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

Simulating synergism or antagonism in binary mixtures with different modeling approaches - A case study focused on the effect of disinfection by-products on algal growth

This paper aims to test several modeling approaches for predicting toxicity of binary mixtures with potential synergy and antagonism. The approach based on the construction of isoboles was first tested and criticized. In contrast to conventional approaches, and in order to be mathematically consistent with the additivity assumptions, non-linear isoboles have been constructed. This approach was compared with that proposed by Minto et al. (2000), which measures deviations from additivity by considering standardized variables and which considers the entire Hill concentration-response curves. The selected models were tested on a case study related to chlorine-based disinfectant by-products (DBPs), using experimental data describing the effect of five DBPs (monochloroacetic acid, dichloroacetic acid, trichloroacetic acid, bromochloroacetic acid and 1,1-dichloropropan-2-one) on a unicellular green algae Raphidocelis subcapitata. The approach based on the construction of isoboles has shown its limitations. Indeed, in cases where the individual substances involved have different slopes in terms of their Hill concentration-effect relationships, the so-called zone of indetermination can be large. Furthermore, conclusions drawn from isoboles based on EC50s or EC20s may not be consistent. Minto's approach makes it possible to construct interaction indicators that consider the entire Hill concentration-response curve. Response surfaces can be constructed to visualize the areas of concentration of the two substances involved that maximize the interaction effects.

Toxic effects and mechanisms of nanoplastics and sulfonamide antibiotics on Scenedesmus obliquus

The prevalence of nanoplastics (NPs) and sulfonamide antibiotics (SAs) in the aquatic environment is potentially harmful to the environment, and these pollutants are often present in the environment in the form of composite ones, thereby introducing more complex effects and hazards to the environment. Therefore, it is crucial to investigate the toxic effects of the individual target pollutants and their mixtures. In this study, we used Scenedesmus obliquus as the test organisms, two types of NPs: polystyrene (PS) and amine-modified (NH2-PS), four SAs: sulfapyridine (SPY), sulfamethazine (SMR), sulfamethoxypyridazine (SMP), and sulfamethoxazole (SMZ), and their eight binary mixtures were examined. We investigated the toxic interactions of the eight binary mixtures on Scenedesmus obliquus and assessed the impact of the 14 mixtures on the physiological and biochemical properties of Scenedesmus obliquus. Interaction of pollutant assemblages with algal cells observed using field emission scanning electron microscopy. The results showed that the six target pollutants and their eight binary mixtures were significantly toxic to Scenedesmus obliquus within 96 h. The toxicity of individual pollutants was in the order of SPY (EC50: 12.38 mg/L) > SMZ (EC50: 20.43 mg/L) > SMP (EC50: 32.96 mg/L) > SMR (EC50: 41.06 mg/L) > PS (EC50: 284.13 mg/L) > NH2-PS (EC50: 754.13 mg/L); the toxicity of binary mixtures composed of NPs and SAs (89.13 ∼ 1905.46 mg/L) was generally less toxic than that of unitary SAs (12.38 ∼ 41.06 mg/L). Suggesting that the presence of NPs reduced the toxicity of the SAs. The different types of NPs influenced the interaction and toxicity of the mixtures. The effects-based model deviation ratio method was used to quantitatively assess the interactions of the mixture systems in the 10∼90 % experimental effect range. The majority of the PS-containing mixtures exhibited antagonistic interactions. The interactions of NH2-PS-containing mixtures on Scenedesmus obliquus showed different interactions depending on the concentration ratios of the mixture components. The exposure of two NPs and four SAs and their binary mixtures differently promoted or inhibited superoxide dismutase and catalase activities in algal cells to different degrees and resulted in elevated levels of malondialdehyde content, suggesting that oxidative stress led to significant inhibition of chlorophyll content, total protein content, and growth of algal cells. The SEM image can be a more intuitive means of observing the interaction of nanoplastics with algal cells. These findings offer valuable data for the ecological risk assessment of NPs and SAs.

Distinct baseline toxicity of volatile organic compounds (VOCs) in gaseous and liquid phases: Mixture effects and potential molecular mechanisms

Volatile organic compounds (VOCs) are significant pollutants found in various environments, posing health risks. Traditionally, the gaseous VOCs are adsorbed and eluted in liquid phases, and then subjected to toxicity testing, which deviates from the actual exposure scenarios of gaseous VOCs. How the physical states of VOCs (gaseous or liquid) affect their toxicity has not been well understood. This study examined the baseline toxicity of VOCs in both gaseous and liquid phases using a self-assembled passive colonization hydrogel (SAPCH) with luminous bacteria (Vibrio fischeri). The findings revealed that gaseous VOCs exhibited higher baseline toxicity than their liquid counterparts, attributed to the higher free energy and electronic activity of gaseous VOC molecules. Furthermore, the study elucidated that the differences in electronic transitions and energy gaps significantly impact the combined toxicity of VOC mixtures in different phases. Understanding these differences is crucial for assessing the real-world impact of VOCs on health and the environment.

A comprehensive machine learning-based models for predicting mixture toxicity of azole fungicides toward algae (Auxenochlorella pyrenoidosa)

Quantitative structure-activity relationships (QSARs) have been used to predict mixture toxicity. However, current research faces gaps in achieving accurate predictions of the mixture toxicity of azole fungicides. To address this gap, the application of machine learning (ML) algorithms has emerged as an effective strategy. In this study, we applied 12 algorithms, namely, k-nearest neighbor (KNN), kernel k-nearest neighbors (KKNN), support vector machine (SVM), random forest (RF), stochastic gradient boosting (GBM), cubist, bagged multivariate adaptive regression splines (Bagged MARS), eXtreme gradient boosting (XGBoost), boosted generalized linear model (GLMBoost), boosted generalized additive model (GAMBoost), bayesian regularized neural networks (BRNN), and recursive partitioning and regression trees (CART) to build ML models for 225 mixture toxicity of azole fungicides towards Auxenochlorella pyrenoidosa. A total of 36 single ML models and 12 consensus models were developed. The results indicated that models employing concentration addition (CA), independent action (IA), and molecular descriptors (MD) as variables demonstrated superior predictive abilities. The consensus model combining SVM and RF algorithms (labeled as CM0) demonstrated the highest level of accuracy in fitting the data, with a coefficient of determination of 0.980. Additionally, it showed strong predictive abilities when tested with external data, achieving an external R2 value of 0.945 and a Concordance Correlation Coefficient of 0.967. This study provides a positive contribution to the ecological risk assessment of a mixture of azole fungicides.

Classification and regression machine learning models for predicting the combined toxicity and interactions of antibiotics and fungicides mixtures

Antibiotics and triazole fungicides coexist in varying concentrations in natural aquatic environments, resulting in complex mixtures. These mixtures can potentially affect aquatic ecosystems. Accurately distinguishing synergistic and antagonistic mixtures and predicting mixture toxicity are crucial for effective mixture risk assessment. We tested the toxicities of 75 binary mixtures of antibiotics and fungicides against Auxenochlorella pyrenoidosa. Both regression and classification models for these mixtures were developed using machine learning models: random forest (RF), k-nearest neighbors (KNN), and kernel k-nearest neighbors (KKNN). The KKNN model emerged as the best regression model with high values of determination coefficient (R2 = 0.977), explained variance in prediction leave-one-out (Q2LOO = 0.894), and explained variance in external prediction (Q2F1 = 0.929, Q2F2 = 0.929, and Q2F3 = 0.923). The RF model, the leading classifier, exhibited high accuracy (accuracy = 1 for the training set and 0.905 for the test set) in distinguishing the synergistic and antagonistic mixtures. These results provide crucial value for the risk assessment of mixtures.

Screening for frequently detected quaternary ammonium mixture systems in waters based on frequent itemset mining and prediction of their toxicity

Screening and prioritizing research on frequently detected mixture systems in the environment is of great significance, as conducting toxicity testing on all mixtures is impractical. Therefore, the frequent itemset mining (FIM) was introduced and applied in this paper to identify variables that commonly co-occur in a dataset. Based on the dataset of the quaternary ammonium compounds (QACs) in the water environment, the four frequent QAC mixture systems with detection rate ≥ 35 % were found, including [BDMM]+Cl--[BTMM]+Cl- (M1), [BDMM]+Cl--[BHMM]+Cl- (M2), [BTMM]+Cl- -[BHMM]+Cl- (M3), and [BDMM]+Cl--[BTMM]+Cl--[BHMM]+Cl- (M4). [BDMM]+Cl-, [BTMM]+Cl-, and [BHMM]+Cl- are benzyl dodecyl dimethyl ammonium chloride, benzyl tetradecyl dimethyl ammonium chloride, and benzyl hexadecyl dimethyl ammonium chloride, respectively. Then, the toxicity of the representative mixture rays and components for the four frequently detected mixture systems was tested using Vibrio qinghaiensis sp.-Q67 (Q67) as a luminescent indicator organism at 0.25 and 12 h. The toxicity of the mixtures was predicted using concentration addition (CA) and independent action (IA) models. It was shown that both the components and the representative mixture rays for the four frequently detected mixture systems exhibited obvious acute and chronic toxicity to Q67, and their median effective concentrations (EC50) were below 7 mg/L. Both CA and IA models predicted the toxicity of the four mixture systems well. However, the CA model had a better predictive ability for the toxicity of the M3 and M4 mixtures than IA at 12 h.

Combined effect of zinc and cadmium ions on nitrification performance during the biological nitrogen removal of simulated livestock breeding wastewater

Zinc and cadmium ions are usually found in livestock breeding wastewater, and the mixed ions will have an impact on the biological nitrogen removal. Nitrification performance plays an important role in biological nitrogen removal. In order to investigate the combined effect of zinc and cadmium ions on nitrification performance and to reveal the interactions between zinc and cadmium ions, three concentration ratios of zinc and cadmium ions, as well as 18 different concentration gradients were designed with the direct equipartition ray and the dilution factor method. The effect of pollutants on the nitrification performance of biological nitrogen removal was analyzed by the nonlinear regression equation, and the concentration-addition model was conducted to probe into the relationship between the mixed pollutants and the nitrification performance. The results showed that the effect on nitrification performance increased significantly with the increase of reaction duration and pollutant concentration, which indicated that the effects are concentration-dependent and time-dependent. The concentration-addition model suggested that the interactions between zinc and cadmium ions with different concentration ratios were mainly antagonistic, and as the percentage of cadmium ions in the mixtures increased, the antagonism between the mixtures became stronger. This study will provide a relevant theoretical basis for the regulation of the ratios and concentrations of heavy metal ions during the biological treatment of livestock breeding wastewater.

Toxic interactions at the physiological and biochemical levels of green algae under stress of mixtures of three azole fungicides

Assessing the interactions between environmental pollutants and these mixtures is of paramount significance in understanding their negative effects on aquatic ecosystems. However, existing research often lacks comprehensive investigations into the physiological and biochemical mechanisms underlying these interactions. This study aimed to reveal the toxic mechanisms of cyproconazole (CYP), imazalil (IMA), and prochloraz (PRO) and corresponding these mixtures on Auxenochlorella pyrenoidosa by analyzing the interactions at physiological and biochemical levels. Higher concentrations of CYP, IMA, and PRO and these mixtures resulted in a reduction in chlorophyll (Chl) content and increased total protein (TP) suppression, and malondialdehyde (MDA) content exhibited a negative correlation with algal growth. The activity of catalase (CAT) and superoxide dismutase (SOD) decreased with increasing azole fungicides and their mixture concentrations, correlating positively with growth inhibition. Azole fungicides induced dose-dependent apoptosis in A. pyrenoidosa, with higher apoptosis rates indicative of greater pollutant toxicity. The results revealed concentration-dependent toxicity effects, with antagonistic interactions at low concentrations and synergistic effects at high concentrations within the CYP-IMA mixtures. These interactions were closely linked to the interactions observed in Chl-a, carotenoid (Car), CAT, and cellular apoptosis. The antagonistic effects of CYP-PRO mixtures on A. pyrenoidosa growth inhibition can be attributed to the antagonism observed in Chl-a, Chl-b, Car, TP, CAT, SOD, and cellular apoptosis. This study emphasized the importance of gaining a comprehensive understanding of the physiological and biochemical interactions within algal cells, which may help understand the potential mechanism of toxic interaction.

Time-dependent nonmonotonic concentration-response and synergism of alkyl glycosides with different alkyl side chain to Vibrio qinghaiensis sp. -Q67

Alkyl glycosides (AGs), commonly used nonionic surfactants, may have toxic effects on the environmental organisms. However, the complex concentration-response patterns of AGs with varying alkyl side chains and their mixtures have not been thoroughly studied. Therefore, the luminescence inhibition toxicities of six AGs with different alkyl side chains, namely, ethyl (AG02), butyl (AG04), hexyl (AG06), octyl (AG08), decyl (AG10), and dodecyl (AG12) glucosides, were determined in Vibrio qinghaiensis sp. -Q67 (Q67) at 0.25, 3, 6, 9, and 12 h. The six AGs exhibited time- and side-chain-dependent nonmonotonic concentration- responses toward Q67. AG02, with a short side chain, presented a concentration-response curve (CRC) with two peaks after 6 h and stimulated the luminescence of Q67 at both 6 and 9 h. AG04, AG06, and AG08 showed S-shaped CRCs at five exposure time points, and their toxicities increased with the side-chain length. AG10 and AG12, with long side chains, exhibited hormesis at 9 and 12 h. Molecular docking was performed to explore the mechanism governing the possible influence of AGs on the luminescence response. The effects of AGs on Q67 could be attributed to multiple luminescence-regulatory proteins, including LuxA, LuxC, LuxD, LuxG, LuxI, and LuxR. Notably, LuxR was identified as the primary binding protein among the six AGs. Given that they may co-exist, binary mixtures of AG10 and AG12 were designed to explore their concentration-response patterns and interactions. The results revealed that all AG10-AG12 binary mixture rays showed time-dependent hormesis on Q67, similar to that shown by their individual components. The interactions of these binary mixtures were mainly characterized by low-concentration additive action and high-concentration synergism at different times.

Identification of the single and combined acute toxicity of Cr and Ni with Heterocypris sp. and the quantitative structure-activity relationship (QSAR) model

Mining wastewater with heavy metals poses a serious threat to the ecological environment. However, the acute single and combined ecological effects of heavy metals, such as chromium (Cr) and nickel (Ni), on freshwater ostracods, and the development of relevant prediction models, remain poorly understood. In this study, Heterocypris sp. was chosen to investigate the single and combined acute toxicity of Cr and Ni. Then, the quantitative structure-activity relationship (QSAR) model was used to predict the combined toxicity of Cr and Ni. The single acute toxicity experiments revealed high toxicity for both Cr and Ni. In addition, Cr exhibited greater toxicity compared to Ni, as evidenced by its lower 96-hour half-lethal concentration (LC50) of 1.07 mg/L compared to 4.7 mg/L for Ni. Furthermore, the combined acute toxicity experiments showed that the toxicity of Cr-Ni was higher than Ni but lower than Cr. Compared with the concentration addition (CA) and independent action (IA) models, the predicted results of the QSAR model were more consistent with the experimental results for the Cr-Ni combined acute toxicity. So, the high accuracy of QSAR model identified its feasibility to predict the toxicity of heavy metal pollutants in mining wastewater.

Beneficial or harmful: Time-dependent hormesis induced by typical disinfectants and their mixtures with toxicological interaction

Disinfectants and their mixtures can induce hormesis. However, how the mixture hormesis is related to those of components and the interactions in disinfectant mixtures remain unclear. In this paper, the luminescence inhibition toxicities of chlorinated sodium phosphate (CSP), dodecyl dimethyl benzyl ammonium bromide (DOB), dodecyl dimethyl benzyl ammonium chloride (DOC), ethanol (EtOH), glutaraldehyde (GLA), hydrogen peroxide (H2O2), isopropyl alcohol (IPA), n-propanol (NPA), and 20 mixture rays in four mixture systems (EtOH-H2O2, DOB-H2O2, DOC-EtOH, and EtOH-IPA-NPA) containing at least one component showing hormesis to Vibrio qinghaiensis sp.-Q67 (Q67) were determined at 0.25, 3, 6, 9, and 12 h. The synergism-antagonism heatmap based on independent action model (noted as SAHmapIA) was developed to systematically evaluate the interactions in various mixtures. It was shown that five disinfectants (CSP, EtOH, H2O2, NPA, and IPA) and 17 mixture rays exhibited time-dependent hormesis. The hormetic component was responsible for the hormesis of the mixture rays. Most mixture rays showed low- concentration/dose additive action and high-concentration/dose synergism at different time. This study further exemplified the interrelationship between the hormesis in the mixtures and their components and implied the need to pay attention to the time-dependent hormesis and interactions induced by the disinfectants.

Predictive in silico models for aquatic toxicity of cosmetic and personal care additive mixtures

As emerging environmental contaminants, cosmetic and personal care additives (CPCAs) may have less oversight than other consumer products. Their continuous release and pseudopersistence could cause long-term harm to the aquatic environment. Since CPCAs generally exist in the form of mixtures in the environment, prediction and analysis of their mixture toxicity are crucial for ecological risk assessment. In this study, the acute toxicity of five typical CPCA mixtures to Daphnia magna was tested. The combined toxicity of binary mixtures was examined with the traditional concentration addition (CA) and independent action (IA) model. Overall, the synergistic effect of the five CPCAs may be caused mainly by methylparaben. In addition, reliable approaches for quantitative structure-activity relationship (QSAR) model development were explored. Specifically, 18 QSAR models were developed by three dataset partitioning techniques (Kennard-Stone's algorithm division, Euclidean distance based division, and sorted activity based division), two descriptor filtering methods (genetic algorithm and stepwise multiple linear regression) and three regression methods (multiple linear regression, partial least squares and support vector machine). Sixteen equations were applied for the calculation of the mixture descriptors to screen the functional expression of the mixture descriptors with the largest contribution to the mixture toxicity. A new comprehensive parameter that integrates internal and external validation was proposed for QSAR models evaluation. The mixture toxicity is mainly related the 3D distribution of atomic masses and the spatial distribution of the molecule electronic properties. Rigorously validated and externally predictive QSAR models were developed for predicting the toxicity of binary CPCAs mixtures with any ratio, in the applicability domain. The best possible work frame for construction and validation of QSAR models to provide reliable predictions on the mixture toxicity was proposed.

Reproductive toxicity of combined effects of endocrine disruptors on human reproduction

Confluence of environmental, genetic, and lifestyle variables is responsible for deterioration of human fecundity. Endocrine disruptors or endocrine disrupting chemicals (EDCs) may be found in a variety of foods, water, air, beverages, and tobacco smoke. It has been demonstrated in experimental investigations that a wide range of endocrine disrupting chemicals have negative effects on human reproductive function. However, evidence on the reproductive consequences of human exposure to endocrine disrupting chemicals is sparse and/or conflicting in the scientific literature. The combined toxicological assessment is a practical method for assessing the hazards of cocktails of chemicals, co-existing in the environment. The current review provides a comprehensive overview of studies emphasizing the combined toxicity of endocrine disrupting chemicals on human reproduction. Endocrine disrupting chemicals interact with each other to disrupt the different endocrine axes, resulting in severe gonadal dysfunctions. Transgenerational epigenetic effects have also been induced in germ cells, mostly through DNA methylation and epimutations. Similarly, after acute or chronic exposure to endocrine disrupting chemicals combinations, increased oxidative stress (OS), elevated antioxidant enzymatic activity, disrupted reproductive cycle, and reduced steroidogenesis are often reported consequences. The article also discusses the concentration addition (CA) and independent action (IA) prediction models, which reveal the importance of various synergistic actions of endocrine disrupting chemicals mixtures. More crucially, this evidence-based study addresses the research limitations and information gaps, as well as particularly presents the future research views on combined endocrine disrupting chemicals toxicity on human reproduction.

SAHmap: Synergistic-antagonistic heatmap to evaluate the combined synergistic effect of mixtures of three pesticides on multiple endpoints of Caenorhabditis elegans

The environmental pollution caused by toxic chemicals such as pesticides has become a global problem. The mixture of dichlorvos (DIC), dimethoate (DIM), aldicarb (ALD) poses potential risks to the environment and human health. To fully explore the interaction of complex mixtures on Caenorhabditis elegans behavioral toxicity endpoint. This study created a synergistic-antagonistic heatmap (SAHmap) based on the combination index to systematically describe the toxicological interaction prospect of the mixture system. It was shown that the three pesticides and their binary as well as ternary mixture rays have significant concentration-response relationship on three behavioral endpoints of nematodes, From the perspective of synergistic-antagonistic heatmaps, all the mixture rays in the DIC-DIM mixture system showed strong synergism on the three behavioral and lethal endpoints. In the ternary mixture system, the five mixture rays showed different interaction between the behavioral endpoint and the lethal endpoint, and showed slight synergism to two behavioral endpoints as a whole. The emergence of synergism should arouse our attention to these hazardous chemicals. In addition, the use of SAHmap and the significant linear correlation among three behavioral endpoints further improved the efficiency of the study on the behavioral toxicity of pesticide mixtures to Caenorhabditis elegans.

Sensitivity of Ostracods to U, Cd and Cu: The Case of Cypridopsis vidua

The development of uranium mines has been necessary to obtain abundant and scarce uranium resources, but they also bring inevitable radioactive contamination to the surrounding soil, rivers and lakes. This paper explores the sensitivity of Cypridopsis vidua to the radioactive element uranium and the heavy elements cadmium and copper with single and combined acute toxicity experiments and combined toxicity model predictions. The results from the single toxicity experiments showed that the degree of toxic effects was cadmium > copper > uranium. The combined toxicity experiments showed that the compound toxicity of U-Cd and U-Cu was higher than the weakest component and lower than the strongest component, whereas the compound toxicity of Cd-Cu was higher than either of its components. When the overall proportion of a more toxic metal was increased, its mixed toxicity also increased, and vice versa. Combined toxicity predictions showed that the U-Cd combination was best described by the concentration additive (CA) model, the independent action (IA) model was more applicable to the Cd-Cu combination, and the most applicable model for the U-Cu combination changed depending on the concentration gradient. The acute toxicity data from this study provide a reference for the development of wastewater discharge standards for uranium mines, enriches the data related to the toxicity of uranium for ostracods and deepens the understanding of the threat of uranium pollution to aquatic ecosystems.

Inhibitory effect of individual and mixtures of nitrophenols on anaerobic toxicity assay of anaerobic systems: Metabolism and evaluation modeling

The single and combined inhibitory effects of different nitrophenols on the anaerobic toxicity assay (ATA) of anaerobic sludge and the variations in the content of extracellular polymeric substances (EPS) were investigated. The results indicated that 2,4-dinitrophenol (2,4-DNP) demonstrated the highest inhibitory effect, followed by 4-nitrophenol (4-NP) and 2-nitrophenol (2-NP), and the combined effects of binary and ternary nitrophenols induced additive toxicity. Furthermore, 2,4-DNP, the dominant toxic nitrophenol, at various concentrations and toxicant ratios, was the major contributor to the combined inhibitory effects of the nitrophenol mixtures. Abundant EPS could be secreted by the anaerobic sludge under the inhibitory effects of toxic 2-NP, 4-NP, and 2,4-DNP at concentrations from 0 to 200 mg/L to resist the adverse effects of the external environment. The protein contents of both loosely bound EPS (LB-EPS) and tightly bound EPS (TB-EPS) exhibited a better linear positive correlation relationship (R² > 0.92) with the inhibitory rates of 2-NP, 4-NP, and 2,4-DNP, indicating that the proteins generated in the EPS of anaerobic sludge could be a stress response. Therefore, increasing the concentration of the toxic nitrophenols could enhance the stress response and increase protein production. Parallel factor (PARAFAC) analysis for TB-EPS and LB-EPS further confirmed that the major proteins were tyrosine, tryptophan, and aromatic proteins. Moreover, with an increase in the concentrations of 2-NP, 4-NP, and 2,4-DNP from 0 to 200 mg/L, microbial cell lysis and death in anaerobic sludge could be increasingly severe. Thus, this study provides new insights into the inhibitory effects of nitrophenol mixtures, which are frequently found in pharmaceutical and petrochemical effluents, on anaerobic sludge.

New methods of top-to-down mixture toxicity prediction: A case study of eliminating of the effects of cosolvent from binary mixtures

At present, the toxicity prediction of mixtures mainly focuses on the concentration addition (CA) and independent action (IA) based on individual toxicants to predict the toxicity of multicomponent mixtures. This process of predicting the toxicity of multicomponent mixtures based on single substances or low component mixtures is called down-to-top method in this study. However, due to the particularity of some toxicants, we have to use the top-to-down idea to obtain or eliminate the toxicity of some components from mixtures. For example, the toxicity of toxicants is obtained from the toxicity of a mixture with, especially toxic, cosolvent added. In the study, two top-to-down methods, the inverse CA (ICA) and inverse IA (IIA) models, were proposed to eliminate the effects of a certain component from multicomponent mixtures. Furthermore, taking the eight binary mixtures consisting of different shapes of cosolvents (isopropyl alcohol (IPA) having hormesis and dimethyl sulfoxide (DMSO)) and toxicants (two ionic liquids and two pesticides) as an example, combined with the interaction evaluated by CA and IA model, the influence of different shapes of components on top-to-down toxicity prediction was explored. The results showed that cosolvent IPA having hormesis may cause unpredictable effects, even at low concentrations, and should be used with caution. For DMSO, most of the toxicant's toxicity obtained by ICA and IIA models were almost in accordance with those observed experimentally, which showed that ICA and IIA could effectively eliminate the effects of cosolvent, even if toxic cosolvent, from the mixture. Ultimately, a frame of cosolvent use and toxicity correction for the hydrophobic toxicant were suggested based on the top-to-down toxicity prediction method. The proposed methods improve the existing framework of mixture toxicity prediction and provide a new idea for mixture toxicity evaluation and risk assessment.

Prediction on the combined toxicities of stimulation-only and inhibition-only contaminants using improved inverse distance weighted interpolation

The evaluation of ecological risks of contaminant mixtures to organisms is very challenging due to the non-linear response of organisms to each component, especially under the co-existence of both stimulators and inhibitors. Whether the stimulatory effect can reduce or even offset the inhibitory effect would be critical to the risk assessment and the treatment measures of mixed pollutants. Here, the combined toxicity of sodium fluoride (NaF), a stimulator with stimulation rate >100%, and six compounds that cannot induce hormesis (four ionic liquids (ILs) and two pesticides) were studied. The time-dependent toxicity of each toxicant on Vibrio qinghaiensis sp.-Q67 was investigated at 0.25, 2, 4, 6, 8, 10 and 12 h. Results showed that four ILs and two pesticides failed to induce hormesis, while NaF induced hormesis from 2 to 6 h and induced stimulation only after 6 h and reached its maximum (650%) at 12 h. All mixture rays with NaF induced hormesis at different times. In the four NaF-IL mixture systems, the absolute value of maximum stimulation demonstrated an upwards and then a downwards trend with the increasing of mixture ratio of IL. In two NaF-pesticide systems, the maximum stimulation effect declined with the increasing of the mixture ratio of pesticide. The toxicities of the mixture were successfully predicted by the improved inverse distance weighted interpolation, which are not able to be predicted by the commonly used concentration addition or independent action models. This paper shed lights on evaluating the hormesis of mixtures and the ecological risk of fluoride.

Study on the Combined Toxicities and Quantitative Characterization of Toxicity Sensitivities of Three Flavor Chemicals and Their Mixtures to Caenorhabditis elegans

It was shown that flavor chemicals with high toxicity sensitivities mean that small changes in their effective concentrations can lead to significant changes in toxicity. Flavors are widely used in personal care products. However, our study demonstrated that some flavor chemicals and their mixture rays have high toxicity sensitivities to Caenorhabditis elegans (C. elegans), which may have an impact on human health. In this paper, three flavor chemicals (benzyl alcohol, phenethyl alcohol, and cinnamaldehyde) were used as components of the mixture, and three binary mixture systems were constructed, respectively. Five mixture rays were designed for each mixture system by a direct equipartition ray design method. The lethal toxicities of the three flavor chemicals and mixture rays to C. elegans at three exposure volumes were determined. A new concept (inverse of the negative logarithmic concentration span (iSPAN)) was introduced to quantitatively evaluate the toxicity sensitivity of chemicals or mixture rays, and the combination index (CI) was employed to identify the toxicological interactions in the mixtures. It was shown that the three flavor chemicals as well as the binary mixture rays have a significant concentration-response relationship on the lethality of C. elegans. The iSPAN values of the three flavor chemicals and their mixture rays were larger than 3.000, showing very strong toxicity sensitivity to C. elegans. In mixture systems, the toxicity sensitivities of mixture rays with different mixture ratios were also different at different exposure volumes. In addition, it can be seen from the CI heat map that the toxicological interaction not only shows the mixture ratio dependence but also changes with the different exposure volumes, which implies that the mixtures consisting of flavor chemicals with high toxicity sensitivity have complex toxicological interactions. Therefore, in environmental risk assessment, special attention should be paid to chemicals with high toxicity sensitivities.

Combined lethal toxicities of pesticides with similar structures to Caenorhabditis elegans are not necessarily concentration additives

Studies have shown that the mixture toxicity of compounds with similar modes of action (MOAs) is usually predicted by the concentration addition (CA) model. However, due to the lack of toxicological information on compounds, more evidence is needed to determine whether the above conclusion is generally applicable. In general, the same type of compounds with similar chemical structures have similar MOAs, so whether the toxicities of the mixture of these compounds are additive needs to be further studied. In this paper, three types of pesticides with similar chemical structures (three organophosphoruses, two carbamates and two neonicotinoids) that may have similar MOAs were selected and five binary mixture systems were constructed. For each system, five mixture rays with different concentration ratios were designed by the direct equipartition ray design (EquRay) method. The mortality of Caenorhabditis elegans was regarded as the endpoint for the toxicity exposure to single pesticides and binary mixtures. The combined toxicities were evaluated simultaneously using the CA model, isobologram and combination index. The structural similarity of the same type of pesticides was quantitatively analyzed according to the MACCS molecular fingerprint and the slope of dose-response curve at pEC₅₀. The results show that the toxicities of neonicotinoid mixtures and carbamate mixtures are almost antagonistic. The entire mixture system of dichlorvos and dimethoate produced synergism, and four of the five mixture rays of dimethoate and methamidophos induced antagonism, while among the mixture rays of dichlorvos and methamidophos, different concentrations showed different interaction types. The results of structural similarity analysis show that the size of structural similarity showed a certain quantitative relationship with the toxicity interaction of mixtures, that is, the structural similarity of the same type of pesticides may show an additive action in a certain range.

Dynamic and quantitative characterization of antagonism within disinfectant mixtures by a modified area-concentration ratio method

The coexistence of various typical disinfectant pollutants has the potential to produce toxicity interaction towards organisms in the environment. A suitable model is necessary to evaluate the interaction quantitatively. Hence, the area-concentration ratio (ACR) method was modified (MACR) by combing confidence intervals to dynamically and quantitatively evaluate the toxicity interactions within disinfectant mixture pollutants. Disinfectant mixtures were designed by the direct equipartition design ray method using three guanidine disinfectants, chlorhexidine diacetate (CD), chlorhexidine (CHL), and polyhexamethylene biguanidine (POL) and one chlorine-containing disinfectant calcium hypochlorite (CAL). The toxicities of the four disinfectants and their mixtures towards Vibrio qinghaiensis sp.-Q67 (Q67) were determined by the time-dependent toxicity microplate analysis method. And the toxicity mechanism was analyzed by determining the effects of four disinfectants and their binary mixtures on the structure of cell, DNA and proteins (Pro) for Q67. The results show that the toxicities of CD and CHL to Q67vary little with time, but POL and CAL show the obvious time-dependent toxicity. The toxicities of CD, CHL and POL to Q67 are significantly stronger than that of CAL at the same exposure time. The toxicities of three binary mixture systems don't have significant difference in different exposure time. MACR can dynamically, quantitatively and accurately characterize toxicity interactions compared with ACR. According to MACR, the antagonism intensity dynamically changes with the prolongation of exposure time for binary mixture rays of three guanidine disinfectants and CAL, and linearly correlates with the components' concentration ratios. Four disinfectants all can destroy cell membrane and cause desaturation DNA of test organism, and CAL even can destroy the structure of DNA and protein. The probably reason for the antagonism within binary mixtures is the reaction between guanidine group and ClO^-, which is called chemical antaogism.

Single and joint inhibitory effect of nitrophenols on activated sludge

In this study, single and joint inhibitory effects of nitrophenols on activated sludge and variations on the content of extracellular polymeric substances (EPS) were investigated. Results indicate that the nitrophenols adversely affected the organic and NH₃-N removal of activated sludge and the adverse effect of nitrophenols on autotrophic bacteria was higher than that on heterotrophic bacteria. Further, 2,4-dinitrophenol (2,4-DNP) demonstrated the highest inhibitory effect, followed by 4-nitrophenol (4-NP) and 2-nitrophenol (2-NP), and the combined effects of binary and ternary nitrophenols induced additive toxicity. At various concentrations and toxicant ratios, 2,4-DNP, as the dominant toxic nitrophenol, was the major contributor to the joint inhibition effects of the mixed nitrophenols. At lower concentrations of 2-NP (below 100 mg/L), 4-NP (below 50 mg/L), and 2,4-DNP (below 10 mg/L), large amounts of both tightly bound EPS (TB-EPS) and loosely bound EPS (LB-EPS) were secreted for the normal physiological activities of the microbiological cells. After further stimulation with higher concentrations of 2-NP (above 100 mg/L), 4-NP (above 50 mg/L), and 2,4-DNP (above 10 mg/L), the inhibitory effect of nitrophenols on bacterial metabolism evidently increased. However, the EPS production sharply reduced, particularly with respect to protein production. Parallel factor analysis for TB-EPS and LB-EPS further confirmed that the major proteins were tyrosine, tryptophan, and aromatic proteins. Thus, this study provides new insights into the inhibitory effects of mixed nitrophenols, which are frequently found in pharmaceutical and petrochemical effluents.

Combined toxicity of endocrine-disrupting chemicals: A review

The combined toxicological assessment provides a realistic approach for hazard evaluation of chemical cocktails that co-existed in the environment. This review provides a holistic insight into the studies highlighting the mixture toxicity of the endocrine-disrupting chemicals (EDCs), especially focusing on the screening of biochemical pathways and other toxicogenetic endpoints. Reviewed literature showed that numerous multiplexed toxicogenomic techniques were applied to determine reproductive effects in vertebrates, but limited studies were found in non-mammalian species after mixture chemical exposure. Further, we found that the experimental design and concentration selection are the two important parameters in mixture toxicity studies that should be time- and cost-effective, highly precise, and environmentally relevant. A summary of EDC mixtures affecting the thyroid axis, estrogen axis, androgen axis, growth stress, and immune system via in vivo bioassays was also presented. It is interesting to mention that majority of estrogenic effects of the mixtures were sex-dependent, particularly observed in male fish as compared to female fish. Further, the androgen axis was perturbed with serious malformations in male rat testis (epididymal or gubernacular lesions, and deciduous spermatids). Also, transgenerational epigenetic effects were promoted in the F₃ and F₄ generations in the form of DNA methylation epimutations in sperm, increasing polycystic ovaries and reducing the offspring. Similarly, increased oxidative stress, high antioxidant enzymatic activities, disturbed estrous cycle, and decreased steroidogenesis were the commonly found effects after acute or chronic exposure to EDC mixtures. Importantly, the concentration addition (CA) and independent action (IA) models became more prevalent and suitable predictive models to unveil the prominence of synergistic estrogenic and anti-androgenic effects of chemical mixtures. More importantly, this review encompasses the research challenges and gaps in the existing knowledge and specific future research perspectives on combined toxicity.

Concentration Addition, Independent Action, and Quantitative Structure-Activity Relationships for Chemical Mixture Toxicities of the Disinfection By products of Haloacetic Acids on the Green Alga Raphidocelis subcapitata

The potential toxicity of haloacetic acids (HAAs), common disinfection by products (DBPs), has been widely studied; but their combined effects on freshwater green algae remain poorly understood. The present study was conducted to investigate the toxicological interactions of HAA mixtures in the green alga Raphidocelis subcapitata and predict the DBP mixture toxicities based on concentration addition, independent action, and quantitative structure-activity relationship (QSAR) models. The acute toxicities of 6 HAAs (iodoacetic acid [IAA], bromoacetic acid [BAA], chloroacetic acid [CAA], dichloroacetic acid [DCAA], trichloroacetic acid [TCAA], and tribromoacetic acid [TBAA]) and their 68 binary mixtures to the green algae were analyzed in 96-well microplates. Results reveal that the rank order of the toxicity of individual HAAs is CAA > IAA ≈ BAA > TCAA > DCAA > TBAA. With concentration addition as the reference additive model, the mixture effects are synergetic in 47.1% and antagonistic in 25%, whereas the additive effects are only observed in 27.9% of the experiments. The main components that induce synergism are DCAA, IAA, and BAA; and CAA is the main component that causes antagonism. Prediction by concentration addition and independent action indicates that the 2 models fail to accurately predict 72% mixture toxicity at an effective concentration level of 50%. Modeling the mixtures by QSAR was established by statistically analyzing descriptors for the determination of the relationship between their chemical structures and the negative logarithm of the 50% effective concentration. The additive mixture toxicities are accurately predicted by the QSAR model based on 2 parameters, the octanol-water partition coefficient and the acid dissociation constant (pK_a ). The toxicities of synergetic mixtures can be interpreted with the total energy (E_T ) and pK_a of the mixtures. Dipole moment and E_T are the quantum descriptors that influence the antagonistic mixture toxicity. Therefore, in silico modeling may be a useful tool in predicting disinfection by-product mixture toxicities. Environ Toxicol Chem 2021;40:1431-1442. © 2021 SETAC.

Quantitative characterization of toxicity interaction within antibiotic-heavy metal mixtures on Chlorella pyrenoidosa by a novel area-concentration ratio method

Toxicity interaction, synergism and antagonism, may occur when multiple pollutants are exposed to the environment simultaneously, which limits the utility of some standard models to assess toxicity hazards and risks. The development and application of models which can provide an insight into the combined toxicity of pollutants becomes necessary. Therefore, a novel model, area-concentration ratio (ACR) method, was developed to characterize the toxicity interaction within mixtures of three aminoglycoside antibiotics (AGs), kanamycin sulfate (KAN), paromomycin sulfate (PAR), tobramycin (TOB) and one heavy metal copper (Cu) in this study. The inhibition toxicity of single contaminants and mixtures designed by direct equilibration ray method and uniform design ray method to Chlorella pyrenoidosa (C. pyrenoidosa) was determined by the microplate toxicity analysis (MTA). The results showed that the novel method ACR could be used for quantitative characterization of combined toxicity. According to the ACR, all the binary AG antibiotic mixture systems display obvious synergism and weak antagonism. The addition of the heavy metal Cu into binary AG antibiotic mixtures can obviously change toxicity interaction, but toxicity interaction changing trend varies greatly in different ternary mixture systems. Toxicity interaction in the six mixture systems has component concentration-ratio dependence. ACR can be suggested as an effective novel method to quantitatively characterize toxicity interaction when assessing the hazards and risks of the combined pollution.

Assessing the combined toxicity of carbamate mixtures as well as organophosphorus mixtures to Caenorhabditis elegans using the locomotion behaviors as endpoints

Carbamate pesticides (CMs) and organophosphorus pesticides (OPs) have been widely used in agriculture and toxicologically affect non-target organisms. Although there are many reports about their toxicities, the combined behavioral toxicities of CM/OP mixtures on Caenorhabditis elegans have rarely been studied. In this study, body bend inhibition (BBI), head thrash inhibition (HTI), and swimming speed inhibition (SSI) by CMs and OPs were chosen as the toxicity endpoints. The locomotion behavioral toxicities of individual pesticides (carbofuran (CAR), methomyl (MET), chlorpyrifos (CPF), and triazophos (TAP)) and their binary mixtures on C. elegans were determined systematically and the toxicological interaction profiles of various CM/OP mixture rays constructed using the combination index. It was shown that four pesticides and their binary mixture rays have significant inhibitory effects on the locomotion behavior of C. elegans; that is, they produce locomotion behavioral toxicities and the toxicity of two OPs is higher than those of two CMs. The toxicological interactions in the binary CM and OP mixtures are different from each other. For example, one mixture ray (CAR-MET-R1) in the CM system on the SSI endpoint exhibits synergism at all concentration levels, another ray (CAR-MET-R3) displays low-dose synergism and high-dose additive action on BBI and HTI endpoints, and weak synergism at high-dose on SSI, and other rays perform additive action. Two rays (CPF-TAP-R1 and CPF-TAP-R2) in the OP mixture system display low-dose additive action and high-dose antagonism on the three endpoints. Another ray (CPF-TAP-R3) shows the additive action at all concentration levels. It can be concluded that it is not sufficient to evaluate the combined toxicity of binary CM/OP mixtures using only one concentration ratio ray and that it is necessary to examine multiple concentration ratios.

Novel Segmented Concentration Addition Method to Predict Mixture Hormesis of Chlortetracycline Hydrochloride and Oxytetracycline Hydrochloride to Aliivibrio fischeri

Hormesis is a concentration-response phenomenon characterized by low-concentration stimulation and high-concentration inhibition, which typically has a nonmonotonic J-shaped concentration-response curve (J-CRC). The concentration addition (CA) model is the gold standard for studying mixture toxicity. However, the CA model had the predictive blind zone (PBZ) for mixture J-CRC. To solve the PBZ problem, we proposed a segmented concentration addition (SCA) method to predict mixture J-CRC, which was achieved through fitting the left and right segments of component J-CRC and performing CA prediction subsequently. We selected two model compounds including chlortetracycline hydrochloride (CTCC) and oxytetracycline hydrochloride (OTCC), both of which presented J-CRC to Aliivibrio fischeri (AVF). The seven binary mixtures (M1-M7) of CTCC and OTCC were designed according to their molar ratios of 12:1, 10:3, 8:5, 1:1, 5:8, 3:10, and 1:12 referring to the direct equipartition ray design. These seven mixtures all presented J-CRC to AVF. Based on the SCA method, we obtained mixture maximum stimulatory effect concentration (ECm) and maximum stimulatory effect (Em) predicted by SCA, both of which were not available for the CA model. The toxicity interactions of these mixtures were systematically evaluated by using a comprehensive approach, including the co-toxicity coefficient integrated with confidence interval method (CTCICI), CRC, and isobole analysis. The results showed that the interaction types were additive and antagonistic action, without synergistic action. In addition, we proposed the cross point (CP) hypothesis for toxic interactive mixtures presenting J-CRC, that there was generally a CP between mixture observed J-CRC and CA predicted J-CRC; the relative positions of observed and predicted CRCs on either side of the CP would exchange, but the toxic interaction type of mixtures remained unchanged. The CP hypothesis needs to be verified by more mixtures, especially those with synergism. In conclusion, the SCA method is expected to have important theoretical and practical significance for mixture hormesis.

Significant effects of two pesticides on the bacteriostatic activity and antioxidant ability of green tea polyphenols

Green tea polyphenols (GTPs) are widely used in food preservation because of their strong bacteriostatic activity and antioxidant ability, and whether pesticides as common pollutants in food will affect the function of GTPs is worthy of attention.

New Insight Regarding the Relationship Between Enantioselective Toxicity Difference and Enantiomeric Toxicity Interaction from Chiral Ionic Liquids

Chirality is an important property of molecules. The study of biological activity and toxicity of chiral molecules has important theoretical and practical significance for toxicology, pharmacology, and environmental science. The toxicological significance of chiral ionic liquids (ILs) has not been well revealed. In the present study, the enantiomeric joint toxicities of four pairs of chiral ILs 1-alkyl-3-methylimidazolium lactate to Allivibrio fischeri were systematically investigated by using a comprehensive approach including the co-toxicity coefficient (CTC) integrated with confidence interval (CI) method (CTCICI), concentration-response curve (CRC), and isobole analysis. The direct equipartition ray (EquRay) design was used to design five binary mixtures of enantiomers according to molar ratios of 1:5, 2:4, 3:3, 4:2, and 5:1. The toxicities of chiral ILs and their mixtures were determined using the microplate toxicity analysis (MTA) method. Concentration addition (CA) and independent action (IA) were used as the additive reference models to construct the predicted CRC and isobole of mixtures. On the whole, there was an enantioselective toxicity difference between [BMIM]D-Lac and [BMIM]L-Lac, and [HMIM]D-Lac and [HMIM]L-Lac, while no enantioselective toxicity difference was observed for [EMIM]D-Lac and [EMIM]L-Lac, and [OMIM]D-Lac and [OMIM]L-Lac. Thereinto, the enantiomer mixtures of [BMIM]D-Lac and [BMIM]L-Lac, and [HMIM]D-Lac and [HMIM]L-Lac presented antagonistic action, and the enantiomer mixtures of [EMIM]D-Lac and [EMIM]L-Lac, and [OMIM]D-Lac and [OMIM]L-Lac overall presented additive action. Moreover, the greatest antagonistic toxicity interaction occurred at the equimolar ratio of enantiomers. Based on these results, we proposed two hypotheses, (1) chiral molecules with enantioselective toxicity difference tended to produce toxicity interactions, (2) the highest or lowest toxicity was usually at the equimolar ratio and its adjacent ratio for the enantiomer mixture. These hypotheses will need to be further validated by other enantiomer mixtures.

Integrative Assessment of Mixture Toxicity of Three Ionic Liquids on Acetylcholinesterase Using a Progressive Approach from 1D Point, 2D Curve, to 3D Surface

The joint toxicities of [BMIM]BF₄, [BMIM]PF₆, and [HMIM]BF₄ on acetylcholinesterase (AChE) were systematically investigated by using a progressive approach from 1D single effect point, 2D concentration-response curve (CRC), to 3D equivalent-surface (ES) level. The equipartition equivalent-surface design (EESD) method was used to design 10 ternary mixtures, and the direct equipartition ray (EquRay) design was used to design 15 binary mixtures. The toxicities of ionic liquids (ILs) and their mixtures were determined using the microplate toxicity analysis (MTA) method. The concentration addition (CA), independent action (IA), and co-toxicity coefficient (CTC) were used as the additive reference model to analyze the toxic interaction of these mixtures. The results showed that the Weibull function fitted well the CRCs of the three ILs and their mixtures with the coefficient of determination (R²) greater than 0.99 and root-mean-square error (RMSE) less than 0.04. According to the CTC integrated with confidence interval (CI) method (CTCICI) developed in this study, the 25 mixtures were almost all additive action at 20% and 80% effect point levels. At 50% effect, at least half of the 25 mixtures were slightly synergistic action, and the remaining mixtures were additive action. Furthermore, the ESs and CRCs predicted by CA and IA were all within the CIs of mixture observed ESs and CRCs, respectively. Therefore, the toxic interactions of these 25 mixtures were actually additive action. The joint toxicity of the three ILs can be effectively evaluated by the ES method. We also studied the relationship between the mixture toxicities and component concentration proportions. This study can provide reference data for IL risk assessment of combined pollution.

Joint toxicity of six common heavy metals to Chlorella pyrenoidosa

Six common heavy metals (Ni, Fe, Zn, Pb, Cd, and Cr) in the water environment were selected to present five groups of binary mixture systems (Ni-Fe, Ni-Zn, Ni-Pb, Ni-Cd, and Ni-Cr) through a direct equipartition ray design. Microplate toxicity analysis based on Chlorella pyrenoidosa measured the 96-h joint toxicities of the binary mixtures. Toxicity interaction of the binary mixture was analyzed by comparing the observed toxicity data with the reference model (concentration addition). The results indicated that Ni-Fe, Ni-Pb, and Ni-Cr mixtures showed additive effects at concentration tested. It was indicated that Ni-Zn and Ni-Cd mixtures presented additive effects at low concentrations whereas synergistic effects were seen at high concentrations.

Predicting the hormesis and toxicological interaction of mixtures by an improved inverse distance weighted interpolation

The prediction of toxicological interactions and hormesis of chemical mixtures is important because organisms are mostly exposed to numerous contaminants and typically to low dose of these mixtures, and it is still a challenge. Although many models have been developed to predict the mixture toxicities such as concentration addition (CA) and independent action (IA), they cannot solve these challenges perfectly. This study has developed an improved inverse distance weighted (IDW) interpolation for prediction of the mixture toxicities. IDW uses the mixture and the single compound as scatter points in space, and the space can be constructed by the concentration axes of various components in the mixture system. Some known mixtures (or the single compound) closest to the unknown mixture are selected as interpolation nodes. To be more accurate in calculation, a new normalization method for concentration has been proposed through dividing the concentration of the mixture and the single compound by the respective EC₅₀ values. Sixteen binary mixture systems are selected for leave-one-out cross-validation and three binary mixture systems are selected for external validation. The results show that the accuracy of IDW is ≥95% for three types of mixtures including no hormetic component, one hormetic component (show no toxicological interaction), and two hormetic components. The IDW also show higher prediction accuracy than that of CA and IA. The IDW developed in this study can be used to predict the toxicity of various mixture systems, thus providing predictive information for chemical mixtures risk assessment.

Synergetic effects of novel aromatic brominated and chlorinated disinfection byproducts on Vibrio qinghaiensis sp.-Q67

Aromatic halogenated chemicals are an unregulated class of byproducts (DBPs) generated from disinfection processes in the water environment. Information on the toxicological interactions, such as antagonism and synergism, present in DBP mixtures remains limited. This study aimed to determine the toxicological effects of aromatic halogenated DBP mixtures on the freshwater bacterium Vibrio qinghaiensis sp.-Q67. The acute toxicities of seven DBPs and their binary mixtures toward V. qinghaiensis sp.-Q67 were determined through microplate toxicity analysis. The toxicities of single DBPs were ranked as follows: 2,5-dibromohydroquinone > 2,4-dibromophenol > 4-bromo-2-chlorophenol ≈ 2,6-dibromo-4-nitrophenol > 2,6-dichloro-4-nitrophenol > 2-bromo-4-chlorophenol > 4-bromophenol. The percentages of synergism (experimental values higher than the predicted concentration addition) on the levels of 50%, 20%, and 10% effective concentrations reached 61%, 41%, and 31%, respectively. These results indicated that the probability of synergism decreased as concentration levels decreased. The synergetic effects of the compounds were dependent on concentration levels and concentration ratios. The proposed quantitative structure-activity relationship model can be used to predict the interactive toxicities exerted by 105 binary DBP mixture rays of 21 DBP mixture systems.

Polyethylene glycol 400 significantly enhances the stimulation of 2-phenoxyethanol on Vibrio qinghaiensis sp.-Q67 bioluminescence

Previous studies demonstrated long-term stimulation of some commercial personal care products (PCPs) on freshwater luminescent bacteria Vibrio qinghaiensis sp.-Q67 (Q67). However, whether a certain component can affect mixture's hormetic effect is still unknown. In this paper, two of ingredients in PCPs, 2-phenoxyethanol (PhE) and polyethylene glycol 400 (PEG400), were selected as object compounds to explore the relationship between concentration-response (CR) of mixtures and that of a single component. It was found that PEG400 has monotonic CR (MCR) on Q67 both at the short-term (0.25 h) and long-term (12 h) exposures while PhE has MCR at 0.25 h and hormetic CR (HCR) at 12 h. Here, the concentration-response curves (CRCs) of PEG400 at 0.25 and 12 h are overlapped each other and the CRCs of PEG400 are on the right of PhE. If the pEC₅₀ is taken as a toxic index, the toxicities of PEG400 at two times are basically the same, and those of PhE are the same, too, but PhE is twice as toxic as PEG400. For the mixtures of PEG400 and PhE, all rays except R1 have MCRs at 0.25 h while all rays have HCRs at 12 h where the higher the mixture ratio of PhE is, the more negative the maximum stimulation effect is. More importantly, the E_min values of all rays are more negative (1.79-3.17-fold) than that of PhE worked alone, which implies that the introduction of PEG400 significantly enhances stimulative effect of PhE. At 0.25 h, all binary mixture rays but R1 produce a low-concentration additive action and high-concentration synergism. At 12 h, all rays display additive action, antagonism, additive action, and synergism in turn when the concentration changes from low to high. The overall findings suggested toxicological interactions should be considered in the risk assessment of PCPs and their potential impacts on ecological balances.

Using an interpolation-based method (IDVequ) to predict the combined toxicities of hormetic ionic liquids

In the field of computational toxicology, predicting toxicological interaction or hormesis effect of a mixture from individuals is still a challenge. The two most frequently used model concentration addition (CA) and independent action (IA) also cannot solve these challenges perfectly. In this paper, we used IDV_equ (an interpolation method based on the Delaunay triangulation and Voronoi tessellation as well as the training set of direct equipartition ray design (EquRay) mixtures) to predict the toxicities of binary mixtures composed of hormetic ionic liquids (ILs). One of the purposes is to verify the predictive ability of IDV_equ. The other one is to improve the risk assessment of ILs mixtures especial hormetic ILs, because the toxicity reports of ILs mixtures are rarely reported in particular the toxicity of the hormetic ILs mixtures. Hence, we determined time-dependent toxicities of four ILs and their binary mixtures (designed by EquRay) to Vibrio qinghaiensis sp.-Q67 at first. Then, mixture toxicities were predicted and compared using the IDV_equ and CA. The results show that, the accuracy of IDV_equ is higher than the accuracy of CA. And, more important, to some mixtures out of the CA application, IDV_equ also can predict the mixture effects accurately. It showed that IDV_equ can be applied to predict the toxicity of any binary mixture regardless of the type of concentration-response curve of the components. These toxicity data provided useful information for researching the prediction of hormesis or toxicological interaction of the mixture and toxicities of ILs mixtures.

Combined Toxicity of 2,4-Dichlorophenoxyacetic Acid and Its Metabolites 2,4-Dichlorophenol (2,4-DCP) on Two Nontarget Organisms

2,4-Dichlorophenoxyacetic acid (2,4-D), a phenoxyalkanoic acid herbicide, is among the most widely distributed pollutants in the environment. 2,4-Dichlorophenol (2,4-DCP), as the main metabolite of 2,4-D, always accompanies 2,4-D. In this paper, we did research on the combined toxicities of 2,4-D and 2,4-DCP to Vibrio qinghaiensis sp.-Q67 (Q67) and Caenorhabditis elegans. It was found that the toxicity of 2,4-DCP is more severe than that of its parent 2,4-D at any concentration levels whether to Q67 or to C. elegans. Furthermore, 2,4-DCP to Q67 has the time-dependent toxicity. The toxicity of the mixture of 2,4-D and 2,4-DCP to Q67 is increasing with the exposure time, but that to C. elegans does not change over time. There is a good linear relationship between the pEC₅₀/pLC₅₀ value of binary mixture ray of 2,4-D and 2,4-DCP and the mixture ratio of 2,4-DCP, which implies the predictability of mixture toxicity of 2,4-D and 2,4-DCP. The toxicological interactions of the binary mixtures to Q67 are basically additive actions whether at 0.25 or at 12 h. However, most mixtures have antagonistic interactions against C. elegans.

Commercial personal care product mixtures exhibit hormetic concentration-responses to Vibrio qinghaiensis sp.-Q67

The biological effects related to personal care products (PCPs) are almost induced by some active ingredients in the PCPs rather than the PCP itself. In this study, 23 common and widely used toner, skin water, and make-up water (TSM) commodities were directly taken as mixture samples, and Vibrio qinghaiensis sp.-Q67 (Q67) was used as the test organism. The toxicities of the TSMs to Q67 were determined via microplate toxicity analysis at 0.25 h and 12 h. Each TSM commodity can be regarded as a complicated mixture (relative concentration is 1). It was shown that the concentration-response curves (CRCs) of 23 TSMs are monotonic sigmoid-shaped (S-shaped) at 0.25 h, the CRCs of six TSMs are also S-shaped but the other 17 TSMs are non-monotonic hormetic or J-shaped at 12 h. In addition, to effectively characterize the nature of the stimulation and inhibition phases, it is suggested that five parameters such as the EC_L (the median stimulation effective concentration (left)), E_min (the maximum stimulation effect), EC_min (the maximum stimulation effective concentration), ZEP (zero effect point where the effect is 0 and the concentration is ZEP), and EC₅₀ can depict the non-monotonic CRC. To the best of our knowledge, this is the first study about the hormetic CRCs of commercial PCP mixtures.

Toxicological interaction of multi-component mixtures to Vibrio qinghaiensis sp.-Q67 induced by at least three components

It has been stated by researchers that the antibiotic polymyxin B sulfate (POL) is a key component inducing time-dependent antagonism in freshwater luminescent bacteria, Vibrio qinghaiensis sp.-Q67, exposed in the ternary mixture system of the ionic liquids, pesticide and antibiotics. However, the previous statement is limited to ternary and quaternary mixtures without considering situations such as the binary system. In order to prove the direct inducing of antagonism by POL in a more complete and systematic way, two categories of experiments (adding POL in non-antagonistic ternary system and decomposing antagonistic ternary system with POL into the binary system) have been conducted in this paper. The results showed that quaternary mixture systems (adding POL to non-antagonism ternary mixture, up verification) exhibit antagonistic action in a majority of rays, at some point in the experiment. However, by decomposing the antagonistic ternary mixtures with POL into binary mixtures (down verification), the combined toxicities of binary mixtures at all time points in the experiment are additive. Obviously, the POL has a significant contribution to antagonism only in the ternary and quaternary mixtures, but not in the binary mixtures. We can draw a new conclusion that the antagonism of the multi-component mixtures is induced by at least three components (including POL), with complex chemical interactions. Therefore, considering POL's influence of antagonism as an example, future environmental protection practitioners and academic researchers should construct more scenarios of mixtures when assessing the influences and reactions of certain chemicals causing pollutions.

QSAR prediction of additive and non-additive mixture toxicities of antibiotics and pesticide

Antibiotics and pesticides may exist as a mixture in real environment. The combined effect of mixture can either be additive or non-additive (synergism and antagonism). However, no effective predictive approach exists on predicting the synergistic and antagonistic toxicities of mixtures. In this study, we developed a quantitative structure-activity relationship (QSAR) model for the toxicities (half effect concentration, EC₅₀) of 45 binary and multi-component mixtures composed of two antibiotics and four pesticides. The acute toxicities of single compound and mixtures toward Aliivibrio fischeri were tested. A genetic algorithm was used to obtain the optimized model with three theoretical descriptors. Various internal and external validation techniques indicated that the coefficient of determination of 0.9366 and root mean square error of 0.1345 for the QSAR model predicted that 45 mixture toxicities presented additive, synergistic, and antagonistic effects. Compared with the traditional concentration additive and independent action models, the QSAR model exhibited an advantage in predicting mixture toxicity. Thus, the presented approach may be able to fill the gaps in predicting non-additive toxicities of binary and multi-component mixtures.

Time-dependent and Pb-dependent antagonism and synergism towards Vibrio qinghaiensis sp.-Q67 within heavy metal mixtures

Toxicity interaction has aroused many researchers' interest in the combined toxicity of pollutants. Recently, some published studies have shown that the toxicity of some mixture pollutants is time dependent and well correlated with certain components in the mixture. Therefore, to investigate whether toxicity interaction is affected by the exposure time or certain components, synergism and antagonism within typical environmental contaminants of heavy metal mixtures were analyzed in different exposure times. Herein, three binary and one ternary mixture systems were designed by using three heavy metals: cadmium chloride, lead chloride (Pb) and manganese(ii) chloride tetrahydrate (Mn). For each mixture system, five mixture rays with different concentration ratios were arranged by direct equipartition ray design and uniform design ray methods. The toxicities of the three heavy metals and 20 mixture rays towards photobacteria Vibrio qinghaiensis sp.-Q67 (Q67) were determined by the established time-dependent microplate toxicity analysis (t-MTA) in different exposure durations of 0.25, 2, 4, 8 and 12 h. It was shown that the toxicities of three heavy metals (Cd, Pb and Mn) as well as their binary and ternary mixture rays to Q67 were also time dependent, but different metals or mixture rays showed different time characteristics. Surprisingly, some mixture rays exhibited antagonism or synergism with time dependency and the time characteristics varied in different mixture systems. Furthermore, the binary or ternary mixture systems with Pb displayed antagonism, while the Cd–Mn mixture system without Pb exhibited additive action or synergism, which indicated that Pb was probably the causative agent of antagonism produced by mixtures.

Toxicity interaction has gained much interest in the research of toxicity of mixture pollutants.

Global concentration additivity and prediction of mixture toxicities, taking nitrobenzene derivatives as an example

The toxicity of a mixture depends not only on the mixture concentration level but also on the mixture ratio. For a multiple-component mixture (MCM) system with a definite chemical composition, the mixture toxicity can be predicted only if the global concentration additivity (GCA) is validated. The so-called GCA means that the toxicity of any mixture in the MCM system is the concentration additive, regardless of what its mixture ratio and concentration level. However, many mixture toxicity reports have usually employed one mixture ratio (such as the EC₅₀ ratio), the equivalent effect concentration ratio (EECR) design, to specify several mixtures. EECR mixtures cannot simulate the concentration diversity and mixture ratio diversity of mixtures in the real environment, and it is impossible to validate the GCA. Therefore, in this paper, the uniform design ray (UD-Ray) was used to select nine mixture ratios (rays) in the mixture system of five nitrobenzene derivatives (NBDs). The representative UD-Ray mixtures can effectively and rationally describe the diversity in the NBD mixture system. The toxicities of the mixtures to Vibrio qinghaiensis sp.-Q67 were determined by the microplate toxicity analysis (MTA). For each UD-Ray mixture, the concentration addition (CA) model was used to validate whether the mixture toxicity is additive. All of the UD-Ray mixtures of five NBDs are global concentration additive. Afterwards, the CA is employed to predict the toxicities of the external mixtures from three EECR mixture rays with the NOEC, EC₃₀, and EC₇₀ ratios. The predictive toxicities are in good agreement with the experimental toxicities, which testifies to the predictability of the mixture toxicity of the NBDs.

Using Delaunay triangulation and Voronoi tessellation to predict the toxicities of binary mixtures containing hormetic compound

Concentration addition (CA) was proposed as a reasonable default approach for the ecological risk assessment of chemical mixtures. However, CA cannot predict the toxicity of mixture at some effect zones if not all components have definite effective concentrations at the given effect, such as some compounds induce hormesis. In this paper, we developed a new method for the toxicity prediction of various types of binary mixtures, an interpolation method based on the Delaunay triangulation (DT) and Voronoi tessellation (VT) as well as the training set of direct equipartition ray design (EquRay) mixtures, simply IDV_equ. At first, the EquRay was employed to design the basic concentration compositions of five binary mixture rays. The toxic effects of single components and mixture rays at different times and various concentrations were determined by the time-dependent microplate toxicity analysis. Secondly, the concentration-toxicity data of the pure components and various mixture rays were acted as a training set. The DT triangles and VT polygons were constructed by various vertices of concentrations in the training set. The toxicities of unknown mixtures were predicted by the linear interpolation and natural neighbor interpolation of vertices. The IDV_equ successfully predicted the toxicities of various types of binary mixtures.

Quantitative Characterization of the Toxicities of Cd-Ni and Cd-Cr Binary Mixtures Using Combination Index Method

Direct equipartition ray design was used to construct Cd-Ni and Cd-Cr binary mixtures. Microplate toxicity analysis was used to evaluate the toxicity of individual substance and the Cd-Ni and Cd-Cr mixtures on Chlorella pyrenoidosa and Selenastrum capricornutum. The interacting toxicity of the mixture was analyzed with concentration addition (CA) model. In addition, combination index method (CI) was proposed and used to quantitatively characterize the toxicity of the binary mixtures of Cd-Ni and Cd-Cr observed in experiment and find the degree of deviation from the predicted outcome of the CA model, that is, the intensity of interacting toxicity. Results indicate that most of the 20 binary mixtures exhibit enhancing and synergistic effect, and only Cd-Cr-R4 and Cd-Cr-R5 mixtures have relatively high antagonistic effects against C. pyrenoidosa. Based on confidence interval, CI can compare the intensities of interaction of the mixtures under varying levels of effect. The characterization methods are applicable for analyzing binary mixture with complex interaction.

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.

Environmental Application, Fate, Effects, and Concerns of Ionic Liquids: A Review

Ionic liquids (ILs) comprise mostly of organic salts with negligible vapor pressure and low flammability that are proposed as replacements for volatile solvents. ILs have been promoted as "green" solvents and widely investigated for their various applications. Although the utility of these chemicals is unquestionable, their toxic effects have attracted great attention. In order to manage their potential hazards and design environmentally benign ILs, understanding their environmental behavior, fate and effects is important. In this review, environmentally relevant issues of ILs, including their environmental application, environmental behavior and toxicity are addressed. In addition, also presented are the influence of ILs on the environmental fate and toxicity of other coexisting contaminants, important routes for designing nontoxic ILs and the techniques that might be adopted for the removal of ILs.

Linear regression model for predicting interactive mixture toxicity of pesticide and ionic liquid

The nature of most environmental contaminants comes from chemical mixtures rather than from individual chemicals. Most of the existed mixture models are only valid for non-interactive mixture toxicity. Therefore, we built two simple linear regression-based concentration addition (LCA) and independent action (LIA) models that aim to predict the combined toxicities of the interactive mixture. The LCA model was built between the negative log-transformation of experimental and expected effect concentrations of concentration addition (CA), while the LIA model was developed between the negative log-transformation of experimental and expected effect concentrations of independent action (IA). Twenty-four mixtures of pesticide and ionic liquid were used to evaluate the predictive abilities of LCA and LIA models. The models correlated well with the observed responses of the 24 binary mixtures. The values of the coefficient of determination (R (2)) and leave-one-out (LOO) cross-validated correlation coefficient (Q(2)) for LCA and LIA models are larger than 0.99, which indicates high predictive powers of the models. The results showed that the developed LCA and LIA models allow for accurately predicting the mixture toxicities of synergism, additive effect, and antagonism. The proposed LCA and LIA models may serve as a useful tool in ecotoxicological assessment.

Predictability of the time-dependent toxicities of aminoglycoside antibiotic mixtures to Vibrio qinghaiensis sp.-Q67

The combined toxicities of all binary mixtures constructed by four aminoglycoside (AG) antibiotics are concentration additive, which has nothing to do with exposure time, mixture ratio, and concentration level.

Application of the combination index integrated with confidence intervals to study the toxicological interactions of antibiotics and pesticides in Vibrio qinghaiensis sp.-Q67

It is necessary to explore the effect of confidence intervals on the combination index (CI) so that rationally evaluate the toxicological interaction (synergism or antagonism) which is dependent on the concentration ratio, the mixture concentration and the exposure time. To effectively detect the toxicological interaction taking place in mixtures, we combined the CI with the observation-based confidence intervals (OCI) which can characterize the uncertainty in toxicity test and in data fitting. In time scale, the short-term (15min) and long-term (12h) toxicities of three chemicals (imidacloprid (IMI), pirimicarb (PIR) and streptomycin sulfate (STR)) and their binary mixtures on Vibrio qinghaiensis sp.-Q67 were determined by the microplate toxicity analysis (MTA). The mixtures of IMI, PIR and STR have additive actions all but four IMI-PIR rays (R2-R5) at the effect levels above about 30-40% whose long-term toxicological interaction are synergism.