<i>In vivo</i> evaluation of calcium polyphosphate for bone regeneration
Bibliographic record
Abstract
Current problems associated with bone allografts include risk of disease transmission, limited availability, and cost. Synthetic scaffolds have been proposed as substitute graft materials to address these issues. Calcium polyphosphate is a novel synthetic scaffold material that has shown good mechanical properties and biocompatibility. Here, we evaluated calcium polyphosphate in terms of its ability to support cell proliferation and differentiation in vivo. Calcium polyphosphate, morsellized cancellous bone, and hydroxyapatite/tricalcium phosphate particles were seeded with marrow stromal cells and implanted subcutaneously in the back of NOD/Scid mice. At 7, 14, and 28 days the samples were harvested and the proliferation characteristics and gene expression were analyzed. All tested graft materials had similar proliferation characteristics and gene expression. The subcutaneous environment had a stronger impact on the proliferation and differentiation of the cells than the scaffold material itself. However, it was shown that calcium polyphosphate is superior to hydroxyapatite/tricalcium phosphate and bone in its ability to support cell survival in vivo. The study confirmed that calcium polyphosphate has potential for replacing morsellized cancellous bone as a graft material for bone regeneration.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.002 | 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".