Comparative Study of Blue Light with Ultraviolet (UVC) Radiation on Betacoronavirus 1
Bibliographic record
Abstract
The ongoing coronavirus pandemic requires more effective disinfection methods. Disinfection using ultraviolet light (UV), especially longer UVC wavelengths, such as 254 and 270/280 nm, has been proven to have virucidal properties, but its adverse effects on human skin and eyes limit its use to enclosed, unoccupied spaces. Several studies have shown the effectiveness of blue light (405 nm) against bacteria and fungi, but the virucidal property at 405 nm has not been much investigated. Based on previous studies, visible light mediates inactivation by absorbing the porphyrins and reacting with oxygen to produce reactive oxygen species (ROS). This causes oxidative damage to biomolecules, such as proteins, lipids, and nucleic acids, essential constituents of any virus. The virucidal potential of visible light has been speculated because the virus lacks porphyrins. This study demonstrated porphyrin-independent viral inactivation and conducted a comparative analysis of the effectiveness at 405 nm against other UVC wavelengths. The betacoronavirus 1 (strain OC43) was exposed to 405, 270/280, 254, and 222 nm, and its efficacy was determined using a median tissue culture infectious dose, i.e., TCID50. The results support the disinfection potential of visible light technology by providing a quantitative effect that can serve as the basic groundwork for future visible light inactivation technologies. In the future, blue light technology usage can be widened to hospitals, public places, aircraft cabins, and/or infectious laboratories for disinfection purposes.
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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".