Reverse engineering Frost's mechanostat model in mouse tibia: Insights from combined PTH and mechanical loading
Bibliographic record
Abstract
Osteoporosis is a widespread skeletal disease impacting billions, with treatments aimed at enhancing bone mass or preventing bone loss essential for reducing fracture risk and related health complications. Clinical evidence shows that intermittent parathyroid hormone (PTH) treatment increases cortical width at certain skeletal sites, with effects further amplified when combined with mechanical loading (ML), making this pharmacological and exercise approach promising for dual osteoporosis therapy. However, the mechanisms through which PTH enhances osteogenic response are not fully understood. This study uses μ CT endpoint imaging data from the mouse tibia loading model together with mechanical assessment of strain patterns in cortical bone to quantitatively compute parameters in Frost's mechanostat model. Particularly, we investigate the effects of PTH alone and in combination with ML on bone formation threshold and rate. Our analysis shows that PTH alone promotes periosteal bone formation independently of strain patterns induced by habitual loading in a dose-dependent manner. PTH lowers the bone formation modeling threshold ( MES m ) in bones undergoing ML in a dose-dependent and site-specific manner. The highest sensitivity is observed around 37 % of tibial height, where MES m decreases from 1060.6 μ ε in untreated bones to 212.1 μ ε at an 80 μ g/kg/day g PTH dose. This region also exhibits the highest adaptation response, with a maximum modeling velocity (MaxFL) of approximately 7 μ ε /day at 80 μ g/kg/day PTH. Although the formation velocity modulus (FVM) increases in PTH-treated bones compared to untreated ones across all regions, this change is not dose-dependent. • Robust method to reverse-engineer Frost's mechanostat for studying bone adaptation. • PTH alone induces bone formation in a dose-dependent way. • PTH lowers the bone formation modeling threshold in bones in a dose-dependent way. • PTH increases the modeling velocity rate, but this effect is not dose dependent. • Bone modeling formation threshold is PTH and bone region dependent.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".