Bone Organic-Inorganic Phase Ratio Is a Fundamental Determinant of Bone Material Quality
Bibliographic record
Abstract
BACKGROUND: Bone mineral density is widely used by clinicians for screening osteoporosis and assessing bone strength. However, its effectiveness has been reported unsatisfactory. In this study, it is demonstrated that bone organic-inorganic phase ratio is a fundamental determinant of bone material quality measured by stiffness, strength, and toughness. METHODS AND RESULTS: Two-hundred standard bone specimens were fabricated from bovine legs, with a specialized manufacturing method that was designed to reduce the effect of bone anisotropy. Bone mechanical properties of the specimens, including Young's modulus, yield stress, peak stress, and energy-to-failure, were measured by mechanical testing. Organic and inorganic mass contents of the specimens were then determined by bone ashing. Bone density and organic-inorganic phase ratio in the specimens were calculated. Statistical methods were applied to study relationships between the measured mechanical properties and the organic-inorganic phase ratios. Statistical characteristics of organic-inorganic phase ratios in the specimens with top material quality were investigated. Bone organic-inorganic phase ratio had strong Spearman correlation with bone material properties. Bone specimens that had the highest material quality had a very narrow scope of organic-inorganic phase ratio, which could be considered as the "optimal" ratio among the tested specimens. CONCLUSION: Bone organic-inorganic phase ratio is a fundamental determinant of bone material quality. There may exist an "optimal" ratio for the bone to achieve top material quality. Deviation from the "optimal" ratio is probably the fundamental cause of various bone diseases. This study suggests that bone organic-inorganic phase ratio should be considered in clinical assessment of fracture risk.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".