Pathogenesis of Age-Related Osteoporosis: Impaired Mechano-Responsiveness of Bone Is Not the Culprit
Bibliographic record
Abstract
BACKGROUND: According to prevailing understanding, skeletal mechano-responsiveness declines with age and this apparent failure of the mechano-sensory feedback system has been attributed to the gradual bone loss with aging (age-related osteoporosis). The objective of this study was to evaluate whether the capacity of senescent skeleton to respond to increased loading is indeed reduced as compared to young mature skeleton. METHODS AND FINDINGS: 108 male and 101 female rats were randomly assigned into Exercise and Control groups. Exercise groups were subjected to treadmill training either at peak bone mass between 47-61 weeks of age (Mature) or at senescence between 75-102 weeks of age (Senescent). After the training intervention, femoral necks and diaphysis were evaluated with peripheral quantitative computed tomography (pQCT) and mechanical testing; the proximal tibia was assessed with microcomputed tomography (microCT). The microCT analysis revealed that the senescent bone tissue was structurally deteriorated compared to the mature bone tissue, confirming the existence of age-related osteoporosis. As regards the mechano-responsiveness, the used loading resulted in only marginal increases in the bones of the mature animals, while significant exercise-induced increases were observed virtually in all bone traits among the senescent rats. CONCLUSION: The bones of senescent rats displayed a clear ability to respond to an exercise regimen that failed to initiate an adaptive response in mature animals. Thus, our observations suggest that the pathogenesis of age-related osteoporosis is not attributable to impaired mechano-responsiveness of aging skeleton. It also seems that strengthening of even senescent bones is possible--naturally provided that safe and efficient training methods can be developed for the oldest old.
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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) | 0.001 | 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".