The Evaluation of Ectopic Bone Formation Induced by Delivery Systems for Bone Morphogenetic Protein-9 or Its Derived Peptide
Bibliographic record
Abstract
We have earlier shown that a peptide derived from the bone morphogenetic protein-9 (pBMP-9) stimulates mouse preosteoblasts MC3T3-E1 differentiation in vitro. Here, we evaluated the effects of two delivery systems (DSs) for pBMP-9, one based on collagen and the other on chitosan. The release kinetics of BMP-9 (used as control) and pBMP-9 from these DSs were first determined in vitro by using enzyme-linked immunosorbent assay and high performance liquid chromatography assays, respectively. Micro-computerized tomography and histological analysis were then performed to study in vivo the ectopic ossification induced by both DSs containing these molecules in C57BL/6 mouse quadriceps. We found that collagen DS released in vitro about 35% of its BMP-9 within 1 h, whereas chitosan DS released 80%. The pBMP-9 was released from both DSs more slowly for up to 10 days. These release kinetics seemed to fit the Korsmeyer-Peppas model. Only chitosan DS containing BMP-9 induced strong bone formation in all mice quadriceps within 24 days. All mice quadriceps treated by pBMP-9 trapped in this DS also favored bone structures that started to mineralize. However, pBMP-9 in collagen DS failed to promote ectopic ossification within 24 days in vivo. This study highlights the importance to optimize carrier, thus improving the efficiency of pBMP-9 in vivo.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.001 |
| 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".