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Proceedings Paper

Surface plasmon resonance imaging for detection of drug metabolites in water
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Paper Abstract

The analysis of surface water, groundwater, drinking water as well as sewage is important to get information about the contamination of the water cycle. Currently, these time-consuming investigations require special equipment, like for example hyphenated mass spectrometry. Surface plasmon resonance (SPR) is a faster alternative as it is highly sensitive to changes in the dielectric medium next to a thin metal layer and makes it a quasi-universal detector. Therefore, and due to the labelfree nature, SPR is a widely used sensing tool for real‐time monitoring of molecular interactions of various analytes. SPR imaging (SPRi) has several advantages to standard surface plasmon resonance, as it allows to observe many analytes in parallel as well as the integration of referencing technologies. However, the homogenous illumination of a large area (several millimeters) with a small light source is challenging and demands new approaches. Allopurinol, a drug used to lower the blood concentration of urate and hence decrease the affection of gout, gets metabolized to oxipurinol in the body and dropped out almost entirely by urinary excretion. After wastewater treatment, concentrations of oxipurinol up to 21.7 μg•L-1 are detected. Further tracking of oxipurinol in the urban water cycle showed its presence in rivers and streams or even in groundwater. Therefore, the high biological stability of oxipurinol allows this molecule to be used as a marker for domestic wastewater in the environment. For the detection of oxipurinol by SPR graphene was used as receptive layer, as the analyte can bind via π-stacking to this surface. An SPRi technique was developed and compared to conventional SPR system for the detection of oxipurinol.

Paper Details

Date Published: 11 April 2019
PDF: 11 pages
Proc. SPIE 11028, Optical Sensors 2019, 110280W (11 April 2019); doi: 10.1117/12.2522324
Show Author Affiliations
Peter Hausler, Ostbayerische Technische Hochschule Regensburg (Germany)
Lukas Wunderlich, Univ. Regensburg (Germany)
Johannes Fischer, Ostbayerische Technische Hochschule Regensburg (Germany)
Christina Pfab, Univ. Regensburg (Germany)
Simon Heckscher, Univ. Regensburg (Germany)
Thomas Hirsch, Univ. Regensburg (Germany)
Rudolf Bierl, Ostbayerische Technische Hochschule Regensburg (Germany)


Published in SPIE Proceedings Vol. 11028:
Optical Sensors 2019
Francesco Baldini; Jiri Homola; Robert A. Lieberman, Editor(s)

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