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Per- and poly-fluoroalkyl substances (PFAS) are emerging contaminants of concern because of their wide use, persistence, and potential to be hazardous to both humans and the environment. Several PFAS have been designated as substances of concern; however, most PFAS in commerce lack toxicology and exposure data to evaluate their potential hazards and risks. Cardiotoxicity has been identified as a likely human health concern, and cell-based assays are the most sensible approach for screening and prioritization of PFAS. Human-induced pluripotent stem cell (iPSC)-derived cardiomyocytes are a widely used method to test for cardiotoxicity, and recent studies showed that many PFAS affect these cells. Because iPSC-derived cardiomyocytes are available from different donors, they also can be used to quantify human variability in responses to PFAS. The primary objective of this study was to characterize potential human cardiotoxic hazard, risk, and inter-individual variability in responses to PFAS. A total of 56 PFAS from different subclasses were tested in concentration-response using human iPSC-derived cardiomyocytes from 16 donors without known heart disease. Kinetic calcium flux and high-content imaging were used to evaluate biologically-relevant phenotypes such as beat frequency, repolarization, and cytotoxicity. Of the tested PFAS, 46 showed concentration-response effects in at least one phenotype and donor; however, a wide range of sensitivities were observed across donors. Inter-individual variability in the effects could be quantified for 19 PFAS, and risk characterization could be performed for 20 PFAS based on available exposure information. For most tested PFAS, toxicodynamic variability was within a factor of 10 and the margins of exposure were above 100. This study identified PFAS that may pose cardiotoxicity risk and have high inter-individual variability. It also demonstrated the feasibility of using a population-based human in vitro method to quantify population variability and identify cardiotoxicity risks of emerging contaminants.

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An important element of the European Union's "Registration, Evaluation, Authorisation and Restriction of Chemicals" (REACH) regulation is the evaluation by the European Chemicals Agency (ECHA) of testing proposals submitted by the registrants to address data gaps in standard REACH information requirements. The registrants may propose adaptations, and ECHA evaluates the reasoning and issues a written decision. Read-across is a common adaptation type, yet it is widely assumed that ECHA often does not agree that the justifications are adequate to waive standard testing requirements. From 2008 to August 2023, a total of 2,630 Testing Proposals were submitted to ECHA; of these, 1,538 had published decisions that were systematically evaluated in this study. Each document was manually reviewed, and information extracted for further analyses. Read-across hypotheses were standardized into 17 assessment elements (AEs); each submission was classified as to the AEs relied upon by the registrants and by ECHA. Data was analyzed for patterns and associations. Testing Proposal Evaluations (TPEs) with adaptations comprised 23% (353) of the total; analogue (168) or group (136) read-across adaptations were most common. Of 304 read-across-containing TPEs, 49% were accepted; the odds of acceptance were significantly greater for group read-across submissions. The data was analyzed by Annex (i.e., tonnage), test guideline study, read-across hypothesis AEs, as well as target and source substance types and their structural similarity. While most ECHA decisions with both positive and negative decisions on whether the proposed read-across was adequate were context-specific, a number of significant associations were identified that influence the odds of acceptance. Overall, this analysis provides an unbiased overview of 15 years of experience with testing proposal-specific read-across adaptations by both registrants and ECHA. These data will inform future submissions as they identify most critical AEs to increase the odds of read-across acceptance.

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There are two primary sources of uncertainty in the interpretability of toxicity values, like the reference dose (RfD): estimates of the point of departure (POD) and the absence of chemical-specific human variability data. We hypothesize two solutions-employing Bayesian benchmark dose (BBMD) modeling to refine POD determination and combining high-throughput toxicokinetic modeling with population-based toxicodynamic in vitro data to characterize chemical-specific variability. These hypotheses were tested by deriving refined probabilistic estimates for human doses corresponding to a specific effect size (M) in the Ith population percentile (HDM I) across 19 Superfund priority chemicals. HDM I values were further converted to biomonitoring equivalents in blood and urine for benchmarking against human data. Compared to deterministic default-based RfDs, HDM I values were generally more protective, particularly influenced by chemical-specific data on interindividual variability. Incorporating chemical-specific in vitro data improved precision in probabilistic RfDs, with a median 1.4-fold reduction in uncertainty variance. Comparison with US Environmental Protection Agency's Exposure Forecasting exposure predictions and biomonitoring data from the National Health and Nutrition Examination Survey identified chemicals with margins of exposure nearing or below one. Overall, to mitigate uncertainty in regulatory toxicity values and guide chemical risk management, BBMD modeling and chemical-specific population-based human in vitro data are essential.

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Environmental chemicals may contribute to the global burden of cardiovascular disease, but experimental data are lacking to determine which substances pose the greatest risk. Human-induced pluripotent stem cell (iPSC)-derived cardiomyocytes are a high-throughput cardiotoxicity model that is widely used to test drugs and chemicals; however, most studies focus on exploring electro-physiological readouts. Gene expression data may provide additional molecular insights to be used for both mechanistic interpretation and dose-response analyses. Therefore, we hypothesized that both transcriptomic and functional data in human iPSC-derived cardiomyocytes may be used as a comprehensive screening tool to identify potential cardiotoxicity hazards and risks of the chemicals. To test this hypothesis, we performed concentration-response analysis of 464 chemicals from 12 classes, including both pharmaceuticals and nonpharmaceutical substances. Functional effects (beat frequency, QT prolongation, and asystole), cytotoxicity, and whole transcriptome response were evaluated. Points of departure were derived from phenotypic and transcriptomic data, and risk characterization was performed. Overall, 244 (53%) substances were active in at least one phenotype; as expected, pharmaceuticals with known cardiac liabilities were the most active. Positive chronotropy was the functional phenotype activated by the largest number of tested chemicals. No chemical class was particularly prone to pose a potential hazard to cardiomyocytes; a varying proportion (10-44%) of substances in each class had effects on cardiomyocytes. Transcriptomic data showed that 69 (15%) substances elicited significant gene expression changes; most perturbed pathways were highly relevant to known key characteristics of human cardiotoxicants. The bioactivity-to-exposure ratios showed that phenotypic- and transcriptomic-based POD led to similar results for risk characterization. Overall, our findings demonstrate how the integrative use of in vitro transcriptomic and phenotypic data from iPSC-derived cardiomyocytes not only offers a complementary approach for hazard and risk prioritization, but also enables mechanistic interpretation of the in vitro test results to increase confidence in decision-making.

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Non-alcoholic fatty liver disease (NAFLD) is a progressive liver disease, affecting 38% of adults globally. If left untreated, NAFLD may progress to more advanced forms of the disease, including non-alcoholic steatohepatitis (NASH), liver cirrhosis, and fibrosis. Early NAFLD detection is critical to prevent disease progression. Using an obesogenic high-fat and high-sucrose (HF/HS) diet, we characterized the progression of NAFLD in male and female Collaborative Cross CC042 mice after 20-, 40-, and 60-week intervals of chronic HF/HS diet feeding. The incidence and severity of liver steatosis, inflammation, and fibrosis increased in both sexes over time, with male mice progressing to a NASH-like disease state faster than female mice, as indicated by earlier and more pronounced changes in liver steatosis. Histopathological indication of macrovesicular steatosis and gene expression changes of key lipid metabolism genes were found to be elevated in both sexes after 20 weeks of HF/HS diet. Measurement of circulating markers of inflammation (CXCL10 and TNF-α), histopathological analysis of immune cell infiltrates, and gene expression changes in inflammation-related genes indicated significant liver inflammation after 40 and 60 weeks of HF/HS diet exposure in both sexes. Liver fibrosis, as assessed by Picosirius red and Masson's trichrome staining and changes in expression of key fibrosis related genes indicated significant changes after 40 and 60 weeks of HF/HS diet exposure. In conclusion, we present a preclinical animal model of dietary NAFLD progression, which recapitulates human pathophysiological and pathomorphological changes, that could be used to better understand the progression of NAFLD and support development of new therapeutics.

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Per- and poly-fluoroalkyl substances (PFAS) have a wide range of elimination half-lives (days to years) in humans, thought to be in part due to variation in proximal tubule reabsorption. While human biomonitoring studies provide important data for some PFAS, renal clearance (CLrenal) predictions for hundreds of PFAS in commerce requires experimental studies with in vitro models and physiologically-based in vitro-to-in vivo extrapolation (IVIVE). Options for studying renal proximal tubule pharmacokinetics include cultures of renal proximal tubule epithelial cells (RPTECs) and/or microphysiological systems. This study aimed to compare CLrenal predictions for PFAS using in vitro models of varying complexity (96-well plates, static 24-well Transwells and a fluidic microphysiological model, all using human telomerase reverse transcriptase-immortalized and OAT1-overexpressing RPTECs combined with in silico physiologically-based IVIVE. Three PFAS were tested: one with a long half-life (PFOS) and two with shorter half-lives (PFHxA and PFBS). PFAS were added either individually (5 µM) or as a mixture (2 µM of each substance) for 48 h. Bayesian methods were used to fit concentrations measured in media and cells to a three-compartmental model to obtain the in vitro permeability rates, which were then used as inputs for a physiologically-based IVIVE model to estimate in vivo CLrenal. Our predictions for human CLrenal of PFAS were highly concordant with available values from in vivo human studies. The relative values of CLrenal between slow- and faster-clearance PFAS were most highly concordant between predictions from 2D culture and corresponding in vivo values. However, the predictions from the more complex model (with or without flow) exhibited greater concordance with absolute CLrenal. Overall, we conclude that a combined in vitro-in silico workflow can predict absolute CLrenal values, and effectively distinguish between PFAS with slow and faster clearance, thereby allowing prioritization of PFAS with a greater potential for bioaccumulation in humans.

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In vitro models that can faithfully replicate critical aspects of kidney tubule function such as directional drug transport are in high demand in pharmacology and toxicology. Accordingly, development and validation of new models is underway. The objective of this study was to characterize physiological and transport functions of various sources of human renal proximal tubule epithelial cells (RPTECs). We tested TERT1-immortalized RPTEC, including OAT1-, OCT2- or OAT3-overexpressing variants, and primary RPTECs. Cells were cultured on transwell membranes in static (24-well transwells) and fluidic (transwells in PhysioMimix{trade mark, serif} T12 organ-on-chip with 2 mL/s flow) conditions. Barrier formation, transport, and gene expression were evaluated. We show that two commercially available primary RPTECs were not suitable for studies of directional transport on transwells because they formed a substandard barrier even though they exhibited higher expression of transporters, especially under flow. TERT1-parent, -OAT1 and -OAT3 cells formed robust barriers, but were unaffected by flow. TERT1-OAT1 cells exhibited inhibitable para-aminohippurate transport, it was enhanced by flow. However, efficient tenofovir secretion and perfluorooctanoic acid reabsorption by TERT1-OAT1 cells were not modulated by flow. Gene expression showed that TERT1 and TERT1-OAT1 cells were most correlated with human kidney than other cell lines, but that flow did not have noticeable effects. Overall, our data show that addition of flow to in vitro studies of the renal proximal tubule may afford benefits in some aspects of modeling kidney function, but that careful consideration of the impact such adaptations would have on the cost and throughput of the experiments is needed. Significance Statement The topic of reproducibility and robustness of the complex microphysiological systems is looming large in the field of biomedical research; therefore, the uptake of these new models by the end-users is slow. This study systematically compared various RPTEC sources and experimental conditions, aiming to identify the level of model complexity needed for testing renal tubule transport. We demonstrate that while tissue chips may afford some benefits, their throughput and complexity need careful consideration in each context of use.

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To fulfil the promise of reducing reliance on mammalian in vivo laboratory animal studies, new approach methods (NAMs) need to provide a confident basis for regulatory decision-making. However, previous attempts to develop in vitro NAMs-based points of departure (PODs) have yielded mixed results, with PODs from U.S. EPA's ToxCast, for instance, appearing more conservative (protective) but poorly correlated with traditional in vivo studies. Here, we aimed to address this discordance by reducing the heterogeneity of in vivo PODs, accounting for species differences, and enhancing the biological relevance of in vitro PODs. However, we only found improved in vitro-to-in vivo concordance when combining the use of Bayesian model averaging-based benchmark dose modeling for in vivo PODs, allometric scaling for interspecies adjustments, and human-relevant in vitro assays with multiple induced pluripotent stem cell-derived models. Moreover, the available sample size was only 15 chemicals, and the resulting level of concordance was only fair, with correlation coefficients <0.5 and prediction intervals spanning several orders of magnitude. Overall, while this study suggests several ways to enhance concordance and thereby increase scientific confidence in vitro NAMs-based PODs, it also highlights challenges in their predictive accuracy and precision for use in regulatory decision making.

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Per- and polyfluoroalkyl substances (PFAS) are chemicals with important applications; they are persistent in the environment and may pose human health hazards. Regulatory agencies are con­sidering restrictions and bans of PFAS; however, little data exists for informed decisions. Several prioritization strategies were proposed for evaluation of potential hazards of PFAS. Structure-based grouping could expedite the selection of PFAS for testing; still, the hypothesis that structure-effect relationships exist for PFAS requires confirmation. We tested 26 structurally diverse PFAS from 8 groups using human induced pluripotent stem cell-derived hepatocytes and cardiomyocytes, and tested concentration-response effects on cell function and gene expression. Few phenotypic effects were observed in hepatocytes, but negative chronotropy was observed in cardiomyocytes for 8 PFAS. Substance- and cell type-dependent transcriptomic changes were more prominent but lacked substantial group-specific effects. In hepatocytes, we found upregulation of stress-related and extracellular matrix organization pathways, and down-regulation of fat metabolism. In car­diomyocytes, contractility-related pathways were most affected. We derived phenotypic and transcriptomic points of departure and compared them to predicted PFAS exposures. Conservative estimates for bioactivity and exposure were used to derive a bioactivity-to-exposure ratio (BER) for each PFAS; 23 of 26 PFAS had BER > 1. Overall, these data suggest that structure-based PFAS grouping may not be sufficient to predict their biological effects. Testing of individual PFAS may be needed for scientifically-supported decision-making. Our proposed strategy of using two human cell types and considering phenotypic and transcriptomic effects, combined with dose-response analysis and calculation of BER, may be used for PFAS prioritization.

Per- and polyfluoroalkyl substances (PFAS) are man-made chemicals used in many products. However, most of these substances have not been tested for safety, and concerns exist that they may be harmful to human health and/or the environment. This study aimed to use human cell-based models to investigate if some of the PFAS may exhibit hazardous properties and if similarities among substance groups are observed. Few effects were observed in liver cells, but a decrease in beating frequency was observed in heart cells for some PFAS. Gene expression changes were substance-and cell type-dependent. We did not find convincing structure-based similarities among PFAS; this suggests that testing of individual PFAS may be necessary in the future to inform health decisions. Overall, this study showed that a test strategy of using two human cell types, from liver and heart, may inform PFAS prioritization without a need for testing in animals.

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Per- and poly-fluoroalkyl substances (PFAS) are extensively used in commerce leading to their prevalence in the environment. Due to their chemical stability, PFAS are considered to be persistent and bioaccumulative; they are frequently detected in both the environment and humans. Because of this, PFAS as a class (composed of hundreds to thousands of chemicals) are contaminants of very high concern. Little information is available for the vast majority of PFAS, and regulatory agencies lack safety data to determine whether exposure limits or restrictions are needed. Cell-based assays are a pragmatic approach to inform decision-makers on potential health hazards; therefore, we hypothesized that a targeted battery of human in vitro assays can be used to determine whether there are structure-bioactivity relationships for PFAS, and to characterize potential risks by comparing bioactivity (points of departure) to exposure estimates. We tested 56 PFAS from 8 structure-based subclasses in concentration response (0.1-100 µM) using six human cell types selected from target organs with suggested adverse effects of PFAS - human induced pluripotent stem cell (iPSC)-derived hepatocytes, neurons, and cardiomyocytes, primary human hepatocytes, endothelial and HepG2 cells. While many compounds were without effect; certain PFAS demonstrated cell-specific activity highlighting the necessity of using a compendium of in vitro models to identify potential hazards. No class-specific groupings were evident except for some chain length- and structure-related trends. In addition, margins of exposure (MOE) were derived using empirical and predicted exposure data. Conservative MOE calculations showed that most tested PFAS had a MOE in the 1-100 range; ∼20% of PFAS had MOE<1, providing tiered priorities for further studies. Overall, we show that a compendium of human cell-based models can be used to derive bioactivity estimates for a range of PFAS, enabling comparisons with human biomonitoring data. Furthermore, we emphasize that establishing structure-bioactivity relationships may be challenging for the tested PFAS.

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The effects of endocrine-disrupting compounds (EDCs) on the placenta, a critical gestational organ for xenobiotic protection, are well reported; however, models to determine the role of EDCs in placental disruption are limited. An advanced 2nd-trimester human placenta organ-on-chip model (2TPLA-OOC) was developed and validated, with six representative cells of the maternal and the fetal interface interconnected with microchannels. Various EDCs (150 ng mL-1 each of bisphenol A, bisphenol S, and polybrominated diphenyl ethers-47 and -99) were gradually propagated across the chip for 72 hours, and their various effects were determined. Cigarette smoke extract (CSE), an environmental risk factor, was used as a positive control. EDCs produced overall oxidative stress in the placental/decidual cells, induced cell-specific endocrine effects, caused limited (<10%) apoptosis/necrosis in trophoblasts and mesenchymal cells, induced localized inflammation but an overall anti-inflammatory shift, did not change immune cell migration from stroma to decidua, and did not affect placental nutrient transport. Overall, (1) the humanized 2TPLA-OOC recreated the placental organ and generated data distinct from the trophoblast and other cells studied in isolation, and (2) at doses associated with adverse pregnancies, EDCs produced limited and localized insults, and the whole organ compensated for the exposure.

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QT prolongation and the potentially fatal arrhythmia Torsades de Pointes are common causes for withdrawing or restricting drugs; however, little is known about similar liabilities of environmental chemicals. Current in vitro-in silico models for testing proarrhythmic liabilities, using human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM), provide an opportunity to address this data gap. These methods are still low- to medium-throughput and not suitable for testing the tens of thousands of chemicals in commerce. We hypothesized that combining high-throughput population- based in vitro testing in hiPSC-CMs with a fully in silico data analysis workflow can offer sensitive and specific predictions of proarrhythmic potential. We calibrated the model with a published hiPSC-CM dataset of drugs known to be positive or negative for proarrhythmia and tested its performance using internal cross-validation and external validation. Additionally, we used computational down-sampling to examine three study designs for hiPSC-CM data: one replicate of one donor, five replicates of one donor, and one replicate of a population of five donors. We found that the population of five donors had the best performance for predicting proarrhythmic potential. The resulting model was then applied to predict the proarrhythmic potential of environmental chemicals, additionally characterizing risk through margin of exposure (MOE) calculations. Out of over 900 environmental chemicals tested, over 150 were predicted to have proarrhythmic potential, but only seven chemicals had a MOE < 1. We conclude that a high-throughput in vitro-in silico approach using population-based hiPSC-CM testing provides a reasonable strategy to screen environmental chemicals for proarrhythmic potential.

This article discusses a new method for testing the potential harmful effects of environmental chemicals on the heart. We used human heart cells grown in a lab to test the chemicals and developed a computer model to predict their potential to cause dangerous heart rhythms. This method could help identify harmful chemicals more quickly and accurately than current testing methods. The study has the potential to improve evaluation of chemical risks and protect public health without the use of animals.

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Systematic review and evaluation of mechanistic evidence using the Key Characteristics approach was proposed by the International Agency for Research on Cancer (IARC) in 2012 and used by the IARC Monographs Working Groups since 2015. Key Characteristics are 10 features of agents known to cause cancer in humans. From 2015 to 2022, a total of 19 Monographs (73 agents combined) used Key Characteristics for cancer hazard classification. We hypothesized that a retrospective analysis of applications of the Key Characteristics approach to cancer hazard classification using heterogenous mechanistic data on diverse agents would be informative for systematic reviews in decision-making. We extracted information on the conclusions, data types, and the role mechanistic data played in the cancer hazard classification from each Monograph. Statistical analyses identified patterns in the use of Key Characteristics, as well as trends and correlations among Key Characteristics, data types, and ultimate decisions. Despite gaps in data for many agents and Key Characteristics, several significant results emerged. Mechanistic data from in vivo animal, in vitro animal, and in vitro human studies were most impactful in concluding that an agent could cause cancer via a Key Characteristic. To exclude the involvement of a Key Characteristic, data from large-scale systematic in vitro testing programs such as ToxCast, were most informative. Overall, increased availability of systemized data streams, such as human in vitro data, would provide the basis for more confident and informed conclusions about both positive and negative associations and inform expert judgments on cancer hazard.

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Deoxynivalenol (DON) is a mycotoxin frequently observed in cereals and cereal-based foods, with reported toxicological effects including reduced body weight, immunotoxicity and reproductive defects. The European Food Safety Authority used traditional risk assessment approaches to derive a deterministic Tolerable Daily Intake (TDI) of 1 µg/kg-day, however data from human biomarkers studies indicate widespread and variable exposure worldwide, necessitating more sophisticated and advanced methods to quantify population risk. The World Health Organization/International Programme on Chemical Safety (WHO/IPCS) has previously used DON as a case example in replacing the TDI with a probabilistic toxicity value, using default uncertainty and variability distributions to derive the Human Dose corresponding to an effect size M in the Ith percentile of the population (HDMI) for M = 5 % decrease in body weight and I = 1 %. In this study, we extend this case study by incorporating (1) Bayesian modeling approaches, (2) using both in vivo data and in vitro population new approach methods to replace default distributions for interspecies toxicokinetic (TK) differences and intraspecies TK and toxicodynamic (TD) variability, and (3) integrating biomonitoring data and probabilistic dose-response functions to characterize population risk distributions. We first derive an HDMI of 5.5 [1.4-24] µg/kg-day, also using TK modeling to converted the HDMI to Biomonitoring Equivalents, BEMI for comparison with biomonitoring data, with a blood BEMI of 0.53 [0.17-1.6] µg/L and a urinary excretion BEMI of 3.9 [1.0-16] µg/kg-day. We then illustrate how this integrative approach can advance quantitative risk characterization using two human biomonitoring datasets, estimating both the fraction of population with an effect size M ≥ 5 % as well as the distribution of effect sizes. Overall, we demonstrate that integration of Bayesian modeling, human biomonitoring data, and in vitro population-based TD data within the WHO/IPCS probabilistic framework yields more accurate, precise, and comprehensive risk characterization.

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The liver is one of the key organs for exogenous and endogenous metabolism and is often a target for drug- and chemical-driven toxicity. A wide range of experimental approaches has been established to model and characterize the mechanisms of drug- and chemical-induced hepatotoxicity. A number of microfluidics-enabled in vitro models of the liver have been developed, but the unclear translatability of these platforms has hindered their adoption by the pharmaceutical industry; to achieve wide use for drug and chemical safety evaluation, demonstration of reproducibility and robustness under various contexts of use is required. One of these commercially available platforms is the PhysioMimix LC12, a microfluidic device where cells are seeded into a 3D scaffold that is continuously perfused with recirculating cell culture media to mimic liver sinusoids. Previous studies demonstrated this model's functionality and potential applicability to preclinical drug development. However, to gain confidence in PhysioMimix LC12's robustness and reproducibility, supplementary characterization steps are needed, including the assessment of various human hepatocyte sources, contribution of non-parenchymal cells (NPCs), and comparison to other models. In this study, we performed replicate studies averaging 14 days with either primary human hepatocytes (PHHs) or induced pluripotent stem cell (iPSC)-derived hepatocytes, with and without NPCs. Albumin and urea secretion, lactate dehydrogenase, CYP3A4 activity, and metabolism were evaluated to assess basal function and metabolic capacity. Model performance was characterized by different cell combinations under intra- and inter-experimental replication and compared to multi-well plates and other liver platforms. PhysioMimix LC12 demonstrated the highest metabolic function with PHHs, with or without THP-1 or Kupffer cells, for up to 10-14 days. iPSC-derived hepatocytes and PHHs co-cultured with additional NPCs demonstrated sub-optimal performance. Power analyses based on replicate experiments and different contexts of use will inform future study designs due to the limited throughput and high cell demand. Overall, this study describes a workflow for independent testing of a complex microphysiological system for specific contexts of use, which may increase end-user adoption in drug development.

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On February 3, 2023, a train carrying numerous hazardous chemicals derailed in East Palestine, OH, spurring temporary evacuation of residents and a controlled burn of some of the hazardous cargo. Residents reported health symptoms, including headaches and respiratory, skin, and eye irritation. Initial data from U.S. Environmental Protection Agency (EPA) stationary air monitors indicated levels of potential concern for air toxics based on hazard quotient calculations. To provide complementary data, we conducted mobile air quality sampling on February 20 and 21 using proton transfer reaction-mass spectrometry. Measurements were taken at 1 s intervals along routes designed to sample both close to and farther from the derailment. Mobile air monitoring indicated that average concentrations of benzene, toluene, xylenes, and vinyl chloride were below minimal risk levels for intermediate and chronic exposures, similar to EPA stationary monitoring data. Levels of acrolein were high relative to those of other volatile organic compounds, with spatial analyses showing levels in East Palestine up to 6 times higher than the local rural background. Nontargeted analyses identified levels of additional unique compounds above background levels, some displaying spatiotemporal patterns similar to that of acrolein and others exhibiting distinct hot spots. These initial findings warrant follow-up mobile air quality monitoring to characterize longitudinal exposure and risk levels.

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Microphysiological systems are an emerging area of in vitro drug development, and their independent evaluation is important for wide adoption and use. The primary goal of this study was to test reproducibility and robustness of a renal proximal tubule microphysiological system, OrganoPlate 3-lane 40, as an in vitro model for drug transport and toxicity studies. This microfluidic model was compared with static multiwell cultures and tested using several human renal proximal tubule epithelial cell (RPTEC) types. The model was characterized in terms of the functional transport for various tubule-specific proteins, epithelial permeability of small molecules (cisplatin, tenofovir, and perfluorooctanoic acid) versus large molecules (fluorescent dextrans, 60-150 kDa), and gene expression response to a nephrotoxic xenobiotic. The advantages offered by OrganoPlate 3-lane 40 as compared with multiwell cultures are the presence of media flow, albeit intermittent, and increased throughput compared with other microfluidic models. However, OrganoPlate 3-lane 40 model appeared to offer only limited (eg, MRP-mediated transport) advantages in terms of either gene expression or functional transport when compared with the multiwell plate culture conditions. Although OrganoPlate 3-lane 40 can be used to study cellular uptake and direct toxic effects of small molecules, it may have limited utility for drug transport studies. Overall, this study offers refined experimental protocols and comprehensive comparative data on the function of RPETCs in traditional multiwell culture and microfluidic OrganoPlate 3-lane 40, information that will be invaluable for the prospective end-users of in vitro models of the human proximal tubule.

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Exposure characterization of crude oils, especially in time-sensitive circumstances such as spills and disasters, is a well-known analytical chemistry challenge. Gas chromatography-mass spectrometry is commonly used for "fingerprinting" and origin tracing in oil spills; however, this method is both time-consuming and lacks the resolving power to separate co-eluting compounds. Recent advances in methodologies to analyze petroleum substances using high-resolution analytical techniques have demonstrated both improved resolving power and higher throughput. One such method, ion mobility spectrometry-mass spectrometry (IMS-MS), is especially promising because it is both rapid and high-throughput, with the ability to discern among highly homologous hydrocarbon molecules. Previous applications of IMS-MS to crude oil analyses included a limited number of samples and did not provide detailed characterization of chemical constituents. We analyzed a diverse library of 195 crude oil samples using IMS-MS and applied a computational workflow to assign molecular formulas to individual features. The oils were from 12 groups based on geographical and geological origins: non-US (1 group), US onshore (3), and US Gulf of Mexico offshore (8). We hypothesized that information acquired through IMS-MS data would provide a more confident grouping and yield additional fingerprint information. Chemical composition data from IMS-MS was used for unsupervised hierarchical clustering, as well as machine learning-based supervised analysis to predict geographic and source rock categories for each sample; the latter also yielded several novel prospective biomarkers for fingerprinting of crude oils. We found that IMS-MS data have complementary advantages for fingerprinting and characterization of diverse crude oils and that proposed polycyclic aromatic hydrocarbon biomarkers can be used for rapid exposure characterization. Environ Toxicol Chem 2023;42:2336-2349. © 2023 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC.

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Systematic review and evaluation of the mechanistic evidence only recently been instituted in cancer hazard identification step of decision-making. One example of organizing and evaluating mechanistic evidence is the Key Characteristics approach of the International Agency for Research on Cancer (IARC) Monographs on the Identification of Carcinogenic Hazards to Humans. The Key Characteristics of Human Carcinogens were proposed almost 10 years ago and have been used in every IARC Monograph since 2015. We investigated the patterns and associations in the use of Key Characteristics by the independent expert Working Groups. We examined 19 Monographs (2015-2022) that evaluated 73 agents. We extracted information on the conclusions by each Working Group on the strength of evidence for agent-Key Characteristic combinations, data types that were available for decisions, and the role mechanistic data played in the final cancer hazard classification. We conducted both descriptive and association analyses within and across data types. We found that IARC Working Groups were cautious when evaluating mechanistic evidence: for only ∼13% of the agents was strong evidence assigned for any Key Characteristic. Genotoxicity and cell proliferation were most data-rich, while little evidence was available for DNA repair and immortalization Key Characteristics. Analysis of the associations among Key Characteristics revealed that only chemical's metabolic activation was significantly co-occurring with genotoxicity and cell proliferation/death. Evidence from exposed humans was limited, while mechanistic evidence from rodent studies in vivo was often available. Only genotoxicity and cell proliferation/death were strongly associated with decisions on whether mechanistic data was impactful on the final cancer hazard classification. The practice of using the Key Characteristics approach is now well-established at IARC Monographs and other government agencies and the analyses presented herein will inform the future use of mechanistic evidence in regulatory decision-making.

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Human cell-based test methods can be used to evaluate potential hazards of mixtures and products of petroleum refining ("unknown or variable composition, complex reaction products, or biological materials" substances, UVCBs). Analyses of bioactivity and detailed chemical characterization of petroleum UVCBs were used separately for grouping these substances; a combination of the approaches has not been undertaken. Therefore, we used a case example of representative high production volume categories of petroleum UVCBs, 25 lower olefin substances from low benzene naphtha and resin oils categories, to determine whether existing manufacturing-based category grouping can be supported. We collected two types of data: nontarget ion mobility spectrometry-mass spectrometry of both neat substances and their organic extracts and in vitro bioactivity of the organic extracts in five human cell types: umbilical vein endothelial cells and induced pluripotent stem cell-derived hepatocytes, endothelial cells, neurons, and cardiomyocytes. We found that while similarity in composition and bioactivity can be observed for some substances, existing categories are largely heterogeneous. Strong relationships between composition and bioactivity were observed, and individual constituents that determine these associations were identified. Overall, this study showed a promising approach that combines chemical composition and bioactivity data to better characterize the variability within manufacturing categories of petroleum UVCBs.