Neutralization of the eye and skin irritant benzalkonium chloride using UVC radiation
Bibliographic record
Abstract
Purpose Benzalkonium chloride (BAK) is a widely used disinfectant and preservative which is effective against a wide range of viruses (e.g. SARS-CoV and SARS-CoV-2), bacteria and fungi. However, it is toxic to the eye and skin. This study investigated the neutralization of BAK using ultraviolet C (UVC) radiation as an effort to reduce BAK toxicity potential.Methods BAK solutions were irradiated with a germicidal UVC lamp at various doses. Human corneal epithelial cells (HCEC) were then exposed to the UVC-irradiated BAK solutions for 5 minutes. After exposure, the cultures were assessed for metabolic activity using PrestoBlue; for cell viability using confocal microscopy with viability dyes; and for tight junction proteins using immunofluorescence staining for zonula occludens (ZO)-1.Results UVC radiation reduced BAK toxicity on cell metabolic activity in a dose-dependent manner. When the solution depth of BAK was 1.7 mm, the UVC doses needed to completely neutralize the toxicity of BAK 0.005% and 0.01% were 2.093 J/cm2 and 8.374 J/cm2, respectively. The cultures treated with UVC-neutralized BAK showed similar cell metabolic activity and cell viability to those treated with phosphate buffered saline (PBS) (p = 0.806 ∼ 1.000). The expression of ZO-1 was greatly disturbed by untreated BAK; in contrast, ZO-1 proteins were well maintained after exposure to UVC-neutralized BAK.Conclusions Our study demonstrates that the cell toxicity of BAK can be neutralized by UVC radiation, which provides a unique way of detoxifying BAK residues. This finding may be of great value in utilizing the antimicrobial efficacy of BAK (e.g. fighting against SARS-CoV-2) while minimizing its potential hazards to human health and the environment.
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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".