Entrapment of basic fibroblast growth factor (bFGF) in a succinylated chitosan nanoparticle delivery system and release profile
Bibliographic record
Abstract
Basic fibroblast growth factor (bFGF) helps to regulate the proliferation and migration of fibroblasts, the proliferation of endothelial cells, and aids the development of angiogenesis. Its in vivo half-life is on the order of minutes due to extensive degradation and inactivation, which could be potentially reduced by controlled release vehicles. In this study, bFGF was entrapped into chitosan (CS) and N-succinyl-chitosan (SC) nanoparticles, with and without heparin, at two levels of initial loading, followed by further characterization of the particles. Release studies were conducted using radiolabeled bFGF-loaded nanoparticles. Both types of nanoparticles loaded similar amounts of bFGF (60.2 and 68.6% for CS and SC, respectively). The release profile varied greatly among the samples, and a burst release was observed in most cases, with the release amount approaching its final value in the first 6 h. The final amount released varied from 1.5 to 18% of the amount of bFGF-entrapped. The concomitant encapsulation of heparin and the use of SC as a nanoparticle matrix contributed to the largest amount of bFGF release (18%) over the time investigated.
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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) | 0.000 | 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".