title: Simultaneous detection of multiple bioactive pollutants using a multiparametric biochip for water quality monitoring.
abstract: Water is a renewable resource but yet finite. Its sustainable usage and the maintenance of a good quality are essential for an intact environment, human life and a stable economy. Emerging technologies aim for a continuous monitoring of water quality, overcoming periodic analytical sampling, and providing information on the current state of inshore waters in real time. So does the here presented cell-based sensor system which uses RLC-18 cells (rat liver cells) as the detection layer for the detection of water pollutants. The electrical read-out of the system, cellular metabolism, oxygen consumption and morphological integrity detects small changes in the water quality and indicates a possible physiological damage caused. A generalized functional linear model was implemented in order to regress the chemicals present in the sample on the electrical read-out. The chosen environmental pollutants to test the system were chlorpyrifos, an organophosphate pesticide, and tetrabromobisphenol A, a flame retardant. Each chemical gives a very characteristic response, but the toxicity is mitigated if both chemicals are present at once. This will focus our attention on the statistical approach which is able to discriminate between these pollutants.
authors.affiliation: Siemens AG Corporate Technology, 81739 Munich, Germany; Institute of Pharmacy and Molecular Biotechnology, University of Heidelberg, 69120 Heidelberg, Germany.
authors.forename: Christian
authors.initials: C
authors.lastname: Guijarro
authors.affiliation: Siemens AG Corporate Technology, 81739 Munich, Germany; Department of Statistics, Ludwig-Maximilians-University Munich, 80539 Munich, Germany.
authors.forename: Karen
authors.initials: K
authors.lastname: Fuchs
authors.affiliation: Siemens AG Corporate Technology, 81739 Munich, Germany.
authors.forename: Ulrich
authors.initials: U
authors.lastname: Bohrn
authors.affiliation: Siemens AG Corporate Technology, 81739 Munich, Germany. Electronic address: evamaria.stuetz@siemens.com.
authors.forename: Evamaria
authors.initials: E
authors.lastname: Stütz
authors.affiliation: Institute of Pharmacy and Molecular Biotechnology, University of Heidelberg, 69120 Heidelberg, Germany.
authors.forename: Stefan
authors.initials: S
authors.lastname: Wölfl
mesh_terms: D000818:Animals; D015374:Biosensing Techniques / Q000295:instrumentation*; D002460:Cell Line; D004390:Chlorpyrifos / Q000032:analysis* / Q000633:toxicity; D004867:Equipment Design; D005411:Flame Retardants / Q000032:analysis* / Q000633:toxicity; D056656:Lab-On-A-Chip Devices; D008099:Liver / Q000166:cytology / Q000187:drug effects / Q000378:metabolism; D010101:Oxygen Consumption / Q000187:drug effects; D010575:Pesticides / Q000032:analysis* / Q000633:toxicity; D011075:Polybrominated Biphenyls / Q000032:analysis* / Q000633:toxicity; D051381:Rats; D014874:Water Pollutants, Chemical / Q000032:analysis* / Q000633:toxicity; D060753:Water Quality
chemical_list: D005411:Flame Retardants; D010575:Pesticides; D011075:Polybrominated Biphenyls; D014874:Water Pollutants, Chemical; C020806:tetrabromobisphenol A; D004390:Chlorpyrifos
keywords: Cell-based sensor; Chlorpyrifos; Generalized functional linear model; Tetrabromobisphenol A; Water quality monitoring