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Related Concept Videos

Hepatitis01:25

Hepatitis

Hepatitis is an inflammatory condition of the liver most commonly caused by hepatotropic viruses (A–E), though non-infectious causes such as alcohol and drugs also exist.Hepatitis AHepatitis A virus (HAV) is a non-enveloped RNA virus of the Picornaviridae family. It is primarily transmitted via the fecal-oral route, typically through ingestion of contaminated food or water. After ingestion, HAV enters the bloodstream through the oropharynx or intestinal epithelium and reaches the liver. The...

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Related Experiment Video

Updated: May 20, 2026

Detection of Low Copy Number Integrated Viral DNA Formed by In Vitro Hepatitis B Infection
11:14

Detection of Low Copy Number Integrated Viral DNA Formed by In Vitro Hepatitis B Infection

Published on: November 7, 2018

A Fluorescence Imaging- and Deep Learning-Based Approach for Detecting Hepatitis B Virus Integration into Host

Tzu-Hsien Yang1,2, Wen-Tai Chiu1, Yun-Hsuan Chu3

  • 1Department of Biomedical Engineering, Medical Device Innovation Center, National Cheng Kung University, Tainan, Taiwan.

Journal of Imaging Informatics in Medicine
|May 18, 2026
PubMed
Summary
This summary is machine-generated.

Researchers developed a novel fluorescence imaging and deep learning method to detect Hepatitis B virus (HBV) integration in single liver cells. This technique offers a promising approach for identifying HBV DNA integration, a key factor in liver cancer development.

Keywords:
Deep learningFluorescent in situ hybridization (FISH)HBV integrationHepatitis B virus (HBV)

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Last Updated: May 20, 2026

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11:14

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Published on: November 7, 2018

Single-Cell Multiplexed Fluorescence Imaging to Visualize Viral Nucleic Acids and Proteins and Monitor HIV, HTLV, HBV, HCV, Zika Virus, and Influenza Infection
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Real-Time Polymerase Chain Reaction-Based Detection and Quantification of Hepatitis B Virus DNA
04:11

Real-Time Polymerase Chain Reaction-Based Detection and Quantification of Hepatitis B Virus DNA

Published on: December 15, 2023

Area of Science:

  • Hepatology
  • Virology
  • Genomics
  • Artificial Intelligence

Background:

  • Hepatitis B virus (HBV) infection is a major cause of hepatocellular carcinoma.
  • HBV integration into the host genome is implicated in liver carcinogenesis.
  • Current detection methods for HBV integration have limitations in sensitivity, site identification, or cost-effectiveness.

Purpose of the Study:

  • To develop a novel method for detecting HBV DNA integration at the single-cell level.
  • To evaluate the efficacy of fluorescence in situ hybridization combined with deep learning for this purpose.
  • To establish a proof-of-concept for a new diagnostic tool for HBV integration.

Main Methods:

  • Development of a fluorescence in situ hybridization (FISH) approach for visualizing HBV integration in individual liver cells.
  • Application of a deep learning model for analyzing FISH images and identifying integrated HBV DNA.
  • Validation using hepatoma cell lines with and without known HBV DNA integration.

Main Results:

  • The developed FISH approach successfully visualized HBV integration in liver cells.
  • The deep learning model achieved over 90% accuracy in identifying positive and negative control cells.
  • This study demonstrates the feasibility of using fluorescence imaging and AI for single-cell HBV integration detection.

Conclusions:

  • Fluorescence imaging coupled with deep learning provides a sensitive and accurate method for detecting HBV integration at the single-cell level.
  • This approach overcomes limitations of existing methods, offering potential for clinical applications.
  • This work represents a significant advancement in understanding and diagnosing HBV-related liver diseases.