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Noninvasive Detection of Bacterial Infection in Children Using Piezoelectric E-Nose

Currently, antibiotics are often prescribed to children without reason due to the inability to quickly establish the presence of a bacterial etiology of the disease. One way to obtain additional diagnostic information quickly is to study the volatile metabolome of biosamples using arrays of sensors....

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Autores principales: Kuchmenko, Tatiana, Menzhulina, Daria, Shuba, Anastasiia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9658202/
https://www.ncbi.nlm.nih.gov/pubmed/36366200
http://dx.doi.org/10.3390/s22218496
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author Kuchmenko, Tatiana
Menzhulina, Daria
Shuba, Anastasiia
author_facet Kuchmenko, Tatiana
Menzhulina, Daria
Shuba, Anastasiia
author_sort Kuchmenko, Tatiana
collection PubMed
description Currently, antibiotics are often prescribed to children without reason due to the inability to quickly establish the presence of a bacterial etiology of the disease. One way to obtain additional diagnostic information quickly is to study the volatile metabolome of biosamples using arrays of sensors. The goal of this work was to assess the possibility of using an array of chemical sensors with various sensitive coatings to determine the presence of a bacterial infection in children by analyzing the equilibrium gas phase (EGP) of urine samples. The EGP of 90 urine samples from children with and without a bacterial infection (urinary tract infection, soft tissue infection) was studied on the “MAG-8” device with seven piezoelectric sensors in a hospital. General urine analysis with sediment microscopy was performed using a Uriscan Pro analyzer and using an Olympus CX31 microscope. After surgical removal of the source of inflammation, the microbiological studies of the biomaterial were performed to determine the presence and type of the pathogen. The most informative output data of an array of sensors have been established for diagnosing bacterial pathology. Regression models were built to predict the presence of a bacterial infection in children with an error of no more than 15%. An indicator of infection is proposed to predict the presence of a bacterial infection in children with a high sensitivity of 96%.
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spelling pubmed-96582022022-11-15 Noninvasive Detection of Bacterial Infection in Children Using Piezoelectric E-Nose Kuchmenko, Tatiana Menzhulina, Daria Shuba, Anastasiia Sensors (Basel) Article Currently, antibiotics are often prescribed to children without reason due to the inability to quickly establish the presence of a bacterial etiology of the disease. One way to obtain additional diagnostic information quickly is to study the volatile metabolome of biosamples using arrays of sensors. The goal of this work was to assess the possibility of using an array of chemical sensors with various sensitive coatings to determine the presence of a bacterial infection in children by analyzing the equilibrium gas phase (EGP) of urine samples. The EGP of 90 urine samples from children with and without a bacterial infection (urinary tract infection, soft tissue infection) was studied on the “MAG-8” device with seven piezoelectric sensors in a hospital. General urine analysis with sediment microscopy was performed using a Uriscan Pro analyzer and using an Olympus CX31 microscope. After surgical removal of the source of inflammation, the microbiological studies of the biomaterial were performed to determine the presence and type of the pathogen. The most informative output data of an array of sensors have been established for diagnosing bacterial pathology. Regression models were built to predict the presence of a bacterial infection in children with an error of no more than 15%. An indicator of infection is proposed to predict the presence of a bacterial infection in children with a high sensitivity of 96%. MDPI 2022-11-04 /pmc/articles/PMC9658202/ /pubmed/36366200 http://dx.doi.org/10.3390/s22218496 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kuchmenko, Tatiana
Menzhulina, Daria
Shuba, Anastasiia
Noninvasive Detection of Bacterial Infection in Children Using Piezoelectric E-Nose
title Noninvasive Detection of Bacterial Infection in Children Using Piezoelectric E-Nose
title_full Noninvasive Detection of Bacterial Infection in Children Using Piezoelectric E-Nose
title_fullStr Noninvasive Detection of Bacterial Infection in Children Using Piezoelectric E-Nose
title_full_unstemmed Noninvasive Detection of Bacterial Infection in Children Using Piezoelectric E-Nose
title_short Noninvasive Detection of Bacterial Infection in Children Using Piezoelectric E-Nose
title_sort noninvasive detection of bacterial infection in children using piezoelectric e-nose
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9658202/
https://www.ncbi.nlm.nih.gov/pubmed/36366200
http://dx.doi.org/10.3390/s22218496
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