Effect of cell‐based VEGF gene therapy on healing of a segmental bone defect
Bibliographic record
Abstract
Fracture healing requires coordinated coupling between osteogenesis and angiogenesis in which vascular endothelial growth factor (VEGF) plays a key role. We hypothesized that targeted over-expression of angiogenic and osteogenic factors within the fracture would promote bone healing by inducing development of new blood vessels and stimulating/affecting proliferation, survival, and activity of skeletal cells. Using a cell-based method of gene transfer, without viral vector, 5.0 x 10(6) fibroblasts transfected with VEGF were delivered to a 10-mm bone defect in rabbit tibiae (Group 1) (n = 9); control groups were treated with fibroblasts (Group 2) (n = 7), or saline (Group 3) (n = 7) only. After 12 weeks, eight tibial fractures healed in Group 1, compared to four each in Groups 2 and 3. In Group 1, ossification was seen across the entire defect; in Groups 2 and 3, the defects were fibrous and sparsely ossified. Group 1 had more positively stained (CD31) vessels than Groups 2 and 3. MicroCT 3-D showed complete bridging of the new bone for Group 1, but incomplete healing for Groups 2 and 3. MicroCT bone structural parameters showed significant differences between VEGF treatment and control groups (p < 0.05). These results indicate that the cell-based VEGF gene therapy has significant angiogenic and osteogenic effects to enhance healing of a segmental defect in the long bone of rabbits.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".