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      General baseline toxicity QSAR for nonpolar, polar and ionisable chemicals and their mixtures in the bioluminescence inhibition assay with Aliivibrio fischeri

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          Abstract

          A general QSAR model for the Microtox assay with the ionisation-corrected liposome–water distribution ratio is applicable to diverse chemicals including acids and bases.

          Abstract

          The Microtox assay, a bioluminescence inhibition assay with the marine bacterium Aliivibrio fischeri, is one of the most popular bioassays for assessing the cytotoxicity of organic chemicals, mixtures and environmental samples. Most environmental chemicals act as baseline toxicants in this short-term screening assay, which is typically run with only 30 min of exposure duration. Numerous Quantitative Structure–Activity Relationships (QSARs) exist for the Microtox assay for nonpolar and polar narcosis. However, typical water pollutants, which have highly diverse structures covering a wide range of hydrophobicity and speciation from neutral to anionic and cationic, are often outside the applicability domain of these QSARs. To include all types of environmentally relevant organic pollutants we developed a general baseline toxicity QSAR using liposome–water distribution ratios as descriptors. Previous limitations in availability of experimental liposome–water partition constants were overcome by reliable prediction models based on polyparameter linear free energy relationships for neutral chemicals and the COSMO mic model for charged chemicals. With this QSAR and targeted mixture experiments we could demonstrate that ionisable chemicals fall in the applicability domain. Most investigated water pollutants acted as baseline toxicants in this bioassay, with the few outliers identified as uncouplers or reactive toxicants. The main limitation of the Microtox assay is that chemicals with a high melting point and/or high hydrophobicity were outside of the applicability domain because of their low water solubility. We quantitatively derived a solubility cut-off but also demonstrated with mixture experiments that chemicals inactive on their own can contribute to mixture toxicity, which is highly relevant for complex environmental mixtures, where these chemicals may be present at concentrations below the solubility cut-off.

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          Classifying environmental pollutants

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            Environmental toxicology and risk assessment of pharmaceuticals from hospital wastewater.

            In this paper, we evaluated the ecotoxicological potential of the 100 pharmaceuticals expected to occur in highest quantities in the wastewater of a general hospital and a psychiatric center in Switzerland. We related the toxicity data to predicted concentrations in different wastewater streams to assess the overall risk potential for different scenarios, including conventional biological pretreatment in the hospital and urine source separation. The concentrations in wastewater were estimated with pharmaceutical usage information provided by the hospitals and literature data on human excretion into feces and urine. Environmental concentrations in the effluents of the exposure scenarios were predicted by estimating dilution in sewers and with literature data on elimination during wastewater treatment. Effect assessment was performed using quantitative structure-activity relationships because experimental ecotoxicity data were only available for less than 20% of the 100 pharmaceuticals with expected highest loads. As many pharmaceuticals are acids or bases, a correction for the speciation was implemented in the toxicity prediction model. The lists of Top-100 pharmaceuticals were distinctly different between the two hospital types with only 37 pharmaceuticals overlapping in both datasets. 31 Pharmaceuticals in the general hospital and 42 pharmaceuticals in the psychiatric center had a risk quotient above 0.01 and thus contributed to the mixture risk quotient. However, together they constituted only 14% (hospital) and 30% (psychiatry) of the load of pharmaceuticals. Hence, medical consumption data alone are insufficient predictors of environmental risk. The risk quotients were dominated by amiodarone, ritonavir, clotrimazole, and diclofenac. Only diclofenac is well researched in ecotoxicology, while amiodarone, ritonavir, and clotrimazole have no or very limited experimental fate or toxicity data available. The presented computational analysis thus helps setting priorities for further testing. Separate treatment of hospital wastewater would reduce the pharmaceutical load of wastewater treatment plants, and the risk from the newly identified priority pharmaceuticals. However, because high-risk pharmaceuticals are excreted mainly with feces, urine source separation is not a viable option for reducing the risk potential from hospital wastewater, while a sorption step could be beneficial. Copyright © 2010 Elsevier Ltd. All rights reserved.
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              Mixture toxicity and its modeling by quantitative structure-activity relationships.

              Environmental contaminants are frequently encountered as mixtures, and the behavior of chemicals in a mixture may not correspond to that predicted from data on the pure compounds. This paper reviews current quantitative structure-activity relationship (QSAR) methodology for the analysis of mixture toxicity. Interactions of components in a mixture can cause complex and substantial changes in the apparent properties of its constituents, resulting in synergistic or antagonistic effects as opposed to the ideal reference case of additive behavior: concentration addition (CA) and independent action (IA) are two prominent reference models for the evaluation of joint activity, and both have mechanistic support from pharmacology. After discussing graphical tools for analyzing binary mixtures and joint effect indices suitable also for multicomponent mixtures, water solubility and hydrophobicity of mixtures are analyzed with respect to the property contributions of the individual components. With the former, small but significant deviations from ideal behavior are observed even for simple organics, whereas in the case of low concentrations, mixture hydrophobicity was found to agree approximately with the fractional contributions of the components. A variety of studies suggest that mixtures of compounds exerting only one (narcotic or specific) mode of action can be modeled satisfactorily by assuming CA, whereas the interaction of differently acting compounds tends to yield a less than CA joint activity. The QSARs have been used to predict concentrations of components in mixtures from joint effects and defined mixture ratios and have been developed to predict narcotic-type mixture toxicity from molecular descriptors that are calculated as composite properties according to the fractional concentrations of the mixture components. In the case of ionogenic compounds, initial results suggest that CA may serve as a first-order approximation for the joint effect of un-ionized and ionized compound portions.
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                Author and article information

                Journal
                ESPICZ
                Environmental Science: Processes & Impacts
                Environ. Sci.: Processes Impacts
                Royal Society of Chemistry (RSC)
                2050-7887
                2050-7895
                2017
                2017
                : 19
                : 3
                : 414-428
                Affiliations
                [1 ]Helmholtz Centre for Environmental Research – UFZ
                [2 ]DE-04318 Leipzig
                [3 ]Germany
                [4 ]Eberhard Karls University Tübingen
                [5 ]Environmental Toxicology
                [6 ]Department of Clinical Pharmacy
                [7 ]Leipzig University
                Article
                10.1039/C6EM00692B
                44151af8-4234-441d-9df7-184fa45ded77
                © 2017
                History

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