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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| Format: | Article |
| Language: | English |
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MDPI AG
2022-11-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/21/8496 |
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| author | Tatiana Kuchmenko Daria Menzhulina Anastasiia Shuba |
| author_facet | Tatiana Kuchmenko Daria Menzhulina Anastasiia Shuba |
| author_sort | Tatiana Kuchmenko |
| collection | DOAJ |
| 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%. |
| first_indexed | 2024-03-09T18:39:47Z |
| format | Article |
| id | doaj.art-1654256ebe084b85ad60f7d717825a58 |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T18:39:47Z |
| publishDate | 2022-11-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-1654256ebe084b85ad60f7d717825a582023-11-24T06:49:05ZengMDPI AGSensors1424-82202022-11-012221849610.3390/s22218496Noninvasive Detection of Bacterial Infection in Children Using Piezoelectric E-NoseTatiana Kuchmenko0Daria Menzhulina1Anastasiia Shuba2Department of Physical and Analytical Chemistry, Voronezh State University of Engineering Technologies, Voronezh 394000, RussiaPropaedeutics of Childhood Diseases and Polyclinic Pediatrics, Voronezh State Medical University Named after N. N. Burdenko, Voronezh 394000, RussiaDepartment of Physical and Analytical Chemistry, Voronezh State University of Engineering Technologies, Voronezh 394000, RussiaCurrently, 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%.https://www.mdpi.com/1424-8220/22/21/8496piezoelectric sensormicrobalancevolatile organic compoundsbiomarkersurinebacterial infection |
| spellingShingle | Tatiana Kuchmenko Daria Menzhulina Anastasiia Shuba Noninvasive Detection of Bacterial Infection in Children Using Piezoelectric E-Nose Sensors piezoelectric sensor microbalance volatile organic compounds biomarkers urine bacterial infection |
| 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 | piezoelectric sensor microbalance volatile organic compounds biomarkers urine bacterial infection |
| url | https://www.mdpi.com/1424-8220/22/21/8496 |
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