Dietary feeding pattern does not modulate the loss of muscle mass or the decline in metabolic health during short-term bed rest
Bibliographic record
Abstract
Short periods of bed rest lead to the loss of muscle mass and quality. It has been speculated that dietary feeding pattern may have an impact upon muscle protein synthesis rates and, therefore, modulate the loss of muscle mass and quality. We subjected 20 healthy men (age: 25 ± 1 yr, body mass index: 23.8 ± 0.8 kg/m2) to 1 wk of strict bed rest with intermittent (4 meals/day) or continuous (24 h/day) enteral tube feeding. Participants consumed deuterium oxide for 7 days before bed rest and throughout the 7-day bed rest period. Prior to and immediately after bed rest, lean body mass (dual energy X-ray absorptiometry), quadriceps cross-sectional area (CSA; CT), maximal oxygen uptake capacity (V̇o2peak), and whole body insulin sensitivity (hyperinsulinemic-euglycemic clamp) were assessed. Muscle biopsies were collected 7 days before, 1 day before, and immediately after bed rest to assess muscle tracer incorporation. Bed rest resulted in 0.3 ± 0.3 vs. 0.7 ± 0.4 kg lean tissue loss and a 1.1 ± 0.6 vs. 0.8 ± 0.5% decline in quadriceps CSA in the intermittent vs. continuous feeding group, respectively (both P < 0.05), with no differences between groups (both P > 0.05). Moreover, feeding pattern did not modulate the bed rest-induced decline in insulin sensitivity (−46 ± 3% vs. 39 ± 3%; P < 0.001) or V̇o2peak(−2.5 ± 2.2 vs. −8.6 ± 2.2%; P < 0.010) (both P > 0.05). Myofibrillar protein synthesis rates during bed rest did not differ between the intermittent and continuous feeding group (1.33 ± 0.07 vs. 1.50 ± 0.13%/day, respectively; P > 0.05). In conclusion, dietary feeding pattern does not modulate the loss of muscle mass or the decline in metabolic health during 1 wk of bed rest in healthy men.
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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) | 0.001 | 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".