Evidence map›Paper›PMID 35289640›Full record

ArticleApplied and environmental microbiology2022

Mathematical Modeling for Evaluating Inherent Parameters Affecting UVC Decontamination of Indicator Bacteria.

Phetcharat Jaiaue, Jirabhorn Piluk, Kanokon Sawattrakool, Jesnipit Thammakes, Chacriya Malasuk, Sitanan Thitiprasert, Nuttha Thongchul, Siwaruk Siwamogsatham

Open access · greenAbstract read
In one paragraph

Article in Applied and environmental microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
2.1field-weighted citation impact, top 14% of its field
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

7 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
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

8 authors at 2 institutions in 1 country.

Phetcharat JaiaueProgram in Biotechnology, Faculty of Science, Chulalongkorn Universitygrid.7922.e, Bangkok, Thailand.
Jirabhorn PilukResearch Unit in Bioconversion and Bioseparation for Value-Added Chemical Production, Institute of Biotechnology and Genetic Engineering, Chulalongkorn Universitygrid.7922.e, Bangkok, Thailand.
Kanokon SawattrakoolDepartment of Veterinary Microbiology, Faculty of Veterinary Science, Chulalongkorn Universitygrid.7922.e, Bangkok, Thailand.
Jesnipit ThammakesProgram in Biotechnology, Faculty of Science, Chulalongkorn Universitygrid.7922.e, Bangkok, Thailand.
Chacriya MalasukNational Security and Dual-Use Technology Center, National Science and Technology Development Agencygrid.425537.2, Pathumthani, Thailand.
Sitanan ThitiprasertResearch Unit in Bioconversion and Bioseparation for Value-Added Chemical Production, Institute of Biotechnology and Genetic Engineering, Chulalongkorn Universitygrid.7922.e, Bangkok, Thailand.
Nuttha ThongchulResearch Unit in Bioconversion and Bioseparation for Value-Added Chemical Production, Institute of Biotechnology and Genetic Engineering, Chulalongkorn Universitygrid.7922.e, Bangkok, Thailand.ORCID 0000-0002-8624-5441
Siwaruk SiwamogsathamNational Security and Dual-Use Technology Center, National Science and Technology Development Agencygrid.425537.2, Pathumthani, Thailand.
Chulalongkorn University · THNational Science and Technology Development Agency · TH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

UV light is a tool associated with the denaturation of cellular components, DNA damage, and cell disruption. UV treatment is widely used in the decontamination process; however, predicting a sufficient UV dose by using traditional methods is doubtful. In this study, an in-house UVC apparatus was designed to investigate the process of the inactivation of five indicator bacteria when the initial cell concentrations and irradiation intensities varied. Both linear and nonlinear mathematical models were applied to predict the inactivation kinetics. In comparison with the Weibull and modified Chick-Watson models, the Chick-Watson model provided a good fit of the experimental data for five bacteria, Escherichia coli, Klebsiella pneumoniae, Staphylococcus aureus, Streptococcus faecalis, and Bacillus subtilis. The specific death rate (

Indexed as

COVID-19DecontaminationBacteriaDisinfectionGram-Negative BacteriaGram-Positive BacteriaHumansModels, TheoreticalUltraviolet RaysChick-Watson inactivation modeldeath kinetic rate constantindicator bacteriamodified Chick-Watson modelUVC inactivationWeibull model

Identifiers

PMID35289640
PMCPMC9004376
OpenAlexW4220728067

What OpenQuestion holds

Textmetadata
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.