Fabrication and characterization of contact lenses bearing surface‐immobilized layers of intact liposomes
Bibliographic record
Abstract
Intact liposomes were immobilized onto soft contact lenses. In the first step, polyethylenimine was covalently bounded onto the hydroxyl groups available on the surface of a commercial contact lens (Hioxifilcon B). Then, NHS-PEG-biotin molecules were bounded onto the surface amine groups by carbodiimide chemistry. NeutrAvidin were bounded onto the PEG-biotin layer. Liposomes containing PEG-biotinylated lipids were docked onto the surface-immobilized NeutrAvidin. Consecutive addition of further NeutrAvidin and liposome layers enabled fabrication of multilayers. Multilayers of liposomes were also produced by exposing contact lenses coated with NeutrAvidin to liposome aggregates produced by the addition of free biotin in solution. XPS revealed the immobilization of the different layers. By blocking with excess biotin surface-immobilized NeutrAvidin on contact lenses bearing PEG-biotin layers produced under cloud point conditions, ELISA showed that the docking of NeutrAvidin was dependent on biotin-NeutrAvidin affinity binding, with little evidence for nonspecific physisorption; however, it was not possible to differentiate specific versus nonspecific binding of NeutrAvidin attached onto PEG-biotin layers grafted without cloud point conditions. AFM imaging revealed liposome sizes of 106 and 155 nm for layers of liposomes produced (i) by the consecutive addition of further NeutrAvidin and liposomes and (ii) by the exposure of NeutrAvidin-coated contact lenses to liposome aggregates, respectively. The release kinetics of a fluorescent dye demonstrated that intact liposomes had been immobilized onto contact lens surfaces. The stability of surface-immobilized liposomes onto contact lens surfaces showed temperature dependence. Surface-bound liposomes can be stored up to 1 month at 4 degrees C with little release of their content.
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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".