A Comprehensive Study of Osteogenic Calcium Phosphate Silicate Cement: Material Characterization and In Vitro/In Vivo Testing
Bibliographic record
Abstract
Vertebral compression fractures can be successfully restored by injectable bone cements. Here the as-yet unexplored in vitro cytotoxicity, in vivo biodegradation, and osteoconductivity of a new calcium phosphate silicate cements (CPSC) are studied, where monocalcium phosphate (MCP; 5, 10, and 15 wt%) is added to calcium silicate cement (CSC). Setting rate and compressive strength of CPSC decrease with the addition of MCP. The crystallinity, microstructure, and porosity of hardened CPSC are evaluated by X-ray diffractometer, Fourier transform infrared spectroscopy, and microcomputed tomography (CT). It is found that MCP reacts with calcium hydroxide, one of CSC hydration products, to precipitate apatite. While the reaction accelerates the hydration of CSC, the formation of calcium silicate hydrate gel is disturbed and highly porous microstructures form, resulting in weaker compressive strength. In vitro studies demonstrate that CPSC is noncytotoxic to osteoblast cells and promotes their proliferation. In the rabbit tibia implantation model, clinical X-ray and CT scans demonstrate that CPSC biodegrades slower and osseointegrates better than clinically used calcium phosphate cement (CPC). Histological studies demonstrate that CPSC is osteoconductive and induces higher bone formation than CPC, a finding that might warrant future clinical studies.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".