The Effect of Aging and Mechanical Loading on the Metabolism of Articular Cartilage
Bibliographic record
Abstract
OBJECTIVE: The morphology of articular cartilage (AC) enables painless movement. Aging and mechanical loading are believed to influence development of osteoarthritis (OA), yet the connection remains unclear. METHODS: This narrative review describes the current knowledge regarding this area, with the literature search made on PubMed using appropriate keywords regarding AC, age, and mechanical loading. RESULTS: Following skeletal maturation, chondrocyte numbers decline while increasing senescence occurs. Lower cartilage turnover causes diminished maintenance capacity, which produces accumulation of fibrillar crosslinks by advanced glycation end products, resulting in increased stiffness and thereby destruction susceptibility. CONCLUSION: Mechanical loading changes proteoglycan content. Moderate mechanical loading causes hypertrophy and reduced mechanical loading causes atrophy. Overloading produces collagen network damage and proteoglycan loss, leading to irreversible cartilage destruction because of lack of regenerative capacity. Catabolic pathways involve inflammation and the transcription factor nuclear factor-κB. Thus, age seems to be a predisposing factor for OA, with mechanical overload being the likely triggering cause.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".