Changes in brain functional connectivity and muscle strength independent of elbow flexor atrophy following upper limb immobilization in young females
Bibliographic record
Abstract
Muscle disuse induces a decline in muscle strength that exceeds the rate and magnitude of muscle atrophy, suggesting that factors beyond the muscle contribute to strength loss. The purpose of this study was to characterize changes in the brain and neuromuscular system in addition to muscle size following upper limb immobilization in young females. Using a within-participant, unilateral design, 12 females (age: 20.6 ± 2.1 years) underwent 14 days of upper arm immobilization using an elbow brace and sling. Bilateral measures of muscle strength (isometric and isokinetic dynamometry), muscle size (magnetic resonance imaging), voluntary muscle activation capacity, corticospinal excitability, cortical thickness and resting-state functional connectivity were collected before and after immobilization. Immobilization induced a significant decline in isometric elbow flexion (-21.3 ± 19.2%, interaction: P = 0.0440) and extension (-19.9 ± 15.7%, interaction: P = 0.0317) strength in the immobilized arm only. There was no significant effect of immobilization on elbow flexor cross-sectional area (CSA) (-1.2 ± 2.4%, interaction: P = 0.466), whereas elbow extensor CSA decreased (-2.9 ± 2.9%, interaction: P = 0.0177) in the immobilized arm. Immobilization did not differentially alter voluntary activation capacity, corticospinal excitability, or cortical thickness (P > 0.05); however, there were significant changes in the functional connectivity of brain regions related to movement planning and error detection (P < 0.05). This study reveals that elbow flexor strength loss can occur in the absence of significant elbow flexor muscle atrophy, and that the brain represents a site of functional adaptation in response to upper limb immobilization in young females.
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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".