High-Sensitivity Microfluidic Solenoid for Magnetically Tagged Antigen Detection in Early-Stage Infectious Disease Diagnostics
Disciplines
Bioelectrical and Neuroengineering | Biomedical Devices and Instrumentation | Electromagnetics and Photonics | Electronic Devices and Semiconductor Manufacturing | Immunology of Infectious Disease | Pathogenic Microbiology | Signal Processing | Virology
Abstract (300 words maximum)
To quantify biomolecule presence in humans, microbead tagging methods have been utilized extensively in the biomedical field. Our team quantifies infection progression of the Dengue Virus using superparamagnetic microbeads, certain bonds to bioindicators, and a microfluidic solenoid. We propose using the antigen NS1 coupled with ThermoFisher Scientific Dynabeads coated in EDC/NHS, IgG antibody, and IgM antibodies for tagging virus bioindicators. This collective bioindicator complex will be passed through a microfluidic solenoid to induce discrete and countable voltages and therefore countable number of antibodies for our novel early detection method. This novel method addresses challenges in false negative rates and offers enhanced early detection capabilities of viral incubation which is crucial for virus treatment and mitigation.
To improve the sensitivity of the device, the team proposes a strong magnet at one end of the micro-solenoid to pull the magnetically tagged antigen through. This will enable higher acceleration, and subsequent voltage, through the solenoid than conventional mini pumps. To further validate this method, COMSOL Multiphysics software is used to simulate the voltage induced when the magnetically tagged antigens pass through the microfluidic solenoid channel under these conditions.
In addition to optimizing the acceleration of the magnet, a low-noise-amplifier (LNA) and a digital signal processor are utilized to minimize the noise produced while amplifying the induced signal for high sensitivity when detecting the antigens. The team proposes to improve the LNA by adding more paralleled op amps to reduce the noise by a factor of 2 instead of the original √2. An LNA output replication algorithm was developed to avoid direct use of the LNA during DSP filter prototyping. The algorithm was used in Matlab and Simulink to develop an adaptive IIR lowpass filter for the dsPIC33FJ12MC-202 which counted simulated tagged beads accurately.
Academic department under which the project should be listed
SPCEET - Electrical and Computer Engineering
Primary Investigator (PI) Name
Hoseon Lee
High-Sensitivity Microfluidic Solenoid for Magnetically Tagged Antigen Detection in Early-Stage Infectious Disease Diagnostics
To quantify biomolecule presence in humans, microbead tagging methods have been utilized extensively in the biomedical field. Our team quantifies infection progression of the Dengue Virus using superparamagnetic microbeads, certain bonds to bioindicators, and a microfluidic solenoid. We propose using the antigen NS1 coupled with ThermoFisher Scientific Dynabeads coated in EDC/NHS, IgG antibody, and IgM antibodies for tagging virus bioindicators. This collective bioindicator complex will be passed through a microfluidic solenoid to induce discrete and countable voltages and therefore countable number of antibodies for our novel early detection method. This novel method addresses challenges in false negative rates and offers enhanced early detection capabilities of viral incubation which is crucial for virus treatment and mitigation.
To improve the sensitivity of the device, the team proposes a strong magnet at one end of the micro-solenoid to pull the magnetically tagged antigen through. This will enable higher acceleration, and subsequent voltage, through the solenoid than conventional mini pumps. To further validate this method, COMSOL Multiphysics software is used to simulate the voltage induced when the magnetically tagged antigens pass through the microfluidic solenoid channel under these conditions.
In addition to optimizing the acceleration of the magnet, a low-noise-amplifier (LNA) and a digital signal processor are utilized to minimize the noise produced while amplifying the induced signal for high sensitivity when detecting the antigens. The team proposes to improve the LNA by adding more paralleled op amps to reduce the noise by a factor of 2 instead of the original √2. An LNA output replication algorithm was developed to avoid direct use of the LNA during DSP filter prototyping. The algorithm was used in Matlab and Simulink to develop an adaptive IIR lowpass filter for the dsPIC33FJ12MC-202 which counted simulated tagged beads accurately.