Is There A Cessation Of Motor Unit Remodeling As A Compensatory Strategy To Age-related Motor Unit Loss?
Bibliographic record
Abstract
Despite the compensatory process of collateral reinnervation to counteract human age-related muscle fiber denervation, a substantial loss of functioning motor units (MUs) occurs which seems to be accelerated after the 7-8th decades of life. However, it is not known whether there is a limitation or cessation of this process in very old age because to date MU remodelling has not been explored in those above ~85 years of age. PURPOSE: To explore in an accessory elbow extensor muscle electrophysiological factors including, motor unit number estimations (MUNE) and measures of compensatory MU remodeling in men in their 9th and 10th decades of life. METHODS: A maximal compound muscle action potential (CMAP) was recorded from the anconeus in 8 healthy men aged to 82-91 years. Decomposition-enhanced spike-triggered averaging was used to collect surface and intramuscular electromyography (EMG) from the anconeus during a series of submaximal (30% and 50% of the maximal root mean squared (RMS) EMG of the anconeus) voluntary isometric elbow extensor contractions. In addition, motor unit potential (MUP) analysis was performed to provide a detailed assessment of neuromuscular status. RESULTS: Results were compared with a young cohort (~25y of age) published previously using the same procedures. Participants in the current study had CMAPS of ~3 mV, surface motor unit potentials (S-MUPS) of ~168 and ~232 μV at 30 and 50% RMS, resulting in a MUNE of ~23 and ~16 at the two respective intensities. In contrast young adults had CMAPS of ~5.5 mV, but similar S-MUPS of ~155 and ~240 μV at 30% and 50% RMS compared with the old. These values indicate a significant loss of muscle mass, but due to no difference in S-MUPS the old do not show signs of collateral reinnervation. CONCLUSION: Thus, compensatory remodeling may no longer be a viable process to counteract age-related loss of MUs in the very old; although this could be muscle or activity dependent. Supported by NSERC
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".