Paper
17 April 2008 Development of a standardized differential-reflective bioassay for microbial pathogens
Author Affiliations +
Abstract
This research examines standardizing a method for the rapid/semi-automated identification of microbial contaminates. It introduces a method suited to test for food/water contamination, serology, urinalysis and saliva testing for any >1 micron sized molecule that can be effectively bound to an identifying marker with exclusivity. This optical biosensor method seeks to integrate the semi-manual distribution of a collected sample onto a "transparent" substrate array of binding sites that will then be applied to a standard optical data disk and run for analysis. The detection of most microbe species is possible in this platform because the relative scale is greater than the resolution of the standard-scale digital information on a standard CD or DVD. This paper explains the critical first stage in the advance of this detection concept. This work has concentrated on developing the necessary software component needed to perform highly sensitive small-scale recognition using the standard optical disk as a detection platform. Physical testing has made significant progress in demonstrating the ability to utilize a standard optical drive for the purposes of micro-scale detection through the exploitation of CIRC error correction. Testing has also shown a definable trend in the optimum scale and geometry of micro-arrayed attachment sites for the technology's concept to reach achievement.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jay Wilhelm, J. R. X. Auld, and James E. Smith "Development of a standardized differential-reflective bioassay for microbial pathogens", Proc. SPIE 6954, Chemical, Biological, Radiological, Nuclear, and Explosives (CBRNE) Sensing IX, 69540V (17 April 2008); https://doi.org/10.1117/12.777596
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KEYWORDS
Compact discs

Standards development

Software development

Copper

Microorganisms

Particles

Signal detection

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