Imaging Protein Deposits on Contact Lens Materials
Bibliographic record
Abstract
PURPOSE: The majority of studies investigating protein deposition on contact lens materials require that the deposit of interest be removed, potentially resulting in erroneous results if some proteins are not removed adequately. The purpose of this study was to investigate the use of in situ imaging methods to examine protein deposition on conventional poly(2-hydroxyethyl methacrylate) (polyHEMA)-based and silicone hydrogel contact lens materials. METHODS: Six silicone hydrogel and five polyHEMA-based hydrogel contact lens materials were examined by Atomic Force Microscopy (AFM) and/or Scanning Electron Microscopy (SEM) techniques, after being deposited with proteins in an in vitro model. AFM studies examined lenses deposited solely with lysozyme at approximate physiological concentrations and SEM studies were conducted on lenses exposed to a dilute mixture of lysozyme and albumin-conjugated gold spheres. RESULTS: AFM studies demonstrated that the lens materials had markedly differing surface topographies. SEM results showed that galyfilcon A and balafilcon A lenses deposited both lysozyme and albumin in relatively large aggregates, as compared with lotrafilcon A and B, in which the proteins were deposited in a more evenly spread, monolayer formation. Polymacon lenses deposited more protein than any of the silicone hydrogel materials and much of the protein was aggregated together. AFM data indicated that balafilcon A, lotrafilcon A and polymacon deposited lysozyme in a similar manner, with very little lysozyme being deposited in discrete areas. Galyfilcon A behaved very differently, with the lysozyme exhibiting both aggregates as well as string-like formations over the lens surface. CONCLUSIONS: Imaging techniques that allow proteins to be examined in situ show much promise for determining the extent and physical characterization of protein on contact lens materials. These techniques indicate that the pattern of deposition of proteins onto silicone hydrogel contact lens materials differs between materials, depending upon their bulk and surface composition.
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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".