Neuromuscular electrical stimulation and protein during bed rest increases CD11b<sup>+</sup> skeletal muscle macrophages but does not correspond to muscle size or insulin sensitivity
Bibliographic record
Abstract
With this cohort, we previously demonstrated preservation of thigh lean tissue with neuromuscular electrical stimulation combined with protein supplementation (NMES+PRO) treatment during bed rest in healthy older adults. Because macrophage polarization plays a significant role in the repair and maintenance of muscle size and insulin sensitivity, we hypothesized that muscle macrophages would be induced by NMES+PRO and would correspond to an increase in lean mass and an attenuated insulin resistance response altered by bed rest. Older adults (60–80 years old; body mass index < 30 kg/m2) underwent 5 days of bed rest and were randomized to either thrice daily treatment of NMES+PRO (n = 8) or CON (n = 8). Lean mass, insulin sensitivity, and markers of muscle macrophages, inflammation, and connective tissue were determined before and after bed rest. Glucose intolerance and insulin resistance occurred after bed rest but there was not a treatment effect (p > 0.10). Proinflammatory-like macrophages (CD11b+, CD206−) increased (p < 0.05) with NMES+PRO treatment and was different than CON. Minor changes in noncontractile tissue were observed. However, changes in muscle macrophages or extracellular matrix were not related to the preservation of thigh lean mass or insulin resistance. Daily NMES+PRO treatment during bed rest induced a muscle proinflammatory-like macrophage response and was unrelated to muscle size or metabolic function. This study is listed as clinical trial NCT02566590. Novelty Neuromuscular electrical stimulation combined with protein supplementation (NMES+PRO) increased proinflammatory-like macrophages and extracellular matrix content in older adults after bed rest. NMES+PRO changes in macrophages and noncontractile tissue macrophages were not related to muscle size preservation or insulin sensitivity.
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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".