Protein Deposition and Clinical Symptoms in Daily Wear of Etafilcon Lenses
Bibliographic record
Abstract
PURPOSE: To determine the relationship between clinical signs and symptoms and protein deposition over 8 h of wear of etafilcon A lenses in symptomatic and asymptomatic contact lens wearers. METHODS: Thirty adapted soft contact lens wearers (16 symptomatic and 14 asymptomatic) were fitted with etafilcon A lenses. In vivo wettability, non-invasive tear break-up time, and subjective symptoms (vision, comfort, and dryness) were assessed at baseline and after 2, 4, 6, and 8 h. After 2, 4, 6, and 8 h time points, lenses were collected, and total protein, total lysozyme, and active lysozyme deposition were assessed. RESULTS: There was a significant reduction (p = 0.032) in the non-invasive tear break-up time at 8 h in both groups. In the symptomatic group, there was a significant reduction in subjective comfort and dryness ratings at 6 and 8 h measurement with respect to baseline (p < 0.05). There was a significant increase in total lysozyme and total protein deposition (p = 0.027) across all time points in both groups; most of the lysozyme remained active (>94% at 8 h). Pearson's correlations between subjective symptoms and protein deposition showed poor correlations for total protein/lysozyme and any subjective factor (r < 0.3; p > 0.05), and only weak correlations between dryness and % active lysozyme (r = 0.3 to 0.5 for all time points). However, stronger correlations were found between active lysozyme and subjective comfort (r = 0.6 to 0.7; p < 0.001). CONCLUSIONS: In addition to investigating total protein deposited on contact lenses, it is of significant clinical relevance to determine the conformational state of the deposited protein.
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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 | 0.002 |
| 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 | 0.001 | 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".