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Please use this identifier to cite or link to this item: http://repository.li.mahidol.ac.th/dspace/handle/123456789/41950
Title: Microfluidics: Innovative approaches for rapid diagnosis of antibiotic-resistant bacteria
Authors: Amornrat Aroonnual
Tavan Janvilisri
Puey Ounjai
Surang Chankhamhaengdecha
Mahidol University
Keywords: Biochemistry, Genetics and Molecular Biology
Issue Date: 3-Mar-2017
Citation: Essays in Biochemistry. Vol.61, No.1 (2017), 91-101
Abstract: © 2017 The Author(s). The emergence of antibiotic-resistant bacteria has become a major global health concern. Rapid and accurate diagnostic strategies to determine the antibiotic susceptibility profile prior to antibiotic prescription and treatment are critical to control drug resistance. The standard diagnostic procedures for the detection of antibiotic-resistant bacteria, which rely mostly on phenotypic characterization, are time consuming, insensitive and often require skilled personnel,making them unsuitable for point-of-care (POC) diagnosis. Variousmolecular techniques have therefore been implemented to help speed up the process and increase sensitivity. Over the past decade, microfluidic technology has gained great momentum in medical diagnosis as a series of fluid handling steps in a laboratory can be simplified and miniaturized on to a small platform, allowing marked reduction of sample amount, high portability and tremendous possibility for integration with other detection technologies. These advantages render the microfluidic system a great candidate to be developed into an easy-to-use sample-to-answer POC diagnosis suitable for application in remote clinical settings. This review provides an overview of the current development of microfluidic technologies for the nucleic acid based and phenotypic-based detections of antibiotic resistance.
URI: https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85015452793&origin=inward
http://repository.li.mahidol.ac.th/dspace/handle/123456789/41950
ISSN: 00711365
Appears in Collections:Scopus 2016-2017

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