Exercise conditioning in old mice improves skeletal muscle regeneration
Bibliographic record
Abstract
Skeletal muscle possesses the ability to regenerate after injury, but this ability is impaired or delayed with aging. Regardless of age, muscle retains the ability to positively respond to stimuli, such as exercise. We examined whether exercise is able to improve regenerative response in skeletal muscle of aged mice. Twenty-two-month-old male C57Bl/6J mice (n = 20) underwent an 8-wk progressive exercise training protocol [old exercised (O-Ex) group]. An old sedentary (O-Sed) and a sedentary young control (Y-Ctl) group were included. Animals were subjected to injections of cardiotoxin into the tibialis anterior muscle. The tibialis anterior were harvested before [O-Ex/O-Sed/Y-Ctl control (CTL); n = 6], 10 d (O-Ex/O-Sed/Y-Ctl d 10; n = 8), and 28 d (O-Ex/O-Sed/Y-Ctl d 28; n = 6) postinjection. Average fiber cross-sectional area was reduced in all groups at d 10 (CTL: O-Ex: 2499 ± 140; O-Sed: 2320 ± 165; Y-Ctl: 2474 ± 269; d 10: O-Ex: 1191 ± 100; O-Sed: 1125 ± 99; Y-Ctl: 1481 ± 167 µm(2); P < 0.05), but was restored to control values in O-Ex and Y-Ctl groups at d 28 (O-Ex: 2257 ± 181; Y-Ctl: 2398 ± 171 µm(2); P > 0.05). Satellite cell content was greater at CTL in O-Ex (2.6 ± 0.4 satellite cells/100 fibers) compared with O-Sed (1.0 ± 0.1% satellite cells/100 fibers; P < 0.05). Exercise conditioning appears to improve ability of skeletal muscle to regenerate after injury in aged mice.-Joanisse, S., Nederveen, J. P., Baker, J. M., Snijders, T., Iacono, C., Parise, G. Exercise conditioning in old mice improves skeletal muscle regeneration.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".