In silico bioavailability triggers applied to direct and indirect thyroid hormone disruptors

Among endocrine disruption, interference with the thyroid hormone (TH) regulation is of increasing concern. Respective compounds encode through their structural features both the potential for TH disruption, and the bioavailability mitigating the toxicological effect. The aim of this study is to provide a substructure-based screening-level QSAR (quantitative structure-activity relationship) that discriminates bioavailable TH disruptors from not bioavailable counterparts, covering both direct and indirect (retinoid- and AhR-mediated) modes of action. The QSAR has been derived from literature data for 1642 compounds, and takes into account Lipinski's rule-of-five and the brain/blood partition coefficient Kbrain/blood. For its validation, an external test set of 145 substances has been used. For 1787 compounds meeting the model application domain, the model yields only one false negative. The discussion addresses the mechanistic meaning of the bioavailability triggers molecular weight, H-bond donor and acceptor, hydrophobicity (log Kow), and the physicochemical properties underlying log Kbrain/blood. The model may serve as bioavailability-screening step within a decision support system for the predictive assessment of chemicals regarding their potential to disrupt thyroid hormone function in a direct or indirect manner.

Octanol/Air Partition Coefficient─A General-Purpose Fragment Model to Predict Log Koa from Molecular Structure

The octanol/air partition coefficient K_oa is important for assessing the bioconcentration of airborne xenobiotics in foliage and in air-breathing organisms. Moreover, K_oa informs about compound partitioning to aerosols and indoor dust, and complements the octanol/water partition coefficient K_ow and the air/water partition coefficient K_aw for multimedia fate modeling. Experimental log K_oa at 25 °C has been collected from literature for 2161 compounds with molecular weights from 16 to 959 Da. The curated data set covers 18.2 log units (from -1.0 to 17.2). A newly developed fragment model for predicting log K_oa from molecular structure outperforms COSMOtherm, EPI-Suite KOAWIN, OPERA, and linear solvation energy relationships (LSERs) regarding the root-mean-squared error (rms) and the maximum negative and positive errors (mne and mpe) (rms: 0.57 vs 0.86 vs 1.09 vs 1.19 vs 1.05-1.53, mne: -2.55 vs -3.95 vs -7.51 vs -7.54 vs (-5.63) - (-7.34), mpe: 2.91 vs 5.97 vs 7.54 vs 4.24 vs 6.89-10.2 log units). The prediction capability, statistical robustness, and sound mechanistic basis are demonstrated through initial separation into a training and prediction set (80:20%), mutual leave-50%-out validation, and target value scrambling in terms of temporarily wrong compound-K_oa allocations. The new general-purpose model is implemented in a fully automatized form in the ChemProp software available to the public. Regarding K_oa indirectly determined through K_ow and K_aw, a new approach is developed to convert from wet to dry octanol, enabling higher consistency in experimental (and thus also predicted) K_oa.

Henry's Law Constant─A General-Purpose Fragment Model to Predict Log Kaw from Molecular Structure

Henry's law constant is important for assessing the environmental fate of organic compounds, including polar accumulation, indoor contamination, and the impact of airborne predominance on persistence. Moreover, it can be used in the context of alternative 3R bioassays to inform about the compound loss through volatilization as a confounding factor. For 2636 compounds, curated experimental log K_aw (air/water partition coefficient) data at 25° covering 23.6 orders of magnitude (from -18.6 to 5.0) have been collected from the literature. Subsequently, a new fragment model for predicting log K_aw from molecular structures has been developed. According to the root-mean-squared error (rms) and the maximum negative and positive errors (mne and mpe), this general-purpose model outperforms COSMOtherm, EPISuite HENRYWIN, OPERA, and LSER with calculated input parameters significantly (rms 0.50 vs 0.92 vs 1.25 vs 1.28 vs 1.38, mne -2.74 vs -6.78 vs -9.11 vs -6.24 vs -6.27, mpe 2.25 vs 6.22 vs 8.27 vs 11.5 vs 7.69 log units). Initial separation into a training and prediction set (80%:20%), mutual leave-50%-out validation, and target value scrambling (temporarily wrong compound-K_aw allocations) demonstrate the prediction capability, statistical robustness, and mechanistically sound basis of the fragment scheme. The new model is available to the public in fully computerized form through the ChemProp software, and can be combined with a separate existing model to extend the log K_aw prediction to temperatures different from 25 °C.

Computational material flow analysis for thousands of chemicals of emerging concern in European waters

Knowledge of exposure to a wide range of chemicals, and the spatio-temporal variability thereof, is urgently needed in the context of protecting and restoring aquatic ecosystems. This paper discusses a computational material flow analysis to predict the occurrence of thousands of man-made organic chemicals on a European scale, based on a novel temporally and spatially resolved modelling framework. The goal was to increase understanding of pressures by emerging chemicals and to complement surface water monitoring data. The ambition was to provide a first step towards a "real-life" mixture exposure situation accounting for as many chemicals as possible. Comparison of simulated concentrations and chemical monitoring data for 226 substance/basin combinations showed that the simulated concentrations were accurate on average. For 65% and 90% of substance/basin combinations the error was within one and two orders of magnitude respectively. An analysis of the relative importance of uncertainties revealed that inaccuracies in use volume or use type information contributed most to the error for individual substances. To resolve this, we suggest better registration of use types of industrial chemicals, investigation of presence/absence of industrial chemicals in wastewater and runoff samples and more scientific information exchange.

Exposure and ecotoxicological risk assessment of mixtures of top prescribed pharmaceuticals in Swedish freshwaters

Surface water concentrations of 54 pharmaceuticals were predicted for seven major Swedish rivers and the Stockholm City area basins using the STREAM-EU model. These surface water concentrations were used to predict the ecotoxicological impact resulting from the exposure of aquatic organisms to this mixture of 54 pharmaceuticals. STREAM-EU model results indicated that <10 substances were present at median annual water concentrations greater than 10 ng/L with highest concentrations occurring mostly in the more densely populated area of the capital city, Stockholm. There was considerable spatial and temporal variability in the model predictions (1-3 orders of magnitude) due to natural variability (e.g. hydrology, temperature), variations in emissions and uncertainty sources. Local mixture ecotoxicological pressures based on acute EC50 data as well as on chronic NOEC data, expressed as multi-substance potentially affected fraction of species (msPAF), were quantified in 114 separate locations in the waterbodies. It was estimated that 5% of the exposed aquatic species would experience exposure at or above their acute EC50 concentrations (so-called acute hazardous concentration for 5% of species, or aHC5) at only 7% of the locations analyzed (8 out of 114 locations). For the evaluation based on chronic NOEC concentrations, the chronic HC5 (cHC5) is exceeded at 27% of the locations. The acute mixture toxic pressure was estimated to be predominantly caused by only three substances in all waterbodies: Furosemide, Tramadol and Ibuprofen. A similar evaluation of chronic toxic pressure evaluation logically demonstrates that more substances play a significant role in causing a higher chronic toxic pressure at more sites as compared to the acute toxic pressure evaluation. In addition to the three substances contributing most to acute effects, the chronic effects are predominantly caused by another five substances: paracetamol, diclofenac, ethinylestradiol, erythromycin and ciprofloxacin. This study provides regulatory authorities and companies responsible for water quality valuable information for targeting remediation measures and monitoring on a substance and location basis.

Applicability of the fish embryo acute toxicity (FET) test (OECD 236) in the regulatory context of Registration, Evaluation, Authorisation, and Restriction of Chemicals (REACH)

In 2013 the Organisation for Economic Co-operation and Development (OECD) test guideline (236) for fish embryo acute toxicity (FET) was adopted. It determines the acute toxicity of chemicals to embryonic fish. Previous studies show a good correlation of FET with the standard acute fish toxicity (AFT) test; however, the potential of the FET test to predict AFT, which is required by the Registration, Evaluation, Authorisation, and Restriction of Chemicals (REACH) regulation (EC 1907/2006) and the Classification, Labelling and Packaging (CLP) Regulation (EC 1272/2008), has not yet been fully clarified. In 2015 the European Chemicals Agency (ECHA) requested that a consultant perform a scientific analysis of the applicability of FET to predict AFT. The purpose was to compare the toxicity of substances to fish embryos and to adult fish, and to investigate whether certain factors (e.g., physicochemical properties, modes of action, or chemical structures) could be used to define the applicability boundaries of the FET test. Given the limited data availability, the analysis focused on organic substances. The present critical review summarizes the main findings and discusses regulatory application of the FET test under REACH. Given some limitations (e.g., neurotoxic mode of action) and/or remaining uncertainties (e.g., deviation of some narcotic substances), it has been found that the FET test alone is currently not sufficient to meet the essential information on AFT as required by the REACH regulation. However, the test may be used within weight-of-evidence approaches together with other independent, relevant, and reliable sources of information. The present review also discusses further research needs that may overcome the remaining uncertainties and help to increase acceptance of FET as a replacement for AFT in the future. For example, an increase in the availability of data generated according to OECD test guideline 236 may provide evidence of a higher predictive power of the test. Environ Toxicol Chem 2018;37:657-670. © 2017 SETAC.

PBT assessment under REACH: Screening for low aquatic bioaccumulation with QSAR classifications based on physicochemical properties to replace BCF in vivo testing on fish

Aquatic bioconcentration factors (BCFs) are critical in PBT (persistent, bioaccumulative, toxic) and risk assessment of chemicals. High costs and use of more than 100 fish per standard BCF study (OECD 305) call for alternative methods to replace as much in vivo testing as possible. The BCF waiving scheme is a screening tool combining QSAR classifications based on physicochemical properties related to the distribution (hydrophobicity, ionisation), persistence (biodegradability, hydrolysis), solubility and volatility (Henry's law constant) of substances in water bodies and aquatic biota to predict substances with low aquatic bioaccumulation (nonB, BCF<2000). The BCF waiving scheme was developed with a dataset of reliable BCFs for 998 compounds and externally validated with another 181 substances. It performs with 100% sensitivity (no false negatives), >50% efficacy (waiving potential), and complies with the OECD principles for valid QSARs. The chemical applicability domain of the BCF waiving scheme is given by the structures of the training set, with some compound classes explicitly excluded like organometallics, poly- and perfluorinated compounds, aromatic triphenylphosphates, surfactants. The prediction confidence of the BCF waiving scheme is based on applicability domain compliance, consensus modelling, and the structural similarity with known nonB and B/vB substances. Compounds classified as nonB by the BCF waiving scheme are candidates for waiving of BCF in vivo testing on fish due to low concern with regard to the B criterion. The BCF waiving scheme supports the 3Rs with a possible reduction of >50% of BCF in vivo testing on fish. If the target chemical is outside the applicability domain of the BCF waiving scheme or not classified as nonB, further assessments with in silico, in vitro or in vivo methods are necessary to either confirm or reject bioaccumulative behaviour.

Contribution of waste water treatment plants to pesticide toxicity in agriculture catchments

Pesticide residues are frequently found in water bodies and may threaten freshwater ecosystems and biodiversity. In addition to runoff or leaching from treated agricultural fields, pesticides may enter streams via effluents from wastewater treatment plants (WWTPs). We compared the pesticide toxicity in terms of log maximum Toxic Unit (log mTU) of sampling sites in small agricultural streams of Germany with and without WWTPs in the upstream catchments. We found an approximately half log unit higher pesticide toxicity for sampling sites with WWTPs (p < 0.001). Compared to fungicides and insecticides, herbicides contributed most to the total pesticide toxicity in streams with WWTPs. A few compounds (diuron, terbuthylazin, isoproturon, terbutryn and Metazachlor) dominated the herbicide toxicity. Pesticide toxicity was not correlated with upstream distance to WWTP (Spearman's rank correlation, rho = - 0.11, p > 0.05) suggesting that other context variables are more important to explain WWTP-driven pesticide toxicity. Our results suggest that WWTPs contribute to pesticide toxicity in German streams.

Model-predicted occurrence of multiple pharmaceuticals in Swedish surface waters and their flushing to the Baltic Sea

An exposure assessment for multiple pharmaceuticals in Swedish surface waters was made using the STREAM-EU model. Results indicate that Metformin (27 ton/y), Paracetamol (6.9 ton/y) and Ibuprofen (2.33 ton/y) were the drugs with higher amounts reaching the Baltic Sea in 2011. 35 of the studied substances had more than 1 kg/y of predicted flush to the sea. Exposure potential given by the ratio amount of the drug exported to the sea/amount emitted to the environment was higher than 50% for 7 drugs (Piperacillin, Lorazepam, Metformin, Hydroxycarbamide, Hydrochlorothiazide, Furosemide and Cetirizine), implying that a high proportion of them will reach the sea, and below 10% for 27 drugs, implying high catchment attenuation. Exposure potentials were found to be dependent of persistency and hydrophobicity of the drugs. Chemicals with Log D > 2 had exposure potentials <10% regardless of their persistence. Chemicals with Log D  <  -2 had exposure potentials >35% with higher ratios typically achieved for longer half-lives. For Stockholm urban area, 17 of the 54 pharmaceuticals studied had calculated concentrations higher than 10 ng/L. Model agreement with monitored values had an r² = 0.62 for predicted concentrations and an r² = 0.95 for predicted disposed amounts to sea.

Nontargeted detection and identification of (aromatic) amines in environmental samples based on diagnostic derivatization and LC-high resolution mass spectrometry

The presence of aromatic amines in the environment has been in the focus of research, as many of these compounds are known or suspected mutagens and carcinogens. To facilitate the detection of aromatic amines in complex environmental samples by LC-high resolution mass spectrometry, an on-line-post-column and a pre-column derivatization method to label (in an ideal case) all aromatic amines was evaluated by applying different derivatization reagents. 4-Fluoro-7-nitro-2,1,3-benzoxadiazole (NBD-F) was found to be the most promising labeling reagent due to its high reactivity with both primary and secondary amines and its low signal in positive mode electrospray ionization (ESI+). Post-column on-line derivatization did not result in sufficient signal intensities of derivatives. With pre-column derivatization most of the selected aromatic amines resulted in a derivative that shows common fragments of diagnostic value. The selectivity of NBD-F was studied in depth with a data set of 220 compounds with different functional groups showing that also aliphatic amines and some thiols yield a derivative. The developed method was successfully applied to wastewater effluent samples and several derivatives were confirmed by diagnostic neutral losses.

An Integrated Data-Driven Strategy for Safe-by-Design Nanoparticles: The FP7 MODERN Project

The development and implementation of safe-by-design strategies is key for the safe development of future generations of nanotechnology enabled products. The safety testing of the huge variety of nanomaterials that can be synthetized is unfeasible due to time and cost constraints. Computational modeling facilitates the implementation of alternative testing strategies in a time and cost effective way. The development of predictive nanotoxicology models requires the use of high quality experimental data on the structure, physicochemical properties and bioactivity of nanomaterials. The FP7 Project MODERN has developed and evaluated the main components of a computational framework for the evaluation of the environmental and health impacts of nanoparticles. This chapter describes each of the elements of the framework including aspects related to data generation, management and integration; development of nanodescriptors; establishment of nanostructure-activity relationships; identification of nanoparticle categories; hazard ranking and risk assessment.

Micropollutants in European rivers: A mode of action survey to support the development of effect-based tools for water monitoring

Environmental quality monitoring of water resources is challenged with providing the basis for safeguarding the environment against adverse biological effects from exposure to anthropogenic chemicals originating from diffuse and point sources. Although current regulatory efforts focus on monitoring and assessing a few legacy chemicals, many more anthropogenic chemicals are and will become detected in aquatic resources as a result of progress in analytical techniques. Assessing this type of exposure information based on available standard approaches from prospective risk assessment for single chemicals inevitably leads to indication of risk in most surface water bodies. As an alternative to generic assessment approaches, effect-based monitoring approaches are suggested. This offers the advantage of reducing uncertainties of effect extrapolation and additionally accounts for mixture effects. To become a credible complement to chemical monitoring information, however, a better understanding of the capabilities and gaps of available effect-based tools is needed. The authors therefore undertook to 1) compile organic contaminants detected in freshwater monitoring studies, 2) provide a synopsis of the mode of action knowledge available for the detected compounds, 3) perform a hazard ranking to identify priority mixtures, and 4) reflect on the challenges to make bioassays fit for effect-based monitoring. The present Focus article shows that chemical occurrence in European freshwaters seems to be highly variable in composition and relative abundancies. Further, although the present mode of action knowledge remains limited, the authors already see the need for batteries of effect-based tools if a more comprehensive coverage of prevailing effect qualities for mixtures is to be targeted. Finally, they suggest a list of organic compounds that could serve as a reference list for effect-based tool validation studies. Environ Toxicol Chem 2016;35:1887-1899. © 2016 SETAC.

Variation in predicted internal concentrations in relation to PBPK model complexity for rainbow trout

The present study is motivated by the increasing demand to consider internal partitioning into tissues instead of exposure concentrations for the environmental toxicity assessment. To this end, physiologically based pharmacokinetic (PBPK) models can be applied. We evaluated the variation in accuracy of PBPK model outcomes depending on tissue constituents modeled as sorptive phases and chemical distribution tendencies addressed by molecular descriptors. The model performance was examined using data from 150 experiments for 28 chemicals collected from US EPA databases. The simplest PBPK model is based on the "Kow-lipid content" approach as being traditional for environmental toxicology. The most elaborated one considers five biological sorptive phases (polar and non-polar lipids, water, albumin and the remaining proteins) and makes use of LSER (linear solvation energy relationship) parameters to describe the compound partitioning behavior. The "Kow-lipid content"-based PBPK model shows more than one order of magnitude difference in predicted and measured values for 37% of the studied exposure experiments while for the most elaborated model this happens only for 7%. It is shown that further improvements could be achieved by introducing corrections for metabolic biotransformation and compound transmission hindrance through a cellular membrane. The analysis of the interface distribution tendencies shows that polar tissue constituents, namely water, polar lipids and proteins, play an important role in the accumulation behavior of polar compounds with H-bond donating functional groups. For compounds without H-bond donating fragments preferable accumulation phases are storage lipids and water depending on compound polarity.

Inhalation threshold of toxicological concern (TTC) - Structural alerts discriminate high from low repeated-dose inhalation toxicity

The threshold of toxicological concern (TTC) of a compound represents an exposure value below which the associated human health risk is considered negligible. As such, this approach offers assessing the risk of potential toxicants when little or no toxicological information is available. For the inhalation repeated-dose TTC, the goal was to derive structural alerts that discriminate between high- and low-toxic compounds. A further aim was to identify physicochemical parameters related to the inhalation-specific bioavailability of the compounds, and to explore their use as predictors of high vs low toxicity. 296 compounds with subacute, subchronic and chronic inhalation toxicity NOEC (no-observed effect concentration) values were subdivided into three almost equal-sized high-, medium- and low-toxic (HTox, MTox, LTox) potency classes. Whereas the derived 14 HTox and 7 LTox structural alerts yield an only moderate discrimination between these three groups, the high-toxic vs low-toxic mis-classification is very low: LTox-predicted compounds are not HTox to 97.5%, and HTox-predicted compounds not LTox to 88.6%. The probability of a compound being HTox vs LTox is triggered further by physicochemical properties encoding the tendency to evaporate from blood. The new structural alerts may aid in the predictive inhalation toxicity assessment of compounds as well as in designing low-toxicity chemicals, and provide a rationale for the chemistry underlying the toxicological outcome that can also be used for scoping targeted experimental studies.

White paper on the promotion of an integrated risk assessment concept in European regulatory frameworks for chemicals

The vision of a sustainable and safe use of chemicals to protect human health, preserve the environment and maintain the ecosystem requires innovative and more holistic approaches to risk assessment (RA) in order to better inform decision making. Integrated risk assessment (IRA) has been proposed as a solution to current scientific, societal and policy needs. It is defined as the mutual exploitation of environmental risk assessment (ERA) for human health risk assessment (HHRA) and vice versa in order to coherently and more efficiently characterize an overall risk to humans and the environment for better informing the risk analysis process. Extrapolating between species which are relevant for HHRA and ERA requires a detailed understanding of pathways of toxicity/modes of action (MoA) for the various toxicological endpoints. Significant scientific advances, changes in chemical legislation, and increasing environmental consciousness have created a favourable scientific and regulatory environment to develop and promote the concept and vision of IRA. An initial proof of concept is needed to foster the incorporation of IRA approaches into different chemical sectorial regulations and demonstrate their reliability for regulatory purposes. More familiarity and confidence with IRA will ultimately contribute to an overall reduction in in vivo toxicity testing requirements. However, significant progress will only be made if long-term support for MoA-related research is secured. In the short term, further exchange and harmonization of RA terminology, models and methodologies across chemical categories and regulatory agencies will support these efforts. Since societal values, public perceptions and cultural factors are of increasing importance for the acceptance of risk analysis and successful implementation of risk mitigation measures, the integration of socio-economic analysis and socio-behavioural considerations into the risk analysis process may help to produce a more effective risk evaluation and consideration of the risks and benefits associated with the use of chemicals.

Fish embryo toxicity test: identification of compounds with weak toxicity and analysis of behavioral effects to improve prediction of acute toxicity for neurotoxic compounds

The fish embryo toxicity test has been proposed as an alternative for the acute fish toxicity test, but concerns have been raised for its predictivity given that a few compounds have been shown to exhibit a weak acute toxicity in the fish embryo. In order to better define the applicability domain and improve the predictive capacity of the fish embryo test, we performed a systematic analysis of existing fish embryo and acute fish toxicity data. A correlation analysis of a total of 153 compounds identified 28 compounds with a weaker or no toxicity in the fish embryo test. Eleven of these compounds exhibited a neurotoxic mode of action. We selected a subset of eight compounds with weaker or no embryo toxicity (cyanazine, picloram, aldicarb, azinphos-methyl, dieldrin, diquat dibromide, endosulfan, and esfenvalerate) to study toxicokinetics and a neurotoxic mode of action as potential reasons for the deviating fish embryo toxicity. Published fish embryo LC50 values were confirmed by experimental analysis of zebrafish embryo LC50 according to OECD guideline 236. Except for diquat dibromide, internal concentration analysis did not indicate a potential relation of the low sensitivity of fish embryos to a limited uptake of the compounds. Analysis of locomotor activity of diquat dibromide and the neurotoxic compounds in 98 hpf embryos (exposed for 96 h) indicated a specific effect on behavior (embryonic movement) for the neurotoxic compounds. The EC50s of behavior for neurotoxic compounds were close to the acute fish toxicity LC50. Our data provided the first evidence that the applicability domain of the fish embryo test (LC50s determination) may exclude neurotoxic compounds. However, neurotoxic compounds could be identified by changes in embryonic locomotion. Although a quantitative prediction of acute fish toxicity LC50 using behavioral assays in fish embryos may not yet be possible, the identification of neurotoxicity could trigger the conduction of a conventional fish acute toxicity test or application of assessment factors while considering the very good fish embryo-acute fish toxicity correlation for other compounds.

Integrated testing strategy (ITS) for bioaccumulation assessment under REACH

REACH (registration, evaluation, authorisation and restriction of chemicals) regulation requires that all the chemicals produced or imported in Europe above 1 tonne/year are registered. To register a chemical, physicochemical, toxicological and ecotoxicological information needs to be reported in a dossier. REACH promotes the use of alternative methods to replace, refine and reduce the use of animal (eco)toxicity testing. Within the EU OSIRIS project, integrated testing strategies (ITSs) have been developed for the rational use of non-animal testing approaches in chemical hazard assessment. Here we present an ITS for evaluating the bioaccumulation potential of organic chemicals. The scheme includes the use of all available data (also the non-optimal ones), waiving schemes, analysis of physicochemical properties related to the end point and alternative methods (both in silico and in vitro). In vivo methods are used only as last resort. Using the ITS, in vivo testing could be waived for about 67% of the examined compounds, but bioaccumulation potential could be estimated on the basis of non-animal methods. The presented ITS is freely available through a web tool.

Occurrence and toxicity of 331 organic pollutants in large rivers of north Germany over a decade (1994 to 2004)

We analyzed the detection frequencies and concentrations for 331 organic compounds measured between 1994 and 2004 in the four largest rivers of north Germany, the Elbe, Weser, Aller, and Ems Rivers, and we assessed the potential risk for aquatic fauna using experimental and predicted acute toxicity data for the green alga Pseudokirchneriella subcapitata, the crustacean Daphnia magna, and the fish Pimephales promelas. The detection frequency for most compounds decreased significantly from 1994 to 2004. Polycyclic aromatic hydrocarbons (PAHs) were most frequently detected, while pesticides were the most important chemical group concerning toxicity for the standard test organisms. The predicted toxicity for D. magna was significantly higher than for the other organisms and reached levels envisaging acute toxic effects on the invertebrate fauna, still in 2004. Most of the compounds responsible for potential acute effects on aquatic organisms are currently not considered as priority substances in the European Union, while only 2 of 25 priority substances that have been measured occurred at levels that may be relevant in terms of toxicity for the selected test organisms. We conclude that attenuation of pesticides and other organic toxicants should play an increased role in river basin management.

Quantitative read-across for predicting the acute fish toxicity of organic compounds

Read-across enables the interpolation of a property for a target chemical from respective experimental data of sufficiently similar compounds. Employing a set of 692 organic compounds with experimental values for the 96 h fish toxicity toward the fathead minnow in terms of LC(50) (lethal concentration 50%) values, a read-across method has been developed that is based on atom-centered fragments (ACFs) for evaluating chemical similarity. Prediction of log LC(50) proceeds through reading across the toxicity enhancement over predicted narcosis-level toxicity in terms of the respective logarithmic ratio, log T(e), and adding the respective baseline narcosis LC(50) estimated from log K(ow) (octanol/water partition coefficient). Depending on the minimum similarity imposed on a compound to serve as read-across basis for the target chemical, three different standard settings have been introduced, allowing one to perform screening-level estimations as well as predictions with intermediate and good confidence. The respective squared correlation coefficients (r(2)) are 0.73, 0.78, and 0.87, with root-mean square errors (rms) of 0.73, 0.60, and 0.39 log units, respectively. As a general trend, increasing the ACF minimum similarity increases the prediction quality at the cost of decreasing the application range. The method has the potential to assist in the predictive evaluation of fish toxicity for regulatory purposes such as under the REACH legislation.

A new risk assessment approach for the prioritization of 500 classical and emerging organic microcontaminants as potential river basin specific pollutants under the European Water Framework Directive

Given the huge number of chemicals released into the environment and existing time and budget constraints, there is a need to prioritize chemicals for risk assessment and monitoring in the context of the European Union Water Framework Directive (EU WFD). This study is the first to assess the risk of 500 organic substances based on observations in the four European river basins of the Elbe, Scheldt, Danube and Llobregat. A decision tree is introduced that first classifies chemicals into six categories depending on the information available, which allows water managers to focus on the next steps (e.g. derivation of Environmental Quality Standards (EQS), improvement of analytical methods, etc.). The priority within each category is then evaluated based on two indicators, the Frequency of Exceedance and the Extent of Exceedance of Predicted No-Effect Concentrations (PNECs). These two indictors are based on maximum environmental concentrations (MEC), rather than the commonly used statistically based averages (Predicted Effect Concentration, PEC), and compared to the lowest acute-based (PNEC(acute)) or chronic-based thresholds (PNEC(chronic)). For 56% of the compounds, PNECs were available from existing risk assessments, and the majority of these PNECs were derived from chronic toxicity data or simulated ecosystem studies (mesocosm) with rather low assessment factors. The limitations of this concept for risk assessment purposes are discussed. For the remainder, provisional PNECs (P-PNECs) were established from read-across models for acute toxicity to the standard test organisms Daphnia magna, Pimephales promelas and Selenastrum capricornutum. On the one hand, the prioritization revealed that about three-quarter of the 44 substances with MEC/PNEC ratios above ten were pesticides. On the other hand, based on the monitoring data used in this study, no risk with regard to the water phase could be found for eight of the 41 priority substances, indicating a first success of the implementation of the WFD in the investigated river basins.

Effects of pesticides monitored with three sampling methods in 24 sites on macroinvertebrates and microorganisms

Grab water samples, sediment samples, and 2,2,4-trimethylpentane passive samplers (TRIMPS) were used to determine the exposure to 97 pesticides in 24 southeast Australian stream sites over 5 months. Macroinvertebrate communities and selected microorganisms (bacteria, flagellates, ciliates, amoebas, nematodes, and gastrotrichs) were sampled to detect relationships with pesticide toxicity. Sediment samples had the highest estimated toxicities in terms of toxic units (TU) for Daphnia magna (TUDM) and for Selenastrum capricornutum (TUSC). The pesticide-selective SPEARpesticides and the general SIGNAL index for macroinvertebrates exhibited negative linear relationships (r(2) = 0.67 and 0.36, respectively) with pesticide contamination in terms of log maximum TUDM (log mTUDM), suggesting macroinvertebrate community change due to pesticide exposure. Pesticide contamination was the only measured variable explaining variation in ecological quality. Variation in the densities of several microbial groups was best explained by environmental variables other than log TUs. The log mTUDM values derived from sediment concentrations were most important to establish a link with effects on macroinvertebrates, whereas log mTUDM of grab water samples had only minor contribution. Current-use insecticides and fungicides can affect macroinvertebrate communities and monitoring of sediment and continuous water sampling is needed to detect these effects.

Application of preparative capillary gas chromatography (pcGC), automated structure generation and mutagenicity prediction to improve effect-directed analysis of genotoxicants in a contaminated groundwater

BACKGROUND, AIM AND SCOPE

The importance of groundwater for human life cannot be overemphasised. Besides fulfilling essential ecological functions, it is a major source of drinking water. However, in the industrial area of Bitterfeld, it is contaminated with a multitude of harmful chemicals, including genotoxicants. Therefore, recently developed methodologies including preparative capillary gas chromatography (pcGC), MOLGEN-MS structure generation and mutagenicity prediction were applied within effect-directed analysis (EDA) to reduce sample complexity and to identify candidate mutagens in the samples. A major focus was put on the added value of these tools compared to conventional EDA combining reversed-phase liquid chromatography (RP-LC) followed by GC/MS analysis and MS library search.

MATERIALS AND METHODS

We combined genotoxicity testing with umuC and RP-LC with pcGC fractionation to isolate genotoxic compounds from a contaminated groundwater sample. Spectral library information from the NIST05 database was combined with a computer-based structure generation tool called MOLGEN-MS for structure elucidation of unknowns. Finally, we applied a computer model for mutagenicity prediction (ChemProp) to identify candidate mutagens and genotoxicants.

RESULTS AND DISCUSSION

A total of 62 components were tentatively identified in genotoxic fractions. Ten of these components were predicted to be potentially mutagenic, whilst 2,4,6-trichlorophenol, 2,4-dichloro-6-methylphenol and 4-chlorobenzoic acid were confirmed as genotoxicants.

CONCLUSIONS AND PERSPECTIVES

The results suggest pcGC as a high-resolution fractionation tool and MOLGEN-MS to improve structure elucidation, whilst mutagenicity prediction failed in our study to predict identified genotoxicants. Genotoxicity, mutagenicity and carcinogenicity caused by chemicals are complex processes, and prediction from chemical structure still appears to be quite difficult. Progress in this field would significantly support EDA and risk assessment of environmental mixtures.

Trends in economic traits, halothane sensitivity, blood group and enzyme systems of Swiss Landrace and Large White pigs

Pigs deriving from 150 breeding centres constituting a representative section of elite breeding herds (2496 Swiss Landrace pigs, 587 Swiss Large White pigs) were subjected to blood typing during the period 1981 to 1984. Production traits such as daily gain, feed conversion ratio, lean meat content and meat quality score were available to show the trend in these performance traits since 1978. Field data on the halothane reaction of 14 270 Swiss Landrace (SL) pigs were used to assess the porcine stress syndrome during the period 1978-1983. In SL pigs the frequency of the alleles Ha, PhiB and AdaA decreased significantly, and that of the Hc and PhiA increased during the period of the study. The frequency of the Ha allele dropped from 0.36 in 1981 to 0.20 in 1984, whereas the Hc allele rose from 0.22 to 0.37. In Swiss Large White (SLW) pigs, on the other hand, the frequency of the Ha allele increased constantly from 0.31 to 0.37 during this period. An initial frequency of 17.7% (1978) halothane reactors in SL pigs was lowered to 0.7% (1982) after five years of halothane testing. In SL pigs the meat quality scores improved regularly, whereas in SLW pigs it did not change very much. The percentage of PSE animals in the SL breed was reduced from 32.7% in 1978 to 7.1% in 1983. Because the Hal locus is associated with production traits such as meat quality, linkage disequilibria could explain the observed associations between the H and Phi types and production traits.

Recombination rates and gene order for some serum alpha-protease inhibitors and immunoglobulin heavy-chain allotypes in pigs

Linkage analysis between the genes coding for immunoglobulin heavy-chain allotypes and variants of some serum alpha-protease inhibitors produced lod scores above the significance limit of 3. The maximum likelihood estimate of the recombination fraction (theta) ranged from 0.15 to 0.20. Since this is the second report on this linkage group in pigs, the linkage is confirmed. Data from appropriate matings are consistent with a gene order of Pi1-Po1A-(Po1B)-Pi2-Igh1.

External validation and prediction employing the predictive squared correlation coefficient test set activity mean vs training set activity mean

The external prediction capability of quantitative structure-activity relationship (QSAR) models is often quantified using the predictive squared correlation coefficient, q (2). This index relates the predictive residual sum of squares, PRESS, to the activity sum of squares, SS, without postprocessing of the model output, the latter of which is automatically done when calculating the conventional squared correlation coefficient, r (2). According to the current OECD guidelines, q (2) for external validation should be calculated with SS referring to the training set activity mean. Our present findings including a mathematical proof demonstrate that this approach yields a systematic overestimation of the prediction capability that is triggered by the difference between the training and test set activity means. Example calculations with three regression models and data sets taken from literature show further that for external test sets, q (2) based on the training set activity mean may become even larger than r (2). As a consequence, we suggest to always use the test set activity mean when quantifying the external prediction capability through q (2) and to revise the respective OECD guidance document accordingly. The discussion includes a comparison between r (2) and q (2) value ranges and the q (2) statistics for cross-validation.

Mutational analyses of c-FLIPR, the only murine short FLIP isoform, reveal requirements for DISC recruitment

Cellular FLICE-inhibitory protein (c-FLIP) proteins are known as potent inhibitors of death receptor-mediated apoptosis by interfering with caspase-8 activation at the death-inducing signaling complex (DISC). Among the three human isoforms, c-FLIP(long), c-FLIP(short) and c-FLIP(R), the latter isoform is poorly characterized. We report here the characterization of murine c-FLIP(R) and show that it is the only short c-FLIP isoform expressed in mice. By generating several mutants, we demonstrate that both death effector domains (DEDs) are required for DISC binding and the antiapoptotic function of c-FLIP(R). Surprisingly, the C-terminal tail is important for both protein stability and DISC recruitment. Three-dimensional modeling of c-FLIP(R) revealed a substantial similarity of the overall structures and potential interaction motifs with the viral FLIP MC159. We found, however, that c-FLIP(R) uses different structural motifs for its DISC recruitment. Whereas MC159 interferes with interaction and self-oligomerization of the DISC component FADD by its extensive hydrophilic surface, a narrow hydrophobic patch of c-FLIP(R) on the surface of DED2 is crucial for DISC association. Thus, despite the presence of similar tandem DEDs, viral and cellular FLIPs inhibit apoptosis by remarkably divergent mechanisms.