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Evaluation of a micro/nanofluidic chip platform for diagnosis of central nervous system infections: a multi-center prospective study
Central nervous system infection (CNSI) is a significant type of infection that plagues the fields of neurology and neurosurgical science. Prompt and accurate diagnosis of CNSI is a major challenge in clinical and laboratory assessments; however, developing new methods may help improve diagnostic pr...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6994612/ https://www.ncbi.nlm.nih.gov/pubmed/32005939 http://dx.doi.org/10.1038/s41598-020-58670-8 |
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author | Zheng, Guanghui Zhang, Yan Zhang, Lina Qian, Lingye Cai, Yumeng Lv, Hong Kang, Xixiong Guo, Dawen Wang, Xiaoming Huang, Jing Gao, Zhixian Guan, Xiuru Zhang, Guojun |
author_facet | Zheng, Guanghui Zhang, Yan Zhang, Lina Qian, Lingye Cai, Yumeng Lv, Hong Kang, Xixiong Guo, Dawen Wang, Xiaoming Huang, Jing Gao, Zhixian Guan, Xiuru Zhang, Guojun |
author_sort | Zheng, Guanghui |
collection | PubMed |
description | Central nervous system infection (CNSI) is a significant type of infection that plagues the fields of neurology and neurosurgical science. Prompt and accurate diagnosis of CNSI is a major challenge in clinical and laboratory assessments; however, developing new methods may help improve diagnostic protocols. This study evaluated the second-generation micro/nanofluidic chip platform (MNCP-II), which overcomes the difficulties of diagnosing bacterial and fungal infections in the CNS. The MNCP-II is simple to operate, and can identify 44 genus or species targets and 35 genetic resistance determinants in 50 minutes. To evaluate the diagnostic accuracy of the second-generation micro/nanofluidic chip platform for CNSI in a multicenter study. The limit of detection (LOD) using the second-generation micro/nanofluidic chip platform was first determined using six different microbial standards. A total of 180 bacterium/fungi-containing cerebrospinal fluid (CSF) cultures and 26 CSF samples collected from CNSI patients with negative microbial cultures were evaluated using the MNCP-II platform for the identification of microorganism and determinants of genetic resistance. The results were compared to those obtained with conventional identification and antimicrobial susceptibility testing methods. The LOD of the various microbes tested with the MNCP-II was found to be in the range of 250–500 copies of DNA. For the 180 CSF microbe-positive cultures, the concordance rate between the platform and the conventional identification method was 90.00%; eight species attained 100% consistency. In the detection of 9 kinds of antibiotic resistance genes, including carbapenemases, ESBLs, aminoglycoside, vancomycin-related genes, and mecA, concordance rates with the conventional antimicrobial susceptibility testing methods exceeded 80.00%. For carbapenemases and ESBLs-related genes, both the sensitivity and positive predictive values of the platform tests were high (>90.0%) and could fully meet the requirements of clinical diagnosis. MNCP-II is a very effective molecular detection platform that can assist in the diagnosis of CNSI and can significantly improve diagnostic efficiency. |
format | Online Article Text |
id | pubmed-6994612 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Nature Publishing Group UK |
record_format | MEDLINE/PubMed |
spelling | pubmed-69946122020-02-06 Evaluation of a micro/nanofluidic chip platform for diagnosis of central nervous system infections: a multi-center prospective study Zheng, Guanghui Zhang, Yan Zhang, Lina Qian, Lingye Cai, Yumeng Lv, Hong Kang, Xixiong Guo, Dawen Wang, Xiaoming Huang, Jing Gao, Zhixian Guan, Xiuru Zhang, Guojun Sci Rep Article Central nervous system infection (CNSI) is a significant type of infection that plagues the fields of neurology and neurosurgical science. Prompt and accurate diagnosis of CNSI is a major challenge in clinical and laboratory assessments; however, developing new methods may help improve diagnostic protocols. This study evaluated the second-generation micro/nanofluidic chip platform (MNCP-II), which overcomes the difficulties of diagnosing bacterial and fungal infections in the CNS. The MNCP-II is simple to operate, and can identify 44 genus or species targets and 35 genetic resistance determinants in 50 minutes. To evaluate the diagnostic accuracy of the second-generation micro/nanofluidic chip platform for CNSI in a multicenter study. The limit of detection (LOD) using the second-generation micro/nanofluidic chip platform was first determined using six different microbial standards. A total of 180 bacterium/fungi-containing cerebrospinal fluid (CSF) cultures and 26 CSF samples collected from CNSI patients with negative microbial cultures were evaluated using the MNCP-II platform for the identification of microorganism and determinants of genetic resistance. The results were compared to those obtained with conventional identification and antimicrobial susceptibility testing methods. The LOD of the various microbes tested with the MNCP-II was found to be in the range of 250–500 copies of DNA. For the 180 CSF microbe-positive cultures, the concordance rate between the platform and the conventional identification method was 90.00%; eight species attained 100% consistency. In the detection of 9 kinds of antibiotic resistance genes, including carbapenemases, ESBLs, aminoglycoside, vancomycin-related genes, and mecA, concordance rates with the conventional antimicrobial susceptibility testing methods exceeded 80.00%. For carbapenemases and ESBLs-related genes, both the sensitivity and positive predictive values of the platform tests were high (>90.0%) and could fully meet the requirements of clinical diagnosis. MNCP-II is a very effective molecular detection platform that can assist in the diagnosis of CNSI and can significantly improve diagnostic efficiency. Nature Publishing Group UK 2020-01-31 /pmc/articles/PMC6994612/ /pubmed/32005939 http://dx.doi.org/10.1038/s41598-020-58670-8 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. |
spellingShingle | Article Zheng, Guanghui Zhang, Yan Zhang, Lina Qian, Lingye Cai, Yumeng Lv, Hong Kang, Xixiong Guo, Dawen Wang, Xiaoming Huang, Jing Gao, Zhixian Guan, Xiuru Zhang, Guojun Evaluation of a micro/nanofluidic chip platform for diagnosis of central nervous system infections: a multi-center prospective study |
title | Evaluation of a micro/nanofluidic chip platform for diagnosis of central nervous system infections: a multi-center prospective study |
title_full | Evaluation of a micro/nanofluidic chip platform for diagnosis of central nervous system infections: a multi-center prospective study |
title_fullStr | Evaluation of a micro/nanofluidic chip platform for diagnosis of central nervous system infections: a multi-center prospective study |
title_full_unstemmed | Evaluation of a micro/nanofluidic chip platform for diagnosis of central nervous system infections: a multi-center prospective study |
title_short | Evaluation of a micro/nanofluidic chip platform for diagnosis of central nervous system infections: a multi-center prospective study |
title_sort | evaluation of a micro/nanofluidic chip platform for diagnosis of central nervous system infections: a multi-center prospective study |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6994612/ https://www.ncbi.nlm.nih.gov/pubmed/32005939 http://dx.doi.org/10.1038/s41598-020-58670-8 |
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