Infrared Spectrometer (NIRS) during a cycling effort consisting of 2 hours at 65 % of maximal aerobic power (MAP) followed immediately by a 3-minute time-trial (TT). We observed that the consumption of the HFS increased the rate of fat oxidation at the end of the sub-maximal effort (0.61 ± 0.14 vs 0.53 ± 0.17 g×min-1, p < 0.05). We have also shown that the HFS negatively affected the performance in the TT (mean Watts: HCS: 347.0 ± 77.4 vs HFS: 326.5 ± 88.8 W; p < 0.05) and the rating of perceived exertions during the sub-maximal effort (modified Borg Perceived Exertion scale: 1–10) (mean: 3.62 ± 0.58 for HCS vs 4.16 ± 0.62 for HFS; p < 0.05). We did not observe a significant effect of the acute consumption of the HFS compared to the HCS on muscle oxygenation during the cycling effort. Finally, we observed that cyclists who demonstrated a high skeletal muscle deoxygenation relative to their pulmonary oxygen consumption (DHHb/V̇O2) had a higher fat oxidation capacity (higher Fatmax). In conclusion, even though the consumption of HFS increased the rate of fat oxidation at the end of a sub-maximal effort, it did not affect muscle oxygenation and it negatively affected performance and perceived exertion during a time-trial and caused gastro-intestinal distress in some participants. Keywords: Fat oxidation, Skeletal muscle oxygenation, Lipid supplementation, Carbohydrate supplementation, Near Infrared Spectroscopy (NIRS), Cycling, Triathlon.
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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) | 0.000 | 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 | 0.001 |
| 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".