Jove
Visualize
Contact Us
JoVE
x logofacebook logolinkedin logoyoutube logo
ABOUT JoVE
OverviewLeadershipBlogJoVE Help Center
AUTHORS
Publishing ProcessEditorial BoardScope & PoliciesPeer ReviewFAQSubmit
LIBRARIANS
TestimonialsSubscriptionsAccessResourcesLibrary Advisory BoardFAQ
RESEARCH
JoVE JournalMethods CollectionsJoVE Encyclopedia of ExperimentsArchive
EDUCATION
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab ManualFaculty Resource CenterFaculty Site
Terms & Conditions of Use
Privacy Policy
Policies

Related Concept Videos

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by
Same author

An siENPP1-Delivering Bimetallic MOF Nanocomplex Enables Triple Activation of the cGAS-STING Pathway for Synergistic Triple-Negative Breast Cancer Therapy.

Advanced materials (Deerfield Beach, Fla.)·2026
Same author

Magnetically Driven Dual-miRNA Framework Nucleic Acid Biosensing Platform for Precise Classification of Breast Cancer Subtypes.

ACS applied materials & interfaces·2026
Same author

An interface-confined ultrabright AIE nanoparticle-enhanced lateral flow immunoassay platform for full-range and accurate CRP detection.

Talanta·2026
Same author

Characteristics and Outcomes of Patients With Dedifferentiated Liposarcoma in a US Community Setting.

Cancer medicine·2026
Same author

Real-world treatment patterns and outcomes for patients with extensive-stage small-cell lung cancer treated in US community oncology practices.

Frontiers in oncology·2026
Same author

In vivo dynamic hotspot-enhanced Raman spectroscopy via reconfigurable swarming nanoprobes.

Nature communications·2026

Related Experiment Video

Updated: Oct 5, 2025

High-throughput and Comprehensive Drug Surveillance Using Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry
10:17

High-throughput and Comprehensive Drug Surveillance Using Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry

Published on: April 23, 2019

9.8K

Convolutional Neural Network for Accurate Analysis of Methamphetamine With Upconversion Lateral Flow Biosensor.

Lei Huang, Shulin Tian, Wenhao Zhao

    IEEE Transactions on Nanobioscience
    |January 27, 2022
    PubMed
    Summary

    This study introduces a portable fluorescence reader and a convolutional neural network (CNN) for accurate methamphetamine detection. The combined approach enhances the reliability of detecting low methamphetamine concentrations, crucial for combating drug abuse.

    More Related Videos

    Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
    11:54

    Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

    Published on: March 13, 2017

    9.4K
    Fabrication of Electrochemical-DNA Biosensors for the Reagentless Detection of Nucleic Acids, Proteins and Small Molecules
    13:15

    Fabrication of Electrochemical-DNA Biosensors for the Reagentless Detection of Nucleic Acids, Proteins and Small Molecules

    Published on: June 1, 2011

    33.9K

    Related Experiment Videos

    Last Updated: Oct 5, 2025

    High-throughput and Comprehensive Drug Surveillance Using Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry
    10:17

    High-throughput and Comprehensive Drug Surveillance Using Multisegment Injection-Capillary Electrophoresis-Mass Spectrometry

    Published on: April 23, 2019

    9.8K
    Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles
    11:54

    Microfluidic Platform with Multiplexed Electronic Detection for Spatial Tracking of Particles

    Published on: March 13, 2017

    9.4K
    Fabrication of Electrochemical-DNA Biosensors for the Reagentless Detection of Nucleic Acids, Proteins and Small Molecules
    13:15

    Fabrication of Electrochemical-DNA Biosensors for the Reagentless Detection of Nucleic Acids, Proteins and Small Molecules

    Published on: June 1, 2011

    33.9K

    Area of Science:

    • Analytical Chemistry
    • Biomedical Engineering
    • Forensic Science

    Background:

    • Methamphetamine abuse poses significant threats to public health and social stability.
    • Rapid and accurate quantification of methamphetamine is vital for effective control and intervention.
    • Existing detection methods may struggle with accuracy, especially for low concentrations.

    Purpose of the Study:

    • To develop a portable fluorescence reader combined with upconverting nanoparticle-labeled lateral flow immunoassay (LFIA) for methamphetamine quantification.
    • To improve the accuracy of detecting low methamphetamine concentrations, particularly distinguishing between negative and weakly positive samples.
    • To integrate a convolutional neural network (CNN) for enhanced data analysis and improved detection accuracy.

    Main Methods:

    • Development of a portable fluorescence reader for capturing fluorescence intensities from LFIA test and control lines.
    • Utilizing upconverting nanoparticle-labeled antibodies for sensitive detection of methamphetamine.
    • Application of a convolutional neural network (CNN) to analyze image features for accurate quantification, especially at low concentrations (0-0.5 ng/mL).

    Main Results:

    • The developed LFIA system demonstrated a linear range of 0.1-100 ng/mL for methamphetamine quantification.
    • The integration of CNN significantly improved the accuracy of detecting weakly positive and negative methamphetamine samples.
    • The proposed method achieved up to 92% accuracy in distinguishing low-concentration methamphetamine samples.

    Conclusions:

    • The portable fluorescence reader with upconverting nanoparticle-LFIA offers a rapid and accurate method for methamphetamine detection.
    • Convolutional neural networks provide a novel and effective approach for enhancing the analysis of complex immunoassay data, particularly for challenging low-concentration samples.
    • This integrated system holds promise for improved drug abuse monitoring and control strategies.