Identification and Prioritization of Organic Pollutants in Human Milk from the Yangtze River Delta, China.

Pollutants in human milk are critical for evaluating maternal internal exposure and infant external exposure. However, most studies have focused on a limited range of pollutants. Here, 15 pooled samples (prepared from 467 individual samples) of human milk from three areas of the Yangtze River Delta (YRD) in China were analyzed by gas chromatography quadrupole time-of-flight mass spectrometry. In total, 171 compounds of nine types were preliminarily identified. Among these, 16 compounds, including 2,5-di-tert-butylhydroquinone and 2-tert-butyl-1,4-benzoquinone, were detected in human milk for the first time. Partial least-squares discriminant analysis identified ten area-specific pollutants, including 2-naphthylamine, 9-fluorenone, 2-isopropylthianthrone, and benzo[a]pyrene, among pooled human milk samples from Shanghai (n = 3), Jiangsu Province (n = 6), and Zhejiang Province (n = 6). Risk index (RI) values were calculated and indicated that legacy polycyclic aromatic hydrocarbons (PAHs) contributed only 20% of the total RIs for the identified PAHs and derivatives, indicating that more attention should be paid to PAHs with various functional groups. Nine priority pollutants in human milk from the YRD were identified. The most important were 4-tert-amylphenol, caffeine, and 2,6-di-tert-butyl-p-benzoquinone, which are associated with apoptosis, oxidative stress, and other health hazards. The results improve our ability to assess the health risks posed by pollutants in human milk.

Occurrence and Ecological Risk of Alkylamine Triazines in Chinese Estuarine Sediments: An Emerging Class of Persistent, Mobile, and Toxic Substances.

Identifying persistent, mobile, and toxic (PMT) substances from synthetic chemicals is critical for chemical management and ecological risk assessment. Inspired by the triazine analogues (e.g., atrazine and melamine) in the original European Union's list of PMT substances, the occurrence and compositions of alkylamine triazines (AATs) in the estuarine sediments of main rivers along the eastern coast of China were comprehensively explored by an integrated strategy of target, suspect, and nontarget screening analysis. A total of 44 AATs were identified, of which 23 were confirmed by comparison with authentic standards. Among the remaining tentatively identified analogues, 18 were emerging pollutants not previously reported in the environment. Tri- and di-AATs were the dominant analogues, and varied geographic distributions of AATs were apparent in the investigated regions. Toxic unit calculations indicated that there were acute and chronic risks to algae from AATs on a large geographical scale, with the antifouling biocide cybutryne as a key driver. The assessment of physicochemical properties further revealed that more than half of the AATs could be categorized as potential PMT and very persistent and very mobile substances at the screening level. These results highlight that AATs are a class of PMT substances posing high ecological impacts on the aquatic environment and therefore require more attention.

An Integrated Workflow Assisted by In Silico Predictions To Expand the List of Priority Polycyclic Aromatic Compounds.

The limited information in existing mass spectral libraries hinders an accurate understanding of the composition, behavior, and toxicity of organic pollutants. In this study, a total of 350 polycyclic aromatic compounds (PACs) in 9 categories were successfully identified in fine particulate matter by gas chromatography high resolution mass spectrometry. Using mass spectra and retention indexes predicted by in silico tools as complementary information, the scope of chemical identification was efficiently expanded by 27%. In addition, quantitative structure-activity relationship models provided toxicity data for over 70% of PACs, facilitating a comprehensive health risk assessment. On the basis of extensive identification, the cumulative noncarcinogenic risk of PACs warranted attention. Meanwhile, the carcinogenic risk of 53 individual analogues was noteworthy. These findings suggest that there is a pressing need for an updated list of priority PACs for routine monitoring and toxicological research since legacy polycyclic aromatic hydrocarbons (PAHs) contributed modestly to the overall abundance (18%) and carcinogenic risk (8%). A toxicological priority index approach was applied for relative chemical ranking considering the environmental occurrence, fate, toxicity, and analytical availability. A list of 39 priority analogues was compiled, which predominantly consisted of high-molecular-weight PAHs and alkyl derivatives. These priority PACs further enhanced source interpretation, and the highest carcinogenic risk was attributed to coal combustion.

Antimicrobial Transformation Products in the Aquatic Environment: Global Occurrence, Ecotoxicological Risks, and Potential of Antibiotic Resistance.

The global spread of antimicrobial resistance (AMR) is concerning for the health of humans, animals, and the environment in a One Health perspective. Assessments of AMR and associated environmental hazards mostly focus on antimicrobial parent compounds, while largely overlooking their transformation products (TPs). This review lists antimicrobial TPs identified in surface water environments and examines their potential for AMR promotion, ecological risk, as well as human health and environmental hazards using in silico models. Our review also summarizes the key transformation compartments of TPs, related pathways for TPs reaching surface waters and methodologies for studying the fate of TPs. The 56 antimicrobial TPs covered by the review were prioritized via scoring and ranking of various risk and hazard parameters. Most data on occurrences to date have been reported in Europe, while little is known about antibiotic TPs in Africa, Central and South America, Asia, and Oceania. Occurrence data on antiviral TPs and other antibacterial TPs are even scarcer. We propose evaluation of structural similarity between parent compounds and TPs for TP risk assessment. We predicted a risk of AMR for 13 TPs, especially TPs of tetracyclines and macrolides. We estimated the ecotoxicological effect concentrations of TPs from the experimental effect data of the parent chemical for bacteria, algae and water fleas, scaled by potency differences predicted by quantitative structure-activity relationships (QSARs) for baseline toxicity and a scaling factor for structural similarity. Inclusion of TPs in mixtures with their parent increased the ecological risk quotient over the threshold of one for 7 of the 24 antimicrobials included in this analysis, while only one parent had a risk quotient above one. Thirteen TPs, from which 6 were macrolide TPs, posed a risk to at least one of the three tested species. There were 12/21 TPs identified that are likely to exhibit a similar or higher level of mutagenicity/carcinogenicity, respectively, than their parent compound, with tetracycline TPs often showing increased mutagenicity. Most TPs with increased carcinogenicity belonged to sulfonamides. Most of the TPs were predicted to be mobile but not bioaccumulative, and 14 were predicted to be persistent. The six highest-priority TPs originated from the tetracycline antibiotic family and antivirals. This review, and in particular our ranking of antimicrobial TPs of concern, can support authorities in planning related intervention strategies and source mitigation of antimicrobials toward a sustainable future.

Recognition and Prioritization of Chemical Mixtures and Transformation Products in Chinese Estuarine Waters by Suspect Screening Analysis.

Chemical mixtures in surface waters could have significant impacts on exposure risks to human beings and pollution stress to aquatic system. By suspect screening analysis of high-resolution mass spectrometry data, occurrence, and compositions of ToxCast chemicals were investigated in grab estuarine water samples from a combination of 20 rivers that represents approximately 70% of the total river flow discharge along the east coast of China. In total, 59 ToxCast chemicals in seven use categories were identified, in which pesticides, intermediates, and pharmaceuticals were the abundant analogues. Significant differences in pollutant composition profiles were noticed, which possibly reflected singular release pattern and geographical-relevant usage preference (especially for herbicides and fungicides in the pesticide category). With the aid of tentative quantitative/semiquantitative measurement, essential contributors to the cumulative pollutant mass discharges and aquatic acute toxicity potentials were focused onto few particular chemicals. Existence of transformation products was further explored, which indicated that the fates of the selected parent ToxCast chemicals could be influenced by dominating transformation reactions (e.g., N-dealkylation and hydroxylation) and possible environmental factors (i.e., microbial activity). The results emphasize the necessity of suspect screening analysis for assessing the influence of terrestrial emissions of pollutants to the surrounding environment.

An in vitro approach for prioritization and evaluation of chemical effects on glucocorticoid receptor mediated adipogenesis.

Rising obesity rates worldwide have socio-economic ramifications. While genetics, diet, and lack of exercise are major contributors to obesity, environmental factors may enhance susceptibility through disruption of hormone homeostasis and metabolic processes. The obesogen hypothesis contends that chemical exposure early in development may enhance adipocyte differentiation, thereby increasing the number of adipocytes and predisposing for obesity and metabolic disease. We previously developed a primary human adipose stem cell (hASC) assay to evaluate the effect of environmental chemicals on PPARG-dependent adipogenesis. Here, the assay was modified to determine the effects of chemicals on the glucocorticoid receptor (GR) pathway. In differentiation cocktail lacking the glucocorticoid agonist dexamethasone (DEX), hASCs do not differentiate into adipocytes. In the presence of GR agonists, adipocyte maturation was observed using phenotypic makers for lipid accumulation, adipokine secretion, and expression of key genes. To evaluate the role of environmental compounds on adipocyte differentiation, progenitor cells were treated with 19 prioritized compounds previously identified by ToxPi as having GR-dependent bioactivity, and multiplexed assays were used to confirm a GR-dependent mode of action. Five chemicals were found to be strong agonists. The assay was also modified to evaluate GR-antagonists, and 8/10 of the hypothesized antagonists inhibited adipogenesis. The in vitro bioactivity data was put into context with extrapolated human steady state concentrations (Css) and clinical exposure data (Cmax). These data support using a human adipose-derived stem cell differentiation assay to test the potential of chemicals to alter human GR-dependent adipogenesis.

A Comparison of In Vitro Points of Departure with Human Blood Levels for Per- and Polyfluoroalkyl Substances (PFAS).

Per- and polyfluoroalkyl substances (PFAS) are widely used, and their fluorinated state contributes to unique uses and stability but also long half-lives in the environment and humans. PFAS have been shown to be toxic, leading to immunosuppression, cancer, and other adverse health outcomes. Only a small fraction of the PFAS in commerce have been evaluated for toxicity using in vivo tests, which leads to a need to prioritize which compounds to examine further. Here, we demonstrate a prioritization approach that combines human biomonitoring data (blood concentrations) with bioactivity data (concentrations at which bioactivity is observed in vitro) for 31 PFAS. The in vitro data are taken from a battery of cell-based assays, mostly run on human cells. The result is a Bioactive Concentration to Blood Concentration Ratio (BCBCR), similar to a margin of exposure (MoE). Chemicals with low BCBCR values could then be prioritized for further risk assessment. Using this method, two of the PFAS, PFOA (Perfluorooctanoic Acid) and PFOS (Perfluorooctane Sulfonic Acid), have BCBCR values < 1 for some populations. An additional 9 PFAS have BCBCR values < 100 for some populations. This study shows a promising approach to screening level risk assessments of compounds such as PFAS that are long-lived in humans and other species.

Innovative non-targeted screening approach using High-resolution mass spectrometry for the screening of organic chemicals and identification of specific tracers of soil and dust exposure in children.

Environmental contamination through direct contact, ingestion and inhalation are common routes of children's exposure to chemicals, in which through indoor and outdoor activities associated with common hand-to-mouth, touching objects, and behavioral tendencies, children can be susceptible and vulnerable to organic contaminants in the environment. The objectives of this study were the screening and identification of a wide range of organic contaminants in indoor dust, soil, food, drinking water, and urine matrices (N = 439), prioritizing chemicals to assess children's environmental exposure, and selection of unique tracers of soil and dust ingestion in young children by non-targeted analysis (NTA) using Q-Exactive Orbitrap followed data processing by the Compound Discoverer (v3.3, SP2). Chemical features were first prioritized based on their predominant abundance (peak area>500,000), detection frequency (in >50% of the samples), available information on their uses and potential toxicological effects. Specific tracers of soil and dust exposure in children were selected in this study including Tripropyl citrate and 4-Dodecylbenzenesulfonic acid. The criteria for selection of the tracers were based on their higher abundance, detection frequency, unique functional uses, measurable amounts in urine (suitable biomarker), and with information on gastrointestinal absorption, metabolism, and excretion, and were further confirmed by authentic standards. We are proposing for the first time suitable unique tracers for dust ingestion by children.

Chemistry domain of applicability evaluation against existing estrogen receptor high-throughput assay-based activity models.

Introduction: The U. S. Environmental Protection Agency's Endocrine Disruptor Screening Program (EDSP) Tier 1 assays are used to screen for potential endocrine system-disrupting chemicals. A model integrating data from 16 high-throughput screening assays to predict estrogen receptor (ER) agonism has been proposed as an alternative to some low-throughput Tier 1 assays. Later work demonstrated that as few as four assays could replicate the ER agonism predictions from the full model with 98% sensitivity and 92% specificity. The current study utilized chemical clustering to illustrate the coverage of the EDSP Universe of Chemicals (UoC) tested in the existing ER pathway models and to investigate the utility of chemical clustering to evaluate the screening approach using an existing 4-assay model as a test case. Although the full original assay battery is no longer available, the demonstrated contribution of chemical clustering is broadly applicable to assay sets, chemical inventories, and models, and the data analysis used can also be applied to future evaluation of minimal assay models for consideration in screening. Methods: Chemical structures were collected for 6,947 substances via the CompTox Chemicals Dashboard from the over 10,000 UoC and grouped based on structural similarity, generating 826 chemical clusters. Of the 1,812 substances run in the original ER model, 1,730 substances had a single, clearly defined structure. The ER model chemicals with a clearly defined structure that were not present in the EDSP UoC were assigned to chemical clusters using a k-nearest neighbors approach, resulting in 557 EDSP UoC clusters containing at least one ER model chemical. Results and Discussion: Performance of an existing 4-assay model in comparison with the existing full ER agonist model was analyzed as related to chemical clustering. This was a case study, and a similar analysis can be performed with any subset model in which the same chemicals (or subset of chemicals) are screened. Of the 365 clusters containing >1 ER model chemical, 321 did not have any chemicals predicted to be agonists by the full ER agonist model. The best 4-assay subset ER agonist model disagreed with the full ER agonist model by predicting agonist activity for 122 chemicals from 91 of the 321 clusters. There were 44 clusters with at least two chemicals and at least one agonist based upon the full ER agonist model, which allowed accuracy predictions on a per-cluster basis. The accuracy of the best 4-assay subset ER agonist model ranged from 50% to 100% across these 44 clusters, with 32 clusters having accuracy ≥90%. Overall, the best 4-assay subset ER agonist model resulted in 122 false-positive and only 2 false-negative predictions compared with the full ER agonist model. Most false positives (89) were active in only two of the four assays, whereas all but 11 true positive chemicals were active in at least three assays. False positive chemicals also tended to have lower area under the curve (AUC) values, with 110 out of 122 false positives having an AUC value below 0.214, which is lower than 75% of the positives as predicted by the full ER agonist model. Many false positives demonstrated borderline activity. The median AUC value for the 122 false positives from the best 4-assay subset ER agonist model was 0.138, whereas the threshold for an active prediction is 0.1. Conclusion: Our results show that the existing 4-assay model performs well across a range of structurally diverse chemicals. Although this is a descriptive analysis of previous results, several concepts can be applied to any screening model used in the future. First, the clustering of the chemicals provides a means of ensuring that future screening evaluations consider the broad chemical space represented by the EDSP UoC. The clusters can also assist in prioritizing future chemicals for screening in specific clusters based on the activity of known chemicals in those clusters. The clustering approach can be useful in providing a framework to evaluate which portions of the EDSP UoC chemical space are reliably covered by in silico and in vitro approaches and where predictions from either method alone or both methods combined are most reliable. The lessons learned from this case study can be easily applied to future evaluations of model applicability and screening to evaluate future datasets.

Integrating mechanistic and polymorphism data to characterize human genetic susceptibility for environmental chemical risk assessment in the 21st century.

Response to environmental chemicals can vary widely among individuals and between population groups. In human health risk assessment, data on susceptibility can be utilized by deriving risk levels based on a study of a susceptible population and/or an uncertainty factor may be applied to account for the lack of information about susceptibility. Defining genetic susceptibility in response to environmental chemicals across human populations is an area of interest in the NAS' new paradigm of toxicity pathway-based risk assessment. Data from high-throughput/high content (HT/HC), including -omics (e.g., genomics, transcriptomics, proteomics, metabolomics) technologies, have been integral to the identification and characterization of drug target and disease loci, and have been successfully utilized to inform the mechanism of action for numerous environmental chemicals. Large-scale population genotyping studies may help to characterize levels of variability across human populations at identified target loci implicated in response to environmental chemicals. By combining mechanistic data for a given environmental chemical with next generation sequencing data that provides human population variation information, one can begin to characterize differential susceptibility due to genetic variability to environmental chemicals within and across genetically heterogeneous human populations. The integration of such data sources will be informative to human health risk assessment.

Integrating high-throughput exposure assessment and in vitro screening data to prioritize endocrine-active potential and dietary risks of pesticides and veterinary drug residues in animal products.

New approach methodologies in toxicology, such as in vitro high-throughput screening (HTS), can minimize the use of experimental animals and allow mechanism-based predictions of in vivo toxicity. HTS data has been increasingly used in the regulatory context; however, only a few studies integrated dietary exposure and HTS data to foster chemical prioritization in food. Additionally, the endocrine-associated risk of veterinary drug residues in food is yet to be fully characterized. This study aims to systematically compare the translated HTS data with the acceptable daily intake (ADI) values and prioritize the pesticides and veterinary drug residues (n = 294) in food using the exposure-activity ratio (EAR) and Toxicological Prioritization index (ToxPi). The dietary exposure assessment was accomplished using a stochastic human exposure and dose simulation high-throughput model (SHEDS-HT). We selected 76 HTS assays from 12 nuclear receptors to represent the molecular initiating event (MIE) of endocrine-disrupting phenotypes. Chemical prioritization was achieved using 4 methods (i.e., EAR-OED, EAR-ADI, ToxPi-exposure + ADI, and ToxPi-exposure + endocrine score), where the consensus prioritized chemicals were fipronil, furazolidone, oxolinic acid, and oxytetracycline for the Taiwanese population. This case study demonstrates the utility of HTS data in fostering regulatory decisions on chemicals, especially for those lacking comprehensive toxicity data.

Prioritization of risks posed by synthetic chemicals manufactured in China toward humans and the environment via persistence, bioaccumulation, mobility and toxicity properties.

Over a third of the global chemical production and sales occurred in China, which make effective assessment and management for chemicals produced by China's chemical industry essential not just for China but for the world. Here, we systematical assessed the persistence (P), bioaccumulation (B), mobility (M) and toxicity (T) potency properties for the chemicals listed in Inventory of Existing Chemical Substances of China (IECSC) via experimental data retrieved from large scale databases and in silico data generated with well-established models. Potential PBT, PMT and PB&MT substances were identified. High risk potentials were highlighted for groups of synthetic intermediates, raw materials, as well as a series of biocides. The potential PBT and PMT synthetic intermediates and/or raw materials unique to the IECSC were dominated with organofluorines, for example, the intermediates used as electronic light-emitting materials. Meanwhile, the biocides unique to the IECSC were mainly organochlorines. Some conventional classes of insecticides, such as organochlorines and pyrethroids, were classified as being of high concern. We further identified a group of PB&MT substances that were considered to be both "bioaccumulative" and "mobile". Their properties and common substructures for several major clusters were characterized. The present results prioritized groups of substances with high potentials to cause adverse effects to the environment and humans, many of which have not yet been fully recognized.

Chemical prioritization of pharmaceuticals and personal care products in an urban tributary of the Potomac River.

Pharmaceuticals and personal care products (PPCPs) are incredibly diverse in terms of chemical structures, physicochemical properties, and modes of action, making their environmental impacts challenging to assess. New chemical prioritization methodologies have emerged that compare contaminant monitoring concentrations to multiple toxicity data sources, including whole organism and high-throughput data, to develop a list of "high priority" chemicals requiring further study. We applied such an approach to assess PPCPs in Hunting Creek, an urban tributary of the Potomac River near Washington, DC, which has experienced extensive human population growth. We estimated potential risks of 99 PPCPs from surface water and sediment collected upstream and downstream of a major wastewater treatment plant (WWTP), nearby combined sewer overflows (CSO), and in the adjacent Potomac River. The greatest potential risks to the aquatic ecosystem occurred near WWTP and CSO outfalls, but risk levels rapidly dropped below thresholds of concern - established by previous chemical prioritization studies - in the Potomac mainstem. These results suggest that urban tributaries, rather than larger rivers, are important to monitor because their lower or intermittent flow may not adequately dilute contaminants of concern. Common psychotropics, such as fluoxetine and venlafaxine, presented the highest potential risks, with toxicity quotients often > 10 in surface water and > 1000 in sediment, indicating the need for further field studies. Several ubiquitous chemicals such as caffeine and carbamazepine also exceeded thresholds of concern throughout our study area and point to specific neurotoxic and endocrine modes of action that warrant further investigation. Since many "high priority" chemicals in our analysis have also triggered concerns in other areas around the world, better coordination is needed among environmental monitoring programs to improve global chemical prioritization efforts.

Leveraging Multiple Data Streams for Prioritization of Mixtures for Hazard Characterization.

There is a growing need to establish alternative approaches for mixture safety assessment of polycyclic aromatic hydrocarbons (PAHs). Due to limitations with current component-based approaches, and the lack of established methods for using whole mixtures, a promising alternative is to use sufficiently similar mixtures; although, an established framework is lacking. In this study, several approaches are explored to form sufficiently similar mixtures. Multiple data streams including environmental concentrations and empirically and predicted toxicity data for cancer and non-cancer endpoints were used to prioritize chemical components for mixture formations. Air samplers were analyzed for unsubstituted and alkylated PAHs. A synthetic mixture of identified PAHs was created (Creosote-Fire Mix). Existing toxicity values and chemical concentrations were incorporated to identify hazardous components in the Creosote-Fire Mix. Sufficiently similar mixtures of the Creosote-Fire Mix were formed based on (1) relative abundance; (2) toxicity values; and (3) a combination approach incorporating toxicity and abundance. Hazard characterization of these mixtures was performed using high-throughput screening in primary normal human bronchial epithelium (NHBE) and zebrafish. Differences in chemical composition and potency were observed between mixture formation approaches. The toxicity-based approach (Tox Mix) was the most potent mixture in both models. The combination approach (Weighted-Tox Mix) was determined to be the ideal approach due its ability to prioritize chemicals with high exposure and hazard potential.

Identifying the link between chemical exposures and breast cancer in African American women via integrated in vitro and exposure biomarker data.

Among women, breast cancer is the most prevalent form of cancer worldwide and has the second highest mortality rate of any cancer in the United States. The breast cancer related death rate is 40 % higher in non-Hispanic Black women compared to non-Hispanic White women. The incidence of triple negative breast cancer (TNBC), an aggressive subtype of breast cancer for which there is no targeted therapy, is also approximately three times higher for Black, relative to, White women. The drivers of these differences are poorly understood. Here, we aimed to identify chemical exposures which play a role in breast cancer disparities. Using chemical biomonitoring data from the National Health and Nutrition Examination Survey (NHANES) and biological activity data from the EPA's ToxCast program, we assessed the toxicological profiles of chemicals to which US Black women are disproportionately exposed. We conducted a literature search to identify breast cancer targets in ToxCast to analyze the response of chemicals with exposure disparities in these assays. Forty-three chemical biomarkers are significantly higher in Black women. Investigation of these chemicals in ToxCast resulted in 32,683 assays for analysis, 5172 of which contained nonzero values for the concentration at which the dose-response fitted model reaches the cutoff considered "active". Of these chemicals BPA, PFOS, and thiram are most comprehensively assayed. 2,5-dichlorophenol, 1,4-dichlorobenzene, and methyl and propyl parabens had higher biomarker concentrations in Black women and moderate testing and activity in ToxCast. The distribution of active concentrations for these chemicals in ToxCast assays are comparable to biomarker concentrations in Black women NHANES participants. Through this integrated analysis, we identify that multiple chemicals, including thiram, propylparaben, and p,p' DDE, have disproportionate exposures in Black women and have breast cancer associated biological activity at human exposure relevant doses.

Effects-based monitoring of bioactive compounds associated with municipal wastewater treatment plant effluent discharge to the South Platte River, Colorado, USA.

Previous studies have detected numerous organic contaminants and in vitro bioactivities in surface water from the South Platte River near Denver, Colorado, USA. To evaluate the temporal and spatial distribution of selected contaminants of emerging concern, water samples were collected throughout 2018 and 2019 at 11 sites within the S. Platte River and surrounding tributaries with varying proximities to a major wastewater treatment plant (WWTP). Water samples were analyzed for pharmaceuticals, pesticides, steroid hormones, and wastewater indicators and screened for in vitro biological activities. Multiplexed, in vitro assays that simultaneously screen for agonistic activity against 24 human nuclear receptors detected estrogen receptor (ER), peroxisome proliferator activated receptor-gamma (PPARγ), and glucocorticoid receptor (GR) bioactivities in water samples near the WWTP outflow. Targeted in vitro bioassays assessing ER, GR, and PPARγ agonism corroborated bioactivities for ER (up to 55 ± 9.7 ng/L 17ß-estradiol equivalents) and GR (up to 156 ± 28 ng/L dexamethasone equivalents), while PPARγ activity was not confirmed. To evaluate the potential in vivo significance of the bioactive contaminants, sexually-mature fathead minnows were caged at six locations upstream and downstream of the WWTP for 5 days after which targeted gene expression analyses were performed. Significant up-regulation of male hepatic vitellogenin was observed at sites with corresponding in vitro ER activity. No site-related differences in GR-related transcript abundance were detected in female adipose or male livers, suggesting observed environmental concentrations of GR-active contaminants do not induce a detectable in vivo response. In line with the lack of detectable targeted in vitro PPARÉ£ activity, there were no significant effects on PPARÉ£-related gene expression. Although the chemicals responsible for GR and PPAR-mediated bioactivities are unknown, results from the present study provide insights into the significance (or lack thereof) of these bioactivities relative to short-term in situ fish exposures.

Utilizing High-Throughput Screening Data, Integrative Toxicological Prioritization Index Score, and Exposure-Activity Ratios for Chemical Prioritization: A Case Study of Endocrine-Active Pesticides in Food Crops.

Endocrine-active chemicals can directly act on nuclear receptors and trigger the disturbances of metabolism and a homeostatic system, which are important risk factors for complicating chronic diseases in humans. The endocrine-active potentials of pesticides acting on estrogen, androgen, and thyroid hormone receptors have been extensively evaluated for pesticides; however, the effects on other receptors are less understood. This study aims to comprehensively characterize and prioritize the endocrine-active pesticides using an exposure-activity ratio (EAR) method and toxicological prioritization index (ToxPi). The aggregate exposure assessment of pesticides was performed using a computational exposure model [stochastic human exposure and dose simulation high-throughput model (SHEDS-HT)]. Minimum in vitro point of departure values were converted to human oral equivalent doses via in vitro-to-in vivo extrapolation. The overall endocrine-disrupting potentials of pesticides were evaluated via 76 assays, representing 11 nuclear receptors. EARs and ToxPi scores were then derived to prioritize 79 pesticides in food. This case study demonstrates that EAR profiling can inform the regulatory agencies for a relevant chemical prioritization, which would direct in-depth health risk assessments in the future.

Characterizing honey bee exposure and effects from pesticides for chemical prioritization and life cycle assessment.

Agricultural pesticides are key contributors to pollinator decline worldwide. However, methods for quantifying impacts associated with pollinator exposure to pesticides are currently missing in comparative risk screening, chemical substitution and prioritization, and life cycle impact assessment methods. To address this gap, we developed a method for quantifying pesticide field exposure and ecotoxicity effects of honey bees as most economically important pollinator species worldwide. We defined bee intake and dermal contact fractions representing respectively oral and dermal exposure per unit mass applied, and tested our model on two pesticides applied to oilseed rape. Our results show that exposure varies between types of forager bees, with highest dermal contact fraction of 59 ppm in nectar foragers for lambda-cyhalothrin (insecticide), and highest oral intake fractions of 32 and 190 ppm in nectar foragers for boscalid (fungicide) and lambda-cyhalothrin, respectively. Hive oral exposure is up to 115 times higher than forager oral exposure. Combining exposure with effect estimates yields impacts, which are three orders of magnitude higher for the insecticide. Overall, nectar foragers are the most affected forager type for both pesticides, dominated by oral exposure. Our framework constitutes an important step toward integrating pollinator impacts in chemical substitution and life cycle impact assessment, and should be expanded to cover all relevant pesticide-crop combinations.

An Integrated Approach Using Publicly Available Resources for Identifying and Characterizing Chemicals of Potential Toxicity Concern: Proof-of-Concept With Chemicals That Affect Cancer Pathways.

We developed an integrated, modular approach to predicting chemical toxicity relying on in vitro assay data, linkage of molecular targets to disease categories, and software for ranking chemical activity and examining structural features (chemotypes). We evaluate our approach in a proof-of-concept exercise to identify and prioritize chemicals of potential carcinogenicity concern. We identified 137 cancer pathway-related assays from a subset of U.S. EPA's ToxCast platforms. We mapped these assays to key characteristics of carcinogens and found they collectively assess 5 of 10 characteristics. We ranked all 1061 chemicals screened in Phases I and II of ToxCast by their activity in the selected cancer pathway-related assays using Toxicological Prioritization Index software. More chemicals used as biologically active agents (eg, pharmaceuticals) ranked in the upper 50% versus lower 50%. Twenty-three chemotypes are enriched in the top 5% (n = 54) of chemicals; these features may be important for their activity in cancer pathway-related assays. The biological coverage of the ToxCast assays related to cancer pathways is limited and short-term assays may not capture the biology of some key characteristics. Metabolism is also minimal in the assays. The ability of our approach to identify chemicals with cancer hazard is limited with the current input data, but we expect that our approach can be applied with future iterations of ToxCast and other data for improved chemical prioritization and characterization. The novel approach and proof-of-concept exercise described here for ranking chemicals for potential carcinogenicity concern is modular, adaptable, and amenable to evolving data streams.

Characterizing the effects of missing data and evaluating imputation methods for chemical prioritization applications using ToxPi.

BACKGROUND: The Toxicological Priority Index (ToxPi) is a method for prioritization and profiling of chemicals that integrates data from diverse sources. However, individual data sources ("assays"), such as in vitro bioassays or in vivo study endpoints, often feature sections of missing data, wherein subsets of chemicals have not been tested in all assays. In order to investigate the effects of missing data and recommend solutions, we designed simulation studies around high-throughput screening data generated by the ToxCast and Tox21 programs on chemicals highlighted by the Agency for Toxic Substances and Disease Registry's (ATSDR) Substance Priority List (SPL), which helps prioritize environmental research and remediation resources. RESULTS: Our simulations explored a wide range of scenarios concerning data (0-80% assay data missing per chemical), modeling (ToxPi models containing from 160-700 different assays), and imputation method (k-Nearest-Neighbor, Max, Mean, Min, Binomial, Local Least Squares, and Singular Value Decomposition). We find that most imputation methods result in significant changes to ToxPi score, except for datasets with a small number of assays. If we consider rank change conditional on these significant changes to ToxPi score, we find that ranks of chemicals in the minimum value imputation, SVD imputation, and kNN imputation sets are more sensitive to the score changes. CONCLUSIONS: We found that the choice of imputation strategy exerted significant influence over both scores and associated ranks, and the most sensitive scenarios were those involving fewer assays plus higher proportions of missing data. By characterizing the effects of missing data and the relative benefit of imputation approaches across real-world data scenarios, we can augment confidence in the robustness of decisions regarding the health and ecological effects of environmental chemicals.