Physiologically Based Toxicokinetic Modeling of Bisphenols in Zebrafish (Danio rerio) Accounting for Variations in Metabolic Rates, Brain Distribution, and Liver Accumulation

Predictive modeling and interpretability analysis of bioconcentration factors for organic chemicals in fish using machine learning

Chemicals are misused and released into the environment, causing adverse effects on people and ecosystems. Assessing the potential environmental risks of these chemicals before their use is crucial. The bioconcentration factor (BCF) is a key parameter used to describe the extent of chemical bioaccumulation. However, previous experiments to determine BCF values are often time-consuming and costly. In this study, a machine learning (ML) model was developed to predict BCF values using molecular descriptors and 9 algorithms. The random forest (RF) model demonstrated strong predictive performance, achieving Rtrain2 and Rtest2 values of 0.949 and 0.935. Moreover, it required only 10 easily obtainable features. The Tanimoto similarity coefficient based on molecular structure was used to characterize the applicability domain (AD). We employed SHAP method, which identified primary factors, including hydrophobicity, molecular volume and shape, polarizability and lipophilicity, that have significantly affected BCF values. Furthermore, partial dependence plots (PDP) and 2D interaction were utilized to delve deeper into the relationship between feature values and model predictions. Results showed that MollogP>4.5, SM1_Dzv>0, SM1_Dzp>0, and ZM1C1>35 were linked to higher lgBCF values (3.2 L/kg), indicating stronger bioconcentration potential. Conversely, under other conditions that suggested weaker bioconcentration capacities, the focus should move to environmental migration. The study provided valuable insights into the factors that influence the bioaccumulation of chemicals, while the RF models can be an effective tool for assessing the bioconcentration potential of chemicals.

Construction of carboxyl-functionalized hyper-cross-linked porous polymers using waste polystyrene for effective adsorption of phenolic contaminants

The extensive presence of phenolic organic contaminants (POCs) poses a serious threat to humans. Meanwhile, the upcycling/reusing of waste polystyrene to reduce the exponential growth of plastic pollution is a very important environmental issue. Addressing these demands, a series of carboxyl-functional hypercrosslinked polymers (labeled PP-HCPs) were constructed by knitting waste polystyrene with pyromellitic dianhydride at different ratios through a one-step Friedel-Crafts reaction for effective adsorption of POCs. Among the prepared PP-HCPs, PP-HCP2 displayed a large specific surface area with high adsorption capacity (37.3 mg g-1) for POCs. Using PP-HCP2 as solid phase extraction sorbent, six POCs were effectively extracted from water and peach drink samples, then subjected to high-performance liquid chromatography-ultraviolet detection. The method demonstrated good linearity in the range of 0.03-100.0 ng mL-1 for water samples and 0.06-100.0 ng mL-1 for peach drinks under optimum experimental conditions. At a signal-to-noise ratio of 3, low detection limits were found to be 0.01-0.10 ng mL-1 for water samples and 0.02-0.15 ng mL-1 for peach drinks. Good accuracy and repeatability were achieved with recoveries of 85.3-111.8 % and the relative standard deviations below 8.6 %. The PP-HCP2-based approach can be employed as a dependable and sensitive tool to detect POCs in water and peach drink samples. This work delivers a simple and economically viable approach to fabricate carboxyl-functional HCPs by converting waste foam into high-value-added sorbent, with great significance for sustainable development.

Chemical risk assessment in food animals via physiologically based pharmacokinetic modeling - Part II: Environmental pollutants on animal and human health assessments

Human activities generate a large amount of environmental pollutants, including drugs and agricultural and industrial chemicals that are released into the air, water, and soil. Environmental pollutants can enter food animals through contaminated feed and water, posing risks to human health via the food chain. Physiologically based pharmacokinetic (PBPK) modeling is used to predict the target organ dosimetry informing human health risk assessment. However, there is a lack of critical reviews concerning PBPK models for environmental pollutants in food animals in the last several years (2020-2024). This review is part of a series of reviews focusing on applications of PBPK models for drugs and environmental chemicals in food animals to inform human health and food safety assessments. Part I is focused on veterinary drugs. The present article is Part II and focuses on environmental chemicals, including pesticides, polychlorinated biphenyls (PCBs), bisphenols, and per- and polyfluoroalkyl substances (PFAS). This article discusses the existing challenges in developing PBPK models for environmental pollutants and shares our perspectives on future directions, including the combinations of in vitro to in vivo extrapolation (IVIVE), machine learning and artificial intelligence, read-across approaches, and quantitative pharmacodynamic modeling to enhance the potential applications of PBPK models in assessing human health and food safety.

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.

Exposure and hazard of bisphenol A, S and F: a multi-biomarker approach in three-spined stickleback

Due to the estrogenic behavior of bisphenol (BP) A, industries have developed many substitutes, such as BPS and BPF. However, due to their structural similarities, adverse effects on reproduction are currently observed in various organisms, including fish. Even if new results have shown impacts of these bisphenols on many other physiological functions, their mode of action remains unclear. In this context, we proposed to better understand the impact of BPA, BPS, and BPF on immune responses (leucocyte sub-populations, cell death, respiratory burst, lysosomal presence, and phagocytic activity) and on biomarkers of metabolic detoxification (ethoxyresorufin-O-deethylase, EROD, and glutathione S-transferase, GST) and oxidative stress (glutathione peroxidase, GPx, and lipid peroxidation with thiobarbituric acid reactive substance method, TBARS) in an adult sentinel fish species, the three-spined stickleback. In order to enhance our understanding of how biomarkers change over time, it is essential to determine the internal concentration responsible for the observed responses. Therefore, it is necessary to explore the toxicokinetics of bisphenols. Thus, sticklebacks were exposed either to 100 μg/L of BPA, BPF or BPS for 21 days, or for seven days to 10 and 100 μg/L of BPA or BPS followed by seven days of depuration. Although BPS has very different TK, due to its lower bioaccumulation compared to BPA and BPF, BPS affect oxidative stress and phagocytic activity in the same way. For those reasons, the replacement of BPA by any substitute should be made carefully in terms of risk assessment on aquatic ecosystems.

Interaction of GPER-1 with the endocrine signaling axis in breast cancer

G Protein-Coupled Estrogen Receptor 1 (GPER-1) is a membrane estrogen receptor that has emerged as a key player in breast cancer development and progression. In addition to its direct influence on estrogen signaling, a crucial interaction between GPER-1 and the hypothalamic-pituitary-gonadal (HPG) axis has been evidenced. The novel and complex relationship between GPER-1 and HPG implies a hormonal regulation with important homeostatic effects on general organ development and reproductive tissues, but also on the pathophysiology of cancer, especially breast cancer. Recent research points to a great versatility of GPER-1, interacting with classical estrogen receptors and with signaling pathways related to inflammation. Importantly, through its activation by environmental and synthetic estrogens, GPER-1 is associated with hormone therapy resistance in breast cancer. These findings open new perspectives in the understanding of breast tumor development and raise the possibility of future applications in the design of more personalized and effective therapeutic approaches.

Construction of interpretable ensemble learning models for predicting bioaccumulation parameters of organic chemicals in fish

Accurate prediction of bioaccumulation parameters is essential for assessing exposure, hazards, and risks of chemicals. However, the majority of prediction models on bioaccumulation parameters are individual models based on a single algorithm and lack model interpretation, resulting in unsatisfactory prediction accuracy due to inherent constraints of the algorithm and weak interpretability. Ensemble learning (EL) that combine multiple algorithms, coupled with SHapley Additive exPlanation (SHAP) method, may overcome the limitations. Herein, EL models were constructed for three bioaccumulation parameters using datasets covering 2496 chemicals. The EL models demonstrated superior prediction accuracy compared to both individual models developed in this study and those from previous research, achieving a coefficient of determination of up to 0.861 on the validation sets. Applicability domains were characterized using a structure-activity landscape-based (abbreviated as ADSAL) methodology. The optimal EL models, together with the ADSAL, were successfully used to predict bioaccumulation parameters for 4374 chemicals included in the Inventory of Existing Chemical Substances of China. Model interpretation using the SHAP method offered insight into key features influencing bioaccumulation potential, including hydrophobicity, water solubility, polarizability, ionization potential, weight, and volume of molecules. Overall, the study provides data and models to support the sound management and risk assessment of chemicals.

Enantioselective ecotoxicity of promethazine in two freshwater organisms: daphnia (Daphnia magna) and zebrafish (Danio rerio)

Chiral pharmaceuticals, racemic or enantiomerically pure forms and their metabolites, can reach aquatic ecosystems via wastewater effluents (inefficient treatment operations) or by direct human disposal. They may negatively affect nontarget organisms even at low environmental concentrations. To make an accurate risk evaluation, the (eco)toxicity of both enantiomers needs to be assessed. Promethazine (PMZ) is a chiral antihistamine that has been detected in aquatic ecosystems owing to its high consumption. Promethazine undergoes metabolism in the liver, producing chiral metabolites such as promethazine sulfoxide (PMZSO) and N-desmethylpromethazine (DMPMZ) that reach water bodies. However, knowledge regarding the enantioselective toxicity of PMZ and its metabolites on aquatic organisms is missing. This study aimed to explore the potential enantioselective toxicity of PMZ and its metabolites on two relevant freshwater organisms, daphniid and fish, representing different trophic levels. The half maximal effect concentrations (EC50s) in Daphnia magna of PMZ, DMPMZ, and PMZSO were 2.33, 2.31, > 4 mg L-1, respectively, > 4 and 2.50 mg L-1 for (R) and (S)-PMZ, respectively, and > 4 mg L-1 for the enantiomers of DMPMZ and PMZSO. In studies involving zebrafish, Danio rerio, (R, S)-PMZ showed a median lethal concentration (LC50) of .72 mg L-1, and specific assays revealed that (R)-PMZ exhibited more pronounced adverse effects on larvae at the embryonic, morphological, and biochemical level than the racemate and (S)-PMZ. Toxicity and potential bioaccumulation of these compounds in daphniids and fish were also conducted using in silico tests through proprietary software. The results revealed a concordance between the experimental and predicted EC50 and LC50 values in both species.

Cyano-functionalized porous hyper-crosslinked cationic polymers for efficient preconcentration and detection of phenolic endocrine disruptors in fresh water and fish

Sensitively analyzing phenolic endocrine-disrupting chemicals (EDCs) in environmental substrates and aquatic organisms provides a significant challenge. Here, we developed a novel porous hyper-crosslinked ionic polymer bearing cyano groups (CN-HIP) as adsorbent for the highly efficient solid phase extraction (SPE) of phenolic EDCs in water and fish. The CN-HIP gave an excellent adsorption capability for targeted EDCs over a wide pH range, and the adsorption capacity was superior to that of several common commercial SPE adsorbents. The coexistence of electrostatic forces, hydrogen bond, and π-π interactions was confirmed as the main adsorption mechanism. A sensitive quantitative method was established by coupling CN-HIP based SPE method with high-performance liquid chromatography for the simultaneously determining trace bisphenol A, bisphenol F, bisphenol B and 4-tert-butylphenol in fresh water and fish. The method afforded lower detection limits (S/N = 3) (at 0.03-0.10 ng mL-1 for water and 0.8-4.0 ng g-1 for fish), high accuracy (the recovery of spiked sample at 88.0%-112 %) and high precision (the relative standard deviation < 8.5 %). This work provides a feasible method for detecting phenolic EDCs, and also opens a new perspective in developing functionalized cationic adsorbent.

Quantification of additives in beached plastic debris from Aotearoa New Zealand

Plastics have become an essential part of modern society. Their properties can be easily manipulated by incorporating additives to impart desirable attributes, such as colour, flexibility, or stability. However, many additives are classified as hazardous substances. To better understand the risk of plastic pollution within marine ecosystems, the type and concentration of additives in plastic debris needs to be established. We report the quantification of thirty-one common plastic additives (including plasticisers, antioxidants, and UV stabilisers) in beached plastic debris collected across Aotearoa New Zealand. Additives were isolated from the plastic debris by solvent extraction and quantified using high-resolution liquid chromatography-mass spectrometry. Twenty-five of the target additives were detected across 200 items of debris, with plasticisers detected at the highest frequency (99 % detection frequency). Additives were detected in all samples, with a median of four additives per debris item. A significantly higher number of additives were detected per debris item for polyvinyl chloride (median = 7) than polyethylene or polypropylene (median = 4). The additives bis(2-ethylhexyl) phthalate, diisononyl phthalate, diisodecyl phthalate, and antioxidant 702 were detected at the highest concentrations (up to 196,930 μg/g). The sum concentration of additives per debris item (up to 320,325 μg/g) was significantly higher in polyvinyl chloride plastics (median 94,716 μg/g) compared to other plastic types, primarily due to the presence of phthalate plasticisers. Non-target analysis was consistent with the targeted analysis, indicating a higher number and concentration of additives in polyvinyl chloride debris items compared to all other polymer types. Feature identification indicated the presence of more additives than previously detected in the targeted analysis, including plasticisers (phthalate and non-phthalate), processing aids, and nucleating agents. This study highlights phthalates and polyvinyl chloride as key targets for consideration in ecotoxicology and risk assessments, and the development of policies to reduce the impacts of plastic pollution.

Application of machine learning in the study of development, behavior, nerve, and genotoxicity of zebrafish

Machine learning (ML) as a novel model-based approach has been used in studying aquatic toxicology in the environmental field. Zebrafish, as an ideal model organism in aquatic toxicology research, has been widely used to study the toxic effects of various pollutants. However, toxicity testing on organisms may cause significant harm, consume considerable time and resources, and raise ethical concerns. Therefore, ML is used in related research to reduce animal experiments and assist researchers in conducting toxicological research. Although ML techniques have matured in various fields, research on ML-based aquatic toxicology is still in its infancy due to the lack of comprehensive large-scale toxicity databases for environmental pollutants and model organisms. Therefore, to better understand the recent research progress of ML in studying the development, behavior, nerve, and genotoxicity of zebrafish, this review mainly focuses on using ML modeling to assess and predict the toxic effects of zebrafish exposure to different toxic chemicals. Meanwhile, the opportunities and challenges faced by ML in the field of toxicology were analyzed. Finally, suggestions and perspectives were proposed for the toxicity studies of ML on zebrafish in future applications.

Assessing dietary bisphenol A exposure among Koreans: comprehensive database construction and analysis using the Korea National Health and Nutrition Examination Survey

Bisphenol A (BPA) exposure primarily occurs through dietary intake. This study aimed to estimate the extent of dietary BPA exposure among Koreans. A thorough literature search was conducted to establish a BPA content database encompassing common foods consumed in Korea, including various food raw materials and processed food products. Dietary exposure levels were estimated by integrating the constructed BPA database with comprehensive nationwide 24 h-dietary recall datasets. The finding revealed that dietary BPA exposure was low for most Koreans, with a mean of 14.5 ng/kg bw/day, but was higher for preschool-age children (over 23 ng). Canned foods accounted for 9-36% of the total dietary exposure of the highest dietary exposure groups; while across all age groups, a considerable amount was derived from canned tuna, contribution of canned fruits and canned coffee (milk-containing) was high for preschool-age children and adults, respectively. Notably, for adults, a substantial proportion also stemmed from beer packaged in cans. While diet contributed over 80% of aggregate exposure for most age groups, preschool-age children experienced 60% exposure through diet due to additional exposure from indoor dust. Even at the high exposure scenario, aggregate BPA exposure levels remained lower than the current tolerable daily intake (TDI) set by the Korean agency (20 μg/kg bw/day). Nevertheless, most Koreans were exposed to BPA levels surpassing the strictest TDI (0.2 ng/kg bw/day) set by the European Food Safety Authority.

Imazalil and prochloraz toxicokinetics in fish probed by a physiologically based kinetic (PBK) model

Azole fungicides are highly suspected endocrine disruptors (EDs) and are frequently detected in surface water. Among them, there are prochloraz (PCZ), a commonly used  molecule for ED studies, and imazalil (IMZ), a highly suspected ED. Little is known about their toxicokinetic (TK) behavior in fish. Hence, research suggested that an improved risk assessment could be achieved by gaining insight into their TK behavior. The aim of this study is to understand and model the TK of both substances in different fish species, irrespective of the scheme of exposure. TK data from the literature were retrieved including different modes of exposure (per os and waterborne). In addition, two experiments on zebrafish exposed to either IMZ or PCZ were performed to address the lack of in vivo TK data. A physiologically based kinetic (PBK) model applied to IMZ and PCZ was developed, capable of modeling different exposure scenarios. The parameters of the PBK model were simultaneously calibrated on datasets reporting internal concentration in several organs in three fish species (original and literature datasets) by Bayesian methods (Monte Carlo Markov Chain). Model predictions were then compared to other experimental data (i.e., excluded from the calibration step) to assess the predictive performance of the model. The results strongly suggest that PCZ and IMZ are actively transported across the gills, resulting in a small fraction being effectively absorbed by the fish. The model's results also confirm that both molecules are extensively metabolized by the liver into mainly glucuronate conjugates. Overall, the model performances were satisfying, predicting internal concentrations in several key organs. On average, 90% of experimental data were predicted within a two-fold range. The PBK model allows the understanding of IMZ and PCZ kinetics profiles by accurately predicting internal concentrations in three different fish species regardless of the exposure scenario. This enables a proper understanding of the mechanism of action of EDs at the molecular initiating event (MIE) by predicting bioaccumulation in target organs, thus linking this MIE to a possible adverse outcome.

A Comparative Study of Phase I and II Hepatic Microsomal Biotransformation of Phenol in Three Species of Salmonidae: Hydroquinone, Catechol, and Phenylglucuronide Formation

The in vitro biotransformation of phenol at 11 °C was studied using pre-spawn adult rainbow (Oncorhynchus mykiss) (RBT), brook (Salvelinus fontinalis) (BKT), and lake trout (Salvelinus namaycush) (LKT) hepatic microsomal preparations. The incubations were optimized for time, cofactor concentration, pH, and microsomal protein concentration. Formation of Phase I ring-hydroxylation and Phase II glucuronidation metabolites was quantified using HPLC with dual-channel electrochemical and UV detection. The biotransformation of phenol over a range of substrate concentrations (1 to 180 mM) was quantified, and the Michaelis-Menten kinetics constants, Km and Vmax, for the formation of hydroquinone (HQ), catechol (CAT), and phenylglucuronide (PG) were calculated. Species differences were noted in the Km values for Phase I enzyme production of HQ and CAT, with the following rank order of apparent enzyme affinity for substrate: RBT > BKT = LKT. However, no apparent differences in the Km for Phase II metabolism of phenol to PG were detected. Conversely, while there were no apparent differences in Vmax between species for HQ or CAT formation, the apparent maximum capacity for PG formation was significantly less in LKT than that observed for RBT and BKT. These experiments provide a means to quantify metabolic activation and deactivation of xenobiotics in fish, to compare activation and deactivation reactions across species, and to act as a guide for future predictions of new chemical biotransformation pathways and rates in fish. These experiments provided the necessary rate and capacity (Km and Vmax) inputs that are required to parameterize a fish physiologically based toxicokinetic (PB-TK) model for a reactive chemical that is readily biotransformed, such as phenol. In the future, an extensive database of these rate and capacity parameters on important fish species for selected chemical structures will be needed to allow the effective use of predictive models for reactive, biotransformation chemicals in aquatic toxicology and environmental risk assessment.

Exposure to resorcinol bis (diphenyl phosphate) induces colonization of alien microorganisms with potential impacts on the gut microbiota and metabolic disruption in male zebrafish

Organophosphate esters (OPEs) have been demonstrated to induce various forms of toxicity in aquatic organisms. However, a scarcity of evidence impedes the conclusive determination of whether OPEs manifest sex-dependent toxic effects. Here, we investigated the effects of tris (1-chloro-2-propyl) phosphate (TCPP) and resorcinol bis (diphenyl phosphate) (RDP) on the intestines of both female and male zebrafish. The results indicated that, in comparison to TCPP, RDP induced more pronounced intestinal microstructural damage and oxidative stress, particularly in male zebrafish. 16S rRNA sequencing and metabolomics revealed significant alterations in the species richness and oxidative stress-related metabolites in the intestinal microbiota of zebrafish under exposure to both TCPP and RDP, manifesting gender-specific effects. Based on differential species analysis, we defined invasive species and applied invasion theory to analyze the reasons for changes in the male fish intestinal community. Correlation analysis demonstrated that alien species may have potential effects on metabolism. Overall, this study reveals a pronounced gender-dependent impact on both the intestinal microbiota and metabolic disruptions of zebrafish due to OPEs exposure and offers a novel perspective on the influence of pollutants on intestinal microbial communities and metabolism.

Exploring BPA alternatives - Environmental levels and toxicity review

Bisphenol A alternatives are manufactured as potentially less harmful substitutes of bisphenol A (BPA) that offer similar functionality. These alternatives are already in the market, entering the environment and thus raising ecological concerns. However, it can be expected that levels of BPA alternatives will dominate in the future, they are limited information on their environmental safety. The EU PARC project highlights BPA alternatives as priority chemicals and consolidates information on BPA alternatives, with a focus on environmental relevance and on the identification of the research gaps. The review highlighted aspects and future perspectives. In brief, an extension of environmental monitoring is crucial, extending it to cover BPA alternatives to track their levels and facilitate the timely implementation of mitigation measures. The biological activity has been studied for BPA alternatives, but in a non-systematic way and prioritized a limited number of chemicals. For several BPA alternatives, the data has already provided substantial evidence regarding their potential harm to the environment. We stress the importance of conducting more comprehensive assessments that go beyond the traditional reproductive studies and focus on overlooked relevant endpoints. Future research should also consider mixture effects, realistic environmental concentrations, and the long-term consequences on biota and ecosystems.

Size-dependent vector effect of microplastics on the bioaccumulation of polychlorinated biphenyls in tilapia: A tissue-specific study

Microplastics play a significant role in interactions between organisms and hydrophobic organic contaminants (HOCs), leading to a joint toxic effect on aquatic organisms. This study extensively investigated the tissue-specific accumulation of polychlorinated biphenyls (PCBs) resulting from different sized microplastics in tilapia (Oreochromis mossambicus) using a passive dosing device. Based on biological feeding behavior considerations, 1 mm and 2 μm polystyrene (PS) microplastics with concentrations of 2 and 5 mg L-1 were investigated. A physiologically based toxicokinetic (PBTK) model was applied to evaluate the exchange kinetics and fluxes among the tissues. Moreover, an in vitro simulation experiment was conducted to theoretically validate the vector effect. The findings demonstrated that the effects caused by HOCs and microplastics on organisms were influenced by multiple factors such as size and surface properties. The mass transfer kinetics of HOCs in specific tissues were closely related to their adsorption capacity and position microplastics could reach. Specifically, although 2 μm microplastics exhibited high adsorption capacity for PCBs, they were only retained in the intestines and did not significantly contribute to the bioaccumulation of PCBs in gills or muscle. While 1 mm microplastics were ingested but just paused in the mouth and subsequently flew through the gills with oral mucus. Their vector effects increased the desorption of microplastic-bound PCB-118 in the gill mucus microcosm, thereby facilitating the mass transfer and accumulation of PCB-118 in gills and muscle. This study sheds new light on how the size-dependent vector generated by microplastics affects the tissue-specific accumulation of HOCs in aquatic organisms.

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.

Physiology-informed toxicokinetic model for the zebrafish embryo test developed for bisphenols

Zebrafish embryos (ZFE) is a widely used model organism, employed in various research fields including toxicology to assess e.g., developmental toxicity and endocrine disruption. Variation in effects between chemicals are difficult to compare using nominal dose as toxicokinetic properties may vary. Toxicokinetic (TK) modeling is a means to estimate internal exposure concentration or dose at target and to enable extrapolation between experimental conditions and species, thereby improving hazard assessment of potential pollutants. In this study we advance currently existing TK models for ZFE with physiological ZFE parameters and novel experimental bisphenol data, a class of chemicals with suspected endocrine activity. We developed a five-compartment model consisting of water, plastic, chorion, yolk sack and embryo in which surface area and volume changes as well as the processes of biotransformation and blood circulation influence mass fluxes. For model training and validation, we measured internal concentrations in ZFE exposed individually to BPA, bisphenol AF (BPAF) and Z (BPZ). Bayesian inference was applied for parameter calibration based on the training data set of BPZ. The calibrated TK model predicted internal ZFE concentrations of the majority of external test data within a 5-fold error and half of the data within a 2-fold error for bisphenols A, AF, F, and tetrabromo bisphenol A (TBBPA). We used the developed model to rank the hazard of seven bisphenols based on predicted internal concentrations and measured in vitro estrogenicity. This ranking indicated a higher hazard for BPAF, BPZ, bisphenol B and C (BPB, BPC) than for BPA.

Integrated Approach for Synthetic Cathinone Drug Prioritization and Risk Assessment: In Silico Approach and Sub-Chronic Studies in Daphnia magna and Tetrahymena thermophila

Synthetic cathinones (SC) are drugs of abuse that have been reported in wastewaters and rivers raising concern about potential hazards to non-target organisms. In this work, 44 SC were selected for in silico studies, and a group of five emerging SC was prioritized for further in vivo ecotoxicity studies: buphedrone (BPD), 3,4-dimethylmethcathinone (3,4-DMMC), butylone (BTL), 3-methylmethcathinone (3-MMC), and 3,4-methylenedioxypyrovalerone (MDPV). In vivo short-term exposures were performed with the protozoan Tetrahymena thermophila (28 h growth inhibition assay) and the microcrustacean Daphnia magna by checking different indicators of toxicity across life stage (8 days sublethal assay at 10.00 µg L-1). The in silico approaches predicted a higher toxic potential of MDPV and lower toxicity of BTL to the model organisms (green algae, protozoan, daphnia, and fish), regarding the selected SC for the in vivo experiments. The in vivo assays showed protozoan growth inhibition with MDPV > BPD > 3,4-DMMC, whereas no effects were observed for BTL and stimulation of growth was observed for 3-MMC. For daphnia, the responses were dependent on the substance and life stage. Briefly, all five SC interfered with the morphophysiological parameters of juveniles and/or adults. Changes in swimming behavior were observed for BPD and 3,4-DMMC, and reproductive parameters were affected by MDPV. Oxidative stress and changes in enzymatic activities were noted except for 3-MMC. Overall, the in silico data agreed with the in vivo protozoan experiments except for 3-MMC, whereas daphnia in vivo experiments showed that at sublethal concentrations, all selected SC interfered with different endpoints. This study shows the importance to assess SC ecotoxicity as it can distress aquatic species and interfere with food web ecology and ecosystem balance.