Low energy availability reduces myofibrillar and sarcoplasmic muscle protein synthesis in trained females
Bibliographic record
Abstract
Abstract Low energy availability (LEA) describes a state where the energy intake is insufficient to cover the energy costs of both exercise energy expenditure and basal physiological body functions. LEA has been associated with various physiological consequences, such as reproductive dysfunction. However, the effect of LEA on skeletal muscle protein synthesis in females performing exercise training is still poorly understood. We conducted a randomized controlled trial to investigate the impact of LEA on daily integrated myofibrillar and sarcoplasmic muscle protein synthesis in trained females. Thirty eumenorrheic females were matched based on training history and randomized to undergo 10 days of LEA (25 kcal · kg fat‐free mass (FFM) −1 · day −1 ) or optimal energy availability (OEA, 50 kcal · kg FFM −1 · day −1 ). Before the intervention, both groups underwent a 5‐day ‘run‐in’ period with OEA. All foods were provided throughout the experimental period with a protein content of 2.2 g kg lean mass −1 · day −1 . A standardized, supervised combined resistance and cardiovascular exercise training programme was performed over the experimental period. Daily integrated muscle protein synthesis was measured by deuterium oxide (D 2 O) consumption along with changes in body composition, resting metabolic rate, blood biomarkers and 24 h nitrogen balance. We found that LEA reduced daily integrated myofibrillar and sarcoplasmic muscle protein synthesis compared with OEA. Concomitant reductions were observed in lean mass, urinary nitrogen balance, free androgen index, thyroid hormone concentrations and resting metabolic rate following LEA. These results highlight that LEA may negatively affect skeletal muscle adaptations in females performing exercise training. image Key points Low energy availability (LEA) with potential health and performance impairments is widespread among female athletes. We investigated the impact of 10 days of LEA on daily integrated myofibrillar and sarcoplasmic muscle protein synthesis in young, trained females. We show that LEA impairs myofibrillar and sarcoplasmic muscle protein synthesis in trained females performing exercise training. These findings suggest that LEA may have negative consequences for skeletal muscle adaptations and highlight the importance of ensuring adequate energy availability in female athletes.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".