<i>In Vitro</i> Cholesterol Deposition on Daily Disposable Contact Lens Materials
Bibliographic record
Abstract
PURPOSE: The goal of this study was to analyze how various incubation times affect the uptake of cholesterol on silicone hydrogel (SH) and conventional hydrogel (CH) daily disposable (DD) contact lens materials using an in vitro radiochemical detection method. METHODS: Three SH (somofilcon A, delefilcon A, and narafilcon A) and four CH (etafilcon A, nesofilcon A, ocufilcon A, and nelfilcon A) contact lenses were incubated in an artificial tear solution that contained major tear film components and a portion of radioactive C-cholesterol. Lenses (N = 4) were incubated for four incubation times (2, 6, 12, or 16 h) to assess the effects on cholesterol deposition. Subsequent to the incubation, the lenses were extracted using 2:1 chloroform:methanol, and the extracts were analyzed in a beta counter and (in nanograms per lens) extrapolated from standard curves. RESULTS: In general, cholesterol deposited statistically significantly more on SH lenses than CHs (p ≤ 0.033), with the exception of somofilcon A and nesolfilcon A materials (p = 0.067). Within the SH materials, narafilcon A accumulated the largest quantity of cholesterol (p < 0.05) and somofilcon A the lowest (p < 0.05). The uptake of cholesterol ranged from 22.63 ± 2.98 ng/lens to 97.94 ± 4.18 ng/lens for all lens materials. The accumulation of cholesterol was shown to be continuous throughout the 16 h of incubation, without reaching a plateau (p < 0.001). CONCLUSIONS: For the periods that DD lens materials are worn, cholesterol deposits significantly more onto SH contact lenses than CHs. This could have implications for wearers who have higher levels of lipid in their tears that are fitted with SH DD 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) | 0.002 | 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".