Unseen Risk: Mapping Contamination Hazards to Enhance Risk Perception in Galena Park, Texas.

As extreme weather events have become more frequently observed in recent decades, concerns about exposure to potential flood risk have increased, especially in underserved and socially vulnerable communities. Galena Park, Texas, is a socially vulnerable community that also confronts escalated physical vulnerabilities due to existing flood risks from Buffalo Bayou and the Houston Ship Channel as well as proximity to industrial facilities that emit chemical pollution. To better understand the underlying risks that Galena Park is facing, this research assesses and visualizes the existing contamination hazards associated with the chemical facilities within Galena Park. Through this process, we (1) compute the environmental, health, and physical hazards associated with industrial facilities, (2) spatially geocode the points of contamination sources and flood exposure, and (3) increase awareness of existing risk by visualizing and distributing related information using an ArcGIS Dashboard. The results indicate that there are 169 points of location from 127 industrial facilities, and 24 points were inducing potential chemicals. In total, 126 chemicals have potential physical, health, and environmental hazards. On average, each facility has 2.4 chemicals that could cause potential hazards with a range of zero to 57 chemicals. When examining the specific physical, health, and environmental risks associated with the chemicals, on average each facility has 14.6 types of risks associated with it. This includes, on average, 9.8 types of health hazards, 1.53 physical hazards, and 2.3 environmental hazards per facility. When analyzing the spatial relationship between the chemical exposure and the current flood risk using the Dashboard, it is noticeable that most of the industrial facilities are located in the south of Galena Park, near Buffalo Bayou, where a variety of industrial facilities are clustered. Through this study, we spatially mapped the existing risks in Galena Park that are not readily available to the community and risks that are not currently tangible or visible. The utility of ArcGIS Dashboards affords the opportunity to translate massive databases into digestible knowledge that can be shared and utilized within the community. This study also takes another step toward building community resilience by providing knowledge that can be used to prepare for and respond to disasters. Visualizing unseen risks and promoting awareness can enhance risk perception when supported by scientific knowledge. Further investigation is necessary to enhance preparedness behaviors, identify proper evacuation techniques and routes, and build community networks to comprehensively promote resilience to multi-hazard circumstances.

Quantitative Characterization of Population-Wide Tissue- and Metabolite-Specific Variability in Perchloroethylene Toxicokinetics in Male Mice.

Quantification of interindividual variability is a continuing challenge in risk assessment, particularly for compounds with complex metabolism and multi-organ toxicity. Toxicokinetic variability for perchloroethylene (perc) was previously characterized across 3 mouse strains and in 1 mouse strain with various degrees of liver steatosis. To further characterize the role of genetic variability in toxicokinetics of perc, we applied Bayesian population physiologically based pharmacokinetic (PBPK) modeling to the data on perc and metabolites in blood/plasma and tissues of male mice from 45 inbred strains from the Collaborative Cross (CC) mouse population. After identifying the most influential PBPK parameters based on global sensitivity analysis, we fit the model with a hierarchical Bayesian population analysis using Markov chain Monte Carlo simulation. We found that the data from 3 commonly used strains were not representative of the full range of variability in perc and metabolite blood/plasma and tissue concentrations across the CC population. Using interstrain variability as a surrogate for human interindividual variability, we calculated dose-dependent, chemical-, and tissue-specific toxicokinetic variability factors (TKVFs) as candidate science-based replacements for the default uncertainty factor for human toxicokinetic variability of 100.5. We found that toxicokinetic variability factors for glutathione conjugation metabolites of perc showed the greatest variability, often exceeding the default, whereas those for oxidative metabolites and perc itself were generally less than the default. Overall, we demonstrate how a combination of a population-based mouse model such as the CC with Bayesian population PBPK modeling can reduce uncertainty in human toxicokinetic variability and increase accuracy and precision in quantitative risk assessment.

PBPK modeling of impact of nonalcoholic fatty liver disease on toxicokinetics of perchloroethylene in mice.

BACKGROUND: Nonalcoholic fatty liver disease (NAFLD), a major cause of chronic liver disease in the Western countries with increasing prevalence worldwide, may substantially affect chemical toxicokinetics and thereby modulate chemical toxicity. OBJECTIVES: This study aims to use physiologically-based pharmacokinetic (PBPK) modeling to characterize the impact of NAFLD on toxicokinetics of perchloroethylene (perc). METHODS: Quantitative measures of physiological and biochemical changes associated with the presence of NAFLD induced by high-fat or methionine/choline-deficient diets in C57B1/6 J mice are incorporated into a previously developed PBPK model for perc and its oxidative and conjugative metabolites. Impacts on liver fat and volume, as well as blood:air and liver:air partition coefficients, are incorporated into the model. Hierarchical Bayesian population analysis using Markov chain Monte Carlo simulation is conducted to characterize uncertainty, as well as disease-induced variability in toxicokinetics. RESULTS: NAFLD has a major effect on toxicokinetics of perc, with greater oxidative and lower conjugative metabolism as compared to healthy mice. The NAFLD-updated PBPK model accurately predicts in vivo metabolism of perc through oxidative and conjugative pathways in all tissues across disease states and strains, but underestimated parent compound concentrations in blood and liver of NAFLD mice. CONCLUSIONS: We demonstrate the application of PBPK modeling to predict the effects of pre-existing disease conditions as a variability factor in perc metabolism. These results suggest that non-genetic factors such as diet and pre-existing disease can be as influential as genetic factors in altering toxicokinetics of perc, and thus are likely contribute substantially to population variation in its adverse effects.

Predicting tubular reabsorption with a human kidney proximal tubule tissue-on-a-chip and physiologically-based modeling.

Kidney is a major route of xenobiotic excretion, but the accuracy of preclinical data for predicting in vivo clearance is limited by species differences and non-physiologic 2D culture conditions. Microphysiological systems can potentially increase predictive accuracy due to their more realistic 3D environment and incorporation of dynamic flow. We used a renal proximal tubule microphysiological device to predict renal reabsorption of five compounds: creatinine (negative control), perfluorooctanoic acid (positive control), cisplatin, gentamicin, and cadmium. We perfused compound-containing media to determine renal uptake/reabsorption, adjusted for non-specific binding. A physiologically-based parallel tube model was used to model reabsorption kinetics and make predictions of overall in vivo renal clearance. For all compounds tested, the kidney tubule chip combined with physiologically-based modeling reproduces qualitatively and quantitatively in vivo tubular reabsorption and clearance. However, because the in vitro device lacks filtration and tubular secretion components, additional information on protein binding and the importance of secretory transport is needed in order to make accurate predictions. These and other limitations, such as the presence of non-physiological compounds such as antibiotics and bovine serum albumin in media and the need to better characterize degree of expression of important transporters, highlight some of the challenges with using microphysiological devices to predict in vivo pharmacokinetics.

Montmorillonites Can Tightly Bind Glyphosate and Paraquat Reducing Toxin Exposures and Toxicity.

Among the numerous contaminants of soil, glyphosate and paraquat are two of the most widely used herbicides that are commonly detected in the environment. Soil and sediment contaminated with glyphosate, paraquat, and other environmental toxins can be mobilized and redistributed to lawns, vegetable gardens, parks, and water supplies in vulnerable communities at the site of disasters such as hurricanes and flooding. Glyphosate and paraquat bind strongly to soils containing clays, making their bioavailability (bioaccessibility) from these types of soil very low. Because of their affinity for clay-based soils, it is possible that montmorillonite clays could be administered as a therapeutic agent in the diet of animals and humans to decrease short-term exposure and toxicity. In this study, we investigated the sorption mechanisms of glyphosate and paraquat onto active surfaces of calcium montmorillonite (CM) and sodium montmorillonite (SM) clays and derived binding parameters, including capacity, affinity, and enthalpy. Additionally, we used these parameters to predict the reduction in bioavailability under different pH and temperature conditions and to estimate the theoretical dose of clay that could protect against severe paraquat toxicity and lethality. Computational modeling and simulation studies depicted toxin sorption mechanisms at different pH values. Additionally, a toxin-sensitive living organism (Hydra vulgaris) was used to confirm the safety of the clay and its ability to protect against toxicity from glyphosate and paraquat. The high efficacy of CM and SM shown in this study supports the natural binding activity of glyphosate and paraquat to clay-based soils. Following disasters and medical emergencies, montmorillonite clays could be administered by capsules and tablets, or added to food and flavored water, to reduce toxin bioavailability and human and animal exposures.

Differential toxicity of water versus gavage exposure to trichloroethylene in rats.

Trichloroethylene (TCE) is a persistent environmental contaminant that causes male reproductive toxicity. We investigated whether transient increases in TCE exposure modulated male reproductive toxicity by exposing rats via daily oral to repeated gavage exposures (1000 mg/kg/day) and through drinking water (0.6% TCE) for 14 weeks. The gavage route resulted in reversible reduction of epididymis weight, and reduced body weight that persisted for up to 12-weeks after cessation of exposure. Physiologically-based pharmacokinetic modeling predicted that the gavage route results in higher Cmax and AUC exposure of TCE compared to drinking water exposure, explaining the observed differences in toxicity between dosing regimens.

Thorough QT/QTc in a Dish: An In Vitro Human Model That Accurately Predicts Clinical Concentration-QTc Relationships.

"Thorough QT/corrected QT (QTc)" (TQT) studies are cornerstones of clinical cardiovascular safety assessment. However, TQT studies are resource intensive, and preclinical models predictive of the threshold of regulatory concern are lacking. We hypothesized that an in vitro model using induced pluripotent stem cell (iPSC)-derived cardiomyocytes from a diverse sample of human subjects can serve as a "TQT study in a dish." For 10 positive and 3 negative control drugs, in vitro concentration-QTc, computed using a population Bayesian model, accurately predicted known in vivo concentration-QTc. Moreover, predictions of the percent confidence that the regulatory threshold of 10 ms QTc prolongation would be breached were also consistent with in vivo evidence. This "TQT study in a dish," consisting of a population-based iPSC-derived cardiomyocyte model and Bayesian concentration-QTc modeling, has several advantages over existing in vitro platforms, including higher throughput, lower cost, and the ability to accurately predict the in vivo concentration range below the threshold of regulatory concern.

Beyond the RfD: Broad Application of a Probabilistic Approach to Improve Chemical Dose-Response Assessments for Noncancer Effects.

BACKGROUND: The National Academies recommended risk assessments redefine the traditional noncancer Reference Dose (RfD) as a probabilistically derived risk-specific dose, a framework for which was recently developed by the World Health Organization (WHO). OBJECTIVES: Our aim was to assess the feasibility and implications of replacing traditional RfDs with probabilistic estimates of the human dose associated with an effect magnitude M and population incidence I (HDMI). METHODS: We created a comprehensive, curated database of RfDs derived from animal data and developed a standardized, automated, web-accessible probabilistic dose-response workflow implementing the WHO framework. RESULTS: We identified 1,464 RfDs and associated endpoints, representing 608 chemicals across many types of effects. Applying our standardized workflow resulted in 1,522 HDMI values. Traditional RfDs are generally within an order of magnitude of the HDMI lower confidence bound for I=1% and M values commonly used for benchmark doses. The greatest contributor to uncertainty was lack of benchmark dose estimates, followed by uncertainty in the extent of human variability. Exposure at the traditional RfD frequently implies an upper 95% confidence bound of several percent of the population affected. Whether such incidences are considered acceptable is likely to vary by chemical and risk context, especially given the wide range of severity of the associated effects, from clinical chemistry to mortality. CONCLUSIONS: Overall, replacing RfDs with HDMI estimates can provide a more consistent, scientifically rigorous, and transparent basis for risk management decisions, as well as support additional decision contexts such as economic benefit-cost analysis, risk-risk tradeoffs, life-cycle impact analysis, and emergency response. https://doi.org/10.1289/EHP3368.

A human population-based organotypic in vitro model for cardiotoxicity screening.

Assessing inter-individual variability in responses to xenobiotics remains a substantial challenge, both in drug development with respect to pharmaceuticals and in public health with respect to environmental chemicals. Although approaches exist to characterize pharmacokinetic variability, there are no methods to routinely address pharmacodynamic variability. In this study, we aimed to demonstrate the feasibility of characterizing inter-individual variability in a human in vitro model. Specifically, we hypothesized that genetic variability across a population of iPSC-derived cardiomyocytes translates into reproducible variability in both baseline phenotypes and drug responses. We measured baseline and drug-related effects in iPSC-derived cardiomyocytes from 27 healthy donors on kinetic Ca2+ flux and high-content live cell imaging. Cells were treated in concentration-response with cardiotoxic drugs: isoproterenol (ß-adrenergic receptor agonist/positive inotrope), propranolol (ß-adrenergic receptor antagonist/negative inotrope), and cisapride (hERG channel inhibitor/QT prolongation). Cells from four of the 27 donors were further evaluated in terms of baseline and treatment-related gene expression. Reproducibility of phenotypic responses was evaluated across batches and time. iPSC-derived cardiomyocytes exhibited reproducible donor-specific differences in baseline function and drug-induced effects. We demonstrate the feasibility of using a panel of population-based organotypic cells from healthy donors as an animal replacement experimental model. This model can be used to rapidly screen drugs and chemicals for inter-individual variability in cardiotoxicity. This approach demonstrates the feasibility of quantifying inter-individual variability in xenobiotic responses, and can be expanded to other cell types for which in vitro populations can be derived from iPSCs.

Incorporation of the glutathione conjugation pathway in an updated physiologically-based pharmacokinetic model for perchloroethylene in mice.

BACKGROUND: Perchloroethylene (perc) induced target organ toxicity has been associated with tissue-specific metabolic pathways. Previous physiologically-based pharmacokinetic (PBPK) modeling of perc accurately predicted oxidative metabolites but suggested the need to better characterize glutathione (GSH) conjugation as well as toxicokinetic uncertainty and variability. OBJECTIVES: We updated the previously published "harmonized" perc PBPK model in mice to better characterize GSH conjugation metabolism as well as the uncertainty and variability of perc toxicokinetics. METHODS: The updated PBPK model includes expanded models for perc and its oxidative metabolite trichloroacetic acid (TCA), and physiologically-based sub-models for conjugative metabolites. Previously compiled mouse kinetic data in B6C3F1 and Swiss-Webster mice were augmented to include data from a recent study in male C57BL/6J mice that measured perc and metabolites in serum and multiple tissues. Hierarchical Bayesian population analysis using Markov chain Monte Carlo was conducted to characterize uncertainty and inter-strain variability in perc metabolism. RESULTS: The updated model fit the data as well or better than the previously published "harmonized" PBPK model. Tissue dosimetry for both oxidative and conjugative metabolites was successfully predicted across the three strains of mice, with estimated residuals errors of 2-fold for majority of data. Inter-strain variability across three strains was evident for oxidative metabolism; GSH conjugation data were only available for one strain. CONCLUSIONS: This updated PBPK model fills a critical data gap in quantitative risk assessment by predicting the internal dosimetry of perc and its oxidative and GSH conjugation metabolites and lays the groundwork for future studies to better characterize toxicokinetic variability.

A study of the quality and hygienic conditions of spring water in Mongolia.

UNLABELLED: An assessment on quality and hygienic conditions of spring water was undertaken in Mongolia in 2004 with financial and technical support from the World Health Organization through AGFUND. METHODOLOGY: A total of 127 springs, 99 from rural areas and 28 from Ulaanbaatar city were included in the study. The study included hygienic conditions, physical, microbiological and chemical parameters of springs. Based on the results of laboratory analysis, the quality of springs were classified into five degrees of contamination. RESULTS: The majority of springs studied and especially in UB city and the Central region had poor hygienic conditions such as low flow rate, turbidity or pollution sources in the vicinity of springs. 78% of the total studied springs did not have any protection or upgrade and 22% have only wooden, iron and stone fences. The water quality parameters such as hardness, total dissolved solids, oxygen demand, nitrogenous compounds, total microbial count, Escherichia coli were also significantly higher in springs located in UB city, the Central region and the East region. 47.6% of all studied aimag's (countryside) spring water were significantly polluted by more than three parameters especially E. coli, ammonia, oxygen demand, which indicated a recent contamination by human and animal excreta in water. CONCLUSION: The current study revealed that the majority of springs in peri urban areas close to UB city and the Central region had poor hygienic conditions. Different levels of contamination using both microbiological and chemical tests were found in studied springs. It is recommended that regular assessment of spring water quality be undertaken to create awareness among communities and local authorities for further protection and upgrading of spring water sources.