Bibliographic record
Abstract
STUDY DESIGN: A literature review was conducted. OBJECTIVES: To review the discovery of the bone morphogenetic proteins and describe the bone morphogenetic protein products that will or may be available for clinical use. SUMMARY OF BACKGROUND DATA: Bone morphogenetic proteins comprise the osteoinductive component of several tissue engineering products in late-stage development as replacements for autogenous bone graft, and for bone augmentation and repair. METHODS: The literature on bone morphogenetic proteins was reviewed. RESULTS: Bone morphogenetic proteins were discovered originally on the basis of their presence in osteoinductive extracts of bone matrix. Molecular cloning of bone morphogenetic proteins demonstrated that they are a family of related differentiation factors, each capable of inducing the formation of new bone tissue when implanted. Two of the molecules in clinical use, recombinant human bone morphogenetic protein-2 and recombinant human bone morphogenetic protein-7 (OP-1) are produced in a biotechnology process using recombinant deoxyribonucleic acid technology that offers unlimited supply and substantial control over purity and reproducible activity. A third material, bovine bone morphogenetic protein extract, is extracted from bone, and contains a mixture of bone morphogenetic protein molecules. Each of these molecules, although osteoinductive in vivo, has different physiologic roles and biologic activities in vivo and in vitro. Successful development of a product for use in spinal fusion involves selecting the osteoinductive molecule, the amount of the bone morphogenetic protein required, and the method of delivery, as well as conducting subsequent preclinical and clinical studies to evaluate its efficacy and safety. CONCLUSIONS: On the basis of the data provided in this issue of Spine, some of these bone morphogenetic protein-based products provide for revolutionary therapies in orthopedic practice.
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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.012 | 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".