Factors that Influence <i>In Vitro</i> Cholesterol Deposition on Contact Lenses
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to analyze the impact that incubation time, lipid concentration, and solution replenishment have on silicone hydrogel (SiHy) and conventional hydrogel (CH) contact lens cholesterol deposition via in vitro radiochemical experiments. METHODS: Four SiHy (senofilcon A, lotrafilcon B, comfilcon A, balafilcon A) and two CH (etafilcon A and omafilcon A) contact lenses were incubated in an artificial tear solution (ATS) that contained major tear film proteins, lipids, salts, salts, and a trace amount of radioactive C-cholesterol. Lenses were incubated for various incubation times (1, 3, 7, 14, or 28 days), with three concentrations of lipid (0.5×, 1×, 2× tear film concentration) and with or without solution replenishment to assess each variable's impact on cholesterol deposition. After incubation, the lenses were extracted using 2:1 chloroform:methanol, extracts were analyzed in a beta counter and masses (micrograms per lens) were extrapolated from standard curves. RESULTS: Within the SiHy materials, balafilcon A deposited the greatest amount of cholesterol (p < 0.001) and lotrafilcon B the lowest (p < 0.001). The CH lens materials showed significantly lower uptake amounts than any of the SiHy lens materials (p < 0.001). The uptake of cholesterol ranged from 0.01 ± 0.01 μg/lens to 3.22 ± 0.34 μg/lens for all lens materials. Kinetic uptake of cholesterol was shown to be continuous throughout the 28 days of incubation without plateau (p < 0.001), and varying the lipid concentration did impact the resulting cholesterol deposition (p < 0.001). Replenishing the ATS every other day also affected cholesterol deposition throughout the experiment. Overall, the deposition pattern was 2× > replenishing > 1× > 0.5×. CONCLUSIONS: Overall, SiHy lenses deposit significantly more cholesterol than CH lens materials, and the mass of lipid deposited is dependent on the contact lens material, length of incubation, concentration of lipids in the ATS, and the replenishment of ATS.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".