A Physiologically Based Pharmacokinetic (PBPK) Modeling Framework for Mixtures of Dioxin-like Compounds

Advancing exposure science through artificial intelligence: Neural ordinary differential equations for predicting blood concentrations of volatile organic compounds

Volatile organic compounds (VOCs) are a significant concern for human health and environmental safety, requiring accurate models to predict their concentrations in body fluids for effective risk assessments. This study evaluates the application of neural ordinary differential equations (Neural ODEs), a novel artificial intelligence (AI)-based framework, in predicting blood concentrations of two representative VOCs: dibromomethane (DBM) and methylchloroform (MCF). Using data across multiple concentrations, Neural ODEs demonstrated robust predictive performance, achieving lower mean absolute percentage errors (MAPEs) than conventional Physiologically Based Pharmacokinetic (PBPK) models in most scenarios. For DBM, Neural ODEs achieved a MAPE of 6.56 % at 10,000 ppm, outperforming PBPK in low-to-moderate exposure levels. Neural ODEs yielded a MAPE of 25.55 % for MCF at 10,000 ppm, though accuracy declined at lower concentrations, such as 10 ppm. The findings emphasize the adaptability of Neural ODEs for diverse cases while discussing potential advancements such as integrating real-time monitoring tools and hybrid modeling approaches. This study underscores the value of Neural ODEs as a versatile tool for toxicological forecasting, environmental monitoring, and regulatory decision-making.

Dioxins and their impact: a review of toxicity, persistence, and novel remediation strategies

Dioxins rank among the most hazardous persistent organic pollutants, presenting a serious threat due to their long environmental lifespan and capacity for bioaccumulation. This comprehensive review delves into the historical, chemical, and toxicological aspects of dioxins, spotlighting significant incidents such as the Seveso disaster and the repercussions of Agent Orange. The review offers a thorough analysis of the sources of dioxin formation, encompassing natural occurrences like volcanic eruptions and wildfires, alongside man-made activities such as industrial combustion and waste incineration. It examines regional variations in dioxin contamination, revealing air concentrations that can range from less than 0.01 pg TEQ per m3 in remote regions to as high as 2 pg TEQ per m3 in urban environments. With global dioxin emissions estimated at around 97.0 kg TEQ per year, Asia and Africa emerge as the highest emitters among the continents, with the total global dioxin release approximately at 100.4 kg TEQ annually. Dioxin emissions per capita show stark contrasts across six continents, from 10.77 g TEQ per capita in Europe to a concerning 71.66 g TEQ per capita in Oceania. Furthermore, the concentration of dioxin compounds produced during combustion varies significantly, ranging from 15 to 555 ng m-2. While dioxin emission regulations are intricate and differ globally, most nations require that concentrations remain below one ng m-2. Globally, dioxin production is estimated at 17 226 kilograms annually, equating to about 287 kilograms in toxic equivalent (TEQ). This review critically examines the severe health implications of dioxins, which include carcinogenic effects, endocrine disruption, and immunotoxicity. Innovative remediation strategies, such as using nanomaterials for adsorption and advanced oxidation processes, are identified as promising pathways to tackle this pressing issue. Ultimately, this review underscores the necessity for enhanced monitoring systems and comprehensive policy frameworks to facilitate sustainable dioxin management and regulatory compliance. Taking decisive action is vital to protect public health and the environment from the ongoing threat posed by dioxins.

Studying interaction effects on toxicokinetics in zebrafish combining experimental and modelling approaches

Humans and wildlife are exposed to a complex mixture of anthropogenic chemicals of which only a few have been subjected to regulations. Chemical risk assessment is currently based on evaluating single chemicals, which is costly, time-consuming, and neglect toxicokinetic and toxicodynamic mixture effects. This study focused on interaction effects on the absorption, distribution, metabolism and excretion (ADME) processes of selected chemicals representing potential modulators of these processes. Adult female zebrafish (Danio rerio) were exposed to selected mixture of 11 chemicals and bioconcentration factors (BCFs) on tissue level were determined for 9 of them: bisphenol A (BPA), bisphenol AF (BPAF), bisphenol Z (BPZ), triclosan, tribromophenol, pentachlorophenol, heptafluorobutyric acid (PFBA), perfluorobutanesulfonic acid (PFBS), and perfluorooctanesulfonic acid (PFOS). Comparison of BCFs of bisphenols obtained from single chemical exposure experiments versus the current study revealed no statistically significant differences (p > 0.05), implying no mixture effects on kinetics of bisphenols at investigated concentrations. The same conclusion was reached using two physiologically based kinetic (PBK) models, developed for individual bisphenols and per- and polyfluoroalkyl substances (PFAS), showing good model fit for BPA, BPZ, BPAF, and PFOS. To simulate exposure scenarios where kinetic interaction effects may occur through competitive protein binding in blood, a new PBK model was developed. Simulations where zebrafish were dosed with BPA and BPZ, individually, and combined with varying levels of PFOS, showed that competitive binding to serum proteins alter tissue levels of bisphenols when levels of PFOS exceeded 1 μg/L. This indicates that chemicals acting in concert could perturb ADME but only at higher levels or in complex mixtures.

The Role of Simulation Science in Public Health at the Agency for Toxic Substances and Disease Registry: An Overview and Analysis of the Last Decade

Environmental exposures are ubiquitous and play a significant, and sometimes understated, role in public health as they can lead to the development of various chronic and infectious diseases. In an ideal world, there would be sufficient experimental data to determine the health effects of exposure to priority environmental contaminants. However, this is not the case, as emerging chemicals are continuously added to this list, furthering the data gaps. Recently, simulation science has evolved and can provide appropriate solutions using a multitude of computational methods and tools. In its quest to protect communities across the country from environmental health threats, ATSDR employs a variety of simulation science tools such as Physiologically Based Pharmacokinetic (PBPK) modeling, Quantitative Structure-Activity Relationship (QSAR) modeling, and benchmark dose (BMD) modeling, among others. ATSDR's use of such tools has enabled the agency to evaluate exposures in a timely, efficient, and effective manner. ATSDR's work in simulation science has also had a notable impact beyond the agency, as evidenced by external researchers' widespread appraisal and adaptation of the agency's methodology. ATSDR continues to advance simulation science tools and their applications by collaborating with researchers within and outside the agency, including other federal/state agencies, NGOs, the private sector, and academia.

Studying mixture effects on uptake and tissue distribution of PFAS in zebrafish (Danio rerio) using physiologically based kinetic (PBK) modelling

Per- and polyfluoroalkyl substances (PFAS) are ubiquitously distributed in the aquatic environment. They include persistent, mobile, bioaccumulative, and toxic chemicals and it is therefore critical to increase our understanding on their adsorption, distribution, metabolism, excretion (ADME). The current study focused on uptake of seven emerging PFAS in zebrafish (Danio rerio) and their potential maternal transfer. In addition, we aimed at increasing our understanding on mixture effects on ADME by developing a physiologically based kinetic (PBK) model capable of handling co-exposure scenarios of any number of chemicals. All studied chemicals were taken up in the fish to varying degrees, whereas only perfluorononanoate (PFNA) and perfluorooctanoate (PFOA) were quantified in all analysed tissues. Perfluorooctane sulfonamide (FOSA) was measured at concerningly high concentrations in the brain (Cmax over 15 μg/g) but also in the liver and ovaries. All studied PFAS were maternally transferred to the eggs, with FOSA and 6:2 perfluorooctane sulfonate (6,2 FTSA) showing significant (p < 0.02) signs of elimination from the embryos during the first 6 days of development, while perfluorobutane sulfonate (PFBS), PFNA, and perfluorohexane sulfonate (PFHxS) were not eliminated in embryos during this time-frame. The mixture PBK model resulted in >85 % of predictions within a 10-fold error and 60 % of predictions within a 3-fold error. At studied levels of PFAS exposure, competitive binding was not a critical factor for PFAS kinetics. Gill surface pH influenced uptake for some carboxylates but not the sulfonates. The developed PBK model provides an important tool in understanding kinetics under complex mixture scenarios and this use of New Approach Methodologies (NAMs) is critical in future risk assessment of chemicals and early warning systems.

Hepatic cholesterol biosynthesis and dioxin-induced dysregulation: A multiscale computational approach

Humans are constantly exposed to lipophilic persistent organic pollutants (POPs) that accumulate in fatty foods. Among the numerous POPs, dioxins, in particular 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), can impact several organ systems. While the hazard is clearly recognized, it is still difficult to develop a comprehensive understanding of the overall health impacts of dioxins. As chemical toxicity testing is steadily adopting new approach methodologies (NAMs), it becomes imperative to develop computational models that can bridge the data gaps between in vitro testing and in vivo outcomes. As an effort to address this challenge, we propose a multiscale computational approach using a "template-and-anchor" (T&A) structure. A template is a high-level umbrella model that permits the integration of information from various, detailed anchor models. In the present study, we use this T&A approach to describe the effect of TCDD on cholesterol dynamics. Specifically, we represent hepatic cholesterol biosynthesis as an anchor model that is perturbed by TCDD, leading to steatosis, along with alterations of plasma cholesterol. In the future, incorporating pertinent information from all anchor models into the template model will allow the characterization of the global effects of dioxin, which can subsequently be translated into overall - and ultimately personalized - human health risk assessment.

Endocrine Disruptor Compounds in Environment: Focus on Women’s Reproductive Health and Endometriosis

Endometriosis is an estrogen-dependent gynecologic illness that has long-term effects on a woman’s fertility, physical health, and overall quality of life. Growing evidence suggests that endocrine-disrupting chemicals (EDCs) may be etiologically involved in the development and severity of the disease. We consider the available human evidence on EDCs and endometriosis, limiting ourselves to studies that have individually assessed chemical amounts in women. Dioxins, BPA, Phthalates, and other endocrine disruptors, like DDT, are among the evidence indicating an environmental etiology for endometriosis. Collectively, this review describes how environmental toxins are linked to lower fertility in women, as well as a number of reproductive diseases, focusing on the pathology of endometriosis and its treatments. Importantly, this review can be used to investigate techniques for preventing the negative effects of EDC exposure.

Consequences of reprogramming acetyl-CoA metabolism by 2,3,7,8-tetrachlorodibenzo-p-dioxin in the mouse liver

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) is a persistent environmental contaminant that induces the progression of steatosis to steatohepatitis with fibrosis in mice. Furthermore, TCDD reprograms hepatic metabolism by redirecting glycolytic intermediates while inhibiting lipid metabolism. Here, we examined the effect of TCDD on hepatic acetyl-coenzyme A (acetyl-CoA) and β-hydroxybutyrate levels as well as protein acetylation and β-hydroxybutyrylation. Acetyl-CoA is not only a central metabolite in multiple anabolic and catabolic pathways, but also a substrate used for posttranslational modification of proteins and a surrogate indicator of cellular energy status. Targeted metabolomic analysis revealed a dose-dependent decrease in hepatic acetyl-CoA levels coincident with the phosphorylation of pyruvate dehydrogenase (E1), and the induction of pyruvate dehydrogenase kinase 4 and pyruvate dehydrogenase phosphatase, while repressing ATP citrate lyase and short-chain acyl-CoA synthetase gene expression. In addition, TCDD dose-dependently reduced the levels of hepatic β-hydroxybutyrate and repressed ketone body biosynthesis gene expression. Moreover, levels of total hepatic protein acetylation and β-hydroxybutyrylation were reduced. AMPK phosphorylation was induced consistent with acetyl-CoA serving as a cellular energy status surrogate, yet subsequent targets associated with re-establishing energy homeostasis were not activated. Collectively, TCDD reduced hepatic acetyl-CoA and β-hydroxybutyrate levels eliciting starvation-like conditions despite normal levels of food intake.