The Impact of Incubation Conditions on <i>In Vitro</i> Phosphatidylcholine Deposition on Contact Lens Materials
Bibliographic record
Abstract
SIGNIFICANCE: Previous in vitro measurements of contact lenses commonly investigate the impact of nonpolar tear film lipids (i.e., sterols). Polar lipids, however, are equally important stabilizing components of the tear film. This research explores and presents further knowledge about various aspects of polar lipid uptake that may impact contact lens performance. PURPOSE: This study evaluated the impact of incubation time, lipid concentration, and replenishment of an artificial tear solution (ATS) on the uptake of phosphatidylcholine (PC) onto conventional hydrogel (CH) and silicone hydrogel (SH) contact lens materials. METHODS: Four SHs and two CH lens materials (n = 4) were soaked in a complex ATS containing radioactive 14C-PC as a probe molecule. Phosphatidylcholine uptake was monitored at various incubation time points (1, 3, 7, 14, and 28 days), with different ATS lipid concentrations (0.5×, 1×, 2×) and with and without regular replenishment of the ATS. Phosphatidylcholine was extracted from the lenses, processed, and counted by a β counter, and accumulated PC (μg/lens) was extrapolated from standard lipid calibration curves. RESULTS: All materials exhibited increasing PC deposition over time. Conventional hydrogel materials showed significantly lower PC uptake rates (P < .001) than any of the SH materials. Increasing lipid concentration in the ATS resulted in increased PC binding onto the contact lens materials (P < .001). Replenishing the ATS every other day, however, impacted the PC deposition differently, showing increased binding (P < .001) on CHs and reduced PC deposition for SH materials (P < .001). CONCLUSIONS: Length of incubation, lipid concentration in the ATS, and renewal of the incubation solution all influenced the amount of PC that sorbed onto various lens materials and therefore need to be considered when conducting future in vitro deposition studies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".