Voluntary wheel running as a training stimulus in mouse muscle function
Bibliographic record
Abstract
This study characterized the efficacy of voluntary wheel running (VWR) to induce an adaptive exercise training response in mouse muscle. Female c57BL/6 mice were allowed free access to a running wheel for a period of 0–21 days. Following VWR access, hindlimb skeletal muscles were measured for changes in weight, contractile properties, and fatigue resistance. An organismal training response was seen as increased voluntary running activity at a rate of 1.9km/d up to day 5 and at a rate of approximately 0.4km/d through day 10 ; resulting in an average daily distance of 13.4km at the trained plateau. An in vivo training effect by VWR was also seen as a 2.4‐fold increase in performance during a treadmill‐based endurance test. Cardiovascular adaptation was evident by a 14% increase in heart weight within seven days of continuous VWR access. The VWR stimulus failed to induce skeletal muscle hypertrophy or increased contractile force. However, VWR gave rise to increased fatigue resistance, improved low‐frequency force recovery from fatigue, and increased twitch relaxation kinetics when the gastrocnemius‐plantaris muscle complex was evaluated in situ . These results support VWR as a means to induce a systemic and muscle‐based endurance training response. These data suggest that unloaded VWR is not an effective means to induce hypertrophy or increased strength in locomotory muscles of mice. By describing the normative response to VWR in mice, we are able to use this training modality as an adaptive stimulus or as an evaluative tool in the organismal and muscular response to disease states or other such perturbations. Supported in part by Shriners Hospitals for Children. JJV was an NIH‐IMSD predoctoral fellow.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.001 | 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".