Azobenzene-Grafted Acrylate Coatings to Modulate Lens Epithelial Cells
Bibliographic record
Abstract
Polymeric intraocular lenses (IOLs) are prosthetics used to replace cataracts to restore vision. However, in 20% or more of cases, lens epithelial cells (LECs) remaining after surgery migrate along the IOL and posterior capsule, causing new vision anomalies, termed posterior capsule opacification (PCO). The surface of the polymeric IOL is identified as a leading factor for the development of their failure, and we hypothesize that specialized coatings could mitigate or prevent these failures. Azobenzene was grafted to coatings made of poly(methacrylic acid- co -isodecyl acrylate) (MAAcoIDA) and poly(methyl methacrylate- co -isodecyl acrylate) (MMcoIDA) to produce a library of acrylic coatings. The azobenzene on the surface of these coatings could reversibly photoisomerize with 365 nm light and complex with β-cyclodextrin (β-CD). Human LEC cell line, B3-LECs, grown on these coatings had modulated protein and gene expression, with lower α-smooth muscle actin protein expression and inflammatory interleukin 6 gene expression in cells incubated on all of the variations of MMcoIDA compared to MAAcoIDA. Azobenzene modifications with and without UV and β-CD treatment also modulated cell behavior where cells on azobenzene-modified MAAcoIDA had decreased live/dead ratios after UV treatments, a potential method to reduce LEC viability. The cells on β-CD-treated azobenzene-modified MAAcoIDA had differences in cell adhesion after UV treatments, illustrating that UV light can be applied to modulate cell behavior in conjunction with β-CD. The different coatings present methods to modulate LEC adhesion, death, and behavior, temporarily when dependent on UV treatments.
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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".