One Week of Bed Rest Leads to Substantial Muscle Atrophy and Induces Whole-Body Insulin Resistance in the Absence of Skeletal Muscle Lipid Accumulation
Bibliographic record
Abstract
Short (<10 days) periods of muscle disuse, often necessary for recovery from illness or injury, lead to various negative health consequences. The current study investigated mechanisms underlying disuse-induced insulin resistance, taking into account muscle atrophy. Ten healthy, young males (age: 23 ± 1 years; BMI: 23.0 ± 0.9 kg · m(-2)) were subjected to 1 week of strict bed rest. Prior to and after bed rest, lean body mass (dual-energy X-ray absorptiometry) and quadriceps cross-sectional area (CSA; computed tomography) were assessed, and peak oxygen uptake (VO2peak) and leg strength were determined. Whole-body insulin sensitivity was measured using a hyperinsulinemic-euglycemic clamp. Additionally, muscle biopsies were collected to assess muscle lipid (fraction) content and various markers of mitochondrial and vascular content. Bed rest resulted in 1.4 ± 0.2 kg lean tissue loss and a 3.2 ± 0.9% decline in quadriceps CSA (both P < 0.01). VO2peak and one-repetition maximum declined by 6.4 ± 2.3 (P < 0.05) and 6.9 ± 1.4% (P < 0.01), respectively. Bed rest induced a 29 ± 5% decrease in whole-body insulin sensitivity (P < 0.01). This was accompanied by a decline in muscle oxidative capacity, without alterations in skeletal muscle lipid content or saturation level, markers of oxidative stress, or capillary density. In conclusion, 1 week of bed rest substantially reduces skeletal muscle mass and lowers whole-body insulin sensitivity, without affecting mechanisms implicated in high-fat diet-induced insulin resistance.
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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) | 0.001 | 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 | 0.001 |
| 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".