TwinDemic detection: A non-enzymatic signal amplification system for on-site detection of multiple respiratory viruses
Year: 2024
Type: article
Abstract: The simultaneous occurrence of multiple respiratory viruses, such as severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 [CoV]) and influenza A virus (IAV), presents a challenge for accurate diagnosis and treatment. To address this, we developed the TwinDemic Detection (TDD) system—an integrated point-of-care diagnostic platform that can simultaneously detect CoV and IAV using a multi-respiratory virus identification approach. The TDD system contains a transparent poly(methyl methacrylate) microfluidic chip with a hydrogel-based gene detection sensor and a handheld fluorescence reader. This system uses a fuel-stimulated DNA probe to detect viral RNA and amplify the fluorescence signal without the need for enzymatic or thermal controls. The system’s performance was tested using 45 human nasopharyngeal samples; results revealed positive and negative predictive values of 93.3 % and 96.7 % for CoV, and 100 % and 96.7 % for IAV, respectively. This system enables the accurate and simultaneous detection of multiple respiratory viruses for public health surveillance and shows potential for use as a point-of-care molecular test to monitor a wider range of viruses in the future. • The TwinDemic Detection system simultaneously detects SARS-CoV-2 and IAV. • It has a microfluidic chip, hydrogel sensors, and a handheld fluorescence reader. • The hydrogel sensor enables enzyme-free isothermal amplification for RNA detection. • The TDD system aids effective public health measures and rapid on-site testing.
Source: Sensors and Actuators B Chemical
Institutions: Osong Medical Innovation Foundation, Korea Research Institute of Bioscience and Biotechnology, Yonsei University, Yonsei University Health System, Korea University of Science and Technology, Gyeongsang National University Changwon Hospital, Sungkyunkwan University, Incheon National University
Language: English
Subfield: Biomedical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: hybrid
Estimated APC paid: $4,500
OpenAlex ID: W4404339133
