General model for estimating partition coefficients to organisms and their tissues using the biological compositions and polyparameter linear free energy relationships

Fugacity- and biotransformation-based mechanistic insights into the trophic transfer of organophosphate flame retardants in a subtropical coastal food web from the Northern Beibu Gulf of China

The bioaccumulation and trophic transfer of organophosphate flame retardants (OPFRs) in marine ecosystems have attracted great attention in recent research, but our understanding of the trophic transfer mechanisms involved is limited. In this study, we investigated the trophodynamics of OPFRs and their metabolites in a subtropical coastal food web collected from the northern Beibu Gulf, China, and characterized their trophodynamics using fugacity- and biotransformation-based approaches. Eleven OPFRs and all seven metabolites were simultaneously quantified in the shellfish, crustacean, pelagic fish, and benthic fish samples, with total concentrations ranging from 164 to 4.11 × 104 and 4.56-4.28 × 103 ng/g lipid weight, respectively. Significant biomagnification was observed only for tris (phenyl) phosphate (TPHP) and tris (2-ethylhexyl) phosphate (TEHP), while other compounds except for tris(2-chloroethyl) phosphate (TCEP) displayed biomagnification trends based on Monte Carlo simulations. Using a fugacity-based approach to normalize the accumulation of OPFRs in biota to their relative biological phase composition, storage lipid is the predominant biological phase for the mass distribution of 2-ethylhexyl diphenyl phosphate (EHDPHP) and TPHP. The water content and structure protein are equally important for TCEP, whereas lipid and structure protein are the two most important phases for other OPFRs. The mass distribution of these OPFRs along with TLs can explain their trophodynamics in the food web. The organophosphate diesters (as OPFR metabolites) also displayed biomagnification trends based on bootstrapped estimation. The correlation analysis and Korganism-water results jointly suggested the metabolites accumulation in high-TL organisms was related to biotransformation processes. The metabolite-backtracked trophic magnification factors for tri-n‑butyl phosphate (TNBP) and TPHP were both greater than the values that accounted for only the parent compounds. This study highlights the incorporation of fugacity and biotransformation analysis to characterize the trophodynamic processes of OPFRs and other emerging pollutants in food webs.

Screening for compounds with bioaccumulation potential in breast milk using their retention behavior in two-dimensional gas chromatography

Discovery of emerging pollutants in breast milk will be helpful for understanding the hazards to human health. However, it is difficult to identify key compounds among thousands present in complex samples. In this study, a method for screening compounds with bioaccumulation potential was developed. The method can decrease the number of compounds needing structural identification because the partitioning properties of bioaccumulative compounds can be mapped onto GC×GC chromatograms through their retention behaviors. Twenty pooled samples from seven provinces in China were analyzed. 1,286 compounds with bioaccumulation potential were selected from over 3,000 compounds. Sixty-two compounds, including aromatic compounds, phthalates, and phenolics etc., were identified with a high level of confidence and then quantified. Among them, twenty-seven compounds were found for the first time in breast milk. Three phthalate plasticizers and two phenolic antioxidants were found in significantly higher concentrations than other compounds. A toxicological priority index approach was applied to prioritize the compounds considering their concentrations, detection frequencies and eight toxic effects. The prioritization indicated that 13 compounds, including bis(2-ethylhexyl) phthalate, dibutyl phthalate, 1,3-di-tert-butylbenzene, phenanthrene, 2,6-di-tert-butyl-1,4-benzoquinone, 2,4-di-tert-butylphenol, and others, showed higher health risks. Meanwhile, some compounds with high risk for a particular toxic effect, such as benzothiazole and geranylacetone, were still noteworthy. This study is important for assessing the risks of human exposure to organic compounds.

Understanding the Impacts of Presystemic Metabolism on the Human Oral Bioavailability of Chemicals

Animal-free new approach methods promote chemical assessments based on the comparison between in vitro bioactivity and human internal concentrations, which necessitates a dependable knowledge of human oral bioavailability, i.e., the fraction of an orally ingested chemical that escapes from presystemic ("first-pass") metabolic processes and eventually enters systemic circulation. Using a physiologically based toxicokinetic model, we show how human oral bioavailability is impacted by presystemic metabolism within the gut lumen, gut wall, and liver and how this impact differs among chemicals with various permeability and stability properties. Our results highlight the gut lumen as a primary site of presystemic metabolism of certain chemicals, such as di-2-ethylhexyl phthalate (DEHP), for which the gut lumen may even exceed the liver in importance of presystemic metabolism due to these metabolic processes occurring in sequence. For chemicals with low transmembrane permeability and low stability, metabolism within the gut lumen is the most remarkable of the three presystemic metabolic processes. Notably, for chemicals that undergo substantial metabolism within the gut lumen, where the metabolites have high permeability, there is a notable discrepancy between the "theoretical bioavailability" (bioavailability of the unchanged parent compound) and the "apparent bioavailability" in measurement practices (bioavailability inferred from measured metabolites). Our work highlights the importance of considering presystemic metabolism, notably within the gut lumen, in human exposure and toxicokinetic modeling.

Mechanistic modelling of amphibian body burdens after dermal uptake of pesticides from soil

Amphibians are currently considered to be covered by pesticide Environmental Risk Assessment schemes by surrogacy assumptions of exposure and susceptibility based on typical laboratory test species such as fish, mammals, and birds. While multiple reviews have shown for this approach to be adequate in the case of aquatic stages, the same cannot be definitively stated for terrestrial stages. Concerns have risen that exposure of amphibians is likely to be highly influenced by dermal absorption, primarily due to the high permeability of their skin and the lack of a protective layer, such as fur or feathers. It is thus hypothesized that dermal uptake could be a significant route of exposure. Consequently, it is necessary to determine the relative importance of different exposure routes that might affect the integrated toxicity outcome for terrestrial amphibian life-stages. Here, a one-compartment Toxicokinetic model was derived and tested using a publicly available dataset containing relevant exposure and uptake information for juvenile anurans exposed to 13 different pesticides. Modelled body burdens were then compared to measured burdens for a total of 815 individuals. Overall, a good concordance between modelled and measured values was observed, with the predicted and measured body burdens differing by a factor of 2 on average (overall R2 of 0.80 and correlation coefficient of 0.89), suggesting good predictivity of the model. Accordingly, the model predicts realistic body burdens for a variety of frog and toad species, and overall, for anurans. As the model includes rehydration (implicit in the evaluated studies) but currently does not account for metabolism, it can be seen as a worst-case assessment. We suggest toxicokinetic models, such as the one here presented, could be used to characterize dermal exposure in amphibians, screen for pesticides of concern, and prioritize risk assessment efforts, whilst reducing the need for de novo vertebrate testing.

Organophosphate esters in edible marine fish: Tissue-specific distribution, species-specific bioaccumulation, and human exposure

Although growing evidences have proved the wide presence of organophosphate esters (OPEs) in marine environments, information on the tissue- and species-specific accumulation characteristics of these emerging pollutants in wild marine fish and the associated human exposure risks are currently lacking. Eleven OPEs were comprehensively investigated for their occurrence and tissue accumulation in 15 marine fish species and their living environment matrices (seawater and sediment) from the Beibu Gulf. The OPE concentrations were statistically higher in the liver (17.6-177 ng/g ww, mean 90.9 ± 52.1 ng/g ww) than those of muscle tissues (2.04-22.9 ng/g ww, mean 10.6 ± 5.6 ng/g ww). Tris (phenyl) phosphate (TPHP) was the most predominant OPE congeners in fish liver, and tris(2-chloropropyl) phosphate (TCIPP) and tris(2-chloroethyl) phosphate (TCEP) were dominant OPEs in the muscle. The results suggested different OPE profiles occurred between the tissues. The median logarithmic bioaccumulation factors (BAFs) of TPHP in the muscle and liver, and TCEP in muscle were higher than the regulatory benchmark value (BCF >3.7), indicating very strong bioaccumulation. Carnivorous benthic fish appear to potentially accumulate TPHP, while pelagic and omnivory fish tend to accumulate TCIPP and TCEP. Except for proteins and phospholipids, no significant relationships were found between OPE levels and other biological properties of the studied fish. The results implied that the species-specific accumulation of OPEs mainly attributed to habitat and feeding habit rather than the difference of biochemical composition among species. Metabolism may have a significant effect on the bioaccumulation of OPEs in marine fish. The dietary risks of OPEs for consumers in different age groups ranged from 2.02 × 10-4 to 3.01 × 10-3, indicating relatively low human exposure risks from fish consumption.

First insights into the bioaccumulation, biotransformation and trophic transfer of typical tetrabromobisphenol A (TBBPA) analogues along a simulated aquatic food chain

Tetrabromobisphenol A (TBBPA) analogues have been investigated for their prevalent occurrence in environments and potential hazardous effects to humans and wildlife; however, there is still limited knowledge regarding their toxicokinetics and trophic transfer in aquatic food chains. Using a developed toxicokinetic model framework, we quantified the bioaccumulation, biotransformation and trophic transfer of tetrabromobisphenol S (TBBPS) and tetrabromobisphenol A di(allyl ether) (TBBPA-DAE) during trophic transfer from brine shrimp (Artemia salina) to zebrafish (Danio rerio). The results showed that the two TBBPA analogues could be readily accumulated by brine shrimp, and the estimated bioconcentration factor (BCF) value of TBBPS (5.68 L kg-1 ww) was higher than that of TBBPA-DAE (1.04 L kg-1 ww). The assimilation efficiency (AE) of TBBPA-DAE in zebrafish fed brine shrimp was calculated to be 16.3%, resulting in a low whole-body biomagnification factor (BMF) in fish (0.684 g g-1 ww). Based on the transformation products screened using ultra-high-performance liquid chromatograph-high resolution mass spectrometry (UPLC-HRMS), oxidative debromination and hydrolysis were identified as the major transformation pathways of TBBPS, while the biotransformation of TBBPA-DAE mainly took place through ether bond breaking and phase-II metabolism. Lower accumulation of TBBPA as a metabolite than its parent chemical was observed in both brine shrimp and zebrafish, with metabolite parent concentration factors (MPCFs) < 1. The investigated BCFs for shrimp of the two TBBPA analogues were only 3.77 × 10-10 - 5.59 × 10-3 times of the theoretical Kshrimp-water based on the polyparameter linear free energy relationships (pp-LFERs) model, and the BMF of TBBPA-DAE for fish was 0.299 times of the predicted Kshrimp-fish. Overall, these results indicated the potential of the trophic transfer in bioaccumulation of specific TBBPA analogues in higher trophic-level aquatic organisms and pointed out biotransformation as an important mechanism in regulating their bioaccumulation processes. ENVIRONMENTAL IMPLICATION: The internal concentration of a pollutant in the body determines its toxicity to organisms, while bioaccumulation and trophic transfer play important roles in elucidating its risks to ecosystems. Tetrabromobisphenol A (TBBPA) analogues have been extensively investigated for their adverse effects on humans and wildlife; however, there is still limited knowledge regarding their toxicokinetics and trophic transfer in aquatic food chains. This study investigated the bioaccumulation, biotransformation and trophic transfer of TBBPS and TBBPA-DAE in a simulated di-trophic food chain. This state-of-art study will provide a reference for further research on this kind of emerging pollutant in aquatic environments.

Multimodal Model to Predict Tissue-to-Blood Partition Coefficients of Chemicals in Mammals and Fish

Tissue-to-blood partition coefficients (Ptb) are key parameters for assessing toxicokinetics of xenobiotics in organisms, yet their experimental data were lacking. Experimental methods for measuring Ptb values are inefficient, underscoring the urgent need for prediction models. However, most existing models failed to fully exploit Ptb data from diverse sources, and their applicability domain (AD) was limited. The current study developed a multimodal model capable of processing and integrating textual (categorical features) and numerical information (molecular descriptors/fingerprints) to simultaneously predict Ptb values across various species, tissues, blood matrices, and measurement methods. Artificial neural network algorithms with embedding layers were used for the multimodal modeling. The corresponding unimodal models were developed for comparison. Results showed that the multimodal model outperformed unimodal models. To enhance the reliability of the model, a method considering categorical features, weighted molecular similarity density, and weighted inconsistency in molecular activities of structure-activity landscapes was used to characterize the AD. The model constrained by the AD exhibited better prediction accuracy for the validation set, with the determination coefficient, root mean-square error, and mean absolute error being 0.843, 0.276, and 0.213 log units, respectively. The multimodal model coupled with the AD characterization can serve as an efficient tool for internal exposure assessment of chemicals.

Multi-task machine learning models for simultaneous prediction of tissue-to-blood partition coefficients of chemicals in mammals

Tissue-to-blood partition coefficients (Ptb) are crucial for assessing the distribution of chemicals in organisms. Given the lack of experimental data and laborious nature of experimental methods, there is an urgent need to develop efficient predictive models. With the help of machine learning algorithms, i,e., random forest (RF), and artificial neural network (ANN), this study developed multi-task (MT) models that can simultaneously predict Ptb values for various mammalian tissues, including liver, muscle, brain, lung, and adipose. Single-task (ST) models using partial least squares regression, RF, and ANN algorithms for each endpoint were established for comparison. Overall, the performances of MT models were superior to those of ST models. The MT model using ANN algorithms showed the highest prediction accuracy with determination coefficients ranging from 0.704 to 0.886, root mean square errors between 0.223 and 0.410, and mean absolute errors ranging from 0.178 to 0.285 log units. Results showed that lipophilicity and polarizability of molecules significantly influence their partition behavior in organisms. Applicability domains (ADs) of the models were characterized by weighted molecular similarity density, and weighted inconsistency in molecular activities of structure-activity landscapes. When constrained by ADs, the models displayed enhanced predictive accuracy, making them valuable tools for the risk assessment and management of chemicals.

Transfer of polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/Fs) and polychlorinated biphenyls (PCBs) from oral exposure into cow's milk - part II: toxicokinetic predictive models for risk assessment

Understanding the transfer of polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs) as well as polychlorinated biphenyls (PCBs) from oral exposure into cow's milk is not purely an experimental endeavour, as it has produced a large corpus of theoretical work. This work consists of a variety of predictive toxicokinetic models in the realms of health and environmental risk assessment and risk management. Their purpose is to provide mathematical predictive tools to organise and integrate knowledge on the absorption, distribution, metabolism and excretion processes. Toxicokinetic models are based on more than 50 years of transfer studies summarised in part I of this review series. Here in part II, several of these models are described and systematically classified with a focus on their applicability to risk analysis as well as their limitations. This part of the review highlights the opportunities and challenges along the way towards accurate, congener-specific predictive models applicable to changing animal breeds and husbandry conditions.

Predicting partitioning from low density polyethylene to blood and adipose tissue by linear solvation energy relationship models

The variety of polymers utilized in medical devices demands for testing of extractables and leachables according to ISO 10993-18:2020 in combination with ISO 10993-1:2018. The extraction of the materials involves the use of organic solvents as well as aqueous buffers to cover a wide range of polarity and pH-values, respectively. To estimate patient exposure to chemicals leaching from a polymer in direct body contact, simulating solvents are applied to best mimic the solubilization and partitioning behavior of the related tissue or body fluid. Here we apply linear solvation energy relationship (LSER) models to predict blood/water and adipose tissue/water partition coefficients. We suggest this predictive approach to project levels of potential leachables, design extraction experiments, and to identify the optimal composition of simulating extraction solvents. We compare our predictions to LSER predictions for commonly applied surrogates like ethanol/water mixtures, butanol, and octanol as well as olive oil, butanone, 1,4-dioxane for blood and adipose tissue, respectively. We therefore selected a set of 26 experimentally determined blood/water partition coefficients and 33 adipose tissue/water partition coefficients, where we demonstrate that based on the root mean squared error rmse the LSER approach performs better than surrogates like octanol or butanol and equally well as 60:40 ethanol/water for blood. For adipose tissue/water partitioning, the experimentally determined octanol/water partition coefficient performs best but the rmse is at the same range as our LSER approach based on experimentally determined descriptors. Further, we applied our approach for 248 extractables where we calculated blood/low density polyethylene (LDPE) and adipose tissue/LDPE partition coefficients. By this approach, we successfully identified chemicals of potential interest to a toxicological evaluation based on the total risk score.

Novel Models for Accurate Estimation of Air-Blood Partitioning: Applications to Individual Compounds and Complex Mixtures of Neutral Organic Compounds

The air-blood partition coefficient (Kab) is extensively employed in human health risk assessment for chemical exposure. However, current Kab estimation approaches either require an extensive number of parameters or lack precision. In this study, we present two novel and parsimonious models to accurately estimate Kab values for individual neutral organic compounds, as well as their complex mixtures. The first model, termed the GC×GC model, was developed based on the retention times of nonpolar chemical analytes on comprehensive two-dimensional gas chromatography (GC×GC). This model is unique in its ability to estimate the Kab values for complex mixtures of nonpolar organic chemicals. The GC×GC model successfully accounted for the Kab variance (R2 = 0.97) and demonstrated strong prediction power (RMSE = 0.31 log unit) for an independent set of nonpolar chemical analytes. Overall, the GC×GC model can be used to estimate Kab values for complex mixtures of neutral organic compounds. The second model, termed the partition model (PM), is based on two types of partition coefficients: octanol to water (Kow) and air to water (Kaw). The PM was able to effectively account for the variability in Kab data (n = 344), yielding an R2 value of 0.93 and root-mean-square error (RMSE) of 0.34 log unit. The predictive power and explanatory performance of the PM were found to be comparable to those of the parameter-intensive Abraham solvation models (ASMs). Additionally, the PM can be integrated into the software EPI Suite, which is widely used in chemical risk assessment for initial screening. The PM provides quick and reliable estimation of Kab compared to ASMs, while the GC×GC model is uniquely suited for estimating Kab values for complex mixtures of neutral organic compounds. In summary, our study introduces two novel and parsimonious models for the accurate estimation of Kab values for both individual compounds and complex mixtures.

Methods for assessing the bioaccumulation of hydrocarbons and related substances in terrestrial organisms: A critical review

This study investigates and reviews methods for the assessment of the terrestrial bioaccumulation potential of hydrocarbons and related organic substances. The study concludes that the unitless biomagnification factor (BMF) and/or the trophic magnification factor (TMF) are appropriate, practical, and thermodynamically meaningful metrics for identifying bioaccumulative substances in terrestrial food chains. The study shows that various methods, including physical-chemical properties like the KOA and KOW , in vitro biotransformation assays, quantitative structure-activity relationships, in vivo pharmacokinetic and dietary bioaccumulation tests, and field-based trophic magnification studies, can inform on whether a substance has the potential to biomagnify in a terrestrial food chain as defined by a unitless BMF exceeding 1. The study further illustrates how these methods can be arranged in a four-tier evaluation scheme for the purpose of screening assessments that aim to minimize effort and costs and expediate bioaccumulation assessment of the vast numbers of organic substances in commerce, identifies knowledge gaps, and provides recommendations for further research to improve bioaccumulation assessment. Integr Environ Assess Manag 2023;19:1433-1456. © 2023 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Paired Liver:Plasma PFAS Concentration Ratios from Adolescents in the Teen-LABS Study and Derivation of Empirical and Mass Balance Models to Predict and Explain Liver PFAS Accumulation

Animal studies have pointed at the liver as a hotspot for per- and polyfluoroalkyl substances (PFAS) accumulation and toxicity; however, these findings have not been replicated in human populations. We measured concentrations of seven PFAS in matched liver and plasma samples collected at the time of bariatric surgery from 64 adolescents in the Teen-Longitudinal Assessment of Bariatric Surgery (Teen-LABS) study. Liver:plasma concentration ratios were perfectly explained (r2 > 0.99) in a multilinear regression (MLR) model based on toxicokinetic (TK) descriptors consisting of binding to tissue constituents and membrane permeabilities. Of the seven matched plasma and liver PFAS concentrations compared in this study, the liver:plasma concentration ratio of perfluoroheptanoic acid (PFHpA) was considerably higher than the liver:plasma concentration ratio of other PFAS congeners. Comparing the MLR model with an equilibrium mass balance model (MBM) suggested that complex kinetic transport processes are driving the unexpectedly high liver:plasma concentration ratio of PFHpA. Intratissue MBM modeling pointed to membrane lipids as the tissue constituents that drive the liver accumulation of long-chain, hydrophobic PFAS, whereas albumin binding of hydrophobic PFAS dominated PFAS distribution in plasma. The liver:plasma concentration data set, empirical MLR model, and mechanistic MBM modeling allow the prediction of liver from plasma concentrations measured in human cohort studies. Our study demonstrates that combining biomonitoring data with mechanistic modeling can identify underlying mechanisms of internal distribution and specific target organ toxicity of PFAS in humans.

Cross-Species Evaluation of Bioaccumulation Thresholds for Air-Breathing Animals

In air-breathing organisms, an organic chemical's susceptibility to elimination via urinary excretion and respiratory exhalation can be judged on the basis of the octanol-water partition ratio (K_OW) and the octanol-air partition ratio (K_OA), respectively. Current regulations specify that chemicals with K_OW values of <10² and K_OA values of <10⁵ may be screened as non-bioaccumulative in air breathers. Here we used a model-based approach to evaluate whether these thresholds are consistent with a biomagnification factor of 1 for 141 different mammals, birds, and reptiles. Animals with lower rates of respiration (e.g., manatees and sloths) and those ingesting high-lipid diets (e.g., polar bears and carnivorous birds) were predicted to be able to biomagnify persistent chemicals with K_OA values of <10⁵. This was also observed for several temperate reptiles due to their lower respiration rates and internal temperatures. Protective K_OA thresholds were determined to be <10^4.85 for mammals, <10^4.60 for birds, <10^4.60 for reptiles at >25 °C, and <10^3.95 for reptiles at ≤25 °C. For all animals, urination alone was not efficient to prevent the biomagnification of any organic chemical. For chemicals with K_OW values of <10¹, we found that biomagnification of persistent chemicals was constrained by the water-air partition ratio (K_WA) rather than K_OA. Differences in physiology may need to be considered in bioaccumulation assessments of air-breathing species.

Using membrane-water partition coefficients in a critical membrane burden approach to aid the identification of neutral and ionizable chemicals that induce acute toxicity below narcosis levels

The risk assessment of thousands of chemicals used in our society benefits from adequate grouping of chemicals based on the mode and mechanism of toxic action (MoA). We measure the phospholipid membrane-water distribution ratio (D_MLW) using a chromatographic assay (IAM-HPLC) for 121 neutral and ionized organic chemicals and screen other methods to derive D_MLW. We use IAM-HPLC based D_MLW as a chemical property to distinguish between baseline narcosis and specific MoA, for reported acute toxicity endpoints on two separate sets of chemicals. The first set comprised 94 chemicals of US EPA's acute fish toxicity database: 47 categorized as narcosis MoA, 27 with specific MoA, and 20 predominantly ionic chemicals with mostly unknown MoA. The narcosis MoA chemicals clustered around the median narcosis critical membrane burden (CMB_narc) of 140 mmol kg^-1 lipid, with a lower limit of 14 mmol kg^-1 lipid, including all chemicals labelled Narcosis_I and Narcosis_II. This maximum 'toxic ratio' (TR) between CMB_narc and the lower limit narcosis endpoint is thus 10. For 23/28 specific MoA chemicals a TR >10 was derived, indicative of a specific adverse effect pathway related to acute toxicity. For 10/12 cations categorized as "unsure amines", the TR <10 suggests that these affect fish via narcosis MoA. The second set comprised 29 herbicides, including 17 dissociated acids, and evaluated the TR for acute toxic effect concentrations to likely sensitive aquatic plant species (green algae and macrophytes Lemna and Myriophyllum), and non-target animal species (invertebrates and fish). For 21/29 herbicides, a TR >10 indicated a specific toxic mode of action other than narcosis for at least one of these aquatic primary producers. Fish and invertebrate TRs were mostly <10, particularly for neutral herbicides, but for acidic herbicides a TR >10 indicated specific adverse effects in non-target animals. The established critical membrane approach to derive the TR provides for useful contribution to the weight of evidence to bin a chemical as having a narcosis MoA or less likely to have acute toxicity caused by a more specific adverse effect pathway. After proper calibration, the chromatographic assay provides consistent and efficient experimental input for both neutral and ionizable chemicals to this approach.

Recent advances for estimating environmental properties for small molecules from chromatographic measurements and the solvation parameter model

The transfer of neutral compounds between immiscible phases in chromatographic or environmental systems can be described by six solute properties (solute descriptors) using the solvation parameter model. The solute descriptors are size (McGowan's characteristic volume), V, excess molar refraction, E, dipolarity/polarizability, S, hydrogen-bond acidity and basicity, A and B, and the gas-liquid partition constant on n-hexadecane at 298.15 K, L. V and E for liquids are accessible by calculation but the other descriptors and E for solids are determined experimentally by chromatographic, liquid-liquid partition, and solubility measurements. These solute descriptors are available for several thousand compounds in the Abraham solute descriptor databases and for several hundred compounds in the WSU experimental solute descriptor database. In the first part of this review, we highlight features important in defining each descriptor, their experimental determination, compare descriptor quality for the two organized descriptor databases, and methods for estimating Abraham solute descriptors. In the second part we focus on recent applications of the solvation parameter model to characterize environmental systems and its use for the identification of surrogate chromatographic models for estimating environmental properties.

Models Used to Predict Chemical Bioaccumulation in Fish from in Vitro Biotransformation Rates Require Accurate Estimates of Blood-Water Partitioning and Chemical Volume of Distribution

Methods for extrapolating measured in vitro intrinsic clearance to a whole-body biotransformation rate constant (kB ) have been developed to support modeled bioaccumulation assessments for fish. The inclusion of extrapolated kB values into existing bioaccumulation models improves the prediction of chemical bioconcentration factors (BCFs), but there remains a tendency for these methods to overestimate BCFs relative to measured values. Therefore, a need exists to evaluate the extrapolation procedure to assess potential sources of error in predicted kB values. We examined how three different approaches (empirically based, composition based, and polyparameter linear free energy relationships [ppLFERs]) used to predict chemical partitioning in vitro (liver S9 system; KS9W ), in blood (KBW ), and in whole fish tissues (KFW ) impact the prediction of a chemical's hepatic clearance binding term (fU ) and apparent volume of distribution (VD ), both of which factor into the calculation of kB and the BCF. Each approach yielded different KS9W , KBW , and KFW values, but resulted in fU values that were of similar magnitude and remained relatively constant at log octanol-water partition ratios (KOW ) greater than 4. This is because KBW and KS9W values predicted by any given approach exhibit a similar dependence on log KOW (i.e., regression slope), which results in a cancelation of "errors" when fU is calculated. In contrast, differences in KBW values predicted by the three approaches translate to differences in VD , and by extension kB and the BCF, which become most apparent at log KOW greater than 6. There is a need to collect KBW and VD data for hydrophobic chemicals in fish that can be used to evaluate and improve existing partitioning prediction approaches in extrapolation models for fish. Environ Toxicol Chem 2023;42:33-45. © 2022 SETAC.

Exploring the role of octanol-water partition coefficient and Henry's law constant in predicting the lipid-water partition coefficients of organic chemicals

Partition coefficients for storage lipid-water (logKlw) and phospholipid-water (logKpw) phases are key parameters to understand the bioaccumulation and toxicity of organic contaminants. However, the published experimental databases of these properties are dwarfs and current estimation approaches are cumbersome. Here, we present partition models that exploit the correlations of logKlw, and of logKpw with the linear combinations of the octanol-water partition coefficient (logKow) and the dimensionless Henry's law constant (air-water partition coefficient, logKaw). The calibrated partition models successfully describe the variations in logKlw data (n = 305, R2 = 0.971, root-mean-square-error (rmse) = 0.375), and in logKpw data (n = 131, R2 = 0.953, rmse = 0.413). With the inputs of logKow and logKaw estimated from the U.S. EPA's EPI Suite, our models of logKlw and logKpw have exhibited rmse = 0.52 with respect to experimental values indicating suitability of these models for inclusion in the EPI Suite. Our models perform similar to or better than the previously reported models such as one parameter partition models, Abraham solvation models, and models based on quantum-chemical calculations. Taken together, our models are robust, easy-to-use, and provide insight into variations of logKlw and logKpw in terms of hydrophobicity and volatility trait of chemicals.

Identifying organic chemicals not subject to bioaccumulation in air-breathing organisms using predicted partitioning and biotransformation properties

Because the respiration processes contributing to the elimination of organic chemicals deviate between air- and water-breathing organisms, existing and widely used procedures for identifying chemicals not subject to bioaccumulation in aquatic organisms based on the octanol-water partition ratio K_OW need to be complemented with similar procedures for organisms respiring air. Here, we propose such a procedure that relies on the comparison of a compound's predicted K_OW , octanol-air partition ratio K_OA , and biotransformation half-life HL_B with three threshold values, below which elimination is judged to be sufficiently rapid to prevent bioaccumulation. The method allows for the consideration of the effect of dissociation on the efficiency of urinary and respiratory elimination. Explicit application of different types of the prediction error, such as the 95% prediction interval or the standard error, allows for variable tolerance for false-negative decisions, that is, the potential to judge a chemical as not bioaccumulative even though it is. A test with a set of more than 1000 diverse organic chemicals confirms the applicability of the prediction methods for a wide range of compounds and the procedure's ability to categorize approximately four-fifth of compounds as being of no bioaccumulation concern, suggesting its usefulness to screen large numbers of commercial chemicals to identify those worthy of further scrutiny. The test also demonstrates that a screening based solely on K_OW and K_OA would be far less effective because the fraction of chemicals that can be judged as sufficiently volatile and/or sufficiently water soluble for rapid respiratory and urinary elimination based on the partitioning properties predicted for their neutral form is relatively small. Future improvements of the proposed procedure depend largely on the development of prediction methods for the biotransformation kinetics in air-breathing organisms and for the potential for renal reabsorption. Integr Environ Assess Manag 2022;18:1297-1312. © 2021 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Exploring the partitioning of hydrophobic organic compounds between water, suspended particulate matter and diverse fish species in a German river ecosystem

BACKGROUND

Bioaccumulation of hydrophobic organic compounds (HOCs) along freshwater food chains is a major environmental concern as top predators in food webs are relevant for human consumption. To characterize and manage the associated risks, considerable numbers of organisms are sampled regularly for monitoring purposes. However, ethical and financial issues call for an alternative, more generic and more robust approach for assessing the internal exposure of fish that circumvents large variability in biota sampling due to interindividual differences. Passive sampling devices (PSDs) offer a fugacity-based approach for pollutant enrichment from different abiotic environmental compartments with a subsequent estimation of bioaccumulation in fish which we explored and compared to HOC concentrations in fish as determined using traditional approaches.

RESULTS

In this study, concentrations in silicone-based PSDs applied to the water phase and suspended particulate matter (SPM) of a river polluted with HOCs were used to estimate the concentration in model lipids at thermodynamic equilibrium with either environmental compartment. For comparison, muscle tissue of seven fish species (trophic level 1.8 to 2.8) was extracted using traditional exhaustive solvent extraction, and the lipid-normalized concentrations of HOCs were determined. The PSD-based data from SPM proved to be a more conservative estimator for HOCs accumulated in fish than those from water. Body length of the fish was found to be more suitable to describe increasing accumulation of HOCs than their trophic level as derived from stable isotope analysis and might offer a suitable alternative for future studies.

CONCLUSIONS

By combining fugacity-based sampling in the abiotic environment, translation into corresponding concentrations in model lipids and body length as an indicator for increasing bioaccumulation in fish, we present a suggestion for a robust approach that may be a meaningful addition to conventional monitoring methods. This approach potentially increases the efficiency of existing monitoring programs without the need to regularly sacrifice vertebrate species.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1186/s12302-022-00644-w.

Activation of the xenobiotic metabolism and oxidative stress response by mixtures of organic pollutants extracted with in-tissue passive sampling from liver, kidney, brain and blubber of marine mammals

We used in-tissue passive equilibrium sampling using the silicone polydimethylsiloxane (PDMS) to transfer chemical mixtures present in organs from marine mammals with lipid contents between 2.3 and 99%into in vitro bioassays. Tissues from five harbor porpoises (Phocoena phocoena), one harbor seal (Phoca vitulina) and one orca (Orcinus orca) from the North and Baltic Seas were sampled until thermodynamic equilibrium was reached. Mixture effects were quantified with cellular reporter gene bioassays targeting the activation of the aryl hydrocarbon receptor (AhR-CALUX), the peroxisome proliferator-activated receptor gamma (PPARγ-bla) and the oxidative stress response (AREc32), with parallel cytotoxicity measurements in all assays. After removing co-extracted lipids and other matrix residues with a non-destructive cleanup method (freeze-out of acetonitrile extract followed by a primary secondary amine sorbent extraction), the activation of the PPARγ and AREc32 were reduced by factors of on average 4.3 ± 0.15 (n = 22) and 2.5 ± 0.23 (n = 18), respectively, whereas the activation of the AhR remained largely unaltered: 1.1 ± 0.075 (n = 6). The liver extracts showed the highest activation, followed by the corresponding kidney and brain extracts, and the blubber extracts of the animals were the least active ones. The activation of the PPARγ by the liver extracts was reduced after cleanup by a factor of 11 ± 0.26 (n = 7) and the AREc32 activity by a factor of 1.9 ± 0.32 (n = 4). The blubber extracts did not activate the AhR up to concentrations where cytotoxicity occurred or up to an acceptable lipid volume fraction of 0.27% as derived from earlier work, whereas all liver extracts that had undergone cleanup activated the AhR. The developed in-tissue passive sampling approach allows a direct comparison of the bioassay responses between different tissues without further normalization and serves as a quantitative method suitable for biomonitoring of environmental biota samples.

The toxicokinetics of bisphenol A and its metabolites in fish elucidated by a PBTK model

Bisphenol A (BPA) is a chemical of major concern due to its endocrine disrupting function, high production volume, and persistence in the aquatic environment. Consequently, organisms such as fish are subject to chronic exposure to BPA. However, physiologically-based toxicokinetic (PBTK) models, which are valuable tools to improve the understanding of a chemical's fate in an organism, have never been specifically adapted to model BPA toxicokinetics (TK) in fish. In our work, an existing PBTK developed for four different fish species was modified to model BPA ADME processes (absorption, distribution, metabolization and excretion). The metabolization of BPA into BPA-monoglucuronide (BPA gluc) and BPA-monosulfate (BPA sulf) and their TK in various organs was taking into account in the model. Experiments were performed to generate BPA TK data in a model species commonly used in ecotoxicology, the stickleback. The model structure had to include two sites of metabolization to simulate BPA TK accurately in stickleback organs. Thus, the fish liver may not be the only site of the metabolization of BPA: plasma or gills could also play a role in BPA metabolization. The PBTK model predictive performance evaluated on literature data in zebrafish and rainbow trout concurs with this conclusion. Finally, a calibration mixing data from the three species was compared to the calibration on stickleback data only.

QSPRs for Predicting Equilibrium Partitioning in Solvent–Air Systems from the Chemical Structures of Solutes and Solvents

Poly-parameter Linear Free Energy Relationships (PPLFERs) based on the Abraham solvation model are a useful tool for predicting and interpreting equilibrium partitioning of solutes in solvent systems. The focus of this work is neutral organic solutes partitioning in neutral organic liquid solvent-air systems. This is a follow-up to previous work (Brown, 2021) which developed predictive empirical correlations between solute descriptors and system parameters, allowing system parameters to be predicted from the solute descriptors of the solvent. A database of solute descriptors, and a database of system parameters supplemented by empirical predictions, form the basis for the development of new Quantitative Structure Property Relationships (QSPRs). A total of 11 QSPRs have been developed for the E, S, A, B and L solute descriptors, and the s, a, b, v, l, and c system parameters. The QSPRs were developed using a group-contribution method referred to as Iterative Fragment Selection. The method includes robust internal and external model validation and a well-defined Applicability Domain, including estimates of prediction uncertainty. System parameters can also be predicted by combining the solute descriptor QSPRs and the empirical correlations. The predictive power of PPLFERs applied using different combinations of experimental data, empirical correlations, and QSPRs are externally validated by predicting partition ratios between solvents and air. The uncertainty for predicting the log10KSA of diverse solutes in diverse solvents using only the new QSPRs and empirical correlations is estimated to be one log10 unit or less.

Evaluating phospholipid- and protein-water partitioning of two groups of chemicals of emerging concern: Diastereo- and enantioselectivity

The partitioning between phospholipids/proteins and water can be used to predict the bioaccumulation potential of chemicals with better accuracy compared with n-octanol-water partition coefficient. However, such partitioning is poorly understood for chiral chemicals, many of which exhibit differential bioaccumulation and toxicity potential between enantiomers. In this study, the enantiospecific liposome-water and bovine serum albumin (BSA)-water partition coefficients (Klip/w and KBSA/w, determined at 25 ℃ and 37 ℃, respectively) were measured by equilibrium dialysis for α-, β-, and γ-hexabromocyclododecane (HBCD) and three β-blockers (propranolol, metoprolol, and sotalol). Raman and fluorescence analyses and molecular docking were conducted to provide additional insights into the partitioning process. Results showed α- and β-HBCD displayed stronger enantioselective partitioning to liposomes with the (-)-form, while (-)-α-HBCD, R-(+)-propranolol, R-(+)-metoprolol, and E2-sotalol favored partitioning to BSA compared with their antipodes. Raman spectra revealed α- and γ-HBCD enhanced and reduced the organization of liposome acyl chains, respectively, and polar interactions enhanced the liposome partitioning of β-blockers. Fluorescence spectra indicated the changed tryptophan microenvironment might influence the BSA steric effect toward HBCD, and electrostatic interactions dominated the formation of BSA-β-blocker complexes. Molecular docking results supported the difference in the thermodynamic nature of interaction between the studied enantiomers and BSA.

Chemical mixtures in human post-mortem tissues assessed by a combination of chemical analysis and in vitro bioassays after extraction with silicone

Passive equilibrium sampling of chemical mixtures from different human post-mortem tissues (liver, brain (cerebrum and cerebellum), adipose tissue) and blood was combined with instrumental analysis using direct sample introduction (DSI) GC-MS/MS and bioanalytical profiling using in vitro bioassays targeting the activation of the aryl hydrocarbon receptor (AhR-CALUX), the adaptive stress response (AREc32) and cytotoxicity. The tissues stemmed from pathology samples collected in two German cities and covered males and females aged 21 to 100 with a mean age of 67 years. Neutral organic chemicals were extracted using polydimethylsiloxane (PDMS) at mass ratios of tissue to PDMS of approximately 6 for blood, 3 for adipose tissue and 10 for liver and brain. Amounts of chemicals in PDMS were converted to lipid-associated concentrations using previously measured partition constants that were chemical-independent despite covering eight orders of magnitude in hydrophobicity. Up to 35 of 99 targeted chemicals were detected in 6 tissues of 16 individuals (88 samples in total), among them legacy persistent organic pollutants (POP) such as DDT and derivatives and polychlorinated biphenyls (PCB) but also modern pesticides and chemicals present in consumer products. POPs were highest in adipose tissue and lipid-associated concentrations increased with age, while concentrations of fragrance materials such as galaxolide were independent of age. In tissues from the same individual, chemical concentrations mostly increased from similar levels in brain and blood to higher levels in liver and highest in adipose tissue. However, easily degradable chemicals such as phenanthrene were mainly detected in blood and brain, and very hydrophilic chemicals were least abundant in adipose tissue. The passive sampling method allows a direct comparison of chemical burden between different tissues and may have forensic applications, for example to study internal distributions or to use one tissue type as a proxy for others. The sum of concentrations of the detected chemicals was positively correlated with the bioassay responses but mixture modeling showed that the detected chemicals explained less than 2% of the activation of the AhR and less than 0.5% of cytotoxicity. This means that more than 10,000 chemicals would need to be included in an analytical method to capture all the effects with many chemicals potentially being below detection limits but still contributing to mixture effects. Therefore, we propose a smart combination of chemical analysis and bioassays to quantify priority chemicals but use bioassay responses as effect-scaled concentrations to capture the entire exposome in future epidemiological studies.

Update and Evaluation of a High-Throughput In Vitro Mass Balance Distribution Model: IV-MBM EQP v2.0

This study demonstrates the utility of an updated mass balance model for predicting the distribution of organic chemicals in in vitro test systems (IV-MBM EQP v2.0) and evaluates its performance with empirical data. The IV-MBM EQP v2.0 tool was parameterized and applied to four independent data sets with measured ratios of bulk medium or freely-dissolved to initial nominal concentrations (e.g., C24/C0 where C24 is the measured concentration after 24 h of exposure and C0 is the initial nominal concentration). Model performance varied depending on the data set, chemical properties (e.g., "volatiles" vs. "non-volatiles", neutral vs. ionizable organics), and model assumptions but overall is deemed acceptable. For example, the r² was greater than 0.8 and the mean absolute error (MAE) in the predictions was less than a factor of two for most neutral organics included. Model performance was not as good for the ionizable organic chemicals included but the r² was still greater than 0.7 and the MAE less than a factor of three. The IV-MBM EQP v2.0 model was subsequently applied to several hundred chemicals on Canada's Domestic Substances List (DSL) with nominal effects data (AC50s) reported for two in vitro assays. We report the frequency of chemicals with AC50s corresponding to predicted cell membrane concentrations in the baseline toxicity range (i.e., >20-60 mM) and tabulate the number of chemicals with "volatility issues" (majority of chemical in headspace) and "solubility issues" (freely-dissolved concentration greater than water solubility after distribution). In addition, the predicted "equivalent EQP blood concentrations" (i.e., blood concentration at equilibrium with predicted cellular concentration) were compared to the AC50s as a function of hydrophobicity (log octanol-water partition or distribution ratio). The predicted equivalent EQP blood concentrations exceed the AC50 by up to a factor of 100 depending on hydrophobicity and assay conditions. The implications of using AC50s as direct surrogates for human blood concentrations when estimating the oral equivalent doses using a toxicokinetic model (i.e., reverse dosimetry) are then briefly discussed.

Fugacity-Based Trophic Magnification Factors Characterize Bioaccumulation of Cyclic Methyl Siloxanes within an Urban Terrestrial Avian Food Web: Importance of Organism Body Temperature and Composition

Trophic magnification of cyclic volatile methyl siloxanes (cVMS) in a terrestrial food web was investigated by measuring concentrations of octamethylcyclotetrasiloxane (D4), decamethylcyclopentasiloxane (D5), and dodecamethylcyclohexasiloxane (D6) and two reference chemicals within air and biota samples from an avian food web located in a mixed urban-agricultural landscape. Terrestrial trophic magnification factors derived from lipid normalized concentrations (TMF_Ls) for D5 and D6 were 0.94 (0.17 SE) and 1.1 (0.23 SE) and not statistically different from 1 (p > 0.05); however, the TMF_L of D4 was 0.62 (0.11 SE) and statistically less than 1 (p < 0.001). TMF_Ls of PCB-153 and p,p'-DDE were 5.6 (2.2 SE) and 6.1 (2.8 SE) and statistically greater than 1 (p < 0.001). TMF_Ls of cVMS in this terrestrial system were similar to those reported in aquatic systems. However, trophic magnification factors derived on a fugacity basis (TMF_Fs), which recognize differences in body temperature and lipid composition between organisms, were greater than corresponding TMF_Ls primarily because a temperature-induced thermodynamic biomagnification of hydrophobic chemicals occurs when endothermic organisms consume poikilothermic organisms. Therefore, we recommend that biomagnification studies of food webs including endothermic and poikilothermic organisms incorporate differences in body temperature and tissue composition to accurately characterize the biomagnification potential of chemicals.

Bioaccumulation of dodecamethylcyclohexasiloxane (D6) in fish

To investigate the bioaccumulation behavior of dodecamethylcyclohexasiloxane (D6, CAS number: 540-97-6) in fish, an OECD-305 style dietary bioaccumulation study of D6 in rainbow trout was conducted in the presence of non-metabolizable reference chemicals. The dietary uptake absorption efficiency of D6 was 14 (3 SE) % and lower than that of the reference chemicals which ranged between 22 (2 SE) to 60 (8 SE) %. The concentration of D6 in the body of the fish showed a rapid 40% drop during the first day of the depuration phase, followed by a slower decline during the remainder of the depuration period. The overall depuration rate constant of D6 was 0.016 (0.0026 SE) d^-1 and significantly greater than those of PCB153 and PCB209, which were not significantly different from zero. During the depuration phase, when fish body weight did not significantly change over time, depuration of D6 appears to be almost entirely due to biotransformation in the body of the fish. The biomagnification factor of D6 in rainbow trout was 0.38 (0.14 SE) kg-lipid kg-lipid^-1, indicating a lack of biomagnification. The bioconcentration factor (BCF) of D6 in Rainbow trout was estimated at 1909 (483 SE) L kg^-1 wet for natural waters of mostly oligotrophic lakes in Northern Canada with an average concentration of total organic carbon of 7.1 mg L^-1. Comparing the bioaccumulation profile of D6 to that of 238 similar profiles for 166 unique chemicals indicates that the bioaccumulation capacity of D6 is markedly less than that of many very hydrophobic organochlorines.

Development and intercomparison of single and multicompartment physiologically-based toxicokinetic models: Implications for model selection and tiered modeling frameworks

This study describes the development and intercomparison of generic physiologically-based toxicokinetic (PBTK) models for humans comprised of internally consistent one-compartment (1Co-) and multi-compartment (MCo-) implementations (G-PBTK). The G-PBTK models were parameterized for an adult male (70 kg) using common physiological parameters and in vitro biotransformation rate estimates and subsequently evaluated using independent concentration versus time data (n = 6) and total elimination half-lives (n = 15) for diverse organic chemicals. The model performance is acceptable considering the inherent uncertainty in the biotransformation rate data and the absence of model calibration. The G-PBTK model was then applied using hypothetical neutral organics, acidic ionizable organics and basic ionizable organics (IOCs) to identify combinations of partitioning properties and biotransformation rates leading to substantial discrepancies between 1Co- and MCo-PBTK calculations for whole body concentrations and half-lives. The 1Co- and MCo-PBTK model calculations for key toxicokinetic parameters are broadly consistent unless biotransformation is rapid (e.g., half-life less than five days). When half-lives are relatively short, discrepancies are greatest for the neutral organics and least for the acidic IOCs which follows from the estimated volumes of distribution (e.g., VD_SS = 9.6-15.4 L/kg vs 0.3-1.6 L/kg for the neutral and acidic compounds respectively) and the related approach to internal chemical equilibrium. The model intercomparisons demonstrate that 1Co-PBTK models can be applied with confidence to many exposure scenarios, particularly those focused on chronic or repeat exposures and for prioritization and screening-level decision contexts. However, MCo-PBTK models may be necessary in certain contexts, particularly for intermittent, short-term and highly variable exposures. A key recommendation to guide model selection and the development of tiered PBTK modeling frameworks that emerges from this study is the need to harmonize models with respect to parameterization and process descriptions to the greatest extent possible when proceeding from the application of simpler to more complex modeling tools as part of chemical assessment activities.

Critical Membrane Concentration and Mass-Balance Model to Identify Baseline Cytotoxicity of Hydrophobic and Ionizable Organic Chemicals in Mammalian Cell Lines

All chemicals can interfere with cellular membranes and this leads to baseline toxicity, which is the minimal toxicity any chemical elicits. The critical membrane burden is constant for all chemicals; that is, the dosing concentrations to trigger baseline toxicity decrease with increasing hydrophobicity of the chemicals. Quantitative structure-activity relationships, based on hydrophobicity of chemicals, have been established to predict nominal concentrations causing baseline toxicity in human and mammalian cell lines. However, their applicability is limited to hydrophilic neutral compounds. To develop a prediction model that includes more hydrophobic and charged organic chemicals, a mass balance model was applied for mammalian cells (AREc32, AhR-CALUX, PPARγ-BLA, and SH-SY5Y) considering different bioassay conditions. The critical membrane burden for baseline toxicity was converted into nominal concentration causing 10% cytotoxicity by baseline toxicity (IC_10,baseline) using a mass balance model whose main chemical input parameter was the liposome-water partition constants (K_lip/w) for neutral chemicals or the speciation-corrected D_lip/w(pH 7.4) for ionizable chemicals plus the bioassay-specific protein, lipid, and water contents of cells and media. In these bioassay-specific models, log(1/IC_10,baseline) increased with increasing hydrophobicity, and the relationship started to level off at log D_lip/w around 2. The bioassay-specific models were applied to 392 chemicals covering a broad range of hydrophobicity and speciation. Comparing the predicted IC_10,baseline and experimental cytotoxicity IC₁₀, known baseline toxicants and many additional chemicals were identified as baseline toxicants, while the others were classified based on specificity of their modes of action in the four cell lines, confirming excess toxicity of some fungicides, antibiotics, and uncouplers. Given the similarity of the bioassay-specific models, we propose a generalized baseline-model for adherent human cell lines: log[1/IC_10,baseline (M)] = 1.23 + 4.97 × (1 - e^{-0.236 log D_lip/w}). The derived models for baseline toxicity may serve for specificity analysis in reporter gene and neurotoxicity assays as well as for planning the dosing for cell-based assays.

Internal and Maternal Distribution of Persistent Organic Pollutants in Sea Turtle Tissues: A Meta-Analysis

We aimed to identify patterns in the internal distribution of persistent organic pollutants (POPs) and assess contributing factors using sea turtles and their offspring as a case study of a long-lived wildlife species. We systematically synthesized 40 years of data and developed a lipid database to test whether lipid-normalized POP concentrations are equal among tissues as expected under steady state for lipophilic compounds. Results supported equal partitioning among tissues with high blood flow or perfusion including the heart, kidney, muscle, and lung. Observed differences in the brain, fat, and blood plasma, however, suggest the physiological influence of the blood-brain barrier, limited perfusion, and protein content, respectively. Polybrominated diphenyl ethers partitioned comparably to legacy POPs. Polycyclic aromatic hydrocarbons, meanwhile, partitioned more into the lung, colon, and muscle compared to the liver under chronic and acute field exposure. Partitioning ratios of individual POPs among tissues were significantly related to the lipophilicity of compounds (as estimated by K_ow) in half of the observed cases, and significant differences between juveniles and adults underscore physiological differences across life stages. The comprehensive tissue partitioning patterns presented here provide a quantitative basis to support comparative assessments of POP pollution derived from biomonitoring among multiple tissues.

Kinetics of Equilibrium Passive Sampling of Organic Chemicals with Polymers in Diverse Mammalian Tissues

Equilibrium passive sampling employing polydimethylsiloxane (PDMS) as a sampling phase can be used for the extraction of complex mixtures of organic chemicals from lipid-rich biota. We extended the method to lean tissues and more hydrophilic chemicals by implementing a mass-balance model for partitioning between lipids, proteins, and water in tissues and by accelerating uptake kinetics with a custom-built stirrer that effectively decreased time to equilibrium to less than 8 days even for a homogenized liver tissue with an only 4% lipid content. The partition constants log K_lipid/PDMS between tissues and PDMS were derived from measured concentration in PDMS and the mass-balance model and were very similar for 40 neutral chemicals with octanol-water partition constants 1.4 < log K_ow < 8.7, that is, log K_lipid/PDMS of 1.26 (95% CI, 1.13-1.39) for the adipose tissue, 1.16 (1.00-1.33) for the liver, and 0.58 (0.42-0.73) for the brain. This conversion factor can be applied to interpret chemical analysis and in vitro bioassays after additionally accounting for a small fraction of coextracted lipids of <0.7% of the PDMS weight. PDMS is more widely applicable for passive sampling of mammalian tissues than previously thought, both, in terms of diversity of chemicals and the range of lipid contents of tissues and, therefore, an ideal method for human biomonitoring to be combined with in vitro bioassays.

Relevance of desorption kinetics and permeability for in vitro-based predictions of hepatic clearance in fish

The impact of desorption kinetics and permeation kinetics on in vitro-based predictions of in vivo hepatic blood clearances is investigated in the present study. Most commonly, possible limitations due to slow desorption of chemicals from albumin or slow permeation of chemicals through cellular membranes are not considered when in vivo clearances are predicted from in vitro biotransformation rate constants. To evaluate whether the most commonly used extrapolation models might thus overlook important kinetic limitations, we compare predictions of in vivo clearance that explicitly consider desorption and permeation kinetics with predictions of in vivo clearance that neglect these aspects. Our results show that strong limitations due to slow permeation kinetics are possible depending on the assumed permeability value. While permeability values estimated with a mechanistic approach are fast enough to avoid significant limitations, other experimentally derived permeability values lead to dramatically decreased in vivo clearance predictions. These latter values lead to unrealistically low in vivo biotransformation estimates. Furthermore, we also evaluated the implications of desorption kinetics using experimentally determined desorption rate constants. These evaluations show that slow desorption kinetics are unlikely to limit in vivo clearance.

A hybrid modeling approach for assessing mechanistic models of small molecule partitioning in vivo using a machine learning-integrated modeling platform

Prediction of the first-in-human dosing regimens is a critical step in drug development and requires accurate quantitation of drug distribution. Traditional in vivo studies used to characterize clinical candidate’s volume of distribution are error-prone, time- and cost-intensive and lack reproducibility in clinical settings. The paper demonstrates how a computational platform integrating machine learning optimization with mechanistic modeling can be used to simulate compound plasma concentration profile and predict tissue-plasma partition coefficients with high accuracy by varying the lipophilicity descriptor logP. The approach applied to chemically diverse small molecules resulted in comparable geometric mean fold-errors of 1.50 and 1.63 in pharmacokinetic outputs for direct tissue:plasma partition and hybrid logP optimization, with the latter enabling prediction of tissue permeation that can be used to guide toxicity and efficacy dosing in human subjects. The optimization simulations required to achieve these results were parallelized on the AWS cloud and generated outputs in under 5 h. Accuracy, speed, and scalability of the framework indicate that it can be used to assess the relevance of other mechanistic relationships implicated in pharmacokinetic-pharmacodynamic phenomena with a lower risk of overfitting datasets and generate large database of physiologically-relevant drug disposition for further integration with machine learning models.

Could chemical exposure and bioconcentration in fish be affected by slow binding kinetics in blood?

The possible implications of slow binding kinetics on respiratory uptake, bioconcentration and exposure of chemicals were evaluated in the present study. Most physiological and chemical information needed for such an evaluation is already known from the literature or can be estimated. However, data for binding kinetics of chemicals in fish plasma have not been reported in the literature yet. In the first part of this study, we therefore experimentally investigated the plasma binding kinetics for ten chemicals, including pollutants like polycyclic aromatic hydrocarbons and a pesticide. The determined desorption rate constants were in the range of 0.4 s-1 to 0.1 s-1. In the second part of this study, we present a comparative modeling analysis of generic predictions with binding kinetics of different velocities. For doing so, a model that explicitly represents binding kinetics in blood was developed and applied for different hypothetical scenarios. The evaluation showed that slow sorption kinetics only limits respiratory uptake and thus influences the levels of bioaccumulation for extreme and, by that, rather unlikely parameter combinations (i.e. for strongly sorbing chemicals with very slow binding kinetics). It can therefore be assumed that limitations on respiratory uptake due to slow binding kinetics in blood are rather unlikely for most chemicals.

Relook on the Linear Free Energy Relationships Describing the Partitioning Behavior of Diverse Chemicals for Polyethylene Water Passive Samplers

Over the past 3 decades, low-density polyethylene (PE) passive sampling devices have been widely used to scout organic chemicals in air, water, sediments, and biotic phases. Experimental partition coefficient data, required to calculate the concentrations in environmental compartments, are not widely available. In this study, we developed and rigorously evaluated linear free energy relationships (LFERs) to predict the partition coefficient between the PE and the water phase (log K _pe-w). Poly-parameter (pp) LFERs based on Abraham solute parameters performed better (root-mean-square error, rmse = 0.333-0.350 log unit) in predicting log K _pe-w compared to the two one-parameter (op) LFERs built on n-hexadecane-water and octanol-water partition coefficients (rmse = 0.41-0.42 log unit), indicating that one parameter is not able to account for all types of interactions experienced by a chemical during PE-water exchange. Dimensionality analyses show that the calibration dataset used to train pp-LFERs fulfills all the requirements to obtain a robust model for log K _pe-w. Van der Waals interactions of the molecule tend to favor the PE phase, and polar interactions of the molecule favor the water phase. The PE phase is the most sensitive to polarizable chemicals compared to other commonly used passive sampling polymeric phases such as polydimethylsiloxane, polyoxymethylene, and polyacrylate. For op-LFERs, the PE phase is better represented by the hexadecane phase than by the octanol phase. A computational method based on the conductor-like screening model for real solvents theory did good job in estimating log K _pe-w for chemicals that were neither very hydrophobic nor very hydrophilic in nature. Our models can be used to reliably predict the log K _pe-w values of simple neutral organic chemicals. This study provides insights into the partitioning behavior of PE samplers compared to other commonly used passive samplers.

Prediction of Unbound Fractions for in Vitro-in Vivo Extrapolation of Biotransformation Data

For in vitro-in vivo extrapolation of biotransformation data, the different sorptive environments in vitro and in vivo need to be considered. The most common approach for doing so is using the ratio of unbound fractions in vitro and in vivo. In the literature, several algorithms for prediction of these unbound fractions are available. In this study, we present a theoretical evaluation of the most commonly used algorithms for prediction of unbound fractions in S9 assays and blood and compare prediction results with empirical values from the literature. The results of this analysis prove a good performance of "composition-based" algorithms, i.e. algorithms that represent the inhomogeneous composition of in vitro assay and in vivo system and describe sorption to the individual components (lipids, proteins, water) in the same way. For strongly sorbing chemicals, these algorithms yield constant values for the ratio of unbound fractions in vitro and in vivo. This is mechanistically plausible, because in these cases, the chemicals are mostly bound, and the ratio of unbound fractions is determined by the volume ratio of sorbing components in both phases.

Partitioning of persistent hydrophobic contaminants to different storage lipid classes

Lipids generally represent the major matrix contributing to the absorptive capacity for hydrophobic organic contaminants in aquatic ecosystems. The aim of the present study was to determine whether contaminants partition to a different degree to the different storage lipid classes: wax ester (WE) and triacylglycerol (TAG). This was undertaken by studying experimentally the partitioning of organochlorine compounds between lipids (WE or TAG) and silicone rubber phase. Our results indicate that hydrophobic compounds have a slightly higher affinity for WE than for TAG. The findings thus corroborate earlier suggestions that contaminants accumulate to a greater extent in food webs with a higher reliance of on WE, such as in the Arctic. This knowledge is of interest since it implies that possible changes in planktonic community species composition, and thereby possible changes in the lipid composition, may have consequences for accumulation of hydrophobic contaminants in apex predators. However, the magnitude of these consequences remains unknown, and there may well be other factors of importance for previously observed higher accumulation of contaminants in Arctic systems. Thus, we have here identified aspects regarding partitioning of contaminants to lipids that need further scrutiny, and there is a need for further quantitative estimates of the suggested difference in absorptive capacities for hydrophobic contaminants between WE and TAG.

Environmental Sorption Behavior of Ionic and Ionizable Organic Chemicals

Traditionally our tools for environmental risk assessment of organic chemicals have been developed for neutral chemicals. However, many commercial chemicals are ionic or ionizable and require different tools and approaches for their assessment. In recent years this task starts to obtain increasing attention but our understanding for their environmental fate is still far behind that for neutral chemicals. This review first gives an overview on the principles that govern ionic partitioning in environmental systems which are more complex than the simple partition processes of neutral chemicals. Second, a summary of our current knowledge on various topics such as bioaccumulation, sorption in soils, and nonspecific-toxicity reveals that ionic species can actually be quite hydrophobic contrary to commonly held beliefs. Eventually, we discuss existing models for the quantitative prediction of organic ions' sorption in soils and biota. We have to assert that the available model tools are quite restricted in their application range compared to neutral chemicals which is due to the higher complexity of the various ionic sorption processes. In order to further advance our understanding more high-quality sorption data are needed with a focus on multivalent and zwitterionic ions in all partition systems as well as cations in biological matrices.

Versatile in silico modeling of partition coefficients of organic compounds in polydimethylsiloxane using linear and nonlinear methods

Environmental fate, behavior and effects of hazardous organic compounds have recently received great attention in diverse environmental phases, including water, atmosphere, soil and sediment. Considering polydimethylsiloxane (PDMS) fibers were validated for the wide application in the determination of partition behavior in passive sampling, in this work, several in silico models were established to predict PDMS-water (K_PDMS-w), PDMS-air (K_PDMS-a) and PDMS-seawater partition coefficients (K_PDMS-sw) of diverse chemicals. This is an attempt to combine conventional linear method and popular nonlinear algorithm for the estimation of partition coefficients between PDMS and different environmental media. All of the developed models showed satisfactory goodness-of-fit with high adjusted correlation coefficient (R²_adj) and were validated to be robust, stable and predictable by various internal and external validation techniques, deriving a wide series of statistical checks. Moreover, it was found that hydrophobicity, polarizability, charge distribution and molecular size of compounds contributed significantly to the model development by interpreting the selected descriptors. Based on the broad applicability domains (ADs), the current study provides suitable tools to fill the experimental data gap for other compounds and to help researchers better understand the mechanistic basis of adsorption behavior of PDMS.

Atropselective Partitioning of Polychlorinated Biphenyls in a HepG2 Cell Culture System: Experimental and Modeling Results

Cell culture models are used to study the toxicity of polychlorinated biphenyls (PCBs); however, it is typically unknown how much PCB enters the cells and, for chiral PCBs, if the partitioning is atropselective. We investigated the partitioning of racemic PCB 91, PCB 95, PCB 132, and PCB 136 in HepG2 cells following a 72 h incubation. PCBs were present in the cell culture medium (60.7-88.8%), cells (8.0-14.6%), and dishes (2.3-7.8%) and displayed atropisomeric enrichment in the cells (enantiomeric fraction [EF] = 0.55-0.77) and dishes (EF = 0.53-0.68). Polyparameter linear free energy relationships coupled with a composition-based model provided a good estimate of the PCB levels in the cells and cell culture medium. The free concentration was subsequently used to extrapolate from the nominal cell culture concentration to PCB tissue levels and vice versa. This approach can be used for in vitro-in vivo extrapolations for all 209 PCB congeners. However, this model (and modified models based on descriptors incorporating atropselective interactions, i.e., relative retention times on chiral columns) did not predict the atropselective partitioning in the cell culture system. Improved chemical descriptors that account for the atropselective binding of PCBs to biological macromolecules are, therefore, needed to predict the atropselective partitioning of PCBs in biological systems.

Fatty liver and impaired hepatic metabolism alter the congener-specific distribution of polychlorinated biphenyls (PCBs) in mice with a liver-specific deletion of cytochrome P450 reductase

Polychlorinated biphenyls (PCBs) are persistent organic pollutants that are linked to adverse health outcomes. PCB tissue levels are determinants of PCB toxicity; however, it is unclear how factors, such as an altered metabolism and/or a fatty liver, affect PCB distribution in vivo. We determined the congener-specific disposition of PCBs in mice with a liver-specific deletion of cytochrome P450 reductase (KO), a model of fatty liver with impaired hepatic metabolism, and wild-type (WT) mice. Eight-week-old male WT (M_WT, n = 3), male KO (M_KO, n = 5), female WT (F_WT, n = 4), and female KO mice (F_KO, n = 4) were exposed orally to Aroclor 1254. PCBs were quantified in adipose, blood, brain, and liver tissues by gas chromatography-mass spectrometry. The ΣPCB levels followed the rank order adipose > liver ∼ brain > blood in WT and adipose ∼ liver > brain > blood in KO mice. PCB levels were much higher in the liver of KO than WT mice, irrespective of the sex. A comparison across exposure groups revealed minor genotype and sex-dependent differences in the PCB congener profiles (cos Θ > 0.92). Within each exposure group, tissue profiles showed small differences between tissues (cos Θ = 0.85 to 0.98). These differences were due to a decrease in metabolically more labile PCB congeners and an increase in congeners resistant to metabolism. The tissue-to-blood ratio of PCBs decreased for adipose, increased for the brain, and remained constant for the liver with an increase in chlorination. While these ratios did not follow the trends predicted using a composition-based model, the agreement between experimental and calculated partition coefficients was reasonable. Although the distribution of PCBs differs between KO and WT mice, the magnitude of the partitioning of PCBs from the blood into tissues can be approximated using composition-based models.

Comparison of a simple and a complex model for BCF prediction using in vitro biotransformation data

A promising approach for bioaccumulation assessment with reduced animal use is the prediction of bioconcentration factors (BCFs) using in vitro biotransformation data. However, it has been recognized that the BCFs predicted using current models often are in poor agreement with experimental BCFs. Furthermore, extrahepatic biotransformation (e.g. in gill or GIT) is usually not accounted for. Here, we compare two BCF prediction models: a simple one-compartment and a more advanced multi-compartment model. Both models are implemented in a two-in-one calculation tool for the prediction of BCFs using in vitro data. Furthermore, both models were set up in a way that in vitro data for extrahepatic biotransformation can be easily considered, if desired. The models differ in their complexity: the one-compartment model is attractive because its simplicity, while the multi-compartment model is characterized by its refined closeness to reality. A comparison of the results shows that both models yield almost identical results for the presently evaluated cases with plausible physiological data. For regulatory purposes, there is thus no reason not to use the simple one-compartment model. However, if it is desired to represent special in vivo characteristics, e.g. first-pass effects or the direct GIT-to-liver blood flow, the multi-compartment model should be used.

Yolk-Water Partitioning of Neutral Organic Compounds in the Model Organism Danio rerio

Yolk is the most important temporary biological compartment of the early life stages of fish embryos. The sorption strength of a chemical to yolk components may significantly influence the distribution of that chemical in the fish embryo. We determined yolk-water partition coefficients (K_yolk/water , in liters of water per kilogram of yolk, normalized to dry wt) for 70 neutral organic chemicals. The log K_yolk/water values range from 0.76 to 6.56. On the basis of these values, we developed polyparameter linear free energy relationship models to predict yolk-water partitioning for a broad range of neutral organic chemicals with a root mean squared error of 0.37 and r² of 0.919. These models can be applied for the prediction of internal concentrations at equilibrium (neglecting biotransformation and active transport) in the zebrafish embryo test system. Environ Toxicol Chem 2020;39:1506-1516. © 2020 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.