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HCV Detection, Discrimination, and Genotyping Technologies

Institute for Applied Chemistry and Department of Chemistry, Hallym University, Chuncheon 200-702, Korea
*
Author to whom correspondence should be addressed.
S.D.W. and S.B.N. Contributed equally. Hence, both of them should be considered as first authors.
Sensors 2018, 18(10), 3423; https://doi.org/10.3390/s18103423
Received: 28 August 2018 / Revised: 5 October 2018 / Accepted: 10 October 2018 / Published: 12 October 2018
(This article belongs to the Special Issue Biosensors for the Detection of Biomarkers)
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Abstract

According to the World Health Organization (WHO), 71 million people were living with Hepatitis C virus (HCV) infection worldwide in 2015. Each year, about 399,000 HCV-infected people succumb to cirrhosis, hepatocellular carcinoma, and liver failure. Therefore, screening of HCV infection with simple, rapid, but highly sensitive and specific methods can help to curb the global burden on HCV healthcare. Apart from the determination of viral load/viral clearance, the identification of specific HCV genotype is also critical for successful treatment of hepatitis C. This critical review focuses on the technologies used for the detection, discrimination, and genotyping of HCV in clinical samples. This article also focuses on advantages and disadvantages of the reported methods used for HCV detection, quantification, and genotyping. View Full-Text
Keywords: HCV; detection; genotyping; quantification; viral load; RT-PCR; nucleic acids; viruses HCV; detection; genotyping; quantification; viral load; RT-PCR; nucleic acids; viruses
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This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
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Warkad, S.D.; Nimse, S.B.; Song, K.-S.; Kim, T. HCV Detection, Discrimination, and Genotyping Technologies. Sensors 2018, 18, 3423.

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