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Proceedings Paper

Ultrafast real-time PCR with integrated melting curve analysis and duplex capacities using a low-cost polymer lab-on-a-chip system
Author(s): Rainer Gransee; Tristan Schneider; Deniz Elyorgun; Xenia Strobach; Tobias Schunck; Theresia Gatscha; Christian Winkler; Julian Höth
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Paper Abstract

Nucleic amplification using quantitative polymeric chain reaction (qPCR) has become the gold standard of molecular testing. These systems offer both amplification and simultaneous fluorescence detection. An ultrafast microfluidic module (allowing 30 PCR cycles in 6 minutes) based on the oscillating fluid plug concept was previously developed [1,2] allowing the amplification of native genomic deoxyribonucleic acid (DNA) molecules. This abstract presents the actual status of the advanced system. The upgraded system generates high quality qPCR amplification plots and additional sensitive melting point analysis comparable to data obtained from commercial real-time cyclers. These features provide the user with all information needed to analyze PCR products. The system uses light emitting diodes (LED) for illumination and a low cost Charge-coupled Device (CCD) camera for optical detection. Image data processing allows the automated process control of the overall system components. The system enables the performance of rapid and robust nucleic acid amplifications together with the integration of real time measurement technology. This allows the amplification and simultaneous quantification of the targeted pathogens. The integration of duplex amplification performance allows the incorporation of the necessary controls into the device to validate the PCR performance. This demonstrator can be run either as fully autonomously working device or as OEM part of a sample-to-answer platform.

Paper Details

Date Published: 13 May 2015
PDF: 7 pages
Proc. SPIE 9487, Smart Biomedical and Physiological Sensor Technology XII, 948706 (13 May 2015); doi: 10.1117/12.2179461
Show Author Affiliations
Rainer Gransee, Fraunhofer ICT-IMM (Germany)
Tristan Schneider, Univ. of Applied Sciences Wiesbaden (Germany)
Deniz Elyorgun, Univ. of Applied Sciences Bingen (Germany)
Xenia Strobach, Fraunhofer ICT-IMM (Germany)
Tobias Schunck, Fraunhofer ICT-IMM (Germany)
Theresia Gatscha, Fraunhofer ICT-IMM (Germany)
Christian Winkler, Fraunhofer ICT-IMM (Germany)
Julian Höth, Fraunhofer ICT-IMM (Germany)


Published in SPIE Proceedings Vol. 9487:
Smart Biomedical and Physiological Sensor Technology XII
Brian M. Cullum; Eric S. McLamore, Editor(s)

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