In vitro and in silico modeling of perfluoroalkyl substances mixture toxicity in an amphibian fibroblast cell line

Advancing toxicity studies of per- and poly-fluoroalkyl substances (pfass) through machine learning: Models, mechanisms, and future directions

Perfluorinated and perfluoroalkyl substances (PFASs), encompassing a vast array of isomeric chemicals, are recognized as typical emerging contaminants with direct or potential impacts on human health and the ecological environment. With the complex and elusive toxicological profiles of PFASs, machine learning (ML) has been increasingly employed in their toxicity studies due to its proficiency in prediction and data analytics. This integration is poised to become a predominant trend in environmental toxicology, propelled by the swift advancements in computational technology. This review diligently examines the literature to encapsulate the varied objectives of employing ML in the toxicity studies of PFASs: (1) Utilizing ML to establish Quantitative Structure-Activity Relationship (QSAR) models for PFASs with diverse toxicity endpoints, facilitating the targeted toxicity prediction of unidentified PFASs; (2) Investigating and substantiating the Adverse Outcome Pathway (AOP) through the synergy of ML and traditional toxicological methods, with this refining the toxicity assessment framework for PFASs; (3) Dissecting and elucidating the features of established ML models to advance Open Research into the toxicity of PFASs, with a primary focus on determinants and mechanisms. The discourse extends to an in-depth examination of ML studies, segregating findings based on their distinct application trajectories. Given that ML represents a nascent paradigm within PFASs research, this review delineates the collective challenges encountered in the ML-mediated study of PFAS toxicity and proffers strategic guidance for ensuing investigations.

Mixtures of legacy and replacement perfluorosulphonic acids (PFSAs) demonstrate ratio-, concentration- and endpoint-dependent synergistic interactions in vitro

The extensive use of poly- and per-fluoroalkyl substances (PFASs) has les to their widespread presence in the environment, raising concerns about potential toxicity. While certain PFASs of concern have been phased-out or banned, new PFASs continue to be produced. Two such substances are perfluoroethylcyclohexane sulphonate (PFECHS) and perfluorobutane sulphamide (FBSA), replacements of perfluoroctanesulphonic acid (PFOS) that have recently been detected in multiple environmental media around the globe. Despite PFASs generally occurring in the environment as mixtures, few data are available outlining the effects of PFAS mixtures. Therefore, this research investigated the interaction potential of binary and ternary mixtures of emerging and legacy PFASs. The immortalized rainbow trout gill cell line (RTgill-W1) was chosen as the experimental model to investigate two apical endpoints: cytotoxicity and phospholipidosis. RTgill-W1 cells were exposed for 24 h to each compound to obtain endpoint-specific effect concentrations (LCx; ECx). These values were then applied to formulate mixture predictions following the Loewes Additivity and Steel and Peckham methods. Based on cytotoxicity, relative potencies of individual compounds were: PFOS > PFECHS > FSBA. PFOS and PFECHS had nearly identical effects on phospholipidosis, while FSBA did not have any effects. Most mixtures had a synergistic effect on cytotoxicity, but the effect was both dose- and ratio-dependent. PFOS and PFECHS were additive at lower concentrations (LC10) and synergistic at higher concentrations (LC50; 3:1, 1:1, and 1:3). PFECHS and FSBA mixtures were synergistic at all doses and ratios (3:1, 1:1, 1:3), while FBSA and PFOS were mainly synergistic at higher concentrations and at ratios favouring PFOS (1:1, 1:3). Tertiary combinations were mainly synergistic. For phospholipidosis, mixtures were strictly additive. These results are strongly suggestive of synergism between emerging PFAS replacements and highlight that independent apical mechanisms of different PFASs could combine to induce unexpected toxicity. Considering that emerging replacements are continuing to increase in concentration in the environment, such mixture scenarios are also likely to continue to increase in probability.

Comparative toxicity assessment of alternative versus legacy PFAS: Implications for two primary trophic levels in freshwater ecosystems

Perfluoroalkyl substances (PFAS) are common environmental pollutants, but their toxicity framework remains elusive. This research focused on ten PFAS, evaluating their impacts on two ecotoxicologically relevant model organisms from distinct trophic levels: the crustacean Daphnia magna and the unicellular green alga Raphidocelis subcapitata. The results showed a greater sensitivity of R. subcapitata compared to D. magna. However, a 10-day follow-up to the 48 h immobilisation test in D. magna showed delayed mortality, underlining the limitations of relying on EC50 s from standard acute toxicity tests. Among the compounds scrutinized, Perfluorodecanoic acid (PFDA) was the most toxic to R. subcapitata, succeeded by Perfluorooctane sulfonate (PFOS), Perfluorobutanoic acid (PFBA), and Perfluorononanoic acid (PFNA), with the latter being the only one to show an algicidal effect. In the same species, assessment of binary mixtures of the compounds that demonstrated high toxicity in the single evaluation revealed either additive or antagonistic interactions. Remarkably, with an EC50 of 31 mg L-1, the short-chain compound PFBA, tested individually, exhibited toxicity levels akin to the notorious long-chain PFOS, and its harm to freshwater ecosystems cannot be ruled out. Despite mounting toxicological evidence and escalating environmental concentrations, PFBA has received little scientific attention and regulatory stewardship. It is strongly advisable that regulators re-evaluate its use to mitigate potential risks to the environmental and human health.

Poly- and perfluoroalkyl substances (PFASs) in amphibians and reptiles - exposure and health effects

Poly- and perfluoroalkyl substances (PFASs) are commonly used in various industries and everyday products, including clothing, electronics, furniture, paints, and many others. PFASs are primarily found in aquatic environments, but also present in soil, air and plants, making them one of the most important and dangerous pollutants of the natural environment. PFASs bioaccumulate in living organisms and are especially dangerous to aquatic and semi-aquatic animals. As endocrine disruptors, PFASs affect many internal organs and systems, including reproductive, endocrine, nervous, cardiovascular, and immune systems. This manuscript represents the first comprehensive review exclusively focusing on PFASs in amphibians and reptiles. Both groups of animals are highly vulnerable to PFASs in the natural habitats. Amphibians and reptiles, renowned for their sensitivity to environmental changes, are often used as crucial bioindicators to monitor ecosystem health and environmental pollution levels. Furthermore, the decline in amphibian and reptile populations worldwide may be related to increasing environmental pollution. Therefore, studies investigating the exposure of amphibians and reptiles to PFASs, as well as their impacts on these organisms are essential in modern toxicology. Summarizing the current knowledge on PFASs in amphibians and reptiles in a single manuscript will facilitate the exploration of new research topics in this field. Such a comprehensive review will aid researchers in understanding the implications of PFASs exposure on amphibians and reptiles, guiding future investigations to mitigate their adverse effects of these vital components of ecosystems.

Understanding PFAS toxicity through cell culture metabolomics: Current applications and future perspectives

Per- and polyfluoroalkyl substances (PFAS), ubiquitous environmental contaminants, pose significant challenges to ecosystems and human health. While cell cultures have emerged as new approach methodologies (NAMs) in ecotoxicity research, metabolomics is an emerging technique used to characterize the small-molecule metabolites present in cells and to understand their role in various biological processes. Integration of metabolomics with cell cultures, known as cell culture metabolomics, provides a novel and robust tool to unravel the complex molecular responses induced by PFAS exposure. In vitro testing also reduces reliance on animal testing, aligning with ethical and regulatory imperatives. The current review summarizes key findings from recent studies utilizing cell culture metabolomics to investigate PFAS toxicity, highlighting alterations in metabolic pathways, biomarker identification, and the potential linkages between metabolic perturbations. Additionally, the paper discusses different types of cell cultures and metabolomics methods used for studies of environmental contaminants and particularly PFAS. Future perspectives on the combination of metabolomics with other advanced technologies, such as single-cell metabolomics (SCM), imaging mass spectrometry (IMS), extracellular flux analysis (EFA), and multi-omics are also explored, which offers a holistic understanding of environmental contaminants. The synthesis of current knowledge and identification of research gaps provide a foundation for future investigations that aim to elucidate the complexities of PFAS-induced cellular responses and contribute to the development of effective strategies for mitigating their adverse effects on human health.

Prenatal exposure to mixtures of per- and polyfluoroalkyl substances and organochlorines affects cognition in adolescence independent of postnatal exposure

BACKGROUND

Studies on cognitive and neurodevelopmental outcomes have shown inconsistent results regarding the association with prenatal exposure to perfluoroalkyl substance (PFAS) and organochlorines. Assessment of mixture effects of correlated chemical exposures that persist in later life may contribute to the unbiased evaluation and understanding of dose-response associations in real-life exposures.

METHODS

For a subset of the 4th Flemish Environment and Health Study (FLEHS), concentrations of four PFAS and six organochlorines were measured in respectively 99 and 153-160 cord plasma samples and 15 years later in adolescents' peripheral serum by Ultra Performance Liquid Chromatography-Tandem Mass Spectrometry (UPLC-MS/MS). Sustained and selective attention were measured at 14-15 years with the Continuous Performance Test (CPT) and Stroop Test as indicators of potential neurodevelopmental deficits. Quantile g-computation was applied to assess the joint associations between prenatal exposure to separate and combined groups of PFAS and organochlorines and performance in the CPT and Stroop Test at adolescence. Subsequently, individual effects of each chemical compound were analyzed in mixed effects models with two sets of covariates. Analytical data at birth and at the time of cognitive assessment allowed for off-setting postnatal exposure.

RESULTS

In mixtures analysis, a simultaneous one-quantile increase in the natural log-transformed values of PFAS and organochlorines combined was associated with a decrease in the mean reaction time (RT) and the reaction time variability (RTV) in the CPT (β = -15.54, 95% CI:-29.64, -1.45, and β = -7.82, 95% CI: -14.97, -0.67 respectively) and for the mixture of PFAS alone with RT (β = -11.94, 95% CI: -23.29, -0.60). In the single pollutant models, these results were confirmed for the association between perfluorohexanesulfonate (PFHxS) with RT (β = -17.95, 95% CI = -33.35, -2.69) and hexachlorobenzene with RTV in the CPT (β = -5.78, 95% CI: -10.39, -0.76). Furthermore, the participants with prenatal exposure above the limit of quantification for perfluorononanoic acid (PFNA) had a significantly shorter RT and RTV in the CPT (β = -23.38, 95% CI: -41.55, -5.94, and β = -9.54, 95% CI: -19.75, -0.43, respectively).

CONCLUSION

Higher prenatal exposure to a PFAS mixture and a mixture of PFAS and organochlorines combined was associated with better sustained and selective attention during adolescence. The associations seemed to be driven by PFHxS and were not linked to exposure levels at the time of assessment.

Southeast Asia's environmental challenges: emergence of new contaminants and advancements in testing methods

Emerging contaminants, including pharmaceuticals, personal care products, microplastics, and per- and poly-fluoroalkyl substances, pose a major threat to both ecosystems and human health in Southeast Asia. As this region undergoes rapid industrialization and urbanization, the increasing presence of unconventional pollutants in water bodies, soil, and various organisms has become an alarming concern. This review comprehensively examines the environmental challenges posed by emerging contaminants in Southeast Asia and recent progress in toxicity testing methods. We discuss the diverse range of emerging contaminants found in Southeast Asia, shedding light on their causes and effects on ecosystems, and emphasize the need for robust toxicological testing methods. This review is a valuable resource for researchers, policymakers, and environmental practitioners working to mitigate the impacts of emerging contaminants and secure a sustainable future for Southeast Asia.

Machine learning - based q-RASAR modeling to predict acute contact toxicity of binary organic pesticide mixtures in honey bees

We have reported here a quantitative read-across structure-activity relationship (q-RASAR) model for the prediction of binary mixture toxicity (acute contact toxicity) in honey bees. Both the quantitative structure-activity relationship (QSAR) and the similarity-based read-across algorithms are used simultaneously for enhancing the predictability of the model. Several similarity and error-based parameters, obtained from the read-across prediction tool, have been put together with the structural and physicochemical descriptors to develop the final q-RASAR model. The calculated statistical and validation metrics indicate the goodness-of-fit, robustness, and good predictability of the partial least squares (PLS) regression model. Machine learning algorithms like ridge regression, linear support vector machine (SVM), and non-linear SVM have been used to further enhance the predictability of the q-RASAR model. The prediction quality of the q-RASAR models outperforms the previously reported quasi-SMILEs-based QSAR model in terms of external correlation coefficient (Q2F1 SVM q-RASAR: 0.935 vs. Q2VLD QSAR: 0.89). In this research, the toxicity values of several new untested binary mixtures have been predicted with the new models, and the reliability of the PLS predictions has been validated by the prediction reliability indicator tool. The q-RASAR approach can be used as reliable, complementary, and integrative to the conventional experimental approaches of pesticide mixture risk assessment.

The regulation of endocrine-disrupting chemicals to minimize their impact on health

Endocrine-disrupting chemicals (EDCs) are substances generated by human industrial activities that are detrimental to human health through their effects on the endocrine system. The global societal and economic burden posed by EDCs is substantial. Poorly defined or unenforced policies can increase human exposure to EDCs, thereby contributing to human disease, disability and economic damage. Researchers have shown that policies and interventions implemented at both individual and government levels have the potential to reduce exposure to EDCs. This Review describes a set of evidence-based policy actions to manage, minimize or even eliminate the widespread use of these chemicals and better protect human health and society. A number of specific challenges exist: defining, identifying and prioritizing EDCs; considering the non-linear or non-monotonic properties of EDCs; accounting for EDC exposure effects that are latent and do not appear until later in life; and updating testing paradigms to reflect 'real-world' mixtures of chemicals and cumulative exposure. A sound strategy also requires partnering with health-care providers to integrate strategies to prevent EDC exposure in clinical care. Critical next steps include addressing EDCs within global policy frameworks by integrating EDC exposure prevention into emerging climate policy.

A Critical Review of Amphibian Per- and Polyfluoroalkyl Substance Ecotoxicity Research Studies: Identification of Screening Levels in Water and Other Useful Resources for Site-Specific Ecological Risk Assessments

With the goal of aiding risk assessors conducting site-specific risk assessments at per- and polyfluoroalkyl substance (PFAS)-contaminated sites, this critical review synthesizes information on the ecotoxicity of PFAS to amphibians in 10 amphibian species and 16 peer-reviewed publications. The studies in this review consisted of spiked-PFAS chronic toxicity experiments with perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), perfluorohexane sulfonate (PFHxS), and 6:2 fluorotelomer sulfonate (6:2 FTS) that evaluated apical endpoints typical of ecological risk-based decision making (survival, growth, and development). Body mass was the most sensitive endpoint, showing clear and biologically meaningful population level adverse effect sizes (≥20% adverse effects). From these results, we recommend chronic no observed effect concentration (NOEC) screening levels of 590 µg/L for PFOS and 130 µg/L for PFOA. At or above recommended chronic lowest observed effect concentration screening levels of 1100 µg/L PFOS and 1400 µg/L PFOA, there is an increased chance of adverse biologically relevant chronic effects. Biologically relevant adverse effects were not observed for PFHxS and 6:2 FTS, so unbounded NOECs of 1300 µg/L PFHxS and 1800 µg/L 6:2 FTS are recommended. Screening levels are also provided for the concentration of PFAS in an amphibian diet, amphibian tissue, and moss substrate. In addition, we recommend bioconcentration factors that can be useful to predict concentrations of PFAS in amphibians using concentrations in water; these values are useful for food web modeling to understand risks to vertebrate wildlife that prey on amphibians. Overall, the present study provides a guide to the wealth of ecotoxicological research on PFAS conducted by our research group and highlights the need for additional work that would improve the understanding of chemical risks to amphibians. Environ Toxicol Chem 2023;42:2078-2090. © 2023 SETAC.

Computational Modeling of Human Serum Albumin Binding of Per- and Polyfluoroalkyl Substances Employing QSAR, Read-Across, and Docking

Per- and polyfluoroalkyl substances (PFAS) are synthetic chemicals in widespread use that have been shown to be toxic to wildlife and humans. Human serum albumin (HSA) is a known transport protein that binds PFAS at various sites, leading to bioaccumulation and long-term toxicity. In silico tools like quantitative structure-activity relationship (QSAR), read-across, and quantitative read-across structure-property relationship (q-RASPR) are proven techniques for modeling chemical toxicity based on experimental data which can be used to predict the toxicity of untested and new chemicals, while at the same time, help to identify the major features responsible for toxicity. Classification-based and regression-based QSAR models are employed in the present study to predict the binding affinities of 24 PFAS to HSA. Regression-based QSAR models revealed that the packing density index (PDI) and quantitative estimation of drug-likeness (QED) descriptors were both positively correlated with higher binding affinity, while the classification-based QSAR model showed the average connectivity index of order 4 (X4A) descriptor was inversely correlated with binding affinity. Whereas molecular docking studies suggested that PFAS with the highest binding affinity to HSA create hydrogen bonds with Arg348 and salt bridges with Arg348 and Arg485, PFAS with lower binding affinity either showed no interactions with either amino acid or only interactions with Arg348. Among the studied PFAS, perfluoroalkyl acids (PFAA) with large carbon chain length (>C10) have one of the lowest binding affinities, compared to PFAA with carbon chain length ranging from 7 to 9, which showed the highest affinity to HSA. Generalized Read-Across (GenRA) was used to predict toxicity outcomes for the top five highest binding affinity PFAS based on 10 structural analogs for each and found that all are predicted as being chronic to sub-chronically toxic to HSA. The developed in silico models presented in this work can provide a framework for designing PFAS alternatives, screening compounds currently in use, and for the study of PFAS mixture toxicity, which is an area of intense research.

Sublethal Exposure of Per- and Polyfluoroalkyl Substances of Varying Chain Length and Polar Functionality Results in Distinct Metabolic Responses in Daphnia magna

Per- and polyfluoroalkyl substances (PFAS) are a class of persistent organic pollutants used in industrial applications because of their physicochemical properties, which results in their ubiquitous presence across environmental matrices. To date, legacy PFAS have been well studied; however, the concentration of alternative PFAS may exceed the concentration of legacy pollutants, and more information is needed regarding the sublethal toxicity at the molecular level of aquatic model organisms, such as Daphnia magna. Perfluorobutanoic acid (PFBA), perfluorohexanoic acid (PFHxA), perfluorohexanesulfonic acid (PFHxS), and perfluorononanoic acid (PFNA) are four widely detected PFAS alternatives of varying chain length and polar functionality that are quantified in aquatic environments. The present study examines the metabolic perturbations of PFAS with varying chemistries to D. magna using targeted mass spectrometry-based metabolomics. Daphnia were acutely exposed to sublethal concentrations of PFBA, PFHxA, PFHxS, and PFNA before the polar metabolite profile was extracted from single organisms. Multivariate analysis demonstrated significant separation between the sublethal concentrations of PFHxA, PFHxS, and PFNA relative to the controls; in sum, longer chain lengths demonstrated greater overall perturbations to the extracted metabolic profiles. Univariate statistics revealed significant perturbations in the concentrations of several amino acids, nucleotides/nucleosides, and neurotransmitters with exposure to PFAS. These metabolic perturbations are consistent with disruptions in energy metabolism (pantothenate and coenzyme A metabolism, histidine metabolism) and protein synthesis (aminoacyl-transfer RNA biosynthesis and amino acid metabolism), which were identified through biochemical pathway analysis. These results provide evidence that although PFAS chemistry (chain length and polar functional group) invokes unique metabolic responses, there is also an underlying toxic mode of action that is common with select PFAS exposure. Overall, the present study highlights the capabilities of environmental metabolomics to elucidate the molecular-level perturbations of pollutants within the same chemical class to model aquatic organisms, which can be used to prioritize risk assessment of substituted PFAS alternatives. Environ Toxicol Chem 2023;42:242-256. © 2022 SETAC.

Chemical similarity and machine learning-based approaches for the prediction of aquatic toxicity of binary and multicomponent pharmaceutical and pesticide mixtures against Aliivibrio fischeri

Different classes of chemicals are present in the environment as mixtures. Among them, pharmaceuticals and pesticides are of major concern due to their improper use and disposal, and subsequent additive and non-additive effects. To assess the environmental risk posed by the mixtures of pharmaceuticals and pesticides, a quantitative structure-activity relationship (QSAR) model has been developed in this study using the pEC₅₀ values of 198 binary and multi-component mixtures against the marine bacterium Aliivibrio fischeri. The developed partial least squares (PLS) model has been rigorously validated and proved to be a robust and extremely predictive one. To address the chances of overestimation of validation metrics, three cross-validation tests (mixtures out, compounds out, and everything out) have been applied, and the results were satisfactory. The use of simple 2-dimensional descriptors makes the prediction much quick, and also makes the model easily interpretable. A machine learning-based chemical read-across prediction has also been performed to justify the effectiveness of selected structural features in this study. In a nutshell, this study proves QSAR and chemical read-across as effective alternative approaches for the toxicity prediction of pharmaceutical and pesticide mixtures and also approves the use of mixture descriptors for modelling mixtures successfully.

Toxicokinetic Modeling of Per- and Polyfluoroalkyl Substance Concentrations within Developing Zebrafish (Danio rerio) Populations

Per- and polyfluoroalkyl substances (PFAS) are pervasive environmental contaminants, and their relative stability and high bioaccumulation potential create a challenging risk assessment problem. Zebrafish (Danio rerio) data, in principle, can be synthesized within a quantitative adverse outcome pathway (qAOP) framework to link molecular activity with individual or population level hazards. However, even as qAOP models are still in their infancy, there is a need to link internal dose and toxicity endpoints in a more rigorous way to further not only qAOP models but adverse outcome pathway frameworks in general. We address this problem by suggesting refinements to the current state of toxicokinetic modeling for the early development zebrafish exposed to PFAS up to 120 h post-fertilization. Our approach describes two key physiological transformation phenomena of the developing zebrafish: dynamic volume of an individual and dynamic hatching of a population. We then explore two different modeling strategies to describe the mass transfer, with one strategy relying on classical kinetic rates and the other incorporating mechanisms of membrane transport and adsorption/binding potential. Moving forward, we discuss the challenges of extending this model in both timeframe and chemical class, in conjunction with providing a conceptual framework for its integration with ongoing qAOP modeling efforts.

Joint toxicity mechanisms of binary emerging PFAS mixture on algae (Chlorella pyrenoidosa) at environmental concentration

Since traditional Per- and polyfluoroalkyl substances (PFAS) were banned in 2009 due to their bioaccumulation, persistence and biological toxicity, the emerging PFAS have been widely used as their substitutes and entered the aquatic environment in the form of mixtures. However, the joint toxicity mechanisms of these emerging PFAS mixtures to aquatic organisms remain largely unknown. Then, based on the testing of growth inhibition, cytotoxicity, photosynthesis and oxidative stress, and the toxicity mechanism of PFAS mixture (Perfluorobutane sulfonate and Perfluorobutane sulfonamide) to algae was explored using the Gene set enrichment analysis (GSEA). The results revealed that all three emerging PFAS treatments had a certain growth inhibitory effect on Chlorella pyrenoidosa (C. pyrenoidosa), but the toxicity of PFAS mixture was stronger than that of individual PFAS and showed a significant synergistic effect at environmental concentration. The joint toxicity mechanisms of binary PFAS mixture to C. pyrenoidosa were related to the damage of photosynthetic system, obstruction of ROS metabolism, and inhibition of DNA replication. Our findings are conductive to adding knowledge in understanding the joint toxicity mechanisms and provide a basis for assessing the environmental risk of emerging PFAS.

Application of cross-validation strategies to avoid overestimation of performance of 2D-QSAR models for the prediction of aquatic toxicity of chemical mixtures

The quantitative structure-activity relationship (QSAR) modelling of mixtures is not as simple as that for individual chemicals, and it needs additional care to avoid overestimation of the performance. In this research, we have developed a 2D-QSAR model using only 2D interpretable and reproducible descriptors to predict the aquatic toxicity of mixtures of polar and non-polar narcotic substances present in the environment. Partial least squares (PLS) regression has been used to model the response variable (log 1/EC50 against Photobacterium phosphoreum) and the structural features of 84 binary mixtures of polar and nonpolar narcotic toxicants complying with the Organization of Economic Co-operation and Development (OECD) protocols. The model was cross-validated by mixtures-out and compounds-out cross-validation to nullify the developmental bias. The reliability of prediction of the model has been judged by the Prediction Reliability Indicator (PRI) tool using a newly designed set. The new model is robust, reproducible, extremely predictive, easily interpretable, and can be used for reliable prediction of aquatic toxicity of any untested chemical mixtures within the applicability domain. We have additionally used a machine learning-based chemical read-across algorithm in this study to improve the quality of predictions for the toxicity of the mixtures with the modelled descriptors.

A Critical Review and Meta-Analysis of Impacts of Per- and Polyfluorinated Substances on the Brain and Behavior

Per- and polyfluoroalkyl substances (PFAS) are a class of structurally diverse synthetic organic chemicals that are chemically stable, resistant to degradation, and persistent in terrestrial and aquatic environments. Widespread use of PFAS in industrial processing and manufacturing over the last 70 years has led to global contamination of built and natural environments. The brain is a lipid rich and highly vascularized organ composed of long-lived neurons and glial cells that are especially vulnerable to the impacts of persistent and lipophilic toxicants. Generally, PFAS partition to protein-rich tissues of the body, primarily the liver and blood, but are also detected in the brains of humans, wildlife, and laboratory animals. Here we review factors impacting the absorption, distribution, and accumulation of PFAS in the brain, and currently available evidence for neurotoxic impacts defined by disruption of neurochemical, neurophysiological, and behavioral endpoints. Emphasis is placed on the neurotoxic potential of exposures during critical periods of development and in sensitive populations, and factors that may exacerbate neurotoxicity of PFAS. While limitations and inconsistencies across studies exist, the available body of evidence suggests that the neurobehavioral impacts of long-chain PFAS exposures during development are more pronounced than impacts resulting from exposure during adulthood. There is a paucity of experimental studies evaluating neurobehavioral and molecular mechanisms of short-chain PFAS, and even greater data gaps in the analysis of neurotoxicity for PFAS outside of the perfluoroalkyl acids. Whereas most experimental studies were focused on acute and subchronic impacts resulting from high dose exposures to a single PFAS congener, more realistic exposures for humans and wildlife are mixtures exposures that are relatively chronic and low dose in nature. Our evaluation of the available human epidemiological, experimental, and wildlife data also indicates heightened accumulation of perfluoroalkyl acids in the brain after environmental exposure, in comparison to the experimental studies. These findings highlight the need for additional experimental analysis of neurodevelopmental impacts of environmentally relevant concentrations and complex mixtures of PFAS.

Emerging trends in nanoparticle toxicity and the significance of using Daphnia as a model organism

Nanoparticle production is on the rise due to its many uses in the burgeoning nanotechnology industry. Although nanoparticles have growing applications, there is great concern over their environmental impact due to their inevitable release into the environment. With uncertainty of environmental concentration and risk to aquatic organisms, the microcrustacean Daphnia spp. has emerged as an important freshwater model organism for risk assessment of nanoparticles because of its biological properties, including parthenogenetic reproduction; small size and short generation time; wide range of endpoints for ecotoxicological studies; known genome, useful for providing mechanistic information; and high sensitivity to environmental contaminants and other stressors. In this review, we (1) highlight the advantages of using Daphnia as an experimental model organism for nanotoxicity studies, (2) summarize the impacts of nanoparticle physicochemical characteristics on toxicity in relation to Daphnia, and (3) summarize the effects of nanoparticles (including nanoplastics) on Daphnia as well as mechanisms of toxicity, and (4) highlight research uncertainties and recommend future directions necessary to develop a deeper understanding of the fate and toxicity of nanoparticles and for the development of safer and more sustainable nanotechnology.

Per- and polyfluoroalkyl substances in the environment

Over the past several years, the term PFAS (per- and polyfluoroalkyl substances) has grown to be emblematic of environmental contamination, garnering public, scientific, and regulatory concern. PFAS are synthesized by two processes, direct fluorination (e.g., electrochemical fluorination) and oligomerization (e.g., fluorotelomerization). More than a megatonne of PFAS is produced yearly, and thousands of PFAS wind up in end-use products. Atmospheric and aqueous fugitive releases during manufacturing, use, and disposal have resulted in the global distribution of these compounds. Volatile PFAS facilitate long-range transport, commonly followed by complex transformation schemes to recalcitrant terminal PFAS, which do not degrade under environmental conditions and thus migrate through the environment and accumulate in biota through multiple pathways. Efforts to remediate PFAS-contaminated matrices still are in their infancy, with much current research targeting drinking water.

PFAS Molecules: A Major Concern for the Human Health and the Environment

Per- and polyfluoroalkyl substances (PFAS) are a group of over 4700 heterogeneous compounds with amphipathic properties and exceptional stability to chemical and thermal degradation. The unique properties of PFAS compounds has been exploited for almost 60 years and has largely contributed to their wide applicability over a vast range of industrial, professional and non-professional uses. However, increasing evidence indicate that these compounds represent also a serious concern for both wildlife and human health as a result of their ubiquitous distribution, their extreme persistence and their bioaccumulative potential. In light of the adverse effects that have been already documented in biota and human populations or that might occur in absence of prompt interventions, the competent authorities in matter of health and environment protection, the industries as well as scientists are cooperating to identify the most appropriate regulatory measures, substitution plans and remediation technologies to mitigate PFAS impacts. In this review, starting from PFAS chemistry, uses and environmental fate, we summarize the current knowledge on PFAS occurrence in different environmental media and their effects on living organisms, with a particular emphasis on humans. Also, we describe present and provisional legislative measures in the European Union framework strategy to regulate PFAS manufacture, import and use as well as some of the most promising treatment technologies designed to remediate PFAS contamination in different environmental compartments.

Predicting the effects of per- and polyfluoroalkyl substance mixtures on peroxisome proliferator-activated receptor alpha activity in vitro

Human exposure to per- and polyfluoroalkyl substances (PFAS) is ubiquitous, with mixtures of PFAS detected in drinking water, food, household dust, and other exposure sources. Animal toxicity studies and human epidemiology indicate that PFAS may act through shared mechanisms including activation of peroxisome proliferator activated receptor α (PPARα). However, the effect of PFAS mixtures on human relevant molecular initiating events remains an important data gap in the PFAS literature. Here, we tested the ability of modeling approaches to predict the effect of diverse PPARα ligands on receptor activity using Cos7 cells transiently transfected with a full length human PPARα (hPPARα) expression construct and a peroxisome proliferator response element-driven luciferase reporter. Cells were treated for 24 h with two full hPPARα agonists (pemafibrate and GW7647), a full and a partial hPPARα agonist (pemafibrate and mono(2-ethylhexyl) phthalate), or a full hPPARα agonist and a competitive antagonist (pemafibrate and GW6471). Receptor activity was modeled with three additive approaches: effect summation, relative potency factors (RPF), and generalized concentration addition (GCA). While RPF and GCA accurately predicted activity for mixtures of full hPPARα agonists, only GCA predicted activity for full and partial hPPARα agonists and a full agonist and antagonist. We then generated concentration response curves for seven PFAS, which were well-fit with three-parameter Hill functions. The four perfluorinated carboxylic acids (PFCA) tended to act as full hPPARα agonists while the three perfluorinated sulfonic acids (PFSA) tended to act as partial agonists that varied in efficacy between 28-67 % of the full agonist, positive control level. GCA and RPF performed equally well at predicting the effects of mixtures with three PFCAs, but only GCA predicted experimental activity with mixtures of PFSAs and a mixture of PFCAs and PFSAs at ratios found in the general population. We conclude that of the three approaches, GCA most accurately models the effect of PFAS mixtures on hPPARα activity in vitro. Understanding the differences in efficacy with which PFAS activate hPPARα is essential for accurately predicting the effects of PFAS mixtures. As PFAS can activate multiple nuclear receptors, future analyses should examine mixtures effects in intact cells where multiple molecular initiating events contribute to proximate effects and functional changes.

Predicting the effects of per- and polyfluoroalkyl substance mixtures on peroxisome proliferator-activated receptor alpha activity in vitro

Human exposure to per- and polyfluoroalkyl substances (PFAS) is ubiquitous, with mixtures of PFAS detected in drinking water, food, household dust, and other exposure sources. Animal toxicity studies and human epidemiology indicate that PFAS may act through shared mechanisms including activation of peroxisome proliferator activated receptor α (PPARα). However, the effect of PFAS mixtures on human relevant molecular initiating events remains an important data gap in the PFAS literature. Here, we tested the ability of modeling approaches to predict the effect of diverse PPARα ligands on receptor activity using Cos7 cells transiently transfected with a full length human PPARα (hPPARα) expression construct and a peroxisome proliferator response element-driven luciferase reporter. Cells were treated for 24 h with two full hPPARα agonists (pemafibrate and GW7647), a full and a partial hPPARα agonist (pemafibrate and mono(2-ethylhexyl) phthalate), or a full hPPARα agonist and a competitive antagonist (pemafibrate and GW6471). Receptor activity was modeled with three additive approaches: effect summation, relative potency factors (RPF), and generalized concentration addition (GCA). While RPF and GCA accurately predicted activity for mixtures of full hPPARα agonists, only GCA predicted activity for full and partial hPPARα agonists and a full agonist and antagonist. We then generated concentration response curves for seven PFAS, which were well-fit with three-parameter Hill functions. The four perfluorinated carboxylic acids (PFCA) tended to act as full hPPARα agonists while the three perfluorinated sulfonic acids (PFSA) tended to act as partial agonists that varied in efficacy between 28-67 % of the full agonist, positive control level. GCA and RPF performed equally well at predicting the effects of mixtures with three PFCAs, but only GCA predicted experimental activity with mixtures of PFSAs and a mixture of PFCAs and PFSAs at ratios found in the general population. We conclude that of the three approaches, GCA most accurately models the effect of PFAS mixtures on hPPARα activity in vitro. Understanding the differences in efficacy with which PFAS activate hPPARα is essential for accurately predicting the effects of PFAS mixtures. As PFAS can activate multiple nuclear receptors, future analyses should examine mixtures effects in intact cells where multiple molecular initiating events contribute to proximate effects and functional changes.

Uncertainty-Informed Deep Transfer Learning of Perfluoroalkyl and Polyfluoroalkyl Substance Toxicity

Perfluoroalkyl and polyfluoroalkyl substances (PFAS) pose a significant hazard because of their widespread industrial uses, environmental persistence, and bioaccumulation. A growing, increasingly diverse inventory of PFAS, including 8163 chemicals, has recently been updated by the U.S. Environmental Protection Agency. However, with the exception of a handful of well-studied examples, little is known about their human toxicity potential because of the substantial resources required for in vivo toxicity experiments. We tackle the problem of expensive in vivo experiments by evaluating multiple machine learning (ML) methods, including random forests, deep neural networks (DNN), graph convolutional networks, and Gaussian processes, for predicting acute toxicity (e.g., median lethal dose, or LD₅₀) of PFAS compounds. To address the scarcity of toxicity information for PFAS, publicly available datasets of oral rat LD₅₀ for all organic compounds are aggregated and used to develop state-of-the-art ML source models for transfer learning. A total of 519 fluorinated compounds containing two or more C-F bonds with known toxicity are used for knowledge transfer to ensembles of the best-performing source model, DNN, to generate the target models for the PFAS domain with access to uncertainty. This study predicts toxicity for PFAS with a defined chemical structure. To further inform prediction confidence, the transfer-learned model is embedded within a SelectiveNet architecture, where the model is allowed to identify regions of prediction with greater confidence and abstain from those with high uncertainty using a calibrated cutoff rate.

Transcriptional effects of binary combinations of PFAS in FaO cells

Per- and polyfluoroalkyl substances (PFAS) represent a large class of structurally diverse chemicals of increasing public concern, mostly due to their chemical stability and undetermined toxicity profiles. In laboratory animals, adverse effects implicated for certain PFAS, perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS) in particular, include liver toxicity and the associated metabolic dysregulation, immune and thyroid alterations, reproductive toxicity, and selected tumors. The broad commercialization and environmental distribution of PFAS has drawn attention to the need for understanding risks associated with combined exposure to multiple PFAS in complex mixtures. The purpose of this investigation is to determine whether binary combinations of PFAS elicit a molecular response that is either greater than or less than the sum of the individual responses. Exposure of FaO rat hepatoma cells for 24 h to 25 μM-200 μM of the 4- and 8-carbon perfluorocarboxylic acids (PFBA and PFOA) or the 4, 6, and 8-carbon perfluorosulfonic acids (PFBS, PFHxS, and PFOS, respectively) individually caused a dose-dependent increase in PPARα-regulated expression of peroxisomal bifunctional enzyme (Ehhadh). Potency increased with carbon number, with the carboxylates eliciting a greater transcriptional response than the corresponding sulfonates. Combined exposure to PFOA and PFBA produced an effect that was significantly less than the sum of the individual responses. The response to the combination of PFOA and PFOS produced a summative effect at concentrations that were not cytotoxic. Combined exposures to PFOS and either PFBS or PFHxS at low noncytotoxic concentrations produced a transcriptional effect that was significantly less than the sum of the individual effects. The results demonstrate that among the five structurally related perfluoroalkyl acids included in this investigation, PPARα transcriptional activation in response to combined binary exposures is consistently at or below that predicted by the sum of the individual effects.

The role of maternal high fat diet on mouse pup metabolic endpoints following perinatal PFAS and PFAS mixture exposure

Per- and polyfluoroalkyl substances (PFAS) are a family of chemicals that are ubiquitous in the environment. Some of these chemicals, such as perfluorooctanesulfonic acid (PFOS), perfluorohexanesulfonate (PFHxS) and perfluorooctanoic acid (PFOA), are found in human sera and have been shown to cause liver steatosis and reduce postnatal survival and growth in rodents. The purpose of this work is to evaluate the impact of diet and PFAS exposure to mouse dam (mus musculus) on the risk to pup liver and metabolism endpoints later in life, as well as evaluate PFAS partitioning to pups. Timed-pregnant dams were fed a standard chow diet or 60 % kcal high fat diet (HFD). Dams were administered either vehicle, 1 mg/kg PFOA, 1 mg/kg PFOS, 1 mg/kg PFHxS, or a PFAS mixture (1 mg/kg of each PFOA, PFOS, and PFHxS) daily via oral gavage from gestation day 1 until postnatal day (PND) 20. At PND 21, livers of dams and 2 pups of each sex were evaluated for lipid changes while remaining pups were weaned to the same diet as the dam for an additional 10 weeks. Dam and pup serum at PND 21 and PND 90 were also evaluated for PFAS concentration, alanine aminotransferase (ALT), leptin and adiponectin, and glycosylated hemoglobin A1c. Perinatal exposure to a HFD, as expected, increased pup body weight, maternal liver weight, pup liver triglycerides, pup serum ALT, and pup serum leptin. PFOA and the PFAS mixture increased liver weights, and. treatment with all three compounds increased liver triglycerides. The maternal HFD increased dam and pup serum PFAS levels, however, was protective against PFOA-induced increase in serum ALT and observed increases in liver triglycerides. The PFAS mixture had very distinct effects when compared to single compound treatment, suggesting some cumulative effects, particularly when evaluating PFAS transfer from dam to pup. This data highlights the importance of diet and mixtures when evaluating liver effect of PFAS and PFAS partitioning.

The new generation PFAS C6O4 does not produce adverse effects on thyroid cells in vitro

PURPOSE

Per- and poly-fluoroalkyl-substances (PFASs) are synthetic compounds that raised concern due to their potential adverse effects on human health. Long-chain PFAS were banned by government rules in many states, and thus, new emerging PFAS were recently introduced as substitutes. Among these, Perfluoro{acetic acid, 2-[(5-methoxy-1,3-dioxolan-4-yl)oxy]}, ammonium salt (C6O4) was recently introduced to produce a range of food contact articles and literature data about this compound are scanty. The aim of this study was to evaluate the in vitro effects of exposure to C6O4, compared with PFOA and PFOS on thyroid cells.

METHODS

FRTL5 rat-thyroid cell lines and normal human thyroid cells (NHT) were incubated with increasing concentrations of C6O4 for 24, 48, 72, and 144 h to assess cell viability by WST-1. Cell viability was confirmed by AnnexinV/PI staining. Long-chain PFAS (PFOA and PFOS) were used at same concentrations as positive controls. The proliferation of cells exposed to C6O4, PFOA, and PFOS was measured by staining with crystal violet and evaluation of optical density after incubation with SDS. Changes in ROS production by FRTL5 and NHT after exposure to C6O4 at short (10, 20, and 30 min) and long-time points (24 h) were evaluated by cytofluorimetry.

RESULTS

C6O4 exposure did not modify FRTL5 and NHT cell viability at any concentration and/or time points with no induction of necrosis/apoptosis. At difference, PFOS exposure reduced cell viability of FRTL5 while and NHT, while PFOA only in FRTL5. FRTL5 and NHT cell proliferation was reduced by incubation with by PFOA and PFOS, but not with C6O4. ROS production by NHT and FRTL5 cells was not modified after C6O4 exposure, at any time/concentration tested.

CONCLUSIONS

The present in vitro study constitutes the first evaluation of the potential adverse effects of the new emerging PFAS C6O4 in cultured rat and human thyroid cells, suggesting its safety for thyroid cells in vitro.

Prediction of aquatic toxicity of chemical mixtures by the QSAR approach using 2D structural descriptors

The rapid industrialization has led to the generation of various organic chemicals and multi-component mixtures which affect the environment adversely. Although organic chemicals are often exposed to the environment as a form of chemical mixtures rather than individual compounds, there is insufficient toxicity data available for the chemical mixtures due to the associated complexities. Most importantly, the nature of toxicity of mixtures is completely different from the individual chemicals, which makes the evaluation more difficult and challenging. In this paper, we have developed QSAR models for various individual and mixture data sets for the prediction of the aquatic toxicity. We have used Partial Least Squares (PLS) regression as a statistical tool to build the models. The various structural features of the individual chemicals and the mixture components have been modeled against the toxicity end point pEC₅₀ (negative logarithm of median effective concentration in molar scale) of the aquatic organisms Photobacterium phosphoreum (marine bacterium) and Selenastrum capricornutum (freshwater algae). The mixture descriptors have been calculated by the weighted descriptor generation approach. The models were developed in accordance with OECD guidelines, and the quality of each model has been adjudged by strict validation parameters. The final models are robust, extremely predictive and interpretable mechanistically which can be used for the prediction of toxicity of untested chemical mixtures under the domain of applicability of the developed models.

Assessing the human health risks of per- and polyfluoroalkyl substances: A need for greater focus on their interactions as mixtures

Humans are exposed to complex mixtures of per- and polyfluoroalkyl substances (PFAS). However, human health risk assessment of PFAS currently relies on animal toxicity data derived from individual substance exposure, which may not adequately predict the risk from combined exposure due to possible interactions that can influence the overall risk. Long-chain perfluoroalkyl acids (PFAAs), particularly perfluorooctane sulfonate (PFOS) and perfluorooctanoic acid (PFOA) are recognised as global emerging contaminants of concern due to their ubiquitous distribution in all environmental media, wildlife, and humans, persistency, bioaccumulative-, toxic-, and human health-risk potentials. This article reviews the current understanding of the human health risks associated with PFAS exposure focusing on more recent toxicological and epidemiological studies from 2010 to 2020. The existing information on PFAA mixtures was also reviewed in an attempt to highlight the need for greater focus on their potential interactions as mixtures within the class of these chemicals. A growing number of toxicological studies have indicated several adverse health outcomes of PFAA exposure, including developmental and reproductive toxicity, neurotoxicity, hepatotoxicity, genotoxicity, immunotoxicity, thyroid disruption, and carcinogenicity. Epidemiological findings further support some of these adverse human health outcomes. However, the mechanisms underlying these adverse effects are not well defined. A few in vitro studies focusing on PFAA mixtures revealed that these compounds may act additively or interact synergistically/antagonistically depending on the species, dose level, dose ratio, and mixture components. Hence, the combined effects or potential interactions of PFAS mixtures should be considered and integrated into toxicity assessment to obtain a realistic and more refined human health risk assessment.

Fire Suppression Agents Combined with Gasoline in Aquatic Ecosystems: A Mixture Approach

Fire suppression agents are recommended for extinguishing fires by flammable liquids and frequently end in water bodies, combined with the fuels. There is a lack of toxicity information on these commercial formulations and the effects of mixtures of fire suppression agents and fuels. The aim of the present study was to evaluate the toxic effects of different fire suppression agents, the gasoline water-soluble fraction (GWSF), and mixtures of each fire suppression agent and GWSF. Individual tests were performed with Daphnia similis and Artemia sp.; the most toxic fire suppression agents to D. similis and Artemia sp. were F-500®, Cold Fire®, Agefoam®, and Kidde Sintex® 1%; the GWSF was the least toxic. The concentration addition model was used to predict the mixture effects and evaluate synergism/antagonism, dose ratio dependence, and dose level dependence. Cold Fire with GWSF showed dose level deviation to D. similis, marked mainly by synergism; for Artemia sp., the dose ratio pattern was predicted, with a synergistic response mainly by Cold Fire. Agefoam and GWSF behaved additively for D. similis and dose ratio for Artemia sp., with synergism being caused by Agefoam. Kidde Sintex 1% with GWSF were dose ratio for both organisms, with Kidde Sintex 1% being responsible for synergism. Our results show that some mixtures of fire suppression agents and GWSF may cause toxicity to aquatic organisms, posing risk in a real environmental scenario, such as a major fire combat. Environ Toxicol Chem 2021;40:767-779. © 2020 SETAC.

PFAS Exposure Pathways for Humans and Wildlife: A Synthesis of Current Knowledge and Key Gaps in Understanding

We synthesize current understanding of the magnitudes and methods for assessing human and wildlife exposures to poly- and perfluoroalkyl substances (PFAS). Most human exposure assessments have focused on 2 to 5 legacy PFAS, and wildlife assessments are typically limited to targeted PFAS (up to ~30 substances). However, shifts in chemical production are occurring rapidly, and targeted methods for detecting PFAS have not kept pace with these changes. Total fluorine measurements complemented by suspect screening using high-resolution mass spectrometry are thus emerging as essential tools for PFAS exposure assessment. Such methods enable researchers to better understand contributions from precursor compounds that degrade into terminal perfluoroalkyl acids. Available data suggest that diet is the major human exposure pathway for some PFAS, but there is large variability across populations and PFAS compounds. Additional data on total fluorine in exposure media and the fraction of unidentified organofluorine are needed. Drinking water has been established as the major exposure source in contaminated communities. As water supplies are remediated, for the general population, exposures from dust, personal care products, indoor environments, and other sources may be more important. A major challenge for exposure assessments is the lack of statistically representative population surveys. For wildlife, bioaccumulation processes differ substantially between PFAS and neutral lipophilic organic compounds, prompting a reevaluation of traditional bioaccumulation metrics. There is evidence that both phospholipids and proteins are important for the tissue partitioning and accumulation of PFAS. New mechanistic models for PFAS bioaccumulation are being developed that will assist in wildlife risk evaluations. Environ Toxicol Chem 2021;40:631-657. © 2020 SETAC.

Per- and Polyfluoroalkyl Substance Toxicity and Human Health Review: Current State of Knowledge and Strategies for Informing Future Research

Reports of environmental and human health impacts of per- and polyfluoroalkyl substances (PFAS) have greatly increased in the peer-reviewed literature. The goals of the present review are to assess the state of the science regarding toxicological effects of PFAS and to develop strategies for advancing knowledge on the health effects of this large family of chemicals. Currently, much of the toxicity data available for PFAS are for a handful of chemicals, primarily legacy PFAS such as perfluorooctanoic acid and perfluorooctane sulfonate. Epidemiological studies have revealed associations between exposure to specific PFAS and a variety of health effects, including altered immune and thyroid function, liver disease, lipid and insulin dysregulation, kidney disease, adverse reproductive and developmental outcomes, and cancer. Concordance with experimental animal data exists for many of these effects. However, information on modes of action and adverse outcome pathways must be expanded, and profound differences in PFAS toxicokinetic properties must be considered in understanding differences in responses between the sexes and among species and life stages. With many health effects noted for a relatively few example compounds and hundreds of other PFAS in commerce lacking toxicity data, more contemporary and high-throughput approaches such as read-across, molecular dynamics, and protein modeling are proposed to accelerate the development of toxicity information on emerging and legacy PFAS, individually and as mixtures. In addition, an appropriate degree of precaution, given what is already known from the PFAS examples noted, may be needed to protect human health. Environ Toxicol Chem 2021;40:606-630. © 2020 SETAC.

Comparison of zebrafish in vitro and in vivo developmental toxicity assessments of perfluoroalkyl acids (PFAAs)

Perfluoroalkyl acids (PFAAs) are persistent environmental contaminants that are associated with various adverse health outcomes. Perfluorooctanoic acid (PFOA) is one of the most prominently detected PFAAs in the environment, which is now replaced with shorter chain carbon compounds including perfluorohexanoic acid (PFHxA) and perfluorobutyric acid (PFBA). The aim of this study was to compare the toxicity of four PFAAs as a function of chain length and head group (carboxylate versus sulfonate) with in vitro and in vivo zebrafish assessments, which were subsequently compared to other cell and aquatic models. Mortality rate increased with chain length (PFOA > PFHxA ≫ PFBA) in both whole embryo/larvae and embryonic cell models. The sulfonate group enhanced toxicity with perfluorobutane sulfonate (PFBS) showing higher toxicity than PFBA and PFHxA in both larvae and cells. Toxicity trends were similar among different aquatic models, but sensitivities varied. Discrepancies with other zebrafish studies were confirmed to be associated with a lack of neutralization of acidic pH of dosing solutions in these other investigations, demonstrating the need for rigor in reporting pH of exposure solutions in all experiments. The zebrafish embryonic cell line was also found to be similar to most other cell lines regardless of exposure length. Overall, results agree with findings in other cell lines and organisms where longer chain length and sulfonate group increase toxicity, except in investigations not neutralizing the exposure solutions for these acidic compounds.

Application of a Framework for Grouping and Mixtures Toxicity Assessment of PFAS: A Closer Examination of Dose-Additivity Approaches

Environmental occurrence and biomonitoring data for per- and polyfluoroalkyl substances (PFAS) demonstrate that humans are exposed to mixtures of PFAS. This article presents a new and systematic analysis of available PFAS toxicity study data using a tiered mixtures risk assessment framework consistent with United States and international mixtures guidance. The lines of evidence presented herein include a critique of whole mixture toxicity studies and analysis of dose-response models based on data from subchronic oral toxicity studies in rats. Based on available data to-date, concentration addition and relative potency factor methods are found to be inappropriate due to differences among sensitive effects and target organ potencies and noncongruent dose-response curves for the same effect endpoints from studies using the same species and protocols. Perfluorooctanoic acid and perfluorooctane sulfonic acid lack a single mode of action or molecular initiating event and our evaluation herein shows they also have noncongruent dose-response curves. Dose-response curves for long-chain perfluoroalkyl sulfonic acids (PFSAs) also significantly differ in shapes of the curves from short-chain PFSAs and perfluoroalkyl carboxylic acids evaluated, and additional differences are apparent when curves are evaluated based on internal or administered dose. Following well-established guidance, the hazard index method applied to perfluoroalkyl carboxylic acids and PFSAs grouped separately is the most appropriate approach for conducting a screening level risk assessment for nonpolymeric PFAS mixtures, given the current state-of-the science. A clear presentation of assumptions, uncertainties, and data gaps is needed before dose-additivity methods, including hazard index , are used to support risk management decisions. Adverse outcome pathway(s) and mode(s) of action information for perfluorooctanoic acid and perfluorooctane sulfonic acid and for other nonpolymer PFAS are key data gaps precluding more robust mixtures methods. These findings can guide the prioritization of future studies on single chemical and whole mixture toxicity studies.

Risk Characterization and Probabilistic Concentration-Response Modeling of Complex Environmental Mixtures Using New Approach Methodologies (NAMs) Data from Organotypic in Vitro Human Stem Cell Assays

BACKGROUND

Risk assessment of chemical mixtures or complex substances remains a major methodological challenge due to lack of available hazard or exposure data. Therefore, risk assessors usually infer hazard or risk from data on the subset of constituents with available toxicity values.

OBJECTIVES

We evaluated the validity of the widely used traditional mixtures risk assessment paradigms, Independent Action (IA) and Concentration Addition (CA), with new approach methodologies (NAMs) data from human cell-based in vitro assays.

METHODS

A diverse set of 42 chemicals was tested both individually and as mixtures for functional and cytotoxic effects in vitro. A panel of induced pluripotent stem cell (iPSCs)-derived models (hepatocytes, cardiomyocytes, endothelial, and neurons) and one primary cell type (HUVEC) were used. Bayesian concentration-response modeling of individual chemicals or their mixtures was performed for a total of 47 phenotypes to derive point-of-departure (POD) values. Probabilistic IA or CA was conducted to estimate the mixture effects based on the bioactivity profiles from the individual chemicals and compared with mixture bioactivity.

RESULTS

All mixtures showed significant bioactivity, even though some were constructed using individual chemical concentrations considered "low" or "safe." Even though CA is much more accurate as a predictor of mixture effects in comparison with IA, with CA-based POD typically within an order of magnitude of the actual mixture, in some cases, the bioactivity of the mixtures appeared to be much greater than that of their components under either additivity assumption.

DISCUSSION

These results suggest that CA is a preferred first approximation for predicting mixture toxicity when data for all constituents are available. However, because the accuracy of additivity assumptions varies greatly across phenotypes, we posit that mixtures and complex substances need to be directly tested for their hazard potential. NAMs provide a practical solution that rapidly yields highly informative data for mixtures risk assessment. https://doi.org/10.1289/EHP7600.

Per- and polyfluoroalkyl substances in soil and sediments: Occurrence, fate, remediation and future outlook

Perfluoroalkyl and polyfluoroalkyl substances (PFASs) are contaminants of great concern due to their wide-spread occurrence and persistence in the environments (i.e., in water, soil and sediment) and potential toxicology even at very low concentration. The main focus of this review is on the PFASs in soil and sediments. More specifically, this review systematically examines the occurrence and toxicological effects with associated risks, fate (i.e., PFASs adsorption by soil and sediment, transportation and transformation, and bioaccumulation), and remediation practices of PFASs in soil and sediment. Various models and equations such as fugacity-based multimedia fate and hydrodynamic models are used to study the fate, transport, and transformation of PFASs. Among different remediation practices, sorption is the dominant process for the removal of PFASs from soil and sediments. Results also indicate that PFASs adsorption onto activated carbon decrease with the increase of carbon chain length in the PFASs. The longer-chain PFASs have larger partition coefficient values than shorter-chained PFASs. Sorption of PFASs to soil and sediments are mainly governed by different electrostatic interactions, hydrogen bonds formation, hydrophobic interactions, organic content in soil and sediments, and ligand exchange. Other technology such as thermal treatment might be potential in the removal of PAFSs, but need further study to elucidate a conclusion. Finally, the associated challenges and future outlook have been included.

Radioanalytical Techniques to Quantitatively Assess the Biological Uptake and In Vivo Behavior of Hazardous Substances

Concern about environmental exposure to hazardous substances has grown over the past several decades, because these substances have adverse effects on human health. Methods used to monitor the biological uptake of hazardous substances and their spatiotemporal behavior in vivo must be accurate and reliable. Recent advances in radiolabeling chemistry and radioanalytical methodologies have facilitated the quantitative analysis of toxic substances, and whole-body imaging can be achieved using nuclear imaging instruments. Herein, we review recent literature on the radioanalytical methods used to study the biological distribution, changes in the uptake and accumulation of hazardous substances, including industrial chemicals, nanomaterials, and microorganisms. We begin with an overview of the radioisotopes used to prepare radiotracers for in vivo experiments. We then summarize the results of molecular imaging studies involving radiolabeled toxins and their quantitative assessment. We conclude the review with perspectives on the use of radioanalytical methods for future environmental research.

Mathematical Modeling Approaches for Assessing the Joint Toxicity of Chemical Mixtures Based on Luminescent Bacteria: A Systematic Review

Developments in industrial applications inevitably accelerate the discharge of enormous substances into the environment, whereas multi-component mixtures commonly cause joint toxicity which is distinct from the simple sum of independent effect. Thus, ecotoxicological assessment, by luminescent bioassays has recently brought increasing attention to overcome the environmental risks. Based on the above viewpoint, this review included a brief introduction to the occurrence and characteristics of toxic bioassay based on the luminescent bacteria. In order to assess the environmental risk of mixtures, a series of models for the prediction of the joint effect of multi-component mixtures have been summarized and discussed in-depth. Among them, Quantitative Structure-Activity Relationship (QSAR) method which was widely applied in silico has been described in detail. Furthermore, the reported potential mechanisms of joint toxicity on the luminescent bacteria were also overviewed, including the Trojan-horse type mechanism, funnel hypothesis, and fishing hypothesis. The future perspectives toward the development and application of toxicity assessment based on luminescent bacteria were proposed.

Combined effects and toxicological interactions of perfluoroalkyl and polyfluoroalkyl substances mixtures in human liver cells (HepG2)

The combined effects and toxicological interactions of perfluoroalkyl and polyfluoroalkyl substances (PFAS) mixtures remain largely unknown even though they occur as complex mixtures in the environment. This study investigated the toxicity of individual and combined PFAS to human liver cell line (HepG2). The Combination Index (CI)-isobologram equation method was used to determine the toxicological interactions of PFAS in binary, ternary and multi-component mixtures. The results indicated that the cytotoxicity of individual PFAS to HepG2 cells increased with increasing carbon chain lengths when separated into non-sulfonated and sulfonated groups. The respective cytotoxicity of PFAS is in the order of PFDA > PFNA > PFOA > PFHpA for perfluoroalkyl carboxylic acids and in the order of PFOS > PFHxS for perfluoroalkane sulfonic acids. The toxicological interaction of PFOS and PFOA with other PFAS clearly showed a different pattern of combined toxicity in HepG2 Cells. The binary, ternary, and multi-component combinations of PFOS with PFOA, PFNA, PFDA, PFHxS, and PFHpA displayed synergistic interactions for almost all inhibitory effect levels tested, whereas, either synergistic or antagonistic effect was observed in mixtures with PFOA. Overall, the pattern of interactions of PFAS mixtures is predominated by synergism, especially at low to medium effect levels; the exceptions to this were the antagonistic interactions found in mixture with PFOA, PFHxS, and PFHpA. These cytotoxicity results may have an implication on the health risk assessment of PFAS mixtures.

Prenatal exposure to per- and polyfluoroalkyl substances and maternal and neonatal thyroid function in the Project Viva Cohort: A mixtures approach

BACKGROUND

Maternal and neonatal thyroid function is critical for growth and neurodevelopment. Exposure to individual per- and polyfluoroalkyl substances (PFAS) can alter circulating thyroid hormone levels, but few studies have investigated effects of combined exposure to multiple PFAS.

OBJECTIVES

Estimate associations of exposure to multiple PFAS during early pregnancy with maternal and neonatal thyroid function.

METHODS

The study population consisted of 726 mothers and 465 neonates from Project Viva, a Boston, Massachusetts area longitudinal pre-birth cohort. We measured six PFAS [perfluorooctanoate (PFOA), perfluorooctane sulfonate (PFOS), perfluorononanoate (PFNA), perfluorohexane sulfonate (PFHxS), 2-(N-ethyl-perfluorooctane sulfonamido)acetate (EtFOSAA), and 2-(N-methyl-perfluorooctane sulfonamido)acetate (MeFOSAA)] and thyroxine (T₄), Free T₄ Index (FT₄I), and thyroid stimulating hormone (TSH) in maternal plasma samples collected during early pregnancy, and neonatal T₄ in postpartum heel sticks. We estimated individual and joint effects of PFAS exposure with thyroid hormone levels using weighted quantile sum (WQS) regression and Bayesian kernel machine regression (BKMR), and evaluated potential non-linearity and interactions among PFAS using BKMR.

RESULTS

Higher concentrations of the PFAS mixture were associated with significantly lower maternal FT₄I, with MeFOSAA, EtFOSAA, PFOA, and PFHxS contributing most to the overall mixture effect in BKMR and WQS regression. In infants, higher concentrations of the PFAS mixture were associated with lower T₄ levels, primarily in males, with PFHxS and MeFOSAA contributing most in WQS, and PFHxS contributing most in BKMR. The PFAS mixture was not associated with maternal T₄ or TSH levels. However, in maternal BKMR analyses, ln-PFOS was positively associated with T₄ levels (Δ25^th to 75th percentile: 0.21 µg/dL; 95% credible interval: -0.03, 0.47) and ln-PFHxS was associated with a non-linear effect on TSH levels.

CONCLUSIONS

These findings support the hypothesis that there may be combined effects of prenatal exposure to multiple PFAS on maternal and neonatal thyroid function, but the direction and magnitude of these effects may vary across individual PFAS.

Using Machine Learning to Classify Bioactivity for 3486 Per- and Polyfluoroalkyl Substances (PFASs) from the OECD List

A recent OECD report estimated that more than 4000 per- and polyfluorinated alkyl substances (PFASs) have been produced and used in a broad range of industrial and consumer applications. However, little is known about the potential hazards (e.g., bioactivity, bioaccumulation, and toxicity) of most PFASs. Here, we built machine-learning-based quantitative structure-activity relationship (QSAR) models to predict the bioactivity of those PFASs. By examining a number of available molecular data sets, we constructed the first PFAS-specific database that contains the bioactivity information on 1012 PFASs for 26 bioassays. On the basis of the collected PFAS data set, we trained 5 different machine learning models that cover a variety of conventional models (e.g., random forest and multitask neural network (MNN)) and advanced graph-based models (e.g., graph convolutional network). Those models were evaluated based on the validation data set. Both MNN and graph-based models demonstrated the best performance. The average of the best area-under-the-curve score for each bioassay is 0.916. For predictions on the OECD list, most of the biologically active PFASs have perfluoroalkyl chain lengths less than 12 and are categorized into fluorotelomer-related compounds and perfluoroalkyl acids and their precursors.

Isobologram Analysis: A Comprehensive Review of Methodology and Current Research

Drug combination is a common method for clinical disease treatment. Whether the combination of drugs is reasonable often affects the result of the disease treatment. Many methods have been used to evaluate interaction between drugs to date. Isobologram analysis has been mathematically proven and widely used to evaluate drug interactions. In this paper, the principle of isobologram analysis and its application in drug interaction evaluation are summarized. The applications of the similar cotoxicity coefficient and fractional inhibitory concentration index in the evaluation of drug interaction are also reviewed. This work is expected to evaluate the effect of formulations scientifically and provide scientific judgment standards for the development of formulations and clinical drug compatibility.