Optimization of a Paper-Based ELISA for a Human Performance Biomarker
Abstract
Monitoring aspects of human performance during various activities has recently become a highly investigated research area. Many new commercial products are available now to monitor human physical activity or responses while performing activities ranging from playing sports, to driving, and even sleeping. However, monitoring cognitive performance biomarkers, such as neuropeptides, is still an emerging field due to the complicated sample collection and processing, as well as the need for a clinical lab to perform analysis. Enzyme-linked immunosorbent assays (ELISAs) provide specific detection of biomolecules with high sensitivity (pM concentrations). Even with the advantage of high sensitivity, most ELISAs need to be performed in a laboratory setting and require around six hours to complete. Transitioning this assay to a platform where it reduces cost, shortens assay time, and is able to be performed outside a lab is invaluable. Recently developed paper diagnostics provide an inexpensive platform to perform ELISAs on; however, the major limiting factor for moving out of the laboratory environment is the measurement and analysis instrumentation. Using something as simple as a digital camera or camera-enabled Windows- or Android-based tablets, we are able to image a paper-based ELISAs (P-ELISAs), perform image analysis, and produce response curves with high correlation to target biomolecule concentration in the 10 pM range. Neuropeptide Y detection was performed Additionally, silver enhancement of Au NPs conjugated with IgG antibodies showed concentration dependent response to IgG; thus, eliminating the need for an enzyme-substrate system. Automated image analysis and quantification of antigen concentrations are able to be performed on Windows- and Android-based mobile platforms.
Document Details
- Document Type
- Technical Report
- Publication Date
- Nov 11, 2013
- Accession Number
- ADA594123
Entities
People
- Daniel K. Griffin
- Ian Papautsky
- Joshua A Hagen
- Nancy Kelley-Loughnane
- Richard C. Murdock
- Shen Li
Organizations
- Air Force Research Laboratory