Literature DB >> 27899699

A Smartphone-Based Genotyping Method for Hepatitis B Virus at Point-of-Care Settings.

Huiqin Jiang1, Di Wu1, Liuwei Song2, Quan Yuan2, Shengxiang Ge2, Xiaoping Min2, Ningshao Xia2, Shizhi Qian3, Xianbo Qiu1.   

Abstract

We reported a rapid, convenient, and easy-to-use genotyping method for hepatitis B virus (HBV) based on the smartphone at point-of-care (POC) settings. To perform HBV genotyping especially for genotypes A, B, C, and D, a smartphone is used to image and analyze a one-step immunoassay lateral flow strip functionalized with genotype-specific monoclonal antibodies (mAbs) on multiple capture lines. A light-emitting diode (LED) positioned on the top of the lateral flow strip is used to shine the multiple capture lines for excitation. Fluorescence detection is obtained with a smartphone whose camera is used to take the fluorescent images. An intelligent algorithm is developed to first identify each capture line from the fluorescent image and then determine the HBV genotype based on a genotyping model. Based on the pattern of the detection signal from different samples, a custom HBV genotyping model is developed. Custom application software running on a smartphone is developed with Java to collect and analyze the fluorescent image, display the genotyping result, and transmit it if necessary. Compared with the existing methods with nucleic acid analysis, more convenient, instant, and efficient HBV genotyping with significantly lower cost and a simpler procedure can be obtained with the developed smartphone POC HBV genotyping method.

Entities:  

Keywords:  HBV genotyping; fluorescent image; intelligent algorithm; lateral flow strip; multiple capture lines

Mesh:

Year:  2016        PMID: 27899699     DOI: 10.1177/2211068216680163

Source DB:  PubMed          Journal:  SLAS Technol        ISSN: 2472-6303            Impact factor:   3.047


  3 in total

Review 1.  Interfacing Pathogen Detection with Smartphones for Point-of-Care Applications.

Authors:  Xiong Ding; Michael G Mauk; Kun Yin; Karteek Kadimisetty; Changchun Liu
Journal:  Anal Chem       Date:  2018-12-03       Impact factor: 6.986

2.  A fluorometric lateral flow assay for visual detection of nucleic acids using a digital camera readout.

Authors:  Maria Magiati; Areti Sevastou; Despina P Kalogianni
Journal:  Mikrochim Acta       Date:  2018-06-04       Impact factor: 5.833

Review 3.  Lateral flow assays for viruses diagnosis: Up-to-date technology and future prospects.

Authors:  Bahar Ince; Mustafa Kemal Sezgintürk
Journal:  Trends Analyt Chem       Date:  2022-07-05       Impact factor: 14.908

  3 in total

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