MétaCan
Menu
Back to cohort
Record W4211228434 · doi:10.1186/s12985-022-01754-w

A UV-LED module that is highly effective at inactivating human coronaviruses and HIV-1

2022· article· en· W4211228434 on OpenAlexafffund
Arvin Tejnarine Persaud, Jonathan Burnie, Laxshaginee Thaya, Liann DSouza, Steven J. Martin, Christina Guzzo

Bibliographic record

VenueVirology Journal · 2022
Typearticle
Languageen
FieldMedicine
TopicInfection Control and Ventilation
Canadian institutionsUniversity of Toronto
FundersMedical Research CouncilNational Institute of Allergy and Infectious DiseasesNatural Sciences and Engineering Research Council of CanadaUniversity of Toronto ScarboroughNational Institutes of HealthUniversity of TorontoUniversity of Bern
KeywordsUltravioletUltraviolet lightBacillus pumilusBiologyVirologyMicrobiologyHuman immunodeficiency virus (HIV)Ultraviolet radiationMaterials scienceOptoelectronicsBacteriaChemistry

Abstract

fetched live from OpenAlex

Ultraviolet (UV) light has previously been established as useful method of disinfection, with demonstrated efficacy to inactivate a broad range of microorganisms. The advent of ultraviolet light-emitting diodes provides advantages in ease of disinfection, in that there can be delivery of germicidal UV with the same light unit that delivers standard white light to illuminate a room. Herein we demonstrate the efficacy and feasibility of ultraviolet light-emitting diodes as a means of decontamination by inactivating two distinct virus models, human coronavirus 229E and human immunodeficiency virus. Importantly, the same dose of ultraviolet light that inactivated human viruses also elicited complete inactivation of ultraviolet-resistant bacterial spores (Bacillus pumilus), a gold standard for demonstrating ultraviolet-mediated disinfection. This work demonstrates that seconds of ultraviolet light-emitting diodes (UV-LED) exposure can inactivate viruses and bacteria, highlighting that UV-LED could be a useful and practical tool for broad sanitization of public spaces.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.102
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.018
GPT teacher head0.285
Teacher spread0.267 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations8
Published2022
Admission routes2
Has abstractyes

Explore more

Same venueVirology JournalSame topicInfection Control and VentilationFrench-language works237,207