Localized drug delivery using crosslinked gelatin gels containing liposomes: Factors influencing liposome stability and drug release
Bibliographic record
Abstract
We describe a drug-delivery vehicle that combines the sustained release properties of liposomes with the structural advantages of crosslinked gelatin gels that can be implanted directly or coated onto medical devices. Liposome inclusion in gelatin gels does not compromise thermal stability nor does it interfere with the resiliency of gels to tensile force. However, electron spin resonance analysis of sequestered DPPC liposomes revealed a slight depression (ca. 1.0 degrees C) of the gel-to-fluid phase transition relative to liposomes in suspension. The level of liposome release from gels was determined by liposome concentration, liposome size, and the presence of poly(ethylene oxide) chains in the gel matrix or in the liposome membrane. Both neutral and charged liposomes displayed relatively high affinities for poly(ethylene glycol)gelatin gels, with only 10-15% release of initially sequestered liposomes while liposomes in which poly(ethylene glycol) was included within the membrane were not as well retained (approximately 65% release). The in vitro efflux of ciprofloxacin from liposomal gels immersed in serum was nearly complete after 24 h compared to 38% release of liposomal chlorhexidine after 6 days. The serum-induced destabilization of liposomal ciprofloxacin depended on the accessibility of serum components to gels as partly immersed gels retained approximately 50% of their load of drug after 24 h. In vivo experiments using a catheterized rabbit model of urinary tract infection revealed the absence of viable Escherichia coli on coated catheter surfaces in seven out of nine cases while all untreated catheter surfaces examined (n = 7) were contaminated.
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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".