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Updated: Jan 10, 2026
Microfluidic Chip Fabrication and Method to Detect Influenza
Published on: March 26, 2013
High throughput influenza A virus detection by isothermal amplification in sequential-injection paper-based
Lucas F de Lima1, Lauro A Pradela-Filho2, Paulo Felipe Neves Estrela3
1Departamento de Química Fundamental, Instituto de Química, Universidade de São Paulo, São Paulo, SP, 05508-000, Brazil; Laboratório de Sensores Químicos Portáteis, Departamento de Química Analítica, Instituto de Química, Universidade Estadual de Campinas - UNICAMP, 13083-970, Campinas, SP, Brazil.
This study presents a rapid, low-cost diagnostic tool for Influenza A virus detection using electrochemical reverse transcription loop-mediated isothermal amplification (E-RT-LAMP) on paper microfluidics. The method offers accurate and sensitive Influenza A virus identification for potential point-of-care use.
Area of Science:
- Biotechnology
- Molecular Diagnostics
- Biosensors
Background:
- Influenza A virus poses a significant threat, necessitating rapid and sensitive diagnostic tools.
- Current laboratory-based methods can be time-consuming and resource-intensive.
Purpose of the Study:
- To develop a novel molecular detection strategy for Influenza A virus.
- To create a low-cost, portable, and sensitive diagnostic platform for point-of-care applications.
Main Methods:
- Integration of Electrochemical reverse transcription Loop-Mediated Isothermal Amplification (E-RT-LAMP) with methylene blue (MB) as a redox probe.
- Utilized sequential-injection paper-based microfluidics (μPAD) with 3D pen-templated electrodes for label-free detection.
- Assessed performance using clinical samples and compared with RT-qPCR.
Main Results:
- Achieved a limit of detection of 9.24 × 101 copies/μL.
- Provided results within seconds, enabling approximately 3 diagnoses per minute.
- Demonstrated 100% accuracy and no cross-reactivity with other respiratory viruses compared to RT-qPCR.
Conclusions:
- The developed E-RT-LAMP μPAD system is a sensitive, rapid, and accurate method for Influenza A virus detection.
- This technology shows significant potential as a point-of-care diagnostic tool, offering an alternative to traditional methods.
