Failed reinnervation in aging skeletal muscle
Bibliographic record
Abstract
BACKGROUND: Skeletal muscle displays a marked accumulation of denervated myofibers at advanced age, which coincides with an acceleration of muscle atrophy. METHODS: In this study, we evaluated the hypothesis that the accumulation of denervated myofibers in advanced age is due to failed reinnervation by examining muscle from young adult (YA) and very old (VO) rats and from a murine model of sporadic denervation secondary to neurotrypsin over-expression (Sarco mouse). RESULTS: Both aging rat muscle and Sarco mouse muscle exhibited marked fiber-type grouping, consistent with repeating cycles of denervation and reinnervation, yet in VO muscle, rapsyn at the endplate increased and was associated with only a 10 % decline in acetylcholine receptor (AChR) intensity, whereas in Sarco mice, there was a decline in rapsyn and a 25 % decrease in AChR intensity. Transcripts of muscle-specific kinase (21-fold), acetylcholine receptor subunits α (68-fold), ε (threefold) and γ (47-fold), neural cell adhesion molecule (66-fold), and runt-related transcription factor 1 (33-fold) were upregulated in VO muscle of the rat, consistent with the marked persistent denervation evidenced by a large proportion of very small fibers (>20 %). In the Sarco mice, there were much smaller increases in denervation transcripts (0-3.5-fold) and accumulation of very small fibers (2-6 %) compared to the VO rat, suggesting a reduced capacity for reinnervation in aging muscle. Despite the marked persistent denervation in the VO rat muscle, transcripts of neurotrophins involved in promoting axonal sprouting following denervation exhibited no increase, and several miRNAs predicted to suppress neurotrophins were elevated in VO rat. CONCLUSIONS: Our results support the hypothesis that the accumulation of denervated fibers with aging is due to failed reinnervation and that this may be affected by a limited neurotrophin response that mediates axonal sprouting following denervation.
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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".