A framework for understanding the bioconcentration of surfactants in fish.

Surfactants are a class of chemicals released in large quantities to water, and therefore bioconcentration in fish is an important component of their safety assessment. Their structural diversity, which encompasses nonionic, anionic, cationic and zwitterionic molecules with a broad range of lipophilicity, makes their evaluation challenging. A strong influence of environmental pH adds a further layer of complexity to their bioconcentration assessment. Here we present a framework that penetrates this complexity. Using simple equations derived from current understanding of the relevant underlying processes, we plot the key bioconcentration parameters (uptake rate constant, elimination rate constant and bioconcentration factor) as a function of its membrane lipid/water distribution ratio and the neutral fraction of the chemical in water at pH 8.1 and at pH 6.1. On this chemical space plot, we indicate boundaries at which four resistance terms (perfusion with water, transcellular, paracellular, and perfusion with blood) limit transport of surfactants across the gills. We then show that the bioconcentration parameters predicted by this framework align well with in vivo measurements of anionic, cationic and nonionic surfactants in fish. In doing so, we demonstrate how the framework can be used to explore expected differences in bioconcentration behavior within a given sub-class of surfactants, to assess how pH will influence bioconcentration, to identify the underlying processes governing bioconcentration of a particular surfactant, and to discover knowledge gaps that require further research. This framework for amphiphilic chemicals may function as a template for improved understanding of the accumulation potential of other ionizable chemicals of environmental concern, such as pharmaceuticals or dyes.

An amended in vitro-in vivo extrapolation model that accounts for first pass clearance effects on chemical bioaccumulation in fish.

Measured rates of in vitro intrinsic clearance for fish may be extrapolated to the whole animal as a means of estimating a whole-body biotransformation rate constant (kB; d-1). This estimate of kB can then be used as an input to existing bioaccumulation prediction models. Most in vitro-in vivo extrapolation/bioaccumulation (IVIVE/B) modeling efforts to date have focused on predicting the chemical bioconcentration in fish (aqueous only exposure), with less attention paid to dietary exposures. Following dietary uptake, biotransformation in the gut lumen, intestinal epithelia, and liver can reduce chemical accumulation; however, current IVIVE/B models do not consider these first pass clearance effects on dietary uptake. Here we present an amended IVIVE/B model that accounts for first pass clearance. The model is then used to examine how biotransformation in the liver and intestinal epithelia (alone or combined) may impact chemical accumulation that occurs during dietary exposure. First pass clearance by the liver can greatly reduce dietary uptake of contaminants, but these effects are only apparent at rapid rates of in vitro biotransformation (first order depletion rate constant kDEP ≥ 10 h-1). The impact of first pass clearance becomes more pronounced when biotransformation in the intestinal epithelia is included in the model. Modelled results suggest that biotransformation in the liver and intestinal epithelia cannot entirely explain reduced dietary uptake reported in several in vivo bioaccumulation tests. This unexplained reduction in dietary uptake is attributed to chemical degradation in the gut lumen. These findings underscore the need for research to directly investigate luminal biotransformation in fish.

A weight of evidence approach for bioaccumulation assessment.

Bioaccumulation assessments conducted by regulatory agencies worldwide use a variety of methods, types of data, metrics, and categorization criteria. Lines of evidence (LoE) for bioaccumulation assessment can include bioaccumulation metrics such as in vivo bioconcentration factor (BCF) and biomagnification factor (BMF) data measured from standardized laboratory experiments, and field (monitoring) data such as BMFs, bioaccumulation factors (BAFs), and trophic magnification factors (TMFs). In silico predictions from mass-balance models and quantitative structure-activity relationships (QSARs) and a combination of in vitro biotransformation rates and in vitro-in vivo extrapolation (IVIVE) models can also be used. The myriad bioaccumulation metrics and categorization criteria and underlying uncertainty in measured or modeled data can make decision-making challenging. A weight of evidence (WoE) approach is recommended to address uncertainty. The Bioaccumulation Assessment Tool (BAT) guides a user through the process of collecting and generating various LoE required for assessing the bioaccumulation of neutral and ionizable organic chemicals in aquatic (water-respiring) and air-breathing organisms. The BAT includes data evaluation templates (DETs) to critically evaluate the reliability of the LoE used in the assessment. The DETs were developed from standardized testing guidance. The approach used in the BAT is consistent with OECD and SETAC WoE principles and facilitates the implementation of chemical policy objectives in chemical assessment and management. The recommended methods are also iterative and tiered, providing pragmatic methods to reduce unnecessary animal testing. General concepts of the BAT are presented and case study applications of the tool for hexachlorobenzene (HCB) and ß-hexachlorocyclohexane (ß-HCH) are demonstrated. The BAT provides a consistent and transparent WoE framework to address uncertainty in bioaccumulation assessment and is envisaged to evolve with scientific and regulatory developments. Integr Environ Assess Manag 2023;19:1235-1253. © 2022 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

Developing an internal threshold of toxicological concern (iTTC).

BACKGROUND: Threshold of Toxicological Concern (TTC) approaches are used for chemical safety assessment and risk-based priority setting for data poor chemicals. TTCs are derived from in vivo No Observed Effect Level (NOEL) datasets involving an external administered dose from a single exposure route, e.g., oral intake rate. Thus, a route-specific TTC can only be compared to a route-specific exposure estimate and such TTCs cannot be used for other exposure scenarios such as aggregate exposures. OBJECTIVE: Develop and apply a method for deriving internal TTCs (iTTCs) that can be used in chemical assessments for multiple route-specific exposures (e.g., oral, inhalation or dermal) or aggregate exposures. METHODS: Chemical-specific toxicokinetics (TK) data and models are applied to calculate internal concentrations (whole-body and blood) from the reported administered oral dose NOELs used to derive the Munro TTCs. The new iTTCs are calculated from the 5th percentile of cumulative distributions of internal NOELs and the commonly applied uncertainty factor of 100 to extrapolate animal testing data for applications in human health assessment. RESULTS: The new iTTCs for whole-body and blood are 0.5 nmol/kg and 0.1 nmol/L, respectively. Because the iTTCs are expressed on a molar basis they are readily converted to chemical mass iTTCs using the molar mass of the chemical of interest. For example, the median molar mass in the dataset is 220 g/mol corresponding to an iTTC of 22 ng/L-blood (22 pg/mL-blood). The iTTCs are considered broadly applicable for many organic chemicals except those that are genotoxic or acetylcholinesterase inhibitors. The new iTTCs can be compared with measured or estimated whole-body or blood exposure concentrations for chemical safety screening and priority-setting. SIGNIFICANCE: Existing Threshold of Toxicological Concern (TTC) approaches are limited in their applications for route-specific exposure scenarios only and are not suitable for chemical risk and safety assessments under conditions of aggregate exposure. New internal Threshold of Toxicological Concern (iTTC) values are developed to address data gaps in chemical safety estimation for multi-route and aggregate exposures.

Dynamic Mass Balance Modeling for Chemical Distribution Over Time in In Vitro Systems With Repeated Dosing.

As toxicologists and risk assessors move away from animal testing and more toward using in vitro models and biological modeling, it is necessary to produce tools to quantify the chemical distribution within the in vitro environment prior to extrapolating in vitro concentrations to human equivalent doses. Although models predicting chemical distribution in vitro have been developed, very little has been done for repeated dosing scenarios, which are common in prolonged experiments where the medium needs to be refreshed. Failure to account for repeated dosing may lead to inaccurate estimations of exposure and introduce bias into subsequent in vitro to in vivo extrapolations. Our objectives were to develop a dynamic mass balance model for repeated dosing in in vitro systems; to evaluate model accuracy against experimental data; and to perform illustrative simulations to assess the impact of repeated doses on predicted cellular concentrations. A novel dynamic in vitro partitioning mass balance model (IV-MBM DP v1.0) was created based on the well-established fugacity approach. We parameterized and applied the dynamic mass balance model to single dose and repeat dosing scenarios, and evaluated the predicted medium and cellular concentrations against available empirical data. We also simulated repeated dosing scenarios for organic chemicals with a range of partitioning properties and compared the in vitro distributions over time. In single dose scenarios, for which only medium concentrations were available, simulated concentrations predicted measured concentrations with coefficients of determination (R 2) of 0.85-0.89, mean absolute error within a factor of two and model bias of nearly one. Repeat dose scenario simulations displayed model bias <2 within the cell lysate, and ∼1.5-3 in the medium. The concordance between simulated and available experimental data supports the predictive capacity of the IV-MBM DP v1.0 tool, but further evaluation as empirical data becomes available is warranted, especially for cellular concentrations.

Predicting the Accumulation of Ionizable Pharmaceuticals and Personal Care Products in Aquatic and Terrestrial Organisms.

The extent to which chemicals bioaccumulate in aquatic and terrestrial organisms represents a fundamental consideration for chemicals management efforts intended to protect public health and the environment from pollution and waste. Many chemicals, including most pharmaceuticals and personal care products (PPCPs), are ionizable across environmentally relevant pH gradients, which can affect their fate in aquatic and terrestrial systems. Existing mathematical models describe the accumulation of neutral organic chemicals and weak acids and bases in both fish and plants. Further model development is hampered, however, by a lack of mechanistic insights for PPCPs that are predominantly or permanently ionized. Targeted experiments across environmentally realistic conditions are needed to address the following questions: (1) What are the partitioning and sorption behaviors of strongly ionizing chemicals among species? (2) How does membrane permeability of ions influence bioaccumulation of PPCPs? (3) To what extent are salts and associated complexes with PPCPs influencing bioaccumulation? (4) How do biotransformation and other elimination processes vary within and among species? (5) Are bioaccumulation modeling efforts currently focused on chemicals and species with key data gaps and risk profiles? Answering these questions promises to address key sources of uncertainty for bioaccumulation modeling of ionizable PPCPs and related contaminants. Environ Toxicol Chem 2022;00:1-11. © 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

In Vivo Bioconcentration of 10 Anionic Surfactants in Rainbow Trout Explained by In Vitro Data on Partitioning and S9 Clearance.

Bioconcentration factors (BCFs) in rainbow trout were measured for 10 anionic surfactants with a range of alkyl chain lengths and different polar head groups. The BCFs ranged from 0.04 L kg-1 ww (for C10SO3) to 1370 L kg-1 ww (C16SO3). There was a strong correlation between the log BCF and log membrane lipid-water distribution ratio (DMLW, r2 = 0.96), and biotransformation was identified as the dominant elimination mechanism. The strong positive influence of DMLW on BCF was attributed to two phenomena: (i) increased partitioning from water into the epithelial membrane of the gill, leading to more rapid diffusion across this barrier and more rapid uptake, and (ii) increased sequestration of the surfactant body burden into membranes and other body tissues, resulting in lower freely dissolved concentrations available for biotransformation. Estimated whole-body in vivo biotransformation rate constants kB-BCF are within a factor three of rate constants estimated from S9 in vitro assays for six of the eight test chemicals for which kB-BCF could be determined. A model-based assessment indicated that the hepatic clearance rate of freely dissolved chemicals was similar for the studied surfactants. The dataset will be useful for evaluation of in silico and in vitro methods to assess bioaccumulation.

Graphical tools for the planning and interpretation of polyurethane foam based passive air sampling campaigns.

Due to low cost and easy handling during sampling and extraction, passive air samplers (PASs) using polyurethane foam (PUF) as a sorbent have become the most commonly deployed PASs for semi-volatile organic compounds (SVOCs). However, depending on the scenario, PUF-PAS may not always be operating in the linear uptake phase, which implies the need to consider how temperature, wind speed, deployment length and chemical properties interact to determine the amount of a target chemical taken up and the fraction of a depuration compound (DC) being lost during deployment. Guidance is, therefore, necessary to quantitatively interpret curvi-linear uptake in the PUF-PAS and avoid selection of DCs unsuited to the deployment conditions. In this study, the PAS-SIM model is used to generate graphical tools that aid in addressing important questions frequently arising during the use of PUF-PASs. Specifically, we generated five charts that display (i) the inherent sampling rate as a function of wind speed and a chemical's molecular diffusivity, (ii) the length of the linear uptake period as a function of chemical properties, temperature and the acceptable deviation from linearity, (iii) the time to 95% equilibrium as influenced by chemical properties, temperature and wind speed, (iv) the dependence of the fractional loss of DCs on chemical properties, temperature, wind speed and deployment length, and (v) the influence of chemical properties, temperature and the total suspended particle concentration on the extent of sorption to atmospheric particles. The charts also facilitate the assessment of the influence of parameter uncertainty. It is hoped that these charts assist with planning and interpreting sampling campaigns based on a mechanistic and quantitative understanding of uptake in PUF-based PASs.

Development and Evaluation of a Holistic and Mechanistic Modeling Framework for Chemical Emissions, Fate, Exposure, and Risk.

BACKGROUND: Large numbers of chemicals require evaluation to determine if their production and use pose potential risks to ecological and human health. For most chemicals, the inadequacy and uncertainty of chemical-specific data severely limit the application of exposure- and risk-based methods for screening-level assessments, priority setting, and effective management. OBJECTIVE: We developed and evaluated a holistic, mechanistic modeling framework for ecological and human health assessments to support the safe and sustainable production, use, and disposal of organic chemicals. METHODS: We consolidated various models for simulating the PROduction-To-EXposure (PROTEX) continuum with empirical data sets and models for predicting chemical property and use function information to enable high-throughput (HT) exposure and risk estimation. The new PROTEX-HT framework calculates exposure and risk by integrating mechanistic computational modules describing chemical behavior and fate in the socioeconomic system (i.e., life cycle emissions), natural and indoor environments, various ecological receptors, and humans. PROTEX-HT requires only molecular structure and chemical tonnage (i.e., annual production or consumption volume) as input information. We evaluated the PROTEX-HT framework using 95 organic chemicals commercialized in the United States and demonstrated its application in various exposure and risk assessment contexts. RESULTS: Seventy-nine percent and 97% of the PROTEX-HT human exposure predictions were within one and two orders of magnitude, respectively, of independent human exposure estimates inferred from biomonitoring data. PROTEX-HT supported screening and ranking chemicals based on various exposure and risk metrics, setting chemical-specific maximum allowable tonnage based on user-defined toxicological thresholds, and identifying the most relevant emission sources, environmental media, and exposure routes of concern in the PROTEX continuum. The case study shows that high chemical tonnage did not necessarily result in high exposure or health risks. CONCLUSION: Requiring only two chemical-specific pieces of information, PROTEX-HT enables efficient screening-level evaluations of existing and premanufacture chemicals in various exposure- and risk-based contexts. https://doi.org/10.1289/EHP9372.

Screening the baseline fish bioconcentration factor of various types of surfactants using phospholipid binding data.

Fish bioconcentration factors (BCFs) are commonly used in chemical hazard and risk assessment. For neutral organic chemicals BCFs are positively correlated with the octanol-water partition ratio (KOW), but KOW is not a reliable parameter for surfactants. Membrane lipid-water distribution ratios (DMLW) can be accurately measured for all kinds of surfactants, using phospholipid-based sorbents. This study first demonstrates that DMLW values for ionic surfactants are more than 100 000 times higher than the partition ratio to fish-oil, representing neutral storage lipid. A non-ionic alcohol ethoxylate surfactant showed almost equal affinity for both lipid types. Accordingly, a baseline screening BCF value for surfactants (BCFbaseline) can be approximated for ionic surfactants by multiplying DMLW by the phospholipid fraction in tissue, and for non-ionic surfactants by multiplying DMLW by the total lipid fraction. We measured DMLW values for surfactant structures, including linear and branched alkylbenzenesulfonates, an alkylsulfoacetate and an alkylethersulfate, bis(2-ethylhexyl)-surfactants (e.g., docusate), zwitterionic alkylbetaines and alkylamine-oxides, and a polyprotic diamine. Together with sixty previously published DMLW values for surfactants, structure-activity relationships were derived to elucidate the influence of surfactant specific molecular features on DMLW. For 23 surfactant types, we established the alkyl chain length at which BCFbaseline would exceed the EU REACH bioaccumulation (B) threshold of 2000 L kg-1, and would therefore require higher tier assessments to further refine the BCF estimate. Finally, the derived BCFbaseline are compared with measured literature in vivo BCF data where available, suggesting that refinements, most notably reliable estimates of biotransformation rates, are needed for most surfactant types.

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.

Biotransformation Potential of Cationic Surfactants in Fish Assessed with Rainbow Trout Liver S9 Fractions.

Biotransformation may substantially reduce the extent to which organic environmental contaminants accumulate in fish. Presently, however, relatively little is known regarding the biotransformation of ionized chemicals, including cationic surfactants, in aquatic organisms. To address this deficiency, a rainbow trout liver S9 substrate depletion assay (RT-S9) was used to measure in vitro intrinsic clearance rates (CLint ; ml min-1 g liver-1 ) for 22 cationic surfactants that differ with respect to alkyl chain length and degree of methylation on the charged nitrogen atom. None of the quaternary N,N,N-trimethylalkylammonium compounds exhibited significant clearance. Rapid clearance was observed for N,N-dimethylalkylamines, and slower rates of clearance were measured for N-methylalkylamine analogs. Clearance rates for primary alkylamines were generally close to or below detectable levels. For the N-methylalkylamines and N,N-dimethylalkylamines, the highest CLint values were measured for C10 -C12 homologs; substantially lower clearance rates were observed for homologs containing shorter or longer carbon chains. Based on its cofactor dependency, biotransformation of C12 -N,N-dimethylamine appears to involve one or more cytochrome P450-dependent reaction pathways, and sulfonation. On a molar basis, N-demethylation metabolites accounted for up to 25% of the N,N-dimethylalkylamines removed during the 2-h assay, and up to 55% of the removed N-methylalkylamines. These N-demethylation products possess greater metabolic stability in the RT-S9 assay than the parent structures from which they derive and may contribute to the overall risk of ionizable alkylamines. The results of these studies provide a set of consistently determined CLint values that may be extrapolated to whole trout to inform in silico bioaccumulation assessments. Environ Toxicol Chem 2021;40:3123-3136. © 2021 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

Bioconcentration of Several Series of Cationic Surfactants in Rainbow Trout.

Cationic surfactants have a strong affinity to sorb to phospholipid membranes and thus possess an inherent potential to bioaccumulate, but there are few measurements of bioconcentration in fish. We measured the bioconcentration of 10 alkylamines plus two quaternary ammonium compounds in juvenile rainbow trout at pH 7.6, and repeated the measurements at pH 6.2 for 6 of these surfactants. The BCF of the amines with chain lengths ≤ C14 was positively correlated with chain length, increasing ∼0.5 log units per carbon. Their BCF was also pH dependent and approximately proportional to the neutral fraction of the amine in the water. The BCFs of the quaternary ammonium compounds showed no pH dependence and were >2 orders of magnitude less than for amines of the same chain length at pH 7.6. This indicates that systemic uptake of permanently charged cationic surfactants is limited. The behavior of the quaternary ammonium compounds and the two C16 amines studied was consistent with previous observations that these surfactants accumulate primarily to the gills and external surfaces of the fish. At pH 7.6 the BCF exceeded 2000 L kg-1 for 4 amines with chains ≥ C13, showing that bioconcentration can be considerable for some longer chained cationic surfactants.

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., VDSS = 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.

Acritical review and weight of evidence approach for assessing the bioaccumulation of phenanthrene in aquatic environments.

Bioaccumulation (B) assessment is challenging because there are various B-metrics from laboratory and field studies, multiple criteria and thresholds for classifying bioaccumulative (B), very bioaccumulative (vB), and not bioaccumulative (nB) chemicals, as well as inherent variability and uncertainty in the data. These challenges can be met using a weight of evidence (WoE) approach. The Bioaccumulation Assessment Tool (BAT) provides a transparent WoE assessment framework that follows Organisation for Economic Co-operation and Development (OECD) principles for performing a WoE analysis. The BAT guides an evaluator through the process of data collection, generation, evaluation, and integration of various lines of evidence (LoE) (i.e., B-metrics) to inform decision-making. Phenanthrene (PHE) is a naturally occurring chemical for which extensive B and toxicokinetics data are available. A B assessment for PHE using the BAT is described that includes a critical evaluation of 74 measured in vivo LoE for fish and invertebrate species from laboratory and field studies. The number of LoE are reasonably well balanced across taxa (i.e., fish and invertebrates) and the different B-metrics. Additionally, in silico and in vitro biotransformation rate estimates and corresponding model-predicted B-metrics are included as corroborating evidence. Application of the BAT provides a consistent, coherent, and scientifically defensible WoE evaluation to conclude that PHE is not bioaccumulative (nB) because the overwhelming majority of the bioconcentration, bioaccumulation, and biomagnification metrics for both fish and invertebrates are below regulatory thresholds. An analysis of the relevant data using fugacity ratios is also provided, showing that PHE does not biomagnify in aquatic food webs. The critical review identifies recommendations to increase the consistency of B assessments, such as improved standardization of B testing guidelines, data reporting requirements for invertebrate studies, and consideration of temperature and salinity effects on certain B-metrics. Integr Environ Assess Manag 2021;17:911-925. © 2021 Concawe. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC).

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

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

Tissue Distribution of Several Series of Cationic Surfactants in Rainbow Trout (Oncorhynchus mykiss) Following Exposure via Water.

Bioaccumulation assessment is important for cationic surfactants in light of their use in a wide variety of consumer products and industrial processes. Because they sorb strongly to natural surfaces and to cell membranes, their bioaccumulation behavior is expected to differ from other classes of chemicals. Divided over two mixtures, we exposed rainbow trout to water containing 10 alkyl amines and 2 quaternary alkylammonium surfactants for 7 days, analyzed different fish tissues for surfactant residues, and calculated the tissues' contribution to fish body burden. Mucus, skin, gills, liver, and muscle each contributed at least 10% of body burden for the majority of the test chemicals. This indicates that both sorption to external surfaces and systemic uptake contribute to bioaccumulation. In contrast to the analogue alkylamine bases, the permanently charged quaternary ammonium compounds accumulated mostly in the gills and were nearly absent in internal tissues, indicating that systemic uptake of the charged form of cationic surfactants is very slow. Muscle-blood distribution coefficients were close to 1 for all alkyl amines, whereas liver-blood distribution coefficients ranged from 13 to 90, suggesting that the dominant considerations for sorption in liver are different from those in blood and muscle. The significant fraction of body burden on external surfaces can have consequences for bioaccumulation assessment.

Application of an Iterative Fragment Selection (IFS) Method to Estimate Entropies of Fusion and Melting Points of Organic Chemicals.

The main objective of this study is to develop and evaluate novel Quantitative Structure-Property Relationships (QSPRs) for predicting entropy of fusion (ΔSM ) and melting point (TM ) of organic chemicals from chemical structure. The QSPRs are developed using the Iterative Fragment Selection (IFS) method that requires only 2D structural information from the user (SMILES codes) for property prediction. The QSPRs also provide information on the applicability domain for each calculation and uncertainty estimates for the predictions. The root mean square error (RMSE) for the external validation sets are 11.8 J mol-1 K-1 and 46.9 K for the ΔSM and TM QSPRs, respectively. The performance of the new QSPRs is comparable to other predictive methods but has advantages with respect to availability and ease of use as well as the guidance on applicability domain for each prediction. Limitations of the new QSPRs are discussed. The QSPRs are coded as a user-friendly, freely available tool.