Different Modes Of Toxic Action Research Articles

Triphenyl phosphate proved more potent than its metabolite diphenyl phosphate in inducing hepatic insulin resistance through endoplasmic reticulum stress

Triphenyl phosphate (TPHP) is a widely used flame retardant and plasticizer and has been detected extensively in environmental media, wildlife and human bodies. Several epidemiological and animal studies have revealed that TPHP exposure is positively associated with glucose homeostasis disruption and diabetes. However, the effects of TPHP on hepatic glucose homeostasis and the underlying mechanisms remain unclear. The present work aimed to investigate the cytotoxicity and glucose metabolism disruption of TPHP and its metabolite diphenyl phosphate (DPHP) within hepatocytes. The cell viability assay undertaken on human normal liver (L02) cells showed that TPHP exhibited more potent hepatotoxicity than DPHP. RNA sequencing (RNA-seq) data showed that TPHP and DPHP presented different modes of toxic action. Insulin resistance is one of the predominant toxicities for TPHP, but not for DPHP. The insulin-stimulated glucose uptake and glycogen synthesis were impaired by TPHP, while DPHP exhibited no significant impairment on these factors. TPHP exposure induced endoplasmic reticulum (ER) stress, and the ER stress antagonist 4-PBA restored the impairment of insulin-stimulated glucose uptake and glycogen synthesis induced by TPHP. TPHP could also induce liver ER stress and insulin resistance in mice. Taken together, the results suggested that TPHP induces more potent insulin resistance through ER stress than its metabolite DPHP.

The chemical exposure toxicity space (CETS) model: Displaying exposure time, aqueous and organic concentration, activity, and onset of toxicity.

A 1‐compartment toxicokinetic model is used to characterize the chemical exposure toxicity space (CETS), providing a novel graphic tool that can aid in the design of aquatic toxicity tests for fish and for interpreting their results. The graph depicts the solution to the differential equation describing the uptake kinetics of a chemical by a modeled fish under conventional bioassay conditions. The model relates the exposure concentration in the water to a dimensionless time and the onset of toxicity as determined by an estimated or assumed critical body residue or incipient lethal aqueous concentration. These concentration graphs are specific to each chemical and exposure and organism parameters and clearly demonstrate differences in toxicity between chemicals and how factors such as hydrophobicity influence the toxic endpoint. The CETS plots can also be used to assess bioconcentration test conditions to ensure that concentrations are well below toxic levels. Illustrative applications are presented using a recent set of high‐quality toxicity data. Conversion of concentrations to chemical activities in the plots enables results for different baseline toxicants to be superimposed. For chemicals that have different modes of toxic action, the increased toxicity then becomes apparent. Implications for design and interpretation of aquatic toxicity tests are discussed. The model, and pictorial visualization of the time‐course of aquatic toxicity tests, may contribute to improvements in test design, implementation, and interpretation, and to reduced animal usage. Environ Toxicol Chem 2017;36:1389–1396. © 2016 The Authors. Environmental Toxicology and Chemistry Published by Wiley Periodicals, Inc. on behalf of SETAC.

Does long-term fungicide exposure affect the reproductive performance of leaf-shredders? A partial life-cycle study using Hyalella azteca

Leaf-shredding amphipods play a critical role in the ecosystem function of leaf litter breakdown, a key process in many low order streams. Fungicides, however, may adversely influence shredders' behavior and the functions they provide, while there is only limited knowledge concerning effects on their reproductive performance. To assess the latter, a semi-static 56-day partial life-cycle bioassay using the model shredder Hyalella azteca (n = 30) was performed applying two environmentally relevant concentrations of a model fungicide mixture (i.e., 5 and 25 μg/L) composed of five fungicides with different modes of toxic action. Variables related to the food processing (leaf consumption and feces production), growth (body length and dry weight), energy reserves (lipid content), and reproduction (amplexus pairs, number and length of offspring) were determined to understand potential implications in the organisms' energy budget. While the fungicides did not affect leaf consumption, both fungicide treatments significantly reduced amphipods' feces production (∼20%) compared to the control. This observation suggests an increased food utilization to counteract the elevated and stress-related energy demand: although growth as well as energy reserves were unaffected, amplexus pairs were less frequently observed in both fungicide treatments (∼50–100%) suggesting a tradeoff regarding energy allocation favoring the maintenance of fundamental functions at the organism level over reproduction. As a result, the time to release of first offspring was delayed in both fungicide treatments (7 and 14 days) and the median number of offspring was significantly lower in the 25-μg/L treatment (100%), whereas offspring length remained unaffected. The results of this study thus indicate that chronic fungicide exposures can negatively impact shredders' reproductive performance. This may translate into lower abundances and thus a reduced contribution to leaf litter breakdown in fungicide-impacted streams with potentially far-reaching consequences for detritus-based food webs.

Acute sensitivity of a broad range of freshwater mussels to chemicals with different modes of toxic action.

Freshwater mussels, one of the most imperiled groups of animals in the world, are generally underrepresented in toxicity databases used for the development of ambient water quality criteria and other environmental guidance values. Acute 96-h toxicity tests were conducted to evaluate the sensitivity of 5 species of juvenile mussels from 2 families and 4 tribes to 10 chemicals (ammonia, metals, major ions, and organic compounds) and to screen 10 additional chemicals (mainly organic compounds) with a commonly tested mussel species, fatmucket (Lampsilis siliquoidea). In the multi-species study, median effect concentrations (EC50s) among the 5 species differed by a factor of ≤2 for chloride, potassium, sulfate, and zinc; a factor of ≤5 for ammonia, chromium, copper, and nickel; and factors of 6 and 12 for metolachlor and alachlor, respectively, indicating that mussels representing different families or tribes had similar sensitivity to most of the tested chemicals, regardless of modes of action. There was a strong linear relationship between EC50s for fatmucket and the other 4 mussel species across the 10 chemicals (r2 = 0.97, slope close to 1.0), indicating that fatmucket was similar to other mussel species; thus, this commonly tested species can be a good surrogate for protecting other mussels in acute exposures. The sensitivity of juvenile fatmucket among different populations or cultured from larvae of wild adults and captive-cultured adults was also similar in acute exposures to copper or chloride, indicating captive-cultured adult mussels can reliably be used to reproduce juveniles for toxicity testing. In compiled databases for all freshwater species, 1 or more mussel species were among the 4 most sensitive species for alachlor, ammonia, chloride, potassium, sulfate, copper, nickel, and zinc; therefore, the development of water quality criteria and other environmental guidance values for these chemicals should reflect the sensitivity of mussels. In contrast, the EC50s of fatmucket tested in the single-species study were in the high percentiles (>75th) of species sensitivity distributions for 6 of 7 organic chemicals, indicating mussels might be relatively insensitive to organic chemicals in acute exposures. Environ Toxicol Chem 2017;36:786-796. Published 2016 Wiley Periodicals, Inc. on behalf of SETAC. This article is a US government work and, as such, is in the public domain in the United States of America.

How benthic diatoms within natural communities respond to eight common herbicides with different modes of action

Herbicides are common pollutants of rivers in agricultural regions. These contaminants include various types of chemicals with different modes of toxic action. Herbicides can have toxic effects on freshwater benthic diatoms, the base of the aquatic food web. We examined the effects of (non-mixture) herbicide exposure to the health of diatoms for eight common herbicides with three different modes of action; the photosystem II (PSII) inhibitors: atrazine, simazine, hexazinone, tebuthiuron and diuron; two auxinic herbicides: MCPA and 2,4-D; and the EPSP synthase inhibitor: glyphosate. Benthic diatoms within riverine communities were exposed to each herbicide in rapid toxicity tests at concentrations of 50, 200 and 500μgL−1. The most sensitive taxa were Gomphonema spp. and Encyonema gracilis. Navicula cryptotenella was the most tolerant to herbicide exposure. There was no significant effect of the different herbicide modes of action at the community level. Herbicide mode of action did not alter which taxa were most sensitive within the community and sensitivity rankings of the dominant diatom taxa were similar for each of the eight herbicides. The consistency of the results between herbicides suggests that freshwater benthic diatoms may be suitable in situ indicators for detecting the toxicity of herbicides with differing modes of action.

Critical body residue to fish of organic pollutants

The internal concentration represented by critical body residue(CBR) is an ideal indicator of the intrinsic toxicity of a chemical that can be used to assess toxicity to aquatic organisms. In this study, we systematically summarized the method for calculation of CBR in fish, CBR values with different modes of toxic action, the relationship between CBR and BCF, and the factors influencing the CBR based on the progress in this field as a result of studies conducted worldwide and our own investigations. The CBRs could be calculated by the LC50 and BCF based on the toxicokinetic model. The modes of toxic action of fish are usually recognized based on classification of organic compounds as acting by non-polar narcosis(baseline compounds), polar narcosis(less inert compounds), or reactive and specific acting mechanisms. Baseline toxicity is associated with chemicals acting narcosis mechanism, which is the reversible suppression of physiological function brought about by hydrophobic binding of chemicals to cell membranes and proteins. The CBRs to fish for narcotic chemicals vary in a narrow range and are close to constant. The CBRs for non-polar narcotic chemicals are higher than those for polar narcotic chemicals. Moreover, non-polar and polar narcotic compounds have different underlying mechanisms. Polar compounds intercalate less deeply into membranes, leading to lower CBR values than non-polar narcotic compounds. Reactive compounds interact and/or react with biological molecules, leading to enhanced toxicity relative to that associated with narcosis, and their CBRs are lower than those of narcotic compounds. Because the CBRs of narcotic compounds are close to constant, their toxicities are mainly affected by bioconcentration and linearly related to hydrophobicity. Conversely, the CBRs of reactive compounds are closely related to the reactivity of chemicals with biomolecules at the target site, with different values being observed for different reactive compounds. Their toxicities are not only related to the bioconcentration factor, but also to the descriptors used to describe the reactivity of chemicals with biomolecules(CBRs). Many factors can affect the CBRs of chemicals. For example, linear models of the relationship between log BCF and log Kow can underestimate the log BCF for compounds with log Kow 0.5 and overestimate the log BCF for compounds with log Kow 7, resulting in larger errors for CBRs calculated from the BCF and LC50 of highly hydrophilic and hydrophobic compounds. Organism size, lipid content, exposure time, metabolism and transformation, and uncertainty of toxic data can also affect the calculation or determination of CBRs.

Exploration of Daphnia behavioral effect profiles induced by a broad range of toxicants with different modes of action.

Behavior is increasingly reported as a sensitive and early indicator of toxicant stress in aquatic organisms. However, the systematic understanding of behavioral effects and comparisons between effect profiles is hampered because the available studies are limited to few chemicals and differ in the exposure conditions and effect parameters examined. The aims of the present study were 1) to explore behavioral responses of Daphnia magna exposed to different toxicants, 2) to compare behavioral effect profiles with regard to chemical modes of action, and 3) to determine the sensitivity and response time of behavioral parameters in a new multi-cell exposure system named Multi-DaphTrack compared with currently utilized tests. Twelve compounds covering different modes of toxic action were selected to sample a wide range of potential effect profiles. Acute standard immobilization tests and 48 h of behavioral tracking were performed in the customized Multi-DaphTrack system and a single-cell commercialized biological early warning system. Contrasting behavioral profiles were observed for average speed (i.e., intensity, time of effect onset, effect duration), but no distinct behavioral profiles could be drawn from the chemical mode of action. Most compounds tested in the Multi-DaphTrack system induced an early and significant average speed increase at concentrations near or below the 10% effective concentration (48 h) of the acute immobilization test, demonstrating that the Multi-DaphTrack system is fast and sensitive. To conclude, behavior endpoints could be used as an alternative or complement to the current acute standard test or chemical analysis for the predictive evaluation of ecotoxic effects of effluents or water bodies.

Towards understanding mechanisms governing cytotoxicity of metal oxides nanoparticles: Hints from nano-QSAR studies

The production of nanomaterials increases every year exponentially and therefore the probability these novel materials that they could cause adverse outcomes for human health and the environment also expands rapidly. We proposed two types of mechanisms of toxic action that are collectively applied in a nano-QSAR model, which provides governance over the toxicity of metal oxide nanoparticles to the human keratinocyte cell line (HaCaT). The combined experimental–theoretical studies allowed the development of an interpretative nano-QSAR model describing the toxicity of 18 nano-metal oxides to the HaCaT cell line, which is a common in vitro model for keratinocyte response during toxic dermal exposure. The comparison of the toxicity of metal oxide nanoparticles to bacteria Escherichia coli (prokaryotic system) and a human keratinocyte cell line (eukaryotic system), resulted in the hypothesis that different modes of toxic action occur between prokaryotic and eukaryotic systems.

Realistic environmental mixtures of micropollutants in surface, drinking, and recycled water: Herbicides dominate the mixture toxicity toward algae

Mixture toxicity studies with herbicides have focused on a few priority components that are most likely to cause environmental impacts, and experimental mixtures were often designed as equipotent mixtures; however, real-world mixtures are made up of chemicals with different modes of toxic action at arbitrary concentration ratios. The toxicological significance of environmentally realistic mixtures has only been scarcely studied. Few studies have simultaneously compared the mixture effect of water samples with designed reference mixtures comprised of the ratios of analytically detected concentrations in toxicity tests. In the present study, the authors address the effect of herbicides and other chemicals on inhibition of photosynthesis and algal growth rate. The authors tested water samples including secondary treated wastewater effluent, recycled water, drinking water, and storm water in the combined algae assay. The detected chemicals were mixed in the concentration ratios detected, and the biological effects of the water samples were compared with the designed mixtures of individual detected chemicals to quantify the fraction of effect caused by unknown chemicals. The results showed that herbicides dominated the algal toxicity in these environmentally realistic mixtures, and the contribution by the non-herbicides was negligible. A 2-stage model, which used concentration addition within the groups of herbicides and non-herbicides followed by the model of independent action to predict the mixture effect of the two groups, could predict the experimental mixture toxicity effectively, but the concentration addition model for herbicides was robust and sufficient for complex mixtures. Therefore, the authors used the bioanalytical equivalency concept to derive effect-based trigger values for algal toxicity for monitoring water quality in recycled and surface water. All water samples tested would be compliant with the proposed trigger values associated with the appropriate guidelines.

A dip-stick type biosensor using bioluminescent bacteria encapsulated in color-coded alginate microbeads for detection of water toxicity

The use of genetically engineered bioluminescent bacteria, in which bioluminescence is induced by different modes of toxic action, represents an alternative to acute toxicity tests using living aquatic organisms (plants, vertebrates, or invertebrates) in an aqueous environment. A number of these bacterial strains have been developed, but there have been no attempts to develop a hand-held type of biosensor for monitoring or identification of toxicity. We report a facile dip-stick type biosensor using genetically engineered bioluminescent bacteria as a new platform for classification and identification of toxicity in water environments. This dip-stick type biosensor is composed of eight different optically color-coded functional alginate beads that each encapsulates a different bioluminescent bacterial strain and its corresponding fluorescent microbead. These color-coded microbeads exhibit easy identification of encapsulated microbeads, since each microbead has a different color code depending on the bioluminescent bacterial strain contained and improved cell-stability compared to liquid culture. This dip-stick type biosensor can discriminate different modes of toxic actions (i.e. DNA damage, oxidative damage, cell-membrane damage, or protein damage) of sample water tested by simply dipping the stick into the water samples. It was found that each color-coded microbead emitted distinct bioluminescence, and each dip-stick type biosensor showed different bioluminescence patterns within 2 hours, depending on the toxic chemicals contained in LB medium, tap water, or river water samples. This dip-stick type biosensor can, therefore, be widely and practically used in checking toxicity of water in the environment primarily in situ, possibly indicating the status of biodiversity.

Simplifying complexity: Mixture toxicity assessment in the last 20 years

Simplifying complexity: Mixture toxicity assessment in the last 20 years

Discrimination of excess toxicity from narcotic effect: Comparison of toxicity of class-based organic chemicals to Daphnia magna and Tetrahymena pyriformis

The discrimination of excess toxicity from narcotic effect plays a crucial role in the study of modes of toxic action for organic compounds. In this paper, the toxicity data of 758 chemicals to Daphnia magna and 993 chemicals to Tetrahymena pyriformis were used to investigate the excess toxicity. The result showed that mode of toxic action of chemicals is species dependent. The toxic ratio (TR) calculated from baseline model over the experimentally determined values showed that some classes (e.g. alkanes, alcohols, ethers, aldehydes, esters and benzenes) shared same modes of toxic action to both D. magna and T. pyriformis. However, some classes may share different modes of toxic action to T. pyriformis and D. magna (e.g. anilines and their derivatives). For the interspecies comparison, same reference threshold need to be used between species toxicity. The excess toxicity indicates that toxicity enhancement is driven by reactive or specific toxicity. However, not all the reactive compounds exhibit excess toxicity. In theory, the TR threshold should not be related with the experimental uncertainty. The experimental uncertainty only brings the difficulty for discriminating the toxic category of chemicals. The real threshold of excess toxicity which is used to identify baseline from reactive chemicals should be based on the critical concentration difference inside body, rather than critical concentration outside body (i.e. EC50 or IGC50). The experimental bioconcentration factors can be greatly different from predicted bioconcentration factors, resulting in different toxic ratios and leading to mis-classification of toxic category and outliers.

Quantifying intrinsic chemical reactivity of molecular structural features for protein binding and reactive toxicity, using the MOSES chemoinformatics system

Covalent binding of xenobiotic compounds to endogenous biomolecular sites, e.g. protein residues, leads to potentially irreversible toxic effects such as enhanced acute toxicity or skin sensitization [1]. This mechanistic knowledge provides the basis for the in silico prediction of these toxicities, as required by the EU REACH legislation and the EU Cosmetics Directive. A general toxicity prediction can be based on three consecutive steps [2]: (1.) Identification of a potential reactive protein binding mechanism via a set of molecular structural features. Those structural features can be encoded by the Chemical Subgraph Representation Markup Language (CSRML), that supports a flexible annotation of meta information, including physicochemical properties as annotations. (2.) Confirmation and quantification of (bio)chemical reactivity. The potential for a chemical to be reactive can be captured by mechanistically based QSAR models. This intrinsic reactivity is calculated rapidly by descriptors of the chemoinformatics platform Molecular Structure Encoding System (MOSES) [3]. It represents electronic, steric and resonance effects in chemical structures. The performances obtained by these reactivity models are close to time-consuming quantum chemical reactivity calculations, e.g., se = 0.44 versus 0.40 for glutathione adduct formation via Michael addition, comparing predicted values to an experimental reactivity dataset [1]. (3.) Establishing a relationship between calculated reactivity and toxicity. The predicted intrinsic reactivity values were linked to the computational prediction for different modes of toxic action, with good correlations between predicted and in vitro toxicity (up to r2=0.86). The combined use of structural information and computed reactivity could assist in the non-animal based risk assessment of chemicals for regulatory purposes and in the application of integrated testing strategies (ITS). The research has received funding from the EU FP7 COSMOS Project (grant agreement n° 266835) and financing from COLIPA.

Application of a chemical reactivity database to predict toxicity for reactive mechanisms

Covalent binding of xenobiotic electrophiles to nucleophilic endogenous biomolecules, e.g. peptides or DNA, is a common molecular initiating event, leading to potentially irreversible toxic effects such as enhanced acute toxicity, skin sensitisation, or mutagenicity. This knowledge provides the basis for the in silico prediction of these toxicities. The potential for a chemical to be reactive can be determined experimentally by a number of chemical tests and therefore can be captured computationally to form (Q)SARs. Providing a source of in chemico data for the reactivity of electrophiles with reference nucleophiles could assist in the non-animal based risk assessment of chemicals for regulatory purposes and in the application of integrated testing strategies (ITS). For this reason, we have compiled a database from a full range of chemical reactivity assays containing various reactivity data of numerous electrophiles forming peptide and DNA adducts. This includes reactivity data, kinetic rate constants, and qualitative information regarding the adducts formed. The data collection facilitates the in silico profiling of toxicologically relevant compounds by grouping and category approaches, and allows for the combination of the following information: the identification of electrophilic compounds; their mechanistic applicability domain and compound class; physical-chemical properties; reactivity data; and toxicological data. These experimental reactivity data were linked to the computational prediction of reactive mechanisms for different modes of toxic action (e.g. acute aquatic toxicity), at which the results indicated that physically meaningful parameters are suitable to explain the varying behaviour of electrophiles. This could be applied for screening purposes based on structural information and the reactivity data could be used to elucidate mechanisms of toxic effects. The funding of the EU FP6 InSilicoTox Marie Curie Project (MTKD-CT-2006-42328) is gratefully acknowledged.

Mixture toxicity of the antiviral drug Tamiflu ® (oseltamivir ethylester) and its active metabolite oseltamivir acid

Tamiflu ® (oseltamivir ethylester) is an antiviral agent for the treatment of influenza A and B. The pro-drug Tamiflu ® is converted in the human body to the pharmacologically active metabolite, oseltamivir acid, with a yield of 75%. Oseltamivir acid is indirectly photodegradable and slowly biodegradable in sewage works and sediment/water systems. A previous environmental risk assessment has concluded that there is no bioaccumulation potential of either of the compounds. However, little was known about the ecotoxicity of the metabolite. Ester hydrolysis typically reduces the hydrophobicity and thus the toxicity of a compound. In this case, a zwitterionic, but overall neutral species is formed from the charged parent compound. If the speciation and predicted partitioning into biological membranes is considered, the metabolite may have a relevant contribution to the overall toxicity. These theoretical considerations triggered a study to investigate the toxicity of oseltamivir acid (OA), alone and in binary mixtures with its parent compound oseltamivir ethylester (OE). OE and OA were found to be baseline toxicants in the bioluminescence inhibition test with Vibrio fischeri. Their mixture effect lay between predictions for concentration addition and independent action for the mixture ratio excreted in urine and nine additional mixture ratios of OE and OA. In contrast, OE was an order of magnitude more toxic than OA towards algae, with a more pronounced effect when the direct inhibition of photosystem II was used as toxicity endpoint opposed to the 24 h growth rate endpoint. The binary mixtures in this assay yielded experimental mixture effects that agreed with predictions for independent action. This is consistent with the finding that OE exhibits slightly enhanced toxicity, while OA acts as baseline toxicant. Therefore, with respect to mixture classification, the two compounds can be considered as acting according to different modes of toxic action, although there are indications that the difference is a toxicokinetic effect, not a true difference of mechanism of toxicity. The general mixture results illustrate the need to consider the role of metabolites in the risk assessment of pharmaceuticals. However, in the concentration ratio of parent to metabolite excreted by humans, the experimental results confirm that the active metabolite does not significantly contribute to the risk quotient of the mixture.

Gene Expression of GST and CYP330A1 in Lipid-Rich and Lipid-Poor Female Calanus finmarchicus (Copepoda: Crustacea) Exposed to Dispersed Oil

The copepod Calanus finmarchicus is a marine ecological key species in the Northern Atlantic food web. This species was exposed to an artificially weathered North Sea oil dispersion (oil droplets and water-soluble fractions [WSF]) and a filtered dispersion (containing only WSF) in serial dilution. Female copepods were divided into lipid-rich and lipid-poor for each exposure followed by gene expression analyses of glutathione S-transferase (GST) and cytochrome P-450 330A1 (CYP330A1). Lipid-rich copepods exhibited elevated transcription of GST and reduced transcription of CYP330A1 after exposure to both dispersed oil and WSF. In contrast, lipid-poor copepods exhibited increased transcription of CYP330A1 following exposure to WSF but not the dispersion. Data suggested that small lipid storage promotes increased bioavailability of accumulated oil compounds. Variations in response in CYP330A1 gene expression indicate that oil constituents may exert different modes of toxic action in copepods depending on their reproductive stages. The contribution of oil droplets to the observed effects seemed to be low as GST gene expression was similar after exposure to both dispersed oil and WSF. However, feeding rate in copepods exposed to dispersed oil was reduced, and this may have decreased the uptake of oil constituents via the diet. Although quantitatively higher mortality was observed in copepods exposed to the highest dispersion levels, this may result from smothering of animals by oil droplets. Furthermore, increasing dilution of both the dispersions and the WSF altered their distributions and chemical composition, which may influence the bioavailability of spilled crude oil to pelagic marine organisms.

Integrated fuzzy concentration addition–independent action (IFCA–IA) model outperforms two-stage prediction (TSP) for predicting mixture toxicity

Mixture toxicities were determined for 12 industrial organic chemicals bearing four different modes of toxic action (MOAs) to Vibrio fischeri, to compare the predictability of the integrated fuzzy concentration addition–independent action (IFCA–IA) model and the two-stage prediction (TSP) model. Three mixtures were designed: The first and second mixtures were based on the ratios of each component at the 1% and 50% effect concentrations (EC 1 and EC 50), respectively; and the third mixture contained an equimolar ratio of individual components. For the EC 1, EC 50 and equimolar ratio, prediction errors from the IFCA–IA model at the 50% experimental mixture effects were 0.3%, 6% and 0.6%, respectively; while for the TSP model, the corresponding errors were 2.8%, 19% and 24%, respectively. Thus, the IFCA–IA model performed better than the TSP model. The IFCA–IA model calculated two weight coefficients from the molecular structural descriptors, which weigh the relation between concentration addition (CA) and independent action (IA) through the fuzzy membership functions. Thus, MOAs are not pre-requisites for mixture toxicity prediction by the IFCA–IA approach, implying the practicability of this method in toxicity assessment of mixtures.

Ecotoxicity of selected nano‐materials to aquatic organisms

Present knowledge concerning the ecotoxic effects of nano-materials is very limited and merits to be documented more fully. For this purpose, we appraised the toxicity of nine metallic nano-powders (copper zinc iron oxide, nickel zinc iron oxide, yttrium iron oxide, titanium dioxide, strontium ferrite, indium tin oxide, samarium oxide, erbium oxide, and holmium oxide) and of two organic nano- powders (fullerene-C60 and single-walled carbon nanotube or SWCNT). After a simple process where nano-powders (NPs) were prepared in aqueous solution and filtered, they were then bioassayed across several taxonomic groups including decomposers (bacteria), primary producers (micro-algae), as well as primary and secondary consumers (micro-invertebrates and fish). Toxicity data generated on the 11 NPs reflected a wide spectrum of sensitivity that was biological level-, test-, and endpoint-specific. With all acute and chronic tests confounded for these 11 NPs, toxicity responses spanned over three orders of magnitude: >463 mg/L (24 h LC50 of the invertebrate Thamnoplatyurus platyurus for fullerene-C60) / 0.3 mg/L (96 h EC50 of the invertebrate Hydra attenuata for indium tin oxide), that is a ratio of 1543. On the basis of the MARA (Microbial Array for Risk Assessment) assay toxic fingerprint concept, it is intimated that NPs may have different modes of toxic action. When mixed in a 1:1 ratio with a certified reference material (CRM) sediment, two solid phase assays and an elutriate assay, respectively, showed that five NPs (copper zinc iron oxide, samarium oxide, erbium oxide, holmium oxide, and SWCNT) were able to increase both CRM sediment toxicity and its elutriate toxicity. This initial investigation suggests that chemicals emerging from nanotechnology may pose a risk to aquatic life in water column and sediment compartments and that further studies on their adverse effects are to be encouraged.

Monitoring of the ecotoxicological hazard potential by polar organic micropollutants in sewage treatment plants and surface waters using a mode-of-action based test battery

We propose and evaluate a mode-of-action based test battery of low-complexity and in-vitro bioassays that can be used as a routine monitoring tool for sewage treatment efficiency and water quality assessment. The test battery comprises five bioassays covering five different modes of toxic action. The bioluminescence inhibition test with Vibrio fischeri and a growth rate inhibition test with the green algae Pseudokirchneriella subcapitata are measures of non-specific integrative effects. A second endpoint in the algae test, the specific inhibition of the efficiency of photosynthesis, gives an account of the presence of herbicides. An enzymatic assay covers an important aspect of insecticidal activity, the inhibition of the acetylcholine esterase activity. Estrogenic effects are assessed with the yeast estrogen screen (YES) and genotoxicity with the umuC test. Three field studies, each lasting six to seven consecutive days, were undertaken at a sewage treatment plant (STP) in Switzerland. Samples were collected in summer and late autumn, under dry and rainy conditions. None of the bioassays gave positive results with raw water in whole effluent toxicity testing. Therefore, water samples from various sites during wastewater treatment and from surface water were enriched with solid-phase extraction. The focus was on non-volatile compounds of average to moderate hydrophobicity, a range that includes most pesticides, biocides and pharmaceuticals. Various polar solid phases were evaluated for their extraction efficiency, disturbance by matrix components and overall performance. We finally selected a mixture of a polymeric sorbent and a C18-sorbent, Lichrolut EN and RP-18 or, alternatively, Empore SDB-RPS disks. All bioassays gave clear and robust responses with the SPE extracts. With the bioassay data the treatment efficiency of the STP can be assessed with respect to different modes of toxic action and accordingly different groups of micropollutants. Furthermore, the data allowed for a comparison between the effluent and the receiving river. In all bioassays the primary effluent had a strong effect and this effect was reduced after passing the STP. Treatment efficiency was high (typically over 90%) but varied from bioassay to bioassay, which is expected because each bioassay detects different types of micropollutants and therefore we cannot expect a common answer.

Discrimination between modes of toxic action of phenols using rule based methods

Rule-based ensemble modelling has been used to develop a model with high accuracy and predictive capabilities for distinguishing between four different modes of toxic action for a set of 220 phenols. The model not only predicts the majority class (polar narcotics) well but also the other three classes (weak acid respiratory uncouplers, pro-electrophiles and soft electrophiles) of toxic action despite the severely skewed distribution among the four investigated classes. Furthermore, the investigation also highlights the merits of using ensemble (or consensus) modelling as an alternative to the more traditional development of a single model in order to promote robustness and accuracy with respect to the predictive capability for the derived model.