Fidelity of Reinnervation Modulates Susceptibility to Aging Muscle Impact and Frailty in Elderly Women
Bibliographic record
Abstract
Background Studies in aging rodent models and elderly men have recognized skeletal muscle denervation as an important factor contributing to age‐related muscle atrophy. This has not yet been assessed in octogenarian women, a population that is at a greater risk of becoming physically frail. On this basis we determined the presence of muscle denervation in prefrail/frail elderly women and its contribution to aging muscle phenotypes compared to a population with high function in advanced age, world class octogenarian track and field athletes. Methods Muscle biopsies were obtained from vastus lateralis muscle from prefrail/frail elderly women (FE, n=17, 77.9±1.5y), master athletes (MA, n=7, 80.9±2.2y) and young inactive (YI, n=12, 24.0±1.0y) controls, to assess denervation‐induced morphological and transcriptional markers. Results The FE group displayed a high abundance of grouped slow fibers, accumulation of very small myofibers, a severe reduction in type IIa to type I size ratio, and an accumulation of neural cell adhesion molecule‐positive myofibers and pyknotic nuclei, consistent with recurring cycles of denervation/reinnervation with a sporadic occurrence of failed reinnervation in prefrail/frail subjects. The MA group exhibited a smaller decline in type IIa/I size ratio, but not attenuated fiber atrophy relative to FE, and this was associated with a higher degree of fiber type I grouping in MA vs FE, suggesting a greater reinnervation of denervated fibers in MA. Consistent with this interpretation, MA had higher mRNA levels of the reinnervation promoting cytokine Fibroblast Growth Factor Binding Protein 1 than FE. Conclusion Our results indicate that the muscle of prefrail/frail elderly women undergoes significant neurogenic atrophy, whereas MA exhibit evidence of superior reinnervation capacity that attenuates functional decline with aging by attenuating aging muscle atrophy through better retention of muscle fiber number. Support or Funding Information This work was supported by Canadian Institute of Health Research (MOP 125986 and MOP 119583 to R.T. Hepple). Part of the expenses involving older participants was supported by an Internal Grant from the Helen McCall Hutchison Family Foundation of the Montreal General Hospital. V. Sonjak was supported by the Bloomberg Manulife Fellowship. K.J. Jacob was supported by a PhD scholarship from the Fonds de recherche du Quebec – Sante (FRQS). This abstract is from the Experimental Biology 2019 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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) | 0.002 | 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".