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Virus detection using nanoparticles and deep neural network-enabled smartphone system.

Mohamed S Draz1,2, Anish Vasan1, Aradana Muthupandian1

  • 1Division of Engineering in Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02139, USA.

Science Advances
|December 17, 2020
PubMed
Summary
This summary is machine-generated.

A new nanoparticle-enabled smartphone system offers rapid and sensitive detection of viruses like hepatitis B, HCV, and Zika. This innovative technology achieves high accuracy without specialized attachments, aiding global health challenges.

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Area of Science:

  • Biotechnology
  • Nanotechnology
  • Infectious Diseases

Background:

  • Emerging and reemerging infections pose significant global health threats.
  • Rapid and sensitive diagnostic tools are crucial for timely intervention and control.
  • Existing methods may require specialized equipment or complex procedures.

Purpose of the Study:

  • To develop and evaluate a nanoparticle-enabled smartphone (NES) system for rapid and sensitive virus detection.
  • To utilize a convolutional neural network (CNN) for analyzing visual patterns generated by nanoprobes.
  • To assess the system's performance in detecting hepatitis B virus (HBV), HCV, and Zika virus (ZIKV).

Main Methods:

  • A microchip captures viruses, which are then labeled with platinum nanoprobes.
  • Nanoprobes induce gas bubble formation in the presence of hydrogen peroxide, creating distinct visual patterns.
  • A CNN-enabled smartphone system analyzes these patterns for virus detection without optical attachments.

Main Results:

  • The CNN-NES system demonstrated high sensitivity in detecting HBV, HCV, and ZIKV.
  • Tested with 134 spiked and infected patient samples, the system achieved 98.97% sensitivity.
  • The system accurately detected viral infections above a clinically relevant threshold of 250 copies/ml.

Conclusions:

  • The developed CNN-NES system provides a simple, rapid, and sensitive method for virus detection.
  • This smartphone-based approach offers a promising tool for combating infectious diseases globally.
  • The technology eliminates the need for external optical hardware, enhancing accessibility.