A new effect residual ratio (ERR) method for the validation of the concentration addition and independent action models

Nanopolystyrene size effect and its combined acute toxicity with halogenated PAHs on Daphnia magna

Nanoplastics (NPs, diameter <1 μm) not only have toxicity but also change the toxicity of other pollutants in water. To date, the nanopolystyrene (nano-PS) size effect and its combined toxicity with halogenated polycyclic aromatic hydrocarbons (HPAHs) remain unclear. In this study, the single toxicity, combined toxicity, and mode of action of the binary mixture of polystyrene (PS) and HPAH were examined. At the same time, the nano-PS size effect on combined toxicity was also discussed. According to our results, the 48 h acute toxicity test results showed that 30 nm PS was highly toxic (EC50-48 h = 1.65 mg/L), 200 nm PS was moderately toxic (EC50-48 h = 17.8 mg/L), and 1 μm PS was lowly toxic (EC50-48 h = 189 mg/L). The NP toxicity decreased with increasing size. HPAHs were highly toxic substances to Daphnia magna (EC50-48 h = 0.12-0.22 mg/L). The mode of action of PS and HPAHs was antagonistic according to the toxicity unit method (TU), additive index method (AI), and mixture toxicity index method (MTI). The size effect of nano-PS operates via two mechanisms: the inherent toxicity of nano-PS and the sorption of pollutants by nano-PS. The former impacts the combined toxicity more than the latter. In the binary mixed system, the larger the particle size and the higher the proportion of NPs in the system, the less toxic the system was. Linear interpolation analysis can be used to predict the combined toxicity of a mixed system with any mixing ratio.

Joint action of binary mixtures based on parameter k·ECx from concentration-response curves in long-term toxicity assay

A previous acute toxicity study of binary mixtures showed that the combined toxicity can be predicted with the parameter k∙EC_x. To systematically investigate the ability of k∙EC_x to predict the chronic combined toxicity of binary mixtures, the toxicity of six contaminants and five binary mixtures was determined by long-term microplate toxicity analysis (L-MTA) using Aliivibrio fischeri as the test organism. The independent action model (IA) and the relative model deviation ratio (rMDR) were employed to determine the relationship between the Δ(k∙EC_x)% and rMDR_x. The results showed that these two factors conformed to the exponential function in long-term toxicity. Owing to the time-dependence of toxicity, the mixture type of chronic toxicity changes to the relative type of acute toxicity. If the acute toxicity of binary mixtures changes their mode of joint action throughout the concentration range, the chronic toxicity will also change their mode of joint action, and vice versa. This study clarified the change rules of the joint action of binary mixtures in acute and chronic toxicity which can promote research on chronic toxicity of binary mixtures.

Study of the joint action of multi-component mixtures based on parameter σ2(k∙ECx) characterizing the shape difference of concentration-response curves

A previous study has revealed that the parameter k∙EC_x, characterizing the shape of concentration-response curves (CRCs), could predict the combined toxicity of binary mixtures. This study further explored the predictability of multi-component mixtures. Eleven component mixtures were designed using the uniform design ray, and the acute toxicity of the eleven environmental pollutants and their mixtures to Vibrio fischeri was determined using microplate toxicity analysis. We used independent action (IA) and the effect residual ratio (ERR_x) models to evaluate the combined toxicity of multi-component mixtures and ascertain the functional relationship between σ²_(k∙ECx), a parameter characterizing the CRC morphological difference of multi-component mixtures, and combined toxicity. The variance σ²_(k∙ECx) of each component characteristic parameter of multi-component mixtures gradually increased in the concentration range, and the relationship between σ²_(k∙ECx) and ERR_x was consistent with the exponential function. The literature verification showed that this rule is generally applicable to the acute toxicity of multi-component mixtures to luminescent bacteria. The exponential function showed the variation rule of the joint action of multi-component mixtures. In the present study, the joint toxicity of multi-component mixtures can be predicted from single toxicity and small amount of multiple toxicity, circumventing complex multi-component toxicity experiments.

Diazepam, metformin, omeprazole and simvastatin: a full discussion of individual and mixture acute toxicity

High consumption of drugs, combined with their presence in the environment, raises concerns about its consequences. Even though researches are often engaged in analyzing substances separately, that is not the environmental reality. Therefore, the aim of this study was to investigate the acute toxicity of the pharmaceuticals simvastatin, metformin, omeprazole and diazepam, and all possible mixtures between them, to the organism Aliivibrio fischeri, verifying possible synergistic or antagonistic effects and assessing byproducts formation. In terms of individual toxicity, omeprazole is the most toxic of the active ingredients, followed by simvastatin, diazepam and, finally, metformin. When the toxicity of mixtures was tested, synergism, antagonism and hormesis were perceived, most probably generated due to byproducts formation. Moreover, it was observed that even when compounds are at concentrations below the non-observed effect concentration (NOEC), there may be toxicity to the mixture. Hence, this work points to the urgent need for more studies involving mixtures, since chemicals are subject to interactions and modifications, can mix, and potentiate or nullify the toxic effect of each other.

Complex toxicological interaction between ionic liquids and pesticides to Vibrio qinghaiensis sp.-Q67

Ionic liquids (ILs) and pesticides may coexist in ecosystems, because more and more people try to extract pesticides from various samples using ILs.

Ecotoxicological evaluation of propranolol hydrochloride and losartan potassium to Lemna minor L. (1753) individually and in binary mixtures

Antihypertensive pharmaceuticals, including the beta-blockers, are one of the most detected therapeutic classes in the environment. The ecotoxicity of propranolol hydrochloride and losartan potassium was evaluated, both individually and combined in a binary mixture, by using the Lemna minor growth inhibition test. The endpoints evaluated in the single-pharmaceutical tests were frond number, total frond area and fresh weight. For the evaluation of the mixture toxicity, the selected endpoint was frond number. Water quality criteria values (WQC) were derived for the protection of freshwater and saltwater pelagic communities regarding the effects induced by propranolol and losartan using ecotoxicological data from the literature, including our data. The risks associated with both pharmaceutical effects on non-target organisms were quantified through the measured environmental concentration (MEC)/predicted-no-effect concentration (PNEC) ratios. For propranolol, the total frond area was the most sensitive endpoint (EC50 = 77.3 mg L(-1)), while for losartan there was no statistically significant difference between the endpoints. Losartan is only slightly more toxic than propranolol. Both concentration addition and independent action models overestimated the mixture toxicity of the pharmaceuticals at all the effect concentration levels evaluated. The joint action of both pharmaceuticals showed an antagonistic interaction to L. minor. Derived WQC assumed lower values for propranolol than for losartan. The MEC/PNEC ratios showed that propranolol may pose a risk for the most sensitive aquatic species, while acceptable risks posed by losartan were estimated for most of aquatic matrices. To the authors knowledge these are the first data about losartan toxicity for L. minor.

Two-stage prediction of the effects of imidazolium and pyridinium ionic liquid mixtures on luciferase

The predicted toxicity of mixtures of imidazolium and pyridinium ionic liquids (ILs) in the ratios of their EC₅₀, EC₁₀, and NOEC (no observed effect concentration) were compared to the observed toxicity of these mixtures on luciferase. The toxicities of EC₅₀ ratio mixture can be effectively predicted by two-stage prediction (TSP) method, but were overestimated by the concentration addition (CA) model and underestimated by the independent action (IA) model. The toxicities of EC₁₀ ratio mixtures can be basically predicted by TSP and CA, but were underestimated by IA. The toxicities of NOEC ratio mixtures can be predicted by TSP and CA in a certain concentration range, but were underestimated by IA. Our results support the use of TSP as a default approach for predicting the combined effect of different types of ILs at the molecular level. In addition, mixtures of ILs mixed at NOEC and EC₁₀ could cause significant effects of 64.1% and 97.7%, respectively. Therefore, we should pay high attention to the combined effects in mixture risk assessment.

Mixture effects of organic micropollutants present in water: towards the development of effect-based water quality trigger values for baseline toxicity

In this study we propose for the first time an approach for the tentative derivation of effect-based water quality trigger values for an apical endpoint, the cytotoxicity measured by the bioluminescence inhibition in Vibrio fischeri. The trigger values were derived for the Australian Drinking Water Guideline and the Australian Guideline for Water Recycling as examples, but the algorithm can be adapted to any other set of guideline values. In the first step, a Quantitative Structure-Activity Relationship (QSAR) describing the 50% effect concentrations, EC50, was established using chemicals known to act according to the nonspecific mode of action of baseline toxicity. This QSAR described the effect of most of the chemicals in these guidelines satisfactorily, with the exception of antibiotics, which were more potent than predicted by the baseline toxicity QSAR. The mixture effect of 10-56 guideline chemicals mixed at various fixed concentration ratios (equipotent mixture ratios and ratios of the guideline values) was adequately described by concentration addition model of mixture toxicity. Ten water samples were then analysed and 5-64 regulated chemicals were detected (from a target list of over 200 chemicals). These detected chemicals were mixed in the ratios of concentrations detected and their mixture effect was predicted by concentration addition. Comparing the effect of these designed mixtures with the effect of the water samples, it became evident that less than 1% of effect could be explained by known chemicals, making it imperative to derive effect-based trigger values. The effect-based water quality trigger value, EBT-EC50, was calculated from the mixture effect concentration predicted for concentration-additive mixture effects of all chemicals in a given guideline divided by the sum of the guideline concentrations for individual components, and dividing by an extrapolation factor that accounts for the number of chemicals contained in the guidelines and for model uncertainties. While this concept was established using the example of Australian recycled water, it can be easily adapted to any other set of water quality guidelines for organic micropollutants. The cytotoxicity based trigger value cannot be used in isolation, it must be applied in conjunction with effect-based trigger values targeting critical specific modes of action such as estrogenicity or photosynthesis inhibition.

Two novel indices for quantitatively characterizing the toxicity interaction between ionic liquid and carbamate pesticides

Compound contamination and toxicity interaction demand the development of models that have an insight into the combined toxicity of chemicals. Two novel mixture toxicity indices, concentration addition index (CAI) and effect addition index (EAI), were developed to quantitatively characterize the toxicity interaction within four binary mixture systems containing carbamate pesticides and 1-benzyl-3-methylimidazolium tetrafluoroborate (IL). To examine the applicability of CAI and EAI, we compared the indices with the other indices such as the sum of toxic unit (STU), model deviation ratio (MDR), and effect residual ratio (ERR) and isobologram approach. The results showed that CAI and EAI could more clearly and effectively characterize the toxicity interaction within IL-pesticide mixtures than the other four methods. According to CAI and EAI, IL-aldicarb, IL-baygon and IL-methomyl mixture systems displayed clear antagonism at relatively low effect regions, while IL-pirimicarb mixture systems basically exhibited additive action. The most interesting observation is that all five indices (CAI, EAI, MDR, ERR, and STU) are well correlated with the concentration ratio of IL in the mixtures.

A novel direct equipartition ray design (EquRay) procedure for toxicity interaction between ionic liquid and dichlorvos

BACKGROUND, AIM AND SCOPE

Pollutants always co-exist in the environment. Determining and characterizing the interaction among chemicals is an important issue. Experimental designs (ED) play an important role in evaluating the interactions. The main aim of our study is to provide the test and analysis of the toxicity interaction with a novel ED method.

MATERIALS AND METHODS

A novel direct equipartition ray design (EquRay) procedure was proposed to effectively and systematically determine the toxicities of binary mixtures on Vibrio qinghaiensis sp.-Q67. Here, one component is ionic liquid, 1-butyl-2,3-dimethylimidazolium chloride (IL1), 1-butylpyridinium bromide (IL2) or N-hexylpyridinium bis(trifluoromethylsulfonyl)imide (IL3), and another is dichlorvos (DIC). The toxicity interaction was evaluated by comparing experiment and additive model together with three-dimension deviation response surface (DRS) analysis.

RESULT

Selecting CA as a reference model, the binary mixtures exerted less than additive (antagonism). Most of the deviations occurred in the centre portion of the DRS where the dCA (deviation from CA) values are between -15% and -26% for IL1-DIC and IL2-DIC mixtures and -10% and -15% for IL3 and DIC. Selecting IA as a additive model, IL1-DIC and IL2-DIC mixtures exhibited less than additive (antagonism) while IL3-DIC displayed an addition action and the absolute values of dIAs (deviation from IA) were less than 10%.

CONCLUSION

A novel EquRay procedure was developed in this study and the EquRay can provide us with the information about the toxicity interaction between binary mixture components (such as DIC and IL) in different concentration regions across different mixture ratios.

Assessing combined toxicity of estrogen receptor agonists in a primary culture of rainbow trout (Oncorhynchus mykiss) hepatocytes

The presence of highly complex mixtures of chemicals in the environment challenges our ability to assess single chemical effects and the interaction that occurs with cellular receptor targets and regulation of endocrine processes. In this study concentration addition (CA) and independent action (IA) prediction models were used to assess the combined toxicity of mixtures of environmental relevant estrogen receptor (ER) agonists (hormones and anthropogenic pollutants) in a primary culture of rainbow trout (Oncorhynchus mykiss) hepatocytes using the ER-mediated production of vitellogenin (Vtg) as a biological marker (biomarker) for estrogenicity. Nine of the eleven tested chemicals induced the production of Vtg and the parameters from the fitted concentration-response curves were used to model four mixtures containing four (17β-estradiol, estrone, estriol and diethylstilbestrol), five (musk ketone, 4-tert-octylphenol, bisphenol A, o,p'-DDT and dibenzothiophene), seven (17β-estradiol, estrone, estriol, diethylstilbestrol, 4-tert-octylphenol, bisphenol A and o,p'-DDT) and nine compounds (17β-estradiol, estrone, estriol, diethylstilbestrol, musk ketone, 4-tert-octylphenol, bisphenol A, o,p'-DDT and dibenzothiophene). The CA and IA prediction model proved to be a good estimation for the combined effect of mixtures of ER agonists at low relative mixture concentration (e.g. relative to the maximum mixture concentrations used), but a deviation from the prediction models was observed when exposing hepatocytes to high relative mixture concentrations. The CA and IA prediction models' ability to predict the combined estrogenic effect of complex mixtures, especially in the low concentration-response range, is of ecological relevance since organisms in the environment generally encounter low concentrations of chemicals from a wide array of chemical groups that may not elicit estrogenic effects on their own.