In vitro assessment of the biocompatibility of chemically treated silicone materials with human lens epithelial cells
Bibliographic record
Abstract
Cytotoxicity testing is a regulatory requirement for safety testing of new ocular implants. In vitro toxicity tests determine whether toxic chemicals are present on a material surface or leach out of the material matrix. A method of evaluating the cytotoxicity of ocular implants was developed using fluorescent viability dyes. To assess the assay's sensitivity in detecting toxic substances on biomaterials, zinc diethydithiocarbamate (ZDEC) and benzalkonium chloride (BAK) were deposited on silicone surfaces at different concentrations. Human lens epithelial cells (HLEC) were added to the surface of these treated silicone surfaces and were assessed for viability. The viability of both the adherent and non-adherent cells was determined using confocal microscopy with, annexin V, ethidium homodimer, and calcein. Cell metabolism was also evaluated using resazurin and the release of inflammatory cytokines was quantified using a multiplex Mesoscale Discovery platform. Confocal microscopy was shown to be a sensitive assay for evaluating material toxicity, as significant toxicity (p < 0.05) from ZDEC and BAK-treated surfaces compared to the untreated silicone control was detected. Patterns of cytokine release from cells varied depending on the toxin evaluated and the toxin concentration and did not directly correlate with the reduction in cell metabolic activity measured by alamarBlue.
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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 | 0.002 | 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 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".