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Related Experiment Video

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Visual Detection of Multiple Nucleic Acids in a Capillary Array

Visual Detection of Multiple Nucleic Acids in a Capillary Array

Published on: November 15, 2017

Deep Learning-Enhanced Hand-Driven Microfluidic Chip for Multiplexed Nucleic Acid Detection Based on RPA/CRISPR.

Tao Xu^1,2, Ying Zhang², Shunji Li²

¹College of Medicine and Biological Information Engineering, Northeastern University, Shenyang, 110169, China.

Advanced Science (Weinheim, Baden-Wurttemberg, Germany)

|March 31, 2025

Summary

This summary is machine-generated.

A new portable system, R-CHIP, enables rapid, accessible detection of high-risk human papillomavirus (HR-HPV) using recombinase polymerase amplification and CRISPR. This technology aids early cervical cancer screening in resource-limited settings.

Keywords:

CRISPR artificial intelligence community screening hand‐driven microfluidic high‐risk human papillomavirus

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Area of Science:

Biotechnology
Molecular Diagnostics
Public Health

Background:

Early detection of high-risk human papillomavirus (HR-HPV) is critical for cervical cancer prognosis.
Current PCR-based methods lack accessibility, hindering screening in resource-limited areas and contributing to high mortality rates.

Purpose of the Study:

To develop a portable, user-friendly system for multiplexed HR-HPV nucleic acid detection.
To improve accessibility and efficiency of cervical cancer screening, particularly in underserved regions.

Main Methods:

Integration of Recombinase polymerase amplification (RPA), CRISPR detection, hand-driven microfluidics, and an AI platform (R-CHIP).
Utilized a smartphone microimaging system with the ResNet-18 deep learning model for automated result readout.
Optimized for high sensitivity (10^-17 M for HPV-16, 10^-18 M for HPV-18) and accuracy.

Main Results:

R-CHIP provides results in under an hour with simple manual operation.
Achieved over 95% accuracy in 300 clinical sample tests for HPV-16 and HPV-18.
Smartphone-based AI readout demonstrated initial prediction accuracies of 96.0% for HPV-16 and 98.0% for HPV-18.

Conclusions:

R-CHIP is a sensitive, accurate, and accessible platform for community-level HR-HPV screening.
The system holds significant potential for early cervical cancer detection and prevention in resource-constrained settings.
The integrated approach offers a model for developing similar diagnostic tools for other diseases.