Optimization of a paper-based ELISA for a human performance biomarker

Area of Science:

• Biomedical Engineering
• Analytical Chemistry
• Human Performance Monitoring

Background:

• Monitoring human cognitive performance is crucial but challenging due to complex biomarker analysis.
• Current enzyme-linked immunosorbent assays (ELISAs) are sensitive but require laboratory settings and long processing times.
• Developing portable, cost-effective methods for biomarker detection is essential for real-world applications.

Purpose of the Study:

• To develop and validate a paper-based ELISA (P-ELISA) platform for rapid, field-deployable biomarker analysis.
• To enable cognitive performance monitoring outside traditional laboratory environments.
• To simplify the detection of neuropeptides and other biomarkers.

Main Methods:

• Utilized paper diagnostics for ELISA implementation, reducing cost and complexity.
• Employed digital cameras and mobile devices (Windows/Android tablets) for imaging and analysis of P-ELISAs.
• Incorporated silver enhancement of gold nanoparticles (Au NPs) for direct antigen detection, bypassing enzyme-substrate systems.
• Developed automated image analysis algorithms for quantification.

Main Results:

• Achieved high correlation between image analysis and target biomolecule concentration in the picomolar (pM) range.
• Demonstrated successful detection of Neuropeptide Y using the P-ELISA platform.
• Showcased a concentration-dependent response for IgG detection via silver-enhanced Au NPs, validating the simplified detection method.
• Confirmed the feasibility of automated quantification on mobile platforms.

Conclusions:

• The developed P-ELISA system offers a sensitive, rapid, and portable solution for biomarker detection.
• Mobile device-based analysis significantly reduces assay time and eliminates the need for specialized laboratory equipment.
• This technology has the potential to revolutionize human performance monitoring by enabling accessible cognitive biomarker analysis.