Advances in osteobiologic materials for bone substitutes
Bibliographic record
Abstract
A significant challenge in the current orthopedics is the development of suitable osteobiologic materials that can replace the conventional allografts, autografts, and xenografts and thereby serve as implant materials as bone substitutes for bone repair or remodelling. The complex biology behind the nanostructure and microstructure of bones and their repair mechanisms, which involve various types of chemical and biomechanical signalling amongst different cells, has set strong requirements for biomaterials to be used in bone tissue engineering. This review presents an overview of various types of osteobiologic materials to facilitate the formation of the functional bone tissue and healing of the bone, covering metallic, ceramic, polymeric, and cell-based graft substitutes, as well as some biomolecular strategies including stem cells, extracellular matrices, growth factors, and gene therapies. Advantages and disadvantages of each type, particularly from the perspective of osteoinductive and osteoconductive capabilities, are discussed. Although the numerous challenges of bone regeneration in tissue engineering and regenerative medicine are yet to be entirely addressed, further advancements in osteobiologic materials will pave the way towards engineering fully functional bone replacement grafts.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".