Chemical mixture toxicology: from descriptive to mechanistic, and going on to in silico toxicology

Principles of dose-setting in toxicology studies: the importance of kinetics for ensuring human safety

Regulatory toxicology seeks to ensure that exposures to chemicals encountered in the environment, in the workplace, or in products pose no significant hazards and produce no harm to humans or other organisms, i.e., that chemicals are used safely. The most practical and direct means of ensuring that hazards and harms are avoided is to identify the doses and conditions under which chemical toxicity does not occur so that chemical concentrations and exposures can be appropriately limited. Modern advancements in pharmacology and toxicology have revealed that the rates and mechanisms by which organisms absorb, distribute, metabolize and eliminate chemicals-i.e., the field of kinetics-often determine the doses and conditions under which hazard, and harm, are absent, i.e., the safe dose range. Since kinetics, like chemical hazard and toxicity, are extensive properties that depend on the amount of the chemical encountered, it is possible to identify the maximum dose under which organisms can efficiently metabolize and eliminate the chemicals to which they are exposed, a dose that has been referred to as the kinetic maximum dose, or KMD. This review explains the rationale that compels regulatory toxicology to embrace the advancements made possible by kinetics, why understanding the kinetic relationship between the blood level produced and the administered dose of a chemical is essential for identifying the safe dose range, and why dose-setting in regulatory toxicology studies should be informed by estimates of the KMD rather than rely on the flawed concept of maximum-tolerated toxic dose, or MTD.

Metabolite Changes in an Estuarine Annelid Following Sublethal Exposure to a Mixture of Zinc and Boscalid

Environmental pollutants such as heavy metals and fungicides pose a serious threat to waterways worldwide. Toxicological assessment of such contaminants is usually conducted using single compound exposures, as it is challenging to understand the effect of mixtures on biota using standard ecotoxicological methods; whereas complex chemical mixtures are more probable in ecosystems. This study exposed Simplisetia aequisetis (an estuarine annelid) to sublethal concentrations of a metal (zinc) and a fungicide (boscalid), both singly and as a mixture, for two weeks. Metabolomic analysis via gas and liquid chromatography-mass spectrometry was used to measure the stress response(s) of the organism following exposure. A total of 75 metabolites, including compounds contributing to the tricarboxylic acid cycle, the urea cycle, and a number of other pathways, were identified and quantified. The multiplatform approach identified distinct metabolomic responses to each compound that differed depending on whether the substance was presented singly or as a mixture, indicating a possible antagonistic effect. The study demonstrates that metabolomics is able to elucidate the effects and mode of action of contaminants and can identify possible outcomes faster than standard ecotoxicological endpoints, such as growth and reproduction. Metabolomics therefore has a possible future role in biomonitoring and ecosystem health assessments.

Toxicity of diatom-derived polyunsaturated aldehyde mixtures on sea urchin Paracentrotus lividus development

Diatom-derived polyunsaturated aldehydes (PUAs), decadienal, heptadienal and octadienal, derive from the oxidation of fatty acids and have cytotoxic and anticancer effects. PUAs, tested separately, induce malformations in sea urchin Paracentrotus lividus embryos. Decadienal induces the worst malformations and lowest survival rates. Interestingly, decadienal, heptadienal and octadienal place in motion several genes to counteract their negative effects. To date, no studies are available reporting on the effects of PUA mixtures on marine invertebrates. Here we test binary and ternary mixtures on embryonic development of P. lividus. Our findings demonstrate that mixtures of PUAs act (i) at morphological level in synergistic way, being much more severe compared to individual PUAs; (ii) at molecular level also reveal an additive effect, affecting almost all fifty genes, previously tested using individual PUAs. This study is relevant from an ecological point of view since diatoms are a major food source for both pelagic and benthic organisms. This work opens new perspectives for understanding the molecular mechanisms that marine organisms use in reacting to environmental natural toxin mixtures such as diatom PUAs.

Bridging the Data Gap From in vitro Toxicity Testing to Chemical Safety Assessment Through Computational Modeling

Chemical toxicity testing is moving steadily toward a human cell and organoid-based in vitro approach for reasons including scientific relevancy, efficiency, cost, and ethical rightfulness. Inferring human health risk from chemical exposure based on in vitro testing data is a challenging task, facing various data gaps along the way. This review identifies these gaps and makes a case for the in silico approach of computational dose-response and extrapolation modeling to address many of the challenges. Mathematical models that can mechanistically describe chemical toxicokinetics (TK) and toxicodynamics (TD), for both in vitro and in vivo conditions, are the founding pieces in this regard. Identifying toxicity pathways and in vitro point of departure (PoD) associated with adverse health outcomes requires an understanding of the molecular key events in the interacting transcriptome, proteome, and metabolome. Such an understanding will in turn help determine the sets of sensitive biomarkers to be measured in vitro and the scope of toxicity pathways to be modeled in silico. In vitro data reporting both pathway perturbation and chemical biokinetics in the culture medium serve to calibrate the toxicity pathway and virtual tissue models, which can then help predict PoDs in response to chemical dosimetry experienced by cells in vivo. Two types of in vitro to in vivo extrapolation (IVIVE) are needed. (1) For toxic effects involving systemic regulations, such as endocrine disruption, organism-level adverse outcome pathway (AOP) models are needed to extrapolate in vitro toxicity pathway perturbation to in vivo PoD. (2) Physiologically-based toxicokinetic (PBTK) modeling is needed to extrapolate in vitro PoD dose metrics into external doses for expected exposure scenarios. Linked PBTK and TD models can explore the parameter space to recapitulate human population variability in response to chemical insults. While challenges remain for applying these modeling tools to support in vitro toxicity testing, they open the door toward population-stratified and personalized risk assessment.

Potentiation of Sodium Metabisulfite Toxicity by Propylene Glycol in Both in Vitro and in Vivo Systems

Many consumer products used in our daily lives result in inhalation exposure to a variety of chemicals, although the toxicities of the active ingredients are not well known; furthermore, simultaneous exposure to chemical mixtures occurs. Sodium metabisulfite (SM) and propylene glycol (PG) are used in a variety of products. Both the cytotoxicity and the sub-acute inhalation toxicity of each chemical and their mixtures were evaluated. Assays for cell viability, membrane damage, and lysosome damage demonstrated that SM over 100 μg/ml induced significant cytotoxicity; moreover, when PG, which was not cytotoxic, was mixed with SM, the cytotoxicity of the mixture was enhanced. Solutions of 1, 5, and 20% SM, each with 1% PG solution, were prepared, and the whole body of rats was exposed to aerosols of the mixture for 6 h/day, 5 days/week for 2 weeks. The rats were sacrificed 1 (exposure group) or 7 days (recovery group) after termination of the exposure. The actual concentration of SM in the low-, medium-, and high-exposure groups was 3.91 ± 1.26, 35.73 ± 6.01, and 80.98 ± 5.47 mg/m³, respectively, and the actual concentration of PG in each group was 6.47 ± 1.25, 8.68 ± 0.6, and 8.84 ± 1.77 mg/m³. The repeated exposure to SM and PG caused specific clinical signs including nasal sound, sneeze, and eye irritation which were not found in SM single exposure. In addition, the body weight of treatment group rats decreased compared to that of the control group rats in a time-dependent manner. The total protein concentration and lactate dehydrogenase activity in the bronchoalveolar lavage fluid (BALF) increased. Histopathological analysis of the lungs, liver, and nasal cavity was performed. Adverse effects were observed in the nasal cavity, with squamous cell metaplasia identified in the front of the nasal cavity in all high-exposure groups, which completely recovered 7 days after exposure was terminated. Whereas inhalation of SM for 2 weeks only reduced body weight in the high-dose group, inhalation of SM and PG mixtures for 2 weeks significantly decreased body weight and induced metaplasia of the respiratory epithelium into squamous cells in the medium- and high-dose groups. In conclusion, PG potentiated the toxicity of SM in human lung epithelial cells and the inhalation toxicity in rats.

Toxicant mixtures in sediment alter gene expression in the cysteine metabolism of Chironomus tepperi

Sediment contamination can pose risks to the environment, and sediment toxicity tests have been developed to isolate the impact of sediment from other factors. Mixtures of contaminants often occur in sediments, and traditional endpoints used in toxicity testing, such as growth, reproduction, and survival, cannot discern the cause of toxicity from chemical mixtures because of complex interactions. In urban waterways, the synthetic pyrethroid bifenthrin and the metal copper are commonly found in mixtures, so the present study was designed to investigate how these contaminants cause toxicity in mixtures. To investigate this, Chironomus tepperi was exposed to environmentally relevant concentrations of copper and bifenthrin-spiked sediments in a 2-way factorial mixture for 5 d. Growth and expression profiles of cysteine metabolism genes were measured after exposure. Growth increased at low copper concentrations, decreased at high copper concentrations, and was unaffected by bifenthrin exposures. Copper exposures induced possible cellular repair by upregulating S-adenosylmethionine synthetase expression and downregulating expression of S-adenosylhomocysteine hydrolase and cystathionine-β-synthase. Metallothionein upregulation was also observed. Bifenthrin exposure altered cysteine metabolism to a lesser extent, downregulating cystathionine-β-synthase and γ-glutamylcysteine synthase. Synergistic, antagonistic, and dose-dependent interactions were observed, and there was evidence of conflicting modes of action and limited substrate production. These findings demonstrate how contextual gene expression changes can be sensitive and specific identifiers of toxicant exposure in mixtures. Environ Toxicol Chem 2017;36:691-698. © 2016 SETAC.

Application of Biologically Based Lumping To Investigate the Toxicokinetic Interactions of a Complex Gasoline Mixture

People are often exposed to complex mixtures of environmental chemicals such as gasoline, tobacco smoke, water contaminants, or food additives. We developed an approach that applies chemical lumping methods to complex mixtures, in this case gasoline, based on biologically relevant parameters used in physiologically based pharmacokinetic (PBPK) modeling. Inhalation exposures were performed with rats to evaluate the performance of our PBPK model and chemical lumping method. There were 109 chemicals identified and quantified in the vapor in the chamber. The time-course toxicokinetic profiles of 10 target chemicals were also determined from blood samples collected during and following the in vivo experiments. A general PBPK model was used to compare the experimental data to the simulated values of blood concentration for 10 target chemicals with various numbers of lumps, iteratively increasing from 0 to 99. Large reductions in simulation error were gained by incorporating enzymatic chemical interactions, in comparison to simulating the individual chemicals separately. The error was further reduced by lumping the 99 nontarget chemicals. The same biologically based lumping approach can be used to simplify any complex mixture with tens, hundreds, or thousands of constituents.

Predicting environmental risk: A road map for the future

Frameworks for environmental risk assessment (ERA) focus on comparing results from separate exposure and effect assessments. Exposure assessment generally relies on mechanistic fate models, whereas the effects assessment is anchored in standard test protocols and descriptive statistics. This discrepancy prevents a useful link between these two pillars of ERA, and jeopardizes the realism and efficacy of the entire process. Similar to exposure assessment, effects assessment requires a mechanistic approach to translate the output of fate models into predictions for impacts on populations and food webs. The aim of this study was to discuss (1) the central importance of the individual level, (2) different strategies of dealing with biological complexity, and (3) the role that toxicokinetic-toxicodynamic (TKTD) models, energy budgets, and molecular biology play in a mechanistic revision of the ERA framework. Consequently, an outline for a risk assessment paradigm was developed that incorporates a mechanistic effects assessment in a consistent manner, and a "roadmap for the future." Such a roadmap may play a critical role to eventually arrive at a more scientific and efficient ERA process, and needs to be used to shape our long-term research agendas.

Modelling of compound combination effects and applications to efficacy and toxicity: state-of-the-art, challenges and perspectives

The development of treatments involving combinations of drugs is a promising approach towards combating complex or multifactorial disorders. However, the large number of compound combinations that can be generated, even from small compound collections, means that exhaustive experimental testing is infeasible. The ability to predict the behaviour of compound combinations in biological systems, whittling down the number of combinations to be tested, is therefore crucial. Here, we review the current state-of-the-art in the field of compound combination modelling, with the aim to support the development of approaches that, as we hope, will finally lead to an integration of chemical with systems-level biological information for predicting the effect of chemical mixtures.

Computational pharmacokinetics/pharmacodynamics of rifampin in a mouse tuberculosis infection model

One critical approach to preclinical evaluation of anti-tuberculosis (anti-TB) drugs is the study of correlations between drug exposure and efficacy in animal TB infection models. While such pharmacokinetic/pharmacodynamic (PK/PD) studies are useful for the identification of optimal clinical dosing regimens, they are resource intensive and are not routinely performed. A mathematical model capable of simulating the PK/PD properties of drug therapy for experimental TB offers a way to mitigate some of the practical obstacles to determining the PK/PD index that best correlates with efficacy. Here, we present a preliminary physiologically based PK/PD model of rifampin therapy in a mouse TB infection model. The computational framework integrates whole-body rifampin PKs, cell population dynamics for the host immune response to Mycobacterium tuberculosis infection, drug-bacteria interactions, and a Bayesian method for parameter estimation. As an initial application, we calibrated the model to a set of available rifampin PK/PD data and simulated a separate dose fractionation experiment for bacterial killing kinetics in the lungs of TB-infected mice. The simulation results qualitatively agreed with the experimentally observed PK/PD correlations, including the identification of area under the concentration-time curve as best correlating with efficacy. This single-drug framework is aimed toward extension to multiple anti-TB drugs in order to facilitate development of optimal combination regimens.

Toxicogenomic analysis in the combined effect of tributyltin and benzo[a]pyrene on the development of zebrafish embryos

There is a growing recognition that the toxic effects of chemical mixtures are been an important issue in toxicological sciences. Tributyltin (TBT) and benzo[a]pyrene (BaP) are widespread pollutants that occur simultaneously in the aquatic environments. This study was designed to examine comprehensively the combined effects of TBT and BaP on zebrafish (Danio rerio) embryos using toxicogenomic approach combined with biochemical detection and morphological analysis, and tried to gain insight into the mechanisms underlying the combined effects of TBT and BaP. The results of toxicogenomic data indicated that: (1) TBT cotreatment rescued the embryos from decreased hatching ratio caused by BaP alone, while the alteration of gene expression (in this article the phrase gene expression is used as a synonym to gene transcription, although in is acknowledged that gene expression can also be regulated by, e.g., translation and mRNA or protein stability) relative to zebrafish hatching in the BaP groups was resumed by the cotreatment with TBT; (2) BaP cotreatment decreased TBT-mediated dorsal curvature, and alleviated the perturbation of Notch pathway caused by TBT alone; (3) cotreatment with TBT decreased BaP-mediated bradycardia, which might be due to that TBT cotreatment alleviated the perturbation in expression of genes related to cardiac muscle cell development and calcium handling caused by BaP alone; 4) TBT cotreatment brought an antagonistic effect on the BaP-mediated oxidative stress and DNA damage. These results suggested that toxicogenomic approach was available for analyzing combined toxicity with high sensitivity and accuracy, which might improve our understanding and predictability for the combined effects of chemicals.

A physiologically based pharmacokinetic model of rifampin in mice

One problem associated with regimen-based development of antituberculosis (anti-TB) drugs is the difficulty of a systematic and thorough in vivo evaluation of the large number of possible regimens that arise from consideration of multiple drugs tested together. A mathematical model capable of simulating the pharmacokinetics and pharmacodynamics of experimental combination chemotherapy of TB offers a way to mitigate this problem by extending the use of available data to investigate regimens that are not initially tested. In order to increase the available mathematical tools needed to support such a model for preclinical anti-TB drug development, we constructed a preliminary whole-body physiologically based pharmacokinetic (PBPK) model of rifampin in mice, using data from the literature. Interindividual variability was approximated using Monte Carlo (MC) simulation with assigned probability distributions for the model parameters. An MC sensitivity analysis was also performed to determine correlations between model parameters and plasma concentration to inform future model development. Model predictions for rifampin concentrations in plasma, liver, kidneys, and lungs, following oral administration, were generally in agreement with published experimental data from multiple studies. Sensitive model parameters included those descriptive of oral absorption, total clearance, and partitioning of rifampin between blood and muscle. This PBPK model can serve as a starting point for the integration of rifampin pharmacokinetics in mice into a larger mathematical framework, including the immune response to Mycobacterium tuberculosis infection, and pharmacokinetic models for other anti-TB drugs.

Impact of chemical proportions on the acute neurotoxicity of a mixture of seven carbamates in preweanling and adult rats

Statistical design and environmental relevance are important aspects of studies of chemical mixtures, such as pesticides. We used a dose-additivity model to test experimentally the default assumptions of dose additivity for two mixtures of seven N-methylcarbamates (carbaryl, carbofuran, formetanate, methomyl, methiocarb, oxamyl, and propoxur). The best-fitting models were selected for the single-chemical dose-response data and used to develop a combined prediction model, which was then compared with the experimental mixture data. We evaluated behavioral (motor activity) and cholinesterase (ChE)-inhibitory (brain, red blood cells) outcomes at the time of peak acute effects following oral gavage in adult and preweanling (17 days old) Long-Evans male rats. The mixtures varied only in their mixing ratios. In the relative potency mixture, proportions of each carbamate were set at equitoxic component doses. A California environmental mixture was based on the 2005 sales of each carbamate in California. In adult rats, the relative potency mixture showed dose additivity for red blood cell ChE and motor activity, and brain ChE inhibition showed a modest greater-than additive (synergistic) response, but only at a middle dose. In rat pups, the relative potency mixture was either dose-additive (brain ChE inhibition, motor activity) or slightly less-than additive (red blood cell ChE inhibition). On the other hand, at both ages, the environmental mixture showed greater-than additive responses on all three endpoints, with significant deviations from predicted at most to all doses tested. Thus, we observed different interactive properties for different mixing ratios of these chemicals. These approaches for studying pesticide mixtures can improve evaluations of potential toxicity under varying experimental conditions that may mimic human exposures.

Mixture toxicity revisited from a toxicogenomic perspective

The advent of new genomic techniques has raised expectations that central questions of mixture toxicology such as for mechanisms of low dose interactions can now be answered. This review provides an overview on experimental studies from the past decade that address diagnostic and/or mechanistic questions regarding the combined effects of chemical mixtures using toxicogenomic techniques. From 2002 to 2011, 41 studies were published with a focus on mixture toxicity assessment. Primarily multiplexed quantification of gene transcripts was performed, though metabolomic and proteomic analysis of joint exposures have also been undertaken. It is now standard to explicitly state criteria for selecting concentrations and provide insight into data transformation and statistical treatment with respect to minimizing sources of undue variability. Bioinformatic analysis of toxicogenomic data, by contrast, is still a field with diverse and rapidly evolving tools. The reported combined effect assessments are discussed in the light of established toxicological dose-response and mixture toxicity models. Receptor-based assays seem to be the most advanced toward establishing quantitative relationships between exposure and biological responses. Often transcriptomic responses are discussed based on the presence or absence of signals, where the interpretation may remain ambiguous due to methodological problems. The majority of mixture studies design their studies to compare the recorded mixture outcome against responses for individual components only. This stands in stark contrast to our existing understanding of joint biological activity at the levels of chemical target interactions and apical combined effects. By joining established mixture effect models with toxicokinetic and -dynamic thinking, we suggest a conceptual framework that may help to overcome the current limitation of providing mainly anecdotal evidence on mixture effects. To achieve this we suggest (i) to design studies to establish quantitative relationships between dose and time dependency of responses and (ii) to adopt mixture toxicity models. Moreover, (iii) utilization of novel bioinformatic tools and (iv) stress response concepts could be productive to translate multiple responses into hypotheses on the relationships between general stress and specific toxicity reactions of organisms.

A biology-based approach for mixture toxicity of multiple endpoints over the life cycle

Typical approaches for analyzing mixture ecotoxicity data only provide a description of the data; they cannot explain observed interactions, nor explain why mixture effects can change in time and differ between endpoints. To improve our understanding of mixture toxicity we need to explore biology-based models. In this paper, we present an integrated approach to deal with the toxic effects of mixtures on growth, reproduction and survival, over the life cycle. Toxicokinetics is addressed with a one-compartment model, accounting for effects of growth. Each component of the mixture has its own toxicokinetics model, but all compounds share the effect of body size on uptake kinetics. The toxicodynamic component of the method is formed by an implementation of dynamic energy budget theory; a set of simple rules for metabolic organization that ensures conservation of mass and energy. Toxicant effects are treated as a disruption of regular metabolic processes such as an increase in maintenance costs. The various metabolic processes interact, which means that mixtures of compounds with certain mechanisms of action have to produce a response surface that deviates from standard models (such as 'concentration addition'). Only by separating these physiological interactions from the chemical interactions between mixture components can we hope to achieve generality and a better understanding of mixture effects. For example, a biology-based approach allows for educated extrapolations to other mixtures, other species, and other exposure situations. We illustrate our method with the interpretation of partial life-cycle data for two polycyclic aromatic hydrocarbons in Daphnia magna.

Assessment of herbal medicinal products: challenges, and opportunities to increase the knowledge base for safety assessment

Although herbal medicinal products (HMP) have been perceived by the public as relatively low risk, there has been more recognition of the potential risks associated with this type of product as the use of HMPs increases. Potential harm can occur via inherent toxicity of herbs, as well as from contamination, adulteration, plant misidentification, and interactions with other herbal products or pharmaceutical drugs. Regulatory safety assessment for HMPs relies on both the assessment of cases of adverse reactions and the review of published toxicity information. However, the conduct of such an integrated investigation has many challenges in terms of the quantity and quality of information. Adverse reactions are under-reported, product quality may be less than ideal, herbs have a complex composition and there is lack of information on the toxicity of medicinal herbs or their constituents. Nevertheless, opportunities exist to capitalise on newer information to increase the current body of scientific evidence. Novel sources of information are reviewed, such as the use of poison control data to augment adverse reaction information from national pharmacovigilance databases, and the use of more recent toxicological assessment techniques such as predictive toxicology and omics. The integration of all available information can reduce the uncertainty in decision making with respect to herbal medicinal products. The example of Aristolochia and aristolochic acids is used to highlight the challenges related to safety assessment, and the opportunities that exist to more accurately elucidate the toxicity of herbal medicines.

Gene expression profiles in rainbow trout, Onchorynchus mykiss, exposed to a simple chemical mixture

Among proposed uses for microarrays in environmental toxiciology is the identification of key contributors to toxicity within a mixture. However, it remains uncertain whether the transcriptomic profiles resulting from exposure to a mixture have patterns of altered gene expression that contain identifiable contributions from each toxicant component. We exposed isogenic rainbow trout Onchorynchus mykiss, to sublethal levels of ethynylestradiol, 2,2,4,4-tetrabromodiphenyl ether, and chromium VI or to a mixture of all three toxicants Fluorescently labeled complementary DNA (cDNA) were generated and hybridized against a commercially available Salmonid array spotted with 16,000 cDNAs. Data were analyzed using analysis of variance (p<0.05) with a Benjamani-Hochberg multiple test correction (Genespring [Agilent] software package) to identify up and downregulated genes. Gene clustering patterns that can be used as "expression signatures" were determined using hierarchical cluster analysis. The gene ontology terms associated with significantly altered genes were also used to identify functional groups that were associated with toxicant exposure. Cross-ontological analytics approach was used to assign functional annotations to genes with "unknown" function. Our analysis indicates that transcriptomic profiles resulting from the mixture exposure resemble those of the individual contaminant exposures, but are not a simple additive list. However, patterns of altered genes representative of each component of the mixture are clearly discernible, and the functional classes of genes altered represent the individual components of the mixture. These findings indicate that the use of microarrays to identify transcriptomic profiles may aid in the identification of key stressors within a chemical mixture, ultimately improving environmental assessment.

Scaling relationships based on partition coefficients and body sizes have similarities and interactions

The LC(50) of compounds with a similar biological effect, at a given exposure period, is frequently plotted log-log against the octanol-water partition coefficient and a straight line is fitted for interpolation purposes. This is also frequently done for physiological properties, such as the weight-specific respiration rate, as function of the body weight of individuals. This paper focuses on the remarkable observation that theoretical explanations for these relationships also have strong similarities. Both can be understood as result of the covariation of the values of parameters of models of a particular type for the underlying processes, while this covariation follows logically from the model structure. The one-compartment model for the uptake and elimination of compounds by organisms is basic to the BioConcentration Factor (BCF), or the partition coefficient; the standard Dynamic Energy Budget model is basic to the (ultimate) body size. The BCF is the ratio of the uptake and the elimination rates; the maximum body length is the ratio of the assimilation (i.e. uptake of resources) and the maintenance (i.e. use of resources) rates. This paper discusses some shortcomings of descriptive approaches and conceptual aspects of theoretical explanations. The strength of the theory is in the combination of why metabolic transformation depends both on the BCF and the body size. We illustrate the application of the theory with several data sets from the literature.

Chemical mixture toxicity testing with Vibrio fischeri: combined effects of binary mixtures for ten soft electrophiles

The toxicity of 30 binary combinations of 10 soft electrophiles was examined in Microtox using dose-response curve (DRC) analysis. Chemicals from three groups of soft electrophiles-vinyl Michael acceptors (I--react with a thiol group), dicarbonyl reactive agents (II--react with a primary amine), and alpha-haloactivation compounds (III--react with a thiol group)--were selected for testing to evaluate the relationship between molecular site of chemical action and combined toxic effect. For each combination tested, each single agent was tested alone at six duplicated concentrations and three 1:1 mixtures of the agents were also tested, each at six duplicated concentrations. Exposure duration was 15 min for each single agent and mixture test. Sigmoid DRCs for each single chemical and mixture were constructed and the single chemical curves were used to develop a theoretical dose-addition DRC for the combination. Additivity quotient (AQ) values for slope and EC50 were calculated by dividing the actual mixture slope or EC50 for a given combination by the predicted slope or EC50, respectively, from the theoretical dose-addition DRC. Three criteria were selected for value in determining the combined effect obtained for each combination: (1) slope AQ 95% confidence interval (CI) overlap with 1.0 (1.0=dose addition), (2) EC50 AQ 95% CI overlap with 1.0, and (3) mean mixture data point 95% and 99% CI overlap with the theoretical dose-addition DRC. Each of three sham combinations showed combined effects consistent with dose addition for each criterion. Dose addition was expected for 15 nonsham combinations (nine within-group combinations and six group I:III combinations) and a nondose-additive effect was expected for 12 combinations (all I:II and II:III combinations). Actual combined effects obtained by incorporating all three criteria (noted above) showed only six instances of dose addition. Therefore, time-dependent toxicity (TDT) tests of each soft electrophile alone and for three nonpolar narcotic chemicals alone were conducted, using 15-, 30-, and 45-min exposure durations, to assess the time-dependent nature of the toxicity. Results of the TDT tests suggested that five had fully (or nearly fully) TDT (interpreted as an irreversible effect representing one molecular site of action), five of the soft electrophiles had partially TDT (i.e., representing two or more molecular sites of action for the agents, one irreversible and one reversible), and the three nonpolar narcotics had no TDT (i.e., a fully reversible toxic effect). With this TDT information, the combined effects for 25 of the 27 mixtures, although rather complex, could be explained. It is noteworthy that all combined effects obtained, whether concluded to be dose-additive or not, were close to dose-additive for hazard assessment purposes.

Developmental toxicity of combined ethylbenzene and methylethylketone administered by inhalation to rats

Pregnant Sprague-Dawley rats were exposed to ethylbenzene (EB; 0, 250, or 1000 ppm) and methylethylketone (MEK; 0, 1000, or 3000 ppm), alone and in combination, by inhalation, for 6h/day, during days 6-20 of gestation. Maternal toxicity, evidenced by decreased in body weight gain and food consumption, tended to be greater after simultaneous exposures to the high concentrations of 1000 ppm EB and 3000 ppm MEK, when compared to the treatments with individual compounds. No significant increase in embryo/fetal lethality or incidence of malformations and variations was observed in any of the treatment groups. Fetal body weight was significantly reduced after individual treatment with 1000 ppm EB or 3000 ppm MEK, and in the combined groups. There was no evidence of interaction between EB and MEK in causing developmental toxicity.