Evidence map›Paper›PMID 38146756›Full record

ArticleArhiv za higijenu rada i toksikologiju2022

UVC-LED-based face mask design and efficacy against common germs.

Ali Gelir, Faruk Asicioglu, Aysegul S Yilmaz, Mert Kuskucu, Mehmet Doymaz, Onur B Özdemir, Devrim Sarıbal, Seda Salman, Ömer F Kadi, Sedat Özdemir and 1 more

Abstract read
In one paragraph

Article in Arhiv za higijenu rada i toksikologiju, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

11 authors.

Ali GelirIstanbul Technical University, Physics Engineering Department, Istanbul, Turkey.
Faruk AsiciogluIstanbul University-Cerrahpaşa, Institute of Forensic Science and Legal Medicine, Istanbul, Turkey.
Aysegul S YilmazIstanbul University-Cerrahpaşa, Institute of Forensic Science and Legal Medicine, Istanbul, Turkey.
Mert KuskucuIstanbul University-Cerrahpaşa Faculty of Medicine, Istanbul, Turkey.
Mehmet DoymazBezmialemVakıf University, Department of Medical Microbiology, Istanbul, Turkey.
Onur B ÖzdemirIstanbul Technical University, Physics Engineering Department, Istanbul, Turkey.
Devrim SarıbalIstanbul University-Cerrahpaşa Faculty of Medicine, Istanbul, Turkey.
Seda SalmanIstanbul University-Cerrahpaşa Faculty of Medicine, Istanbul, Turkey.
Ömer F KadiIstanbul Technical University, Physics Engineering Department, Istanbul, Turkey.
Sedat ÖzdemirHaliç University Faculty of Medicine, Istanbul, Turkey.
Sinem N SeyhanIstanbul Technical University, Physics Engineering Department, Istanbul, Turkey.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

During the Covid-19 pandemic, one of the best means of personal protection was using face masks. In this context, the World Health Organization has declared the attempts to produce masks inactivating airborne virus species a welcome initiative. This preliminary study aimed to prove that airborne germs passing through a mask filter cartridge can be destroyed by the rays emitted from UVC LEDs placed in such cartridge. We therefore designed such a face mask and tested the efficiency of UVC LEDs placed in its cartridge against common contaminants, gram-positive

Indexed as

COVID-19MasksHumansPandemicsSARS-CoV-2antibacterial maskantibakterijska maskaA/Puerto Rico/8/1934 influenza viruscorona virusCOVID-19javno zdravstvokoronavirusP. aeruginosaprotective maskpublic healthS. aureusvirus influence A/Puerto Rico/8/1934zaštitna maska

Identifiers

PMID38146756
PMCPMC10750322

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.