Dual intelligent multiplexing sensor for accurate disease management with portable NMR

Area of Science:

• Biomedical Engineering
• Nanotechnology
• Infectious Disease Diagnostics

Background:

• Emerging infectious diseases require advanced diagnostic tools for early detection and monitoring.
• Conventional diagnostic methods often lack sensitivity and provide limited clinical information.
• Limitations include reliance on specialized equipment and binary output.

Purpose of the Study:

• To develop a novel diagnostic approach for sensitive and simultaneous detection of multiple analytes in complex biological samples.
• To integrate time-domain micro-nuclear magnetic resonance (TD-μNMR) with a dual intelligent relaxometric sensing (DIS) system.
• To leverage machine learning algorithms for enhanced diagnostic capabilities.

Main Methods:

• Utilized a DIS system combining Fe3O4 and MnO nanoparticles with machine learning.
• Exploited distinct T1 and T2 relaxometric profiles of nanoparticles for analyte detection.
• Employed specific molecular recognition on nanoparticles to induce measurable NMR sensor changes.

Main Results:

• Demonstrated multiplexed detection of SARS-CoV-2 antigens and antibodies.
• Showcased the system's ability to detect both endogenous immune responses and exogenous viral markers.
• Achieved sensitive NMR sensing through nanoparticle-induced relaxometric changes.

Conclusions:

• The novel TD-μNMR-based DIS system offers a promising platform for advanced diagnostics of infectious diseases.
• This approach overcomes limitations of conventional tests by providing sensitive, multiplexed detection.
• The technology holds potential for early detection and comprehensive patient monitoring.