Towards novel measurements of remodeling activity in cortical bone: implications for osteoporosis and related pharmaceutical treatments
Bibliographic record
Abstract
Bone remodelling is performed by basic multicellular units (BMUs) that resorb and subsequently form discrete packets of bone tissue. Normally, the resorption and formation phases of BMU activity are tightly coupled spatially and temporally to promote relatively stable bone mass and bone quality. However, dysfunctional remodelling can lead to bone loss and is the underlying cause of osteoporosis. This review surveys how BMU activity is altered in postmenopausal, disuse and glucocorticoid-induced osteoporosis as well as the impact of anabolic and anti-resorptive pharmaceutical treatments. The dysfunctional remodelling observed during disease and following medical intervention bares many testable hypotheses regarding the regulation of BMU activity and may provide novel insights that challenge existing paradigms of remodelling dynamics, particularly the poorly understood BMU coupling mechanisms. Most bone remodelling research has focused on trabecular bone and 2D analyses, as technical challenges limit the direct assessment of BMU activity in cortical bone. Recent advances in imaging technology present an opportunity to investigate cortical bone remodelling in vivo. This review discusses innovative experimental methods, such as 3D and 4D (i.e. time- lapsed) evaluation of BMU morphology and trajectory, that may be leveraged to improve the understanding of the spatio-temporal coordination of BMUs in cortical bone.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".