Uptake and Release of Dexamethasone Phosphate From Silicone Hydrogel and Group I, II, and IV Hydrogel Contact Lenses
Bibliographic record
Abstract
OBJECTIVES: To investigate the uptake and release kinetics of the synthetic glucocorticoid anti-inflammatory drug dexamethasone into various conventional and silicone hydrogel contact lens materials. METHODS: Three conventional and six silicone hydrogel lenses were used in this study. A 0.1% dexamethasone solution was formulated and used to dope the various contact lens materials. The uptake and release of the drug was measured using a UV-visible light spectrophotometer at various time points during a period of 24 hr for each phase. RESULTS: Statistical analysis showed that all lenses took up a significant amount of dexamethasone. Alphafilcon A and lotrafilcon A showed the greatest uptake of dexamethasone, at 118 +/- 10 microg/lens and 102 +/- 11 microg/lens, respectively, and galyfilcon took up the least amount of drug at 34 +/- 6 microg/lens. The release of the drug from the lens materials was also statistically significant. The majority of the lenses released between 20 and 30 microg/lens, except for alphafilcon A and lotrafilcon A, which released a statistically different amount of drug when compared with the other lens materials. Alphafilcon A released 65 +/- 1.3 microg/lens, whereas lotrafilcon A slowly released only 11 +/- 0.2 microg/lens. CONCLUSIONS: Although most of the lenses released enough drug to have anti-inflammatory action, none of the materials released drug for a long enough period of time to be clinically useful as a drug delivery device.
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) | 0.001 | 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".