The Impact of Intermittent Air Exposure on Lipid Deposition
Bibliographic record
Abstract
PURPOSE: To analyze the impact of intermittent air exposure on the in vitro deposition of two radioactive lipids on various contact lens (CL) materials, using a custom-designed model blink cell. METHODS: Six different CL materials (balafilcon A, lotrafilcon B, comfilcon A, senofilcon A, etafilcon A, and omafilcon A) were mounted on the model blink cell pistons, which cycled the lenses in and out of a complex artificial tear solution (ATS) that contained a trace amount of C-cholesterol or C-phosphatidylcholine. For the short-term experiment, air-exposed lenses were continuously cycled in and out of the ATS for 10 h. Longer term incubations for 6 days were tested with lotrafilcon B and balafilcon A materials incubated in C-cholesterol ATS. The air-exposed CLs were cycled for 14 h then submerged for 10 h each day. For both experiments, the control lenses were submerged for the entire test period. After incubation, lenses were processed, and deposited masses were quantified. RESULTS: Exposure to air resulted in increased amounts of cholesterol deposited by 1.6 to 4.3 fold on omafilcon A, balafilcon A, comfilcon A, and senofilcon A (p ≤ 0.03) compared with submerged lenses. No differences in deposition were observed for etafilcon A and lotrafilcon B (p > 0.05). The longer term incubation of lotrafilcon B and balafilcon A showed statistically significant increases in cholesterol deposition for both air-exposed lens materials (p < 0.02) with the increase in deposition 1.8× and 2.8×, respectively. For phosphatidylcholine, all air-exposed lenses had increased masses of deposition. These deposits were statistically greater by 1.1 to 1.6 times for omafilcon A, comfilcon A, lotrafilcon B, and senofilcon A (p < 0.04), but not statistically different for etafilcon A or balafilcon A (p > 0.05). CONCLUSIONS: This study found that lipid deposition profiles are CL material dependent and that intermittent air exposure can influence the mass of lipid deposited.
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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".