Arsenic is a worldwide environmental pollutant and a human carcinogen. It is well recognized that the toxicity of arsenicals largely depends on the oxidoreduction states (trivalent or pentavalent) and methylation levels (monomethyl, dimethyl, and trimethyl) that are present during the process of metabolism in mammals. However, presently, the specifics of the metabolic pathway of inorganic arsenicals have yet to be confirmed. In mammals, there are two possible mechanisms that have been proposed for the metabolic pathway of inorganic arsenicals, oxidative methylation, and glutathione conjugation. Oxidative methylation, which was originally proposed in fungi, is based on findings that arsenite (iAsIII) is sequentially converted to monomethylarsonic acid (MMAV) and dimethylarsinic acid (DMAV) in both humans and in laboratory animals such as mice and rats. However, recent in vitro observations have demonstrated that arsenic is only methylated in the presence of glutathione (GSH) or other thiol compounds, which strongly suggests that arsenic is methylated in trivalent forms. The glutathione conjugation mechanism is supported by findings that have shown that most intracellular arsenicals are trivalent and excreted from cells as GSH conjugates. Since non-conjugated trivalent arsenicals are highly reactive with thiol compounds and are easily converted to less toxic corresponding pentavalent arsenicals, the arsenic–glutathione conjugate stability may be the most important factor for determining the toxicity of arsenicals. In addition, “being a non-anionic form” also appears to be a determinant of the toxicity of oxo-arsenicals or thioarsenicals. The present review discusses both the metabolism of arsenic and the toxicity of arsenic metabolites.

Metabolism of arsenic and its toxicological relevance.

Background: Children must be recognized as a sensitive population based on having biological systems and organs in various stages of development. The processes of absorption, distribution, metabolism and elimination of environmental contaminants within a child’s body are considered less advanced than those of adults, making them more susceptible to disease outcomes following even small doses. Children’s unique activities of crawling and practicing increased hand-to-mouth ingestion also make them vulnerable to greater exposures by certain contaminants within specific environments. Approach: There is a need to review the field of children’s environmental exposures in order to understand trends and identify gaps in research, which may lead to better protection of this vulnerable and sensitive population. Therefore, explored here are previously published contemporary works in the broad area of children’s environmental exposures and potential impact on health from around the world. A discussion of children’s exposure to environmental contaminants is best organized under the last four steps of a risk assessment approach: hazard identification, dose-response assessment, exposure assessment (including children’s activity patterns) and risk characterization. We first consider the many exposure hazards that exist in the indoor and outdoor environments, and emerging contaminants of concern that may help guide the risk assessment process in identifying focus areas for children. A section on special diseases of concern is also included. Conclusions: The field of children’s exposures to environmental contaminants is broad. Although there are some well-studied areas offering much insight into children exposures, research is still needed to further our understanding of exposures to newer compounds, growing disease trends and the role of gene-environment interactions that modify adverse health outcomes. It is clear that behaviors of adults and children play a role in reducing or increasing a child’s exposure, where strategies to better communicate and implement risk modifying behaviors are needed, and can be more effective than implementing   changes in the physical environment.

https://www.mdpi.com/1660-4601/14/3/265/pdf

A Review of the Field on Children's Exposure to Environmental Contaminants: A Risk Assessment Approach.

Zearalenone (ZEA), a fungal mycotoxin, and its metabolite zeranol (ZAL) are known estrogen agonists in mammals, and are found as contaminants in food. Zeranol, which is more potent than ZEA and comparable in potency to estradiol, is also added as a growth additive in beef in the US and Canada. This article presents the development and application of a Physiologically-Based Toxicokinetic (PBTK) model for ZEA and ZAL and their primary metabolites, zearalenol, zearalanone, and their conjugated glucuronides, for rats and for human subjects. The PBTK modeling study explicitly simulates critical metabolic pathways in the gastrointestinal and hepatic systems. Metabolic events such as dehydrogenation and glucuronidation of the chemicals, which have direct effects on the accumulation and elimination of the toxic compounds, have been quantified. The PBTK model considers urinary and fecal excretion and biliary recirculation and compares the predicted biomarkers of blood, urinary and fecal concentrations with published in vivo measurements in rats and human subjects. Additionally, the toxicokinetic model has been coupled with a novel probabilistic dietary exposure model and applied to the Jersey Girl Study (JGS), which involved measurement of mycoestrogens as urinary biomarkers, in a cohort of young girls in New Jersey, USA. A probabilistic exposure characterization for the study population has been conducted and the predicted urinary concentrations have been compared to measurements considering inter-individual physiological and dietary variability. The in vivo measurements from the JGS fall within the high and low predicted distributions of biomarker values corresponding to dietary exposure estimates calculated by the probabilistic modeling system. The work described here is the first of its kind to present a comprehensive framework developing estimates of potential exposures to mycotoxins and linking them with biologically relevant doses and biomarker measurements, including a systematic characterization of uncertainties in exposure and dose estimation for a vulnerable population.

/pdf/physiologically-based-toxicokinetic-modeling-of-zearalenone-1x6yivcwit.pdf

Physiologically-Based Toxicokinetic Modeling of Zearalenone and Its Metabolites: Application to the Jersey Girl Study

Life Cycle Assessment (LCA) is a decision-making tool that accounts for multiple impacts across the life cycle of a product or service. This paper presents a conceptual framework to integrate human health impact assessment with risk screening approaches to extend LCA to include near-field chemical sources (e.g., those originating from consumer products and building materials) that have traditionally been excluded from LCA. A new generation of rapid human exposure modeling and high-throughput toxicity testing is transforming chemical risk prioritization and provides an opportunity for integration of screening-level risk assessment (RA) with LCA. The combined LCA and RA approach considers environmental impacts of products alongside risks to human health, which is consistent with regulatory frameworks addressing RA within a sustainability mindset. A case study is presented to juxtapose LCA and risk screening approaches for a chemical used in a consumer product. The case study demonstrates how these new risk ...

Conceptual Framework To Extend Life Cycle Assessment Using Near-Field Human Exposure Modeling and High-Throughput Tools for Chemicals

Arsenic is a major environmental toxin that is detoxified in the liver by biochemical mechanisms that are still under study. In the traditional metabolic pathway, arsenic undergoes two methylation reactions, each followed by a reduction, after which it is exported and released in the urine. Recent experiments show that glutathione plays an important role in arsenic detoxification and an alternative biochemical pathway has been proposed in which arsenic is first conjugated by glutathione after which the conjugates are methylated. In addition, in rats arsenic-glutathione conjugates can be exported into the plasma and removed by the liver in the bile. We have developed a mathematical model for arsenic biochemistry that includes three mechanisms by which glutathione affects arsenic methylation: glutathione increases the speed of the reduction steps; glutathione affects the activity of arsenic methyltranferase; glutathione sequesters inorganic arsenic and its methylated downstream products. The model is based as much as possible on the known biochemistry of arsenic methylation derived from cellular and experimental studies. We show that the model predicts and helps explain recent experimental data on the effects of glutathione on arsenic methylation. We explain why the experimental data imply that monomethyl arsonic acid inhibits the second methylation step. The model predicts time course data from recent experimental studies. We explain why increasing glutathione when it is low increases arsenic methylation and that at very high concentrations increasing glutathione decreases methylation. We explain why the possible temporal variation of the glutathione concentration affects the interpretation of experimental studies that last hours. The mathematical model aids in the interpretation of data from recent experimental studies and shows that the Challenger pathway of arsenic methylation, supplemented by the glutathione effects described above, is sufficient to understand and predict recent experimental data. More experimental studies are needed to explicate the detailed mechanisms of action of glutathione on arsenic methylation. Recent experimental work on the effects of glutathione on arsenic methylation and our modeling study suggest that supplements that increase hepatic glutathione production should be considered as strategies to reduce adverse health effects in affected populations.

/pdf/mathematical-modeling-of-the-effects-of-glutathione-on-k0ixe3dlej.pdf

Mathematical modeling of the effects of glutathione on arsenic methylation

Arsenic is an environmental pollutant, potent human toxicant, and oxidative stress agent with a multiplicity of health effects associated with both acute and chronic exposures. A semi-mechanistic cellular-level toxicokinetic (TK) model was developed in order to describe the uptake, biotransformation and clearance of arsenical species in human hepatocytes. Notable features of this model are the incorporation of arsenic-glutathione complex formation and a "switch-like" formulation to describe the antioxidant response of hepatocytes to arsenic exposure. The cellular-level TK model applies mass action kinetics in order to predict the concentrations of trivalent and pentavalent arsenicals in hepatocytes. The model simulates uptake of arsenite (iAsIII) via aquaporin isozymes 9 (AQP9s), glutathione (GSH) conjugation, methylation by arsenic methyltransferase (AS3MT), efflux through multidrug resistant proteins (MRPs) and the induced antioxidant response via thioredoxin reductase (TR) activity. The model was parameterized by optimization of model estimates for arsenite (iAsIII), monomethylated (MMA) and dimethylated (DMA) arsenicals concentrations with time-course experimental data in human hepatocytes for a time span of 48 hours, and dose-response data at 24 hours for a range of arsenite concentrations from 0.1 to 10 μM. Global sensitivity analysis of the model showed that at low doses the transport parameters had a dominant role, whereas at higher doses the biotransformation parameters were the most significant. A parametric comparison of the TK model with an analogous model developed for rat hepatocytes from the literature demonstrated that the biotransformation of arsenite (e.g. GSH conjugation) has a large role in explaining the variation in methylation between rats and humans. The cellular-level TK model captures the temporal modes of arsenical accumulation in human hepatocytes. It highlighted the key biological processes that influence arsenic metabolism by explicitly modelling the metabolic network of GSH-adducts formation. The parametric comparison with the TK model developed for rats suggests that the variability in GSH conjugation could have an important role in inter-species variability of arsenical methylation. The TK model can be incorporated into larger-scale physiologically based toxicokinetic (PBTK) models of arsenic for improving the estimates of PBTK model parameters.

/pdf/mathematical-model-of-uptake-and-metabolism-of-arsenic-iii-2vxdvbpquf.pdf

Mathematical model of uptake and metabolism of arsenic(III) in human hepatocytes - Incorporation of cellular antioxidant response and threshold-dependent behavior.

Exposure indices for the National Children’s Study: application to inhalation exposures in Queens County, NY

Exposure indices for the National Children's Study: application to inhalation exposures in Queens County, NY.

A challenge for large-scale environmental health investigations such as the National Children's Study (NCS), is characterizing exposures to multiple, co-occurring chemical agents with varying spatiotemporal concentrations and consequences modulated by biochemical, physiological, behavioral, socioeconomic, and environmental factors. Such investigations can benefit from systematic retrieval, analysis, and integration of diverse extant information on both contaminant patterns and exposure-relevant factors. This requires development, evaluation, and deployment of informatics methods that support flexible access and analysis of multiattribute data across multiple spatiotemporal scales. A new "Tiered Exposure Ranking" (TiER) framework, developed to support various aspects of risk-relevant exposure characterization, is described here, with examples demonstrating its application to the NCS. TiER utilizes advances in informatics computational methods, extant database content and availability, and integrative environmental/exposure/biological modeling to support both "discovery-driven" and "hypothesis-driven" analyses. "Tier 1" applications focus on "exposomic" pattern recognition for extracting information from multidimensional data sets, whereas second and higher tier applications utilize mechanistic models to develop risk-relevant exposure metrics for populations and individuals. In this article, "tier 1" applications of TiER explore identification of potentially causative associations among risk factors, for prioritizing further studies, by considering publicly available demographic/socioeconomic, behavioral, and environmental data in relation to two health endpoints (preterm birth and low birth weight). A "tier 2" application develops estimates of pollutant mixture inhalation exposure indices for NCS counties, formulated to support risk characterization for these endpoints. Applications of TiER demonstrate the feasibility of developing risk-relevant exposure characterizations for pollutants using extant environmental and demographic/socioeconomic data.

A Tiered Framework for Risk-Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children’s Study (NCS)

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Mathematical model of uptake and metabolism of arsenic(III) in human hepatocytes - Incorporation of cellular antioxidant response and threshold-dependent behavior.

Exposure indices for the National Children's Study: application to inhalation exposures in Queens County, NY.

A Tiered Framework for Risk-Relevant Characterization and Ranking of Chemical Exposures: Applications to the National Children’s Study (NCS)