Bone regeneration with active angiogenesis by basic fibroblast growth factor gene transfected mesenchymal stem cells seeded on porous β-TCP ceramic scaffolds
Bibliographic record
Abstract
Large segmental bone defect repair remains a clinical and scientific challenge with increasing interest focused on combining gene transfer with tissue engineering techniques. Basic fibroblast growth factor (bFGF) is one of the most prominent osteogenic growth factors that has the potential to accelerate bone healing by promoting the proliferation and differentiation of mesenchymal stem cells (MSCs) and the regeneration of capillary vasculature. However, the short biological half-lives of growth factors may impose severe restraints on their clinical usefulness. Gene-based delivery systems provide a better way of achieving a sustained high concentration of growth factors locally in the defect and delivering a more biologically active product than that achieved by exogenous application of recombinant proteins. The objective of this experimental study was to investigate whether the bFGF gene modified MSCs could enhance the repair of large segmental bone defects. The pcDNA3-bFGF gene transfected MSCs were seeded on biodegradable porous beta tricalcium phosphate (beta-TCP) ceramics and allografted into the 15 mm critical-sized segmental bone defects in the radius of 18 New Zealand White rabbits. The pcDNA3 vector gene transfected MSCs were taken as the control. The follow-up times were 2, 4, 6, 8, 10 and 12 weeks. Scanning electron microscopic, roentgenographic, histologic and immunohistological studies were used to assess angiogenesis and bone regeneration. In vitro, the proliferation and differentiation of bFGF gene transfected MSCs were more active than that of the control groups. In vivo, significantly more new bone formation accompanied by abundant active capillary regeneration was observed in pores of the ceramics loaded with bFGF gene transfected MSCs, compared with control groups. Transfer of gene encoding bFGF to MSCs increases their osteogenic properties by enhancing capillary regeneration, thus providing a rich blood supply for new bone formation. This new bFGF gene enhanced tissue engineering strategy could be of potential benefit to accelerate bone healing, especially in defects caused by atrophic nonunion and avascular necrosis of the femoral head.
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 | 0.000 | 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) | 0.000 | 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 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".