Encapsulation of rhBMP-2 as a Strategy for Dose Shielding Whilst Preserving Structural Integrity, Bioactivity, and Osteogenic Potential
Bibliographic record
Abstract
Recombinant human bone morphogenetic protein-2 (rhBMP-2) is widely used to promote bone regeneration. However, conventional surface-attached delivery on absorbable collagen sponges causes a rapid burst release, excessive inflammation, and suboptimal healing. To overcome these limitations, we developed a thermally controlled Poly(DL-lactide-co-glycolide) (PDLLGA) encapsulation system, designed to stabilize rhBMP-2 and enable controlled release. rhBMP-2 was incorporated in PDLLGA pellets using the hot-melt extrusion of a lyophilized mixture containing poloxamer 407 and hydroxypropyl-β-cyclodextrin, and terminal sterilization (X-ray irradiation). The released rhBMP-2 maintained its molecular integrity after sterilization and remained stable for up to 732 days in storage, as confirmed by sodium dodecyl sulfate polyacrylamide gel electrophoresis (SDS-PAGE) and capillary electrophoresis (CE). Further, high-affinity binding between released rhBMP-2 and BMPR-IA was confirmed by bio-layer interferometry (BLI), and the released protein induced a robust in vitro ALP response, confirming preserved osteogenic activity. Our encapsulation approach for rhBMP-2 using PDLLGA, including the combination product with β-TCP (LDGraft; Locate Bio, Nottingham, UK), provides a stable and bioactive rhBMP-2 delivery strategy with inherent dose-shielding properties, supporting safe, controlled, and effective bone regeneration therapies.
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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 | 0.000 |
| 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 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".