Nonviral Delivery of Basic Fibroblast Growth Factor Gene to Bone Marrow Stromal Cells
Bibliographic record
Abstract
Basic fibroblast growth factor (bFGF) is capable of stimulating osteogenic differentiation of preosteoblast cells in vitro and new bone tissue deposition in vivo. Delivering the gene for the protein, rather than the protein itself, is considered advantageous for bone repair since gene delivery obviates the need to produce the protein in pharmaceutical quantities. To explore the feasibility of bFGF gene delivery by nonviral methods, we transfected primary rat bone marrow stromal cells (BMSC) using cationic polymers (polyethylenimine and poly(L-lysine)-palmitic acid) in vitro. After delivering a bFGF-expression plasmid (pFGF2-IRES-AcGFP) to BMSC, the presence of bFGF in culture supernatants was detected by a commercial ELISA. As much as 0.3 ng bFGF/10(6) cells/day was obtained from the BMSC under optimal conditions. This secretion rate was approximately 100-fold lower than the secretion obtained from immortal, and easy-to-transfect, human 293T cells. These data suggest the feasibility of modifying BMSC with nonviral delivery systems for bFGF expression, but also highlight the need for substantial improvement in transfection rate for an effective therapy.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".