Craniofacial defect regeneration using engineered bone marrow mesenchymal stromal cells
Bibliographic record
Abstract
Large craniofacial bony defects remain a significant clinical challenge. Bone marrow mesenchymal stromal cells (BM-MSCs) constitute a multipotent population. Previously, we developed a novel approach for BM-MSC expansion on 3D CultiSpher-S gelatin microcarrier beads in spin culture with preservation of their multipotentiality, reduction of apoptosis, and enhancement of bone formation in vivo. Here, we hypothesized that such cultured BM-MSCs without exogenous growth factors would respond to the orthopedic microenvironment, thus promoting craniofacial defect regeneration. BM-MSCs isolated from green fluorescent protein (GFP) transgenic rats were ex vivo expanded and transplanted into critical-sized (5-mm diameter) rat calvaria defects. Gelatin beads or defect alone served as controls. By 28 and 42 days, rats were sacrificed for microcomputed tomography (microCT), histologic, and immunohistochemistry examination. MicroCT results demonstrated that BM-MSCs were a statistically significant factor contributing to new bone volume regeneration. Histologic assessment showed that the BM-MSCs group produced more and higher quality new bone compared with beads or defect-alone groups in both osteoinductive and osteoconductive manners. Specifically, immunohistochemical staining identified GFP(+) cells residing in new bone lacunae in conjunction with non-GFP(+) cells. Therefore, ex vivo expanded BM-MSCs at least in part regenerated critical-sized calvaria defects by osteogenic differentiation in vivo.
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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 | 0.000 | 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".