Development of a Curved, Stratified, In Vitro Model to Assess Ocular Biocompatibility
Bibliographic record
Abstract
PURPOSE: To further improve in vitro models of the cornea, this study focused on the creation of a three-dimensional, stratified, curved epithelium; and the subsequent characterization and evaluation of its suitability as a model for biocompatibility testing. METHODS: Immortalized human corneal epithelial cells were grown to confluency on curved cellulose filters for seven days, and were then differentiated and stratified using an air-liquid interface for seven days before testing. Varying concentrations of a commercial ophthalmic solution containing benzalkonium chloride (BAK), a known cytotoxic agent, and two relevant ocular surfactants were tested on the model. A whole balafilcon A lens soaked in phosphate buffered saline (BA PBS) was also used to assess biocompatibility and verify the validity of the model. Viability assays as well as flow cytometry were performed on the cells to investigate changes in cell death and integrin expression. RESULTS: The reconstructed curved corneal epithelium was composed of 3-5 layers of cells. Increasing concentrations of BAK showed dose-dependent decreased cell viability and increased integrin expression and cell death. No significant change in viability was observed in the presence of the surfactants. As expected, the BA PBS combination appeared to be very biocompatible with no adverse change in cell viability or integrin expression. CONCLUSIONS: The stratified, curved, epithelial model proved to be sensitive to distinct changes in cytotoxicity and is suitable for continued assessment for biocompatibility testing of contact lenses. Our results showed that flow cytometry can provide a quantitative measure of the cell response to biomaterials or cytotoxic compounds for both the supernatant and adherent cell populations. As a specifically designed in vitro model of the corneal epithelium, this quantitative model for biocompatibility at the ocular surface may help improve our understanding of cell-material interactions and reduce the use of animal testing.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".