Impact of Lens Care Solutions on Protein Deposition on Soft Contact Lenses
Bibliographic record
Abstract
PURPOSE: To evaluate the effect of four contemporary lens care solutions on total protein, total lysozyme, and active lysozyme extracted from three contact lens materials. METHODS: Adapted contact lens wearers were recruited at three sites, and all subjects were randomly assigned to daily wear of either etafilcon A, galyfilcon A, or senofilcon A for 2 weeks. Four lens care solutions (Biotrue, OPTI-FREE PureMoist, RevitaLens OcuTec, and ClearCare) were used by each subject in random order with a new pair of lenses after a washout period between solutions of at least 4 days. After 2 weeks of daily wear, contact lenses were collected for analysis. Proteins were extracted from a subset of contact lenses (n = 568) and total protein, total lysozyme, and lysozyme activity were quantified using a modified Bradford assay, an enzyme-linked immunosorbent assay, and a micrococcal assay, respectively. RESULTS: Higher levels of total protein were extracted from etafilcon A when used with Biotrue compared to other solutions (p = 0.0001). There were higher levels of total lysozyme extracted from galyfilcon A lenses when used with PureMoist than with Biotrue or ClearCare (p < 0.006). Higher total lysozyme was extracted from senofilcon A when used with RevitaLens OcuTec compared to Biotrue (p = 0.002). Lower lysozyme activity was recovered from senofilcon A lenses with RevitaLens OcuTec when compared to all other care solutions (all p < 0.004). When Biotrue, PureMoist, or RevitaLens OcuTec were used, higher total lysozyme was extracted from galyfilcon A compared to senofilcon A (p < 0.01). When RevitaLens OcuTec was used, higher levels of active lysozyme were extracted from galyfilcon A compared to senofilcon A (p = 0.02). CONCLUSIONS: The ability of lens care solutions to remove protein from lenses varies depending upon the care solution composition and also the polymeric make-up of the contact lens material.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| 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 teacher head, 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".