Development, characterization and clinical use of a biodegradable composite scaffold for bone engineering in oro-maxillo-facial surgery
Bibliographic record
Abstract
We have developed a biodegradable composite scaffold for bone tissue engineering applications with a pore size and interconnecting macroporosity similar to those of human trabecular bone. The scaffold is fabricated by a process of particle leaching and phase inversion from poly(lactideco-glycolide) (PLGA) and two calcium phosphate (CaP) phases both of which are resorbable by osteoclasts; the first a particulate within the polymer structure and the second a thin ubiquitous coating. The 3-5 μm thick osteoconductive surface CaP abrogates the putative foreign body giant cell response to the underlying polymer, while the internal CaP phase provides dimensional stability in an otherwise highly compliant structure. The scaffold may be used as a biomaterial alone, as a carrier for cells or a three-phase drug delivery device. Due to the highly interconnected macroporosity ranging from 81% to 91%, with macropores of 0.8∼1.8 mm, and an ability to wick up blood, the scaffold acts as both a clot-retention device and an osteoconductive support for host bone growth. As a cell delivery vehicle, the scaffold can be first seeded with human mesenchymal cells which can then contribute to bone formation in orthotopic implantation sites, as we show in immune-compromised animal hosts. We have also employed this scaffold in both lithomorph and particulate forms in human patients to maintain alveolar bone height following tooth extraction, and augment alveolar bone height through standard sinus lift approaches. We provide a clinical case report of both of these applications; and we show that the scaffold served to regenerate sufficient bone tissue in the wound site to provide a sound foundation for dental implant placement. At the time of writing, such implants have been in occlusal function for periods of up to 3 years in sites regenerated through the use of the scaffold.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 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".