Females have better metabolic flexibility in different metabolically challenging stimuli
Bibliographic record
Abstract
The first aim was to explore the difference in metabolic flexibility between sexes in response to changing exercise intensity under control conditions. The second aim was to evaluate metabolic flexibility between sexes in response to exercise intensity adding two different metabolically challenging stimuli (glycogen depletion and heat). Eleven males (22 ± 3 years, 176.2 ± 4 cm, 68.4 ± 4.9 kg, and 60.2 ± 4.1 mL/kg FFM/min) and nine females (22 ± 2 years, 166.7 ± 4.5 cm, 61.9 ± 2.9 kg, and 64.2 ± 5.6 mL/kg FFM/min) performed a maximal incremental exercise test (30 W every 3 min) on a cycle ergometer under three conditions: control (24 h high-carbohydrate diet followed by the incremental test), glycogen depletion (glycogen-depletion protocol followed by 24 h low-carbohydrate diet and then the incremental test), and heat (24 h high-carbohydrate diet followed by 30 min passive heating and then the incremental test in heat). In the last minute of each step, lactate was analysed, fat (FATox/FFM) and carbohydrate oxidation (CHox/FFM), and energy expenditure (EE/FFM) normalized to fat-free mass (FFM) was estimated by indirect calorimetry. Females presented a greater FATox/FFM as exercise intensity increases across conditions (control, glycogen depletion, and heat) ( p = 0.006). In contrast, CHox/FFM was not significantly different between sexes at any specific intensity across conditions ( p > 0.05). Consequently, EE/FFM was higher in females throughout the different intensities across conditions ( p = 0.002). Finally, lactate concentration was not different between sexes at the same intensities across conditions ( p = 0.87). In conclusion, females present a greater metabolic flexibility, due to the higher FATox/FFM throughout the different intensities, regardless of whether the test is performed in conditions emphasizing the oxidative pathway (glycogen depletion) or the glycolytic pathway (heat). Clinical trials: NCT05703100
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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) | 0.007 | 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".