Locomotor trade-offs in mice selectively bred for high voluntary wheel running
Bibliographic record
Abstract
We investigated sprint performance and running economy of a unique ;mini-muscle' phenotype that evolved in response to selection for high voluntary wheel running in laboratory mice (Mus domesticus). Mice from four replicate selected (S) lines run nearly three times as far per day as four control lines. The mini-muscle phenotype, resulting from an initially rare autosomal recessive allele, has been favoured by the selection protocol, becoming fixed in one of the two S lines in which it occurred. In homozygotes, hindlimb muscle mass is halved, mass-specific muscle oxidative capacity is doubled, and the medial gastrocnemius exhibits about half the mass-specific isotonic power, less than half the mass-specific cyclic work and power, but doubled fatigue resistance. We hypothesized that mini-muscle mice would have a lower whole-animal energy cost of transport (COT), resulting from lower costs of cycling their lighter limbs, and reduced sprint speed, from reduced maximal force production. We measured sprint speed on a racetrack and slopes (incremental COT, or iCOT) and intercepts of the metabolic rate versus speed relationship during voluntary wheel running in 10 mini-muscle and 20 normal S-line females. Mini-muscle mice ran faster and farther on wheels, but for less time per day. Mini-muscle mice had significantly lower sprint speeds, indicating a functional trade-off. However, contrary to predictions, mini-muscle mice had higher COT, mainly because of higher zero-speed intercepts and postural costs (intercept-resting metabolic rate). Thus, mice with altered limb morphology after intense selection for running long distances do not necessarily run more economically.
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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".