Lysozyme and Lipid Deposition on Silicone Hydrogel Contact Lens Materials
Bibliographic record
Abstract
PURPOSE: We sought to determine whether there were differences in lysozyme (quantity and conformation) and lipid deposition on in vivo worn conventional (etafilcon) and silicone hydrogel (balafilcon and lotrafilcon) contact lenses. METHODS: After extraction, lysozyme concentration in each extract was determined by sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE) and Western blotting. Lysozyme activity was determined by the rate of lysis of Micrococcis lysodeikticus cells. Lipid deposition was determined by high-performance liquid chromatography. RESULTS: Lysozyme deposition on etafilcon lenses was significantly greater than that measured on silicone hydrogel (SH) lenses (985 microg per lens versus 10 and 3 microg per lens for balafilcon and lotrafilcon materials, respectively; P<0.001). The degree to which lysozyme was denatured was influenced by the lens material, with the lowest degree of denaturation (22%) seen on the conventional lens material, as compared with 50% for balafilcon and 80% for lotrafilcon (P<0.001). Lipid deposition was greatest on the SH materials, with up to 600 microg per lens of certain lipid classes being deposited on balafilcon, as compared with 20 microg per lens on etafilcon (P<0.001). CONCLUSION: The quantity and conformation of lysozyme and the quantity of lipid deposited on hydrogel contact lenses is significantly influenced by the composition of the lens material. SH contact lens materials deposit low levels of lysozyme and high levels of lipid deposition compared with ionic contact lens materials. Although SH materials deposit only small amounts of lysozyme, the degree of lysozyme denaturation that occurs is higher relative to that seen on ionic lens materials.
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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".