The Interaction of BMP2‐Induced Defect Healing in Rat and Fixator Stiffness Modulates Matrix Alignment and Contraction
Bibliographic record
Abstract
ABSTRACT Successful fracture healing requires a tight interplay between mechanical and biological cues. In vitro studies illustrated that mechanical loading modulates bone morphogenetic protein (BMP) signaling. However, in the early phases of large bone defect regeneration in vivo, the underlying mechanisms leading to this mechanosensation remained unknown. We investigated the interaction of BMP2 stimulation and mechanical boundary conditions in a rat critical‐sized femoral defect model (5 mm) stabilized with three distinctly different external fixator stiffness. Defects were treated with 5 μg rhBMP2 loaded on an absorbable collagen sponge. Early matrix alignment was monitored by second‐harmonic generation imaging. Bony bridging of defects and successive healing was monitored by histology at day 7 and day 14 as well as in vivo microCT at days 10, 21, and 42 post‐operation. Femora harvested at day 42 were characterized mechanically assessing torsional load to failure ex vivo. At tissue level, differences between groups were visible at day 14 with manifest bone formation in the microCT. Histologically, we observed prolonged chondrogenesis upon flexible fixation, whereas osteogenesis started earlier after rigid and semirigid fixation. At later time points, there was a boost of bone tissue formation upon flexible fixation, whereas other groups already displayed signs of tissue maturation. Based on gene expression profiling, we analyzed the mechanobiological interplay. Already at day 3, these analyses revealed differences in expression pattern, specifically of genes involved in extracellular matrix formation. Gene regulation correlating with fixator stiffness was pronounced at day 7 comprising genes related to immunological processes and cellular contraction. The influence of loading on matrix contraction was further investigated and confirmed in a 3D bioreactor. Taken together, we demonstrate an early onset of mechanical conditions influencing BMP2‐induced defect healing and shed light on gene regulatory networks associated with extracellular matrix organization and contraction that seemed to directly impact healing outcomes. © 2018 The Authors. JBMR Plus is published by Wiley Periodicals, Inc. on behalf of the American Society for Bone and Mineral Research.
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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) | 0.001 | 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".