Bone Morphogenetic Proteins and Smad Expression in Ovine Tendon‐Bone Healing
Bibliographic record
Abstract
PURPOSE: Bone morphogenetic proteins (BMPs) are being developed to improve tendon-bone healing. To do this, it is essential to understand the endogenous expression of BMPs and their downstream signal transduction factors, Smads, during tendon-bone healing. METHODS: An extra-articular patellar tendon-bone healing ovine model was set up, and histologic evaluation of the healing progress at the tendon-bone interface at 1, 2, 3, and 6 weeks was performed. Immunohistochemical staining of BMP-2, BMP-7, Smad1, Smad4, and Smad5 was carried out in all sections. RESULTS: The model revealed formation of a loose granuloma tissue layer between the tendon and bone at 1 week, remodeling starting at 2 weeks, and Sharpey-like collagen fiber formation at 3 and 6 weeks. All detected factors were elevated at the tendon-bone interface during healing, and the expression peaked at 2 to 3 weeks. The cells involved were osteoblastic-like cells, osteoclastic-like cells, mesenchymal cells, and fibroblasts. BMP-7 staining was mainly at the interface close to the bony side, whereas BMP-2 expression shifted to the tendon side at 6 weeks. The expression pattern of Smad1 and Smad5 was similar to that of BMP-7. Smad1 was also found to be expressed in osteoclastic-like cells at 1 and 2 weeks. Smad4 expression was the highest among all of the factors at all time points. CONCLUSIONS: The data suggest that endogenous BMP-2 and BMP-7 participate in tendon-bone healing and their functions involve their downstream signal transduction mediators, Smad1, Smad4, and Smad5. CLINICAL RELEVANCE: The temporal expression of BMPs should be considered when setting up therapeutic strategies using BMPs.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".