Effect of aging and exercise on the tendon
Bibliographic record
Abstract
Here, we review the literature on how tendons respond and adapt to ageing and exercise. With respect to aging, there are considerable changes early in life, but this seems to be maturation rather than aging per se. In vitro data indicate that aging is associated with a decreased potential for cell proliferation and a reduction in the number of stem/progenitor-like cells. Further, there is persuasive evidence that turnover in the core of the tendon after maturity is very slow or absent. Tendon fibril diameter, collagen content, and whole tendon size appear to be largely unchanged with aging, while glycation-derived cross-links increase substantially. Mechanically, aging appears to be associated with a reduction in modulus and strength. With respect to exercise, tendon cells respond by producing growth factors, and there is some support for a loading-induced increase in tendon collagen synthesis in humans, which likely reflects synthesis at the very periphery of the tendon rather than the core. Average collagen fibril diameter is largely unaffected by exercise, while there can be some hypertrophy of the whole tendon. In addition, it seems that resistance training can yield increased stiffness and modulus of the tendon and may reduce the amount of glycation. Exercise thereby tends to counteract the effects of aging.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".