Superior Indices of Neuromuscular Function in Elite Octogenarian Masters Athletes
Bibliographic record
Abstract
Aging is associated with a progressive deterioration of muscle mass and function that leads to greatest clinical impact in those 蠅80 y of age. Conversely, elite octogenarian masters athletes (MA) retain a remarkable degree of physical function. Because aging muscle is profoundly impacted by neuromuscular changes, we hypothesized that muscle of MAs would have attenuated changes in muscle morphology and neuromuscular function compared to non-athlete (NA) controls. Muscle biopsies of vastus lateralis muscle were obtained for analysis of fiber type grouping and fiber size in NA (n = 14, age: 81 ± 4 y) and elite MAs (n = 15, age: 80 ± 5 y). Motor unit number estimate, compound muscle action potential, and strength were conducted in the tibialis anterior muscle. Quadriceps area (QA) and strength (QS), and functional capacity (chair stand and stand-up & go) were also measured. Elite MAs exhibited greater QA (p = 0.015), QS (p = 0.013), and functional performance (p < 0.01) compared to NA. MAs had greater fiber size (p = 0.024), lower percentage of small fibers (< 2500µm; p = 0.031) and more fiber type grouping (p = 0.029) compared to NA. Furthermore, MAs had significantly greater motor unit number estimate and compound muscle action potential than NA. Consistent with our hypothesis, elite MAs exhibited not only superior indices of functional performance and muscle strength, but also better preserved muscle morphology and neuromuscular function including 1) fewer small fibers, 2) increased fiber type grouping (suggesting superior reinnervation), and 3) better retention of motor unit numbers versus NA.
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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 | 0.001 | 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 | 0.000 |
| 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".