Uptake and Release of Ciprofloxacin-HCl From Conventional and Silicone Hydrogel Contact Lens Materials
Bibliographic record
Abstract
OBJECTIVES: To investigate the uptake and release characteristics of the antibiotic ciprofloxacin-HCl in conventional and silicone hydrogel lenses, and evaluate their potential as therapeutic drug delivery devices. METHODS: Nine differing soft contact lens materials were soaked in a 0.3% ciprofloxacin-HCl solution at 34 degrees C. The uptake of the drug into the lenses was measured by the change in concentration over 24 hours using fluorescence spectrophotometry. The lenses were then placed in a buffered saline solution, and the release of the drug from the lenses was also measured using spectrophotometry. RESULTS: The release of drug varied from 0.016 +/- 0.004 mg/lens for lotrafilcon A lenses to 0.42 +/- 0.03 mg/lens for etafilcon A lenses, with an average of 0.133 mg/lens. The 3 conventional lenses used in the study released a statistically significantly different amount of drug when compared with the silicone hydrogels. The release of drug was very rapid, with drug release reaching a plateau after no more than 10 minutes for the majority of the lenses. The majority of the lenses were able to release enough drug to achieve minimum inhibitory concentration 90 for most resistant ocular pathogens. Ciprofloxacin was found to heavily precipitate on the etafilcon A lenses during the release phase at physiologic pH. CONCLUSION: While balafilcon A released the most drug from the silicone hydrogel materials, all materials released the drug too quickly to be effective as drug delivery devices.
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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 | 0.001 |
| 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".