Toxicological Mode Of Action Research Articles

Liquid Crystal Monomer: A Potential PPARγ Antagonist.

Liquid crystal monomers (LCMs) are a large family of artificial ingredients that have been widely used in global liquid crystal display (LCD) industries. As a major constituent in LCDs as well as the end products of e-waste dismantling, LCMs are of growing research interest with regard to their environmental occurrences and biochemical consequences. Many studies have analyzed LCMs in multiple environmental matrices, yet limited research has investigated the toxic effects upon exposure to them. In this study, we combined in silico simulation and in vitro assay validation along with omics integration analysis to achieve a comprehensive toxicity elucidation as well as a systematic mechanism interpretation of LCMs for the first time. Briefly, the high-throughput virtual screen and reporter gene assay revealed that peroxisome proliferator-activated receptor gamma (PPARγ) was significantly antagonized by certain LCMs. Besides, LCMs induced global metabolome and transcriptome dysregulation in HK2 cells. Notably, fatty acid β-oxidation was conspicuously dysregulated, which might be mediated through multiple pathways (IL-17, TNF, and NF-kB), whereas the activation of AMPK and ligand-dependent PPARγ antagonism may play particularly important parts. This study illustrated LCMs as a potential PPARγ antagonist and explored their toxicological mode of action on the trans-omics level, which provided an insightful overview in future chemical risk assessment.

Implementation of the evidence‐based risk assessment for the re‐evaluation of Bisphenol A: preparatory work on Mode of Action studies in mammalian, human and/or in vitro models.

EFSA is implementing evidence-based risk assessments for the re-evaluation of the safety of bisphenol A (BPA) for human health. The aim of this project was to carry out preparatory tasks for the working group on BPA re-evaluation, with particular reference to the preparation of individual summary tables from studies relating to BPA's toxicological mode of action or mechanism, and the production of a narrative and factual summary of these studies when grouped by health outcome category and by effect/endpoint. The first stage of the work was conducted using DistillerSR, the web-based systematic review software used by EFSA which enabled direct access/download to the published documents and provided electronic data collection templates for data extraction and reporting. A total of 1193 published articles were considered and, using the pre-established rules defined by EFSA, 581 were selected for inclusion. Data from these were subsequently extracted into the electronic data collection templates. Using these data with additional reference back to the published articles, a narrative report was produced that sub-divided the studies into eight key toxicological areas: reproduction, neurotoxicity, immune system toxicity, metabolic effects, cardiovascular effects, carcinogenicity, general toxicity and genotoxicity as well as smaller groups of studies that did not fall naturally into these health categories. This narrative report briefly summarises the data extracted.

An Extensive Metabolomics Workflow to Discover Cardiotoxin-Induced Molecular Perturbations in Microtissues.

Discovering modes of action and predictive biomarkers of drug-induced structural cardiotoxicity offers the potential to improve cardiac safety assessment of lead compounds and enhance preclinical to clinical translation during drug development. Cardiac microtissues are a promising, physiologically relevant, in vitro model, each composed of ca. 500 cells. While untargeted metabolomics is capable of generating hypotheses on toxicological modes of action and discovering metabolic biomarkers, applying this technology to low-biomass microtissues in suspension is experimentally challenging. Thus, we first evaluated a filtration-based approach for harvesting microtissues and assessed the sensitivity and reproducibility of nanoelectrospray direct infusion mass spectrometry (nESI-DIMS) measurements of intracellular extracts, revealing samples consisting of 28 pooled microtissues, harvested by filtration, are suitable for profiling the intracellular metabolome and lipidome. Subsequently, an extensive workflow combining nESI-DIMS untargeted metabolomics and lipidomics of intracellular extracts with ultra-high performance liquid chromatography-mass spectrometry (UHPLC-MS/MS) analysis of spent culture medium, to profile the metabolic footprint and quantify drug exposure concentrations, was implemented. Using the synthetic drug and model cardiotoxin sunitinib, time-resolved metabolic and lipid perturbations in cardiac microtissues were investigated, providing valuable data for generating hypotheses on toxicological modes of action and identifying putative biomarkers such as disruption of purine metabolism and perturbation of polyunsaturated fatty acid levels.

The impact of isotretinoin on the pituitary-ovarian axis: An interpretative review of the literature

Isotretinoin (13-cis-retinoic acid), a derivative of vitamin A, is used in the treatment of severe acne resulting in sebum suppression induced by sebocyte apoptosis. Isotretinoin treatment is associated with several adverse effects including teratogenicity, hepatotoxicity, and dyslipidemia. Isotretinoin’s effects on endocrine systems and its potential role as an endocrine disruptor are not yet adequately investigated. This review presents clinical, endocrine, and molecular evidence showing that isotretinoin treatment adversely affects the pituitary-ovarian axis and enhances the risk of granulosa cell apoptosis reducing follicular reserve. Isotretinoin is associated with pro-apoptotic signaling in sebaceous glands through upregulated expression of p53, forkhead box O transcription factors (FOXO1, FOXO3), and tumor necrosis factor-related apoptosis inducing ligand (TRAIL). Two literature searches including clinical and experimental studies respectively support the hypothesis that isotretinoin’s toxicological mode of action on the pituitary-ovarian axis might be caused by over-expressed p53/FOXO1 signaling resulting in gonadotropin suppression and granulosa cell apoptosis. The reduction of follicular reserve by isotretinoin treatment should be especially considered when this drug will be administered for the treatment of acne in post-adolescent women, in whom fertility may be adversely affected. In contrast, isotretinoin treatment may exert beneficial effects in states of hyperandrogenism, especially in patients with polycystic ovary syndrome.

Substitutes mimic the exposure behaviour of REACH regulated phthalates - A review of the German HBM system on the example of plasticizers.

The population is constantly exposed to potentially harmful substances present in the environment, including inter alia food and drinking water, consumer products, and indoor air. Human biomonitoring (HBM) is a valuable tool to determine the integral, internal exposure of the general population, including vulnerable subgroups, to provide the basis for risk assessment and policy advice. The German HBM system comprises of five pillars: (1) the development of suitable analytical methods for new substances of concern, (2) cross-sectional population-representative German Environmental Surveys (GerES), (3) time trend analyses using archived samples from the Environmental Specimen Bank (ESB), (4) the derivation of health-based guidance values as a risk assessment tool, and (5) transfer of data into the European cooperation network HBM4EU. The goal of this paper is to present the complementary elements of the German HBM system and to show its strengths and limitations on the example of plasticizers. Plasticizers have been identified by EU services and HBM4EU partners as priority substances for chemical policy at EU level. Using the complementary elements of the German HBM system, the internal exposure to classical phthalates and novel alternative plasticizers can be reliably monitored. It is shown that market changes, due to regulation of certain phthalates and the rise of substitutes, are rapidly reflected in the internal exposure of the population. It was shown that exposure to DEHP, DiBP, DnBP, and BBzP decreased considerably, whereas exposure to the novel substitutes such as DPHP, DEHTP, and Hexamoll®DINCH has increased significantly. While health-based guidance values for several phthalates (esp. DnBP, DiBP, DEHP) were exceeded quite often at the turn of the millennium, exceedances today have become rarer. Still, also the latest GerES reveals the ubiquitous and concurrent exposures to many plasticizers. Of concern is that the youngest children showed the highest exposures to most of the investigated plasticizers and in some cases their levels of DiBP and DnBP still exceeded health-based guidance values. Over the last years, mixture exposures are increasingly recognized as relevant, especially if the toxicological modes of action are similar. This is supported by a cumulative risk assessment for four endocrine active phthalates which confirms the still concerning cumulative exposure in many young children. Given the adverse health effects of some phthalates and the limited toxicological knowledge of substitutes, exposure reduction and surveillance are needed on German and EU-level. Substitutes need to be monitored, to intervene if exposures are threatening to exceed acceptable levels, or if new toxicological data question their appropriateness. It is strongly recommended to reconsider the use of plastics and plasticizers.

Detection of toxins involved in foodborne diseases caused by Gram-positive bacteria.

Bacterial toxins are food safety hazards causing about 10% of all reported foodborne outbreaks in Europe. Pertinent to Gram-positive pathogens, the most relevant toxins are emetic toxin and diarrheal enterotoxins of Bacillus cereus, neurotoxins of Clostridium botulinum, enterotoxin of Clostridium perfringens, and a family of enterotoxins produced by Staphylococcus aureus and some other staphylococci. These toxins are the most important virulence factors of respective foodborne pathogens and a primary cause of the related foodborne diseases. They are proteins or peptides that differ from each other in their size, structure, toxicity, toxicological end points, solubility, and stability, types of food matrix to which they are mostly related to. These differences influence the characteristics of required detection methods. Therefore, detection of these toxins in food samples, or detection of toxin production capacity in the bacterial isolate, remains one of the cornerstones of microbial food analysis and an essential tool in understanding the relevant properties of these toxins. Advanced research has led into new insights of the incidence of toxins, mechanisms of their production, their physicochemical properties, and their toxicological mode of action and dose-response profile. This review focuses on biological, immunological, mass spectrometry, and molecular assays as the most commonly used detection and quantification methods for toxins of B.cereus, C.botulinum, C.perfringens, and S. aureus. Gathered and analyzed information provides a comprehensive blueprint of the existing knowledge on the principles of these assays, their application in food safety, limits of detection and quantification, matrices in which they are applicable, and type of information they provide to the user.

A general dose-response relationship for chronic chemical and other health stressors and mixtures based on an emergent illness severity model.

Current efforts to assess human health response to chemicals based on high-throughput in vitro assay data on intra-cellular changes have been hindered for some illnesses by lack of information on higher-level extracellular, inter-organ, and organism-level interactions. However, a dose-response function (DRF), informed by various levels of information including apical health response, can represent a template for convergent top-down, bottom-up analysis. In this paper, a general DRF for chronic chemical and other health stressors and mixtures is derived based on a general first-order model previously derived and demonstrated for illness progression. The derivation accounts for essential autocorrelation among initiating event magnitudes along a toxicological mode of action, typical of complex processes in general, and reveals the inverse relationship between the minimum illness-inducing dose, and the illness severity per unit dose (both variable across a population). The resulting emergent DRF is theoretically scale-inclusive and amenable to low-dose extrapolation. The two-parameter single-toxicant version can be monotonic or sigmoidal, and is demonstrated preferable to traditional models (multistage, lognormal, generalized linear) for the published cancer and non-cancer datasets analyzed: chloroform (induced liver necrosis in female mice); bromate (induced dysplastic focia in male inbred rats); and 2-acetylaminofluorene (induced liver neoplasms and bladder carcinomas in 20,328 female mice). Common- and dissimilar-mode mixture models are demonstrated versus orthogonal data on toluene/benzene mixtures (mortality in Japanese medaka, Oryzias latipes, following embryonic exposure). Findings support previous empirical demonstration, and also reveal how a chemical with a typical monotonically-increasing DRF can display a J-shaped DRF when a second, antagonistic common-mode chemical is present. Overall, the general DRF derived here based on an autocorrelated first-order model appears to provide both a strong theoretical/biological basis for, as well as an accurate statistical description of, a diverse, albeit small, sample of observed dose-response data. The further generalizability of this conclusion can be tested in future analyses comparing with traditional modeling approaches across a broader range of datasets.

A Leveraged Signal-to-Noise Ratio (LSTNR) Method to Extract Differentially Expressed Genes and Multivariate Patterns of Expression From Noisy and Low-Replication RNAseq Data.

To life scientists, one important feature offered by RNAseq, a next-generation sequencing tool used to estimate changes in gene expression levels, lies in its unprecedented resolution. It can score countable differences in transcript numbers among thousands of genes and between experimental groups, all at once. However, its high cost limits experimental designs to very small sample sizes, usually N = 3, which often results in statistically underpowered analysis and poor reproducibility. All these issues are compounded by the presence of experimental noise, which is harder to distinguish from instrumental error when sample sizes are limiting (e.g., small-budget pilot tests), experimental populations exhibit biologically heterogeneous or diffuse expression phenotypes (e.g., patient samples), or when discriminating among transcriptional signatures of closely related experimental conditions (e.g., toxicological modes of action, or MOAs). Here, we present a leveraged signal-to-noise ratio (LSTNR) thresholding method, founded on generalized linear modeling (GLM) of aligned read detection limits to extract differentially expressed genes (DEGs) from noisy low-replication RNAseq data. The LSTNR method uses an agnostic independent filtering strategy to define the dynamic range of detected aggregate read counts per gene, and assigns statistical weights that prioritize genes with better sequencing resolution in differential expression analyses. To assess its performance, we implemented the LSTNR method to analyze three separate datasets: first, using a systematically noisy in silico dataset, we demonstrated that LSTNR can extract pre-designed patterns of expression and discriminate between “noise” and “true” differentially expressed pseudogenes at a 100% success rate; then, we illustrated how the LSTNR method can assign patient-derived breast cancer specimens correctly to one out of their four reported molecular subtypes (luminal A, luminal B, Her2-enriched and basal-like); and last, we showed the ability to retrieve five different modes of action (MOA) elicited in livers of rats exposed to three toxicants under three nutritional routes by using the LSTNR method. By combining differential measurements with resolving power to detect DEGs, the LSTNR method offers an alternative approach to interrogate noisy and low-replication RNAseq datasets, which handles multiple biological conditions at once, and defines benchmarks to validate RNAseq experiments with standard benchtop assays.

PXR: Structure-specific activation by hepatotoxic pyrrolizidine alkaloids

Pyrrolizidine alkaloids (PAs) comprise a large group of more than 660 secondary metabolites found in more than 6000 plant species worldwide. Acute PA intoxication induces severe liver damage. Chronic exposure to sub-lethal doses may cause cumulative damage or cancer. Nuclear receptor activation often constitutes a molecular event for xenobiotic-induced toxicity. However, so far nothing is known about potential interactions of PAs with nuclear receptors as a toxicological mode of action. Thus, in the present study PA-dependent activation of a comprehensive panel of nuclear receptors (PPARs, LXRα, RARα, RXRα, FXR, CAR, PXR, ERα/β) was investigated using GAL4/UAS-based transactivation reporter gene assays. To cover the most frequently occurring PA structure types (retronecine, heliotridine and otonecine type; as well as monoester, open-chain diester and cyclic diester) different PAs were analyzed for interaction with nuclear receptors.Most of the nuclear receptors investigated were not affected by the tested PAs. However, significant activation was found for PXR, which was exclusively activated by the open-chain diesters, echimidine and lasiocarpine. Induction of the model PXR target gene CYP3A4 by PAs was verified at the mRNA, protein and enzyme activity level.In conclusion, PXR activation and PXR-mediated induction of CYP3A4 expression by PAs seem to be structure-dependent. Data suggest that only open-chain diesters act as PXR agonists. This might imply that a PXR-mediated mode of action may contribute to the hepatotoxicity of PAs that is dependent on PA structure.

Quantitative Structure-Activity Relationships of Aquatic Narcosis: A Review.

Prior estimation of toxicity of each and every, existing and yet to be synthesized chemicals is a must to elude their adverse effect on the environment. Experimental determination of such parameters is time consuming, cost effective and above all, it demands the sacrifice of many vertebrates. At this end, the REACH regulations advocate for the use of non-testing predictive methods such as read-across, weight-of-evidence and QSAR (quantitative structure-activity relationship) techniques. Among these methods, QSAR is found to be the best as it is based on molecular structure only. The descriptors used in deriving the model in QSAR vary according to the nature of the narcotics as well as the species used for. The success of a model in predicting the toxicity of a narcotic purely depends on the type of descriptors selected that explains the structural features closely related to the property under study. In this review, we have focused on the different types of descriptors and QSAR models used to explain the narcosis phenomenon. Literature was scanned for acute toxicity of chemicals on species like tadpoles, protozoa, planktonic crustaceans, and small fishes like million fish, rainbow fish etc. from different sources. The toxicity and toxicants were classified considering their polarity and specific interactions of the compounds. Due to complex nature of the substrate, the mechanism of action of toxicant is uncertain. However, the overall results obtained from the biological study have been subjected to QSAR studies to obtain various models, which can provide some ideas on the mode of toxicological action. Different types of molecular descriptors derived both experimentally and theoretically have been used in the QSAR studies. Mostly biochemicals have a specific signature on oil/water partition (Ko/w, P), which is the crux in biological activity. Accordingly, the toxicological activities have good correlations with log P. Addition of some more structural descriptors improves the structure-toxicity relationship. Among these, electronic descriptors like EHOMO, ELUMO and ΔE derived from molecular orbitals have been used in the QSAR. ELUMO describing the energy of excited species of the molecule is found to be the most suitable one. Other molecular descriptors used in the QSAR include constitutional, topological and Abraham's solute descriptors. The models derived from the QSAR studies were found to be highly significant to predict the toxicology as well as to throw light on the mechanism. The best descriptor for aquatic narcosis is the KO/W or P. Addition of an electronic parameter (ELUMO) improves the QSAR to some extent. However, substitution of ELUMO by other class of molecular descriptors has also some statistical significance. To have a global QSAR model, in addition to P, some more appropriate descriptors are to be derived either experimentally or theoretically, latter being the more cost effective and easy in derivation.

Toxicogenomics of the flame retardant tris (2-butoxyethyl) phosphate in HepG2 cells using RNA-seq

Tris (2-butoxyethyl) phosphate (TBOEP) is a compound produced at high volume that is used as both a flame retardant and a plasticizer. It is persistent and bioaccumulative, yet little is known of its toxicological modes of action. Such insight may aid risk assessment in a weight-of-evidence approach supplementing current testing strategies. We used an RNA sequencing approach as an unbiased and sensitive tool to explore potential negative health effects of sub-cytotoxic concentrations of TBOEP on the transcriptome of the human liver hepatocellular carcinoma cell line, HepG2, with the lowest concentration used potentially holding relevance to human physiological levels. Over-representation and gene set enrichment analysis corresponded well and revealed that TBOEP treatments resulted in an upregulation of genes involved in protein and energy metabolism, along with DNA replication. Such increases in cell and macromolecule metabolism could explain the increase in mitochondrial activity at lower TBOEP concentrations. In addition, TBOEP affected a wide variety of biological processes, the most notable one being the general stress response, wound healing. Finally, TBOEP showed effects on steroid hormone biosynthesis and activation, regulation, and potentiation of immune responses, in agreement with other studies. As such, this study is the first study investigating genome-wide changes in gene transcription in response to TBOEP in human cells.

Evaluation of anionic surfactant concentrations in US effluents and probabilistic determination of their combined ecological risk in mixing zones

Alcohol sulfates (AS), alcohol ethoxysulfates (AES), linear alkyl benzenesulfonates (LAS) and methyl ester sulfonates (MES) are anionic surfactants that are widely used in household detergents and consumer products resulting in over 1 million tons being disposed of down the drain annually in the US. A monitoring campaign was conducted which collected grab effluent samples from 44 wastewater treatment plants (WWTPs) across the US to generate statistical distributions of effluent concentrations for anionic surfactants. The mean concentrations for AS, AES, LAS and MES were 5.03±4.5, 1.95±0.7, 15.3±19, and 0.35±0.13μg/L respectively. Since each of these surfactants consist of multiple homologues that differ in their toxicity, the concentration of each homologue measured in an effluent sample was converted into a toxic unit (TU) by normalizing to the predicted no effect concentration (PNEC) derived from high tier effects data (mesocosm studies). The statistical distributions of the combined TUs in the effluents were used in combination with distributions of dilution factors for WWTP mixing zones to conduct a US-wide probabilistic risk assessment for the aquatic environment for each of the surfactants. The 90th percentile level of TUs for AS, AES, LAS and MES in mixing zones were 1.89×10−2, 2.73×10−3, 2.72×10−2, and 3.65×10−5 under 7Q10 (lowest river flow occurring over a 7day period every 10years) low flow conditions. Because these surfactants have the same toxicological mode of action, the TUs were summed and the aquatic safety for anionic surfactants as a whole was assessed. At the 90th percentile level under the conservative 7Q10 low flow conditions the forecasted TUs were 4.21×10−2 which indicates that there is a significant margin of safety for the class of anionic surfactants in US aquatic environments.

Mode of action of triflumezopyrim: A novel mesoionic insecticide which inhibits the nicotinic acetylcholine receptor

Triflumezopyrim, a newly commercialized molecule from DuPont Crop Protection, belongs to the novel class of mesoionic insecticides. This study characterizes the biochemical and physiological action of this novel insecticide. Using membranes from the aphid, Myzus persicae, triflumezopyrim was found to displace 3H-imidacloprid with a Ki value of 43 nM with competitive binding results indicating that triflumezopyrim binds to the orthosteric site of the nicotinic acetylcholine receptor (nAChR). In voltage clamp studies using dissociated Periplaneta americana neurons, triflumezopyrim inhibits nAChR currents with an IC50 of 0.6 nM. Activation of nAChR currents was minimal and required concentrations ≥100 μM. Xenopus oocytes expressing chimeric nAChRs (Drosophila α2/chick β2) showed similar inhibitory effects from triflumezopyrim. In P. americana neurons, co-application experiments with acetylcholine reveal the inhibitory action of triflumezopyrim to be rapid and prolonged in nature. Such physiological action is distinct from other insecticides in IRAC Group 4 in which the toxicological mode of action is attributed to nAChR agonism.Mesoionic insecticides act via inhibition of the orthosteric binding site of the nAChR despite previous beliefs that such action would translate to poor insect control. Triflumezopyrim is the first commercialized insecticide from this class and provides outstanding control of hoppers, including the brown planthopper, Nilaparvata lugens, which is already displaying strong resistance to neonicotinoids such as imidacloprid.

Toxicological Assessment of CoO and La2O3 Metal Oxide Nanoparticles in Human Small Airway Epithelial Cells.

Cobalt monoxide (CoO) and lanthanum oxide (La2O3) nanoparticles are 2 metal oxide nanoparticles with different redox potentials according to their semiconductor properties. By utilizing these two nanoparticles, this study sought to determine how metal oxide nanoparticle's mode of toxicological action is related to their physio-chemical properties in human small airway epithelial cells (SAEC). We investigated cellular toxicity, production of superoxide radicals and alterations in gene expression related to oxidative stress, and cellular death at 6 and 24 h following exposure to CoO and La2O3(administered doses: 0, 5, 25, and 50 µg/ml) nanoparticles. CoO nanoparticles induced gene expression related to oxidative stress at 6 h. After characterizing the nanoparticles, transmission electron microscope analysis showed SAEC engulfed CoO and La2O3nanoparticles. CoO nanoparticles were toxic after 6 and 24 h of exposure to 25.0 and 50.0 µg/ml administered doses, whereas, La2O3nanoparticles were toxic only after 24 h using the same administered doses. Based upon the Volumetric Centrifugation Methodin vivoSedimentation, Diffusion, and Dosimetry, the dose of CoO and La2O3nanoparticles delivered at 6 and 24 h were determined to be: CoO: 1.25, 6.25, and 12.5 µg/ml; La2O3: 5, 25, and 50 µg/ml and CoO: 4, 20, and 40 µg/ml; and La2O3: 5, 25, 50 µg/ml, respectively. CoO nanoparticles produced more superoxide radicals and caused greater stimulation of total tyrosine and threonine phosphorylation at both 6 and 24 h when compared with La2O3nanoparticles. Taken together, these data provide evidence that different toxicological modes of action were involved in CoO and La2O3metal oxide nanoparticle-induced cellular toxicity.

Human stem cell-derived hepatocytes: breakthrough of an expedient tool for preclinical assessment of drug-induced liver injury?

human hepatocytes are also prohibitively expensive for high-throughput screening purposes. Problems are also encountered when human hepatic cell lines are used, as these cells are mostly derived from liver cancer patients and do not adequately represent the normal population diversity (Guguen-Guillouzo and Guillouzo 2010). Consequently, innovative approaches to predict adverse liver responses in humans are urgently needed. New developments coming from the rapidly advancing human stem cell research field are in the pipeline (McGivern and Ebert 2013). In fact, due to the biological flexibility of stem cells, biologists and toxicologists strongly believe that once the in vivo mechanisms driving cell differentiation and dedifferentiation are fully understood, stem cells can be modulated a la carte. As a consequence, these cells will obtain the appropriate functionalities that are required for evaluating a particular toxicological mode of action (MoA). As such, stem cells could represent a valuable “fit for purpose” tool in the unraveling of the MoA of a chemical substance at the molecular level. Integration of stem cells in an in vitro setting to screen for toxicity could significantly increase the predictive capacity of the testing platform. Indeed, starting from embryonic and postnatal stem cells, functional hepatocyte-like cells can be generated that possess the required machinery to predict hepatotoxicity and provide valuable human-based toxicological information (Baxter et al. 2010; Snykers et al. 2009; Sullivan et al. 2010). As an immediate consequence of the enormous advancement of “omics” technology during the last decade, an overwhelming amount of biologically relevant information can be generated and thanks to the availability of appropriate computational tools, the obtained data can be relatively easy and quickly interpreted. The first reports on accurate prediction of hepatotoxicity in response to specific Detection of drug toxicity, often occurring late during the drug development process, is of major concern for the pharmaceutical industry and jeopardizes the potential marketing of new chemical entities (Pammolli et al. 2011; Goldkind and Laine 2006). In addition, one of the leading causes of post-marketing withdrawal of pharmaceuticals is drug-induced liver injury (DILI) (Russmann et al. 2009), suggesting that the currently used in vitro and in vivo preclinical models for assessing liver toxicity are not effective enough (Pammolli et al. 2011; Godoy et al. 2013; Olson et al. 2000). In line with recent regulatory developments in Europe for chemicals (EU 2006) and cosmetics (EU 2009), global consensus is growing to introduce, whenever possible, physiologically relevant alternative methods to animal testing, also in the pharmaceutical industry (Bouvier d’Yvoire et al. 2012). Current in vitro approaches for hepatotoxicity screening are mainly based on primary cells of different species, including man, or human hepatomaderived cell lines. Primary human hepatocyte cultures represent the gold standard, but their use is hampered by their low availability and their inability to proliferate in culture (Fraczek et al. 2013). Due to intensive transplantation programs, hepatocytes can be seldom isolated from healthy human livers. Instead, they are obtained from patients suffering from severe liver injuries or coping with a multidrug regimen and therefore often display poor cell quality (Guguen-Guillouzo and Guillouzo 2010). Due to their scarcity, primary

Arsenic exposure and bladder cancer: Quantitative assessment of studies in human populations to detect risks at low doses

While exposures to high levels of arsenic in drinking water are associated with excess cancer risk (e.g., skin, bladder, and lung), exposures at lower levels (e.g., <100–200µg/L) generally are not. Lack of significant associations may result from methodological issues (e.g., inadequate statistical power, exposure misclassification), or a different dose–response relationship at low exposures, possibly associated with a toxicological mode of action that requires a sufficient dose for increased tumor formation. The extent to which bladder cancer risk for low-level arsenic exposure can be statistically measured by epidemiological studies was examined using an updated meta-analysis of bladder cancer risk with data from two new publications. The summary relative risk estimate (SRRE) for all nine studies was elevated slightly, but not significantly (1.07; 95% confidence interval [CI]: 0.95–1.21, p-Heterogeneity [p-H]=0.543). The SRRE among never smokers was 0.85 (95% CI: 0.66–1.08, p-H=0.915), whereas the SRRE was positive and more heterogeneous among ever smokers (1.18; 95% CI: 0.97–1.44, p-H=0.034). The SRRE was statistically significantly lower than relative risks predicted for never smokers in the United States based on linear extrapolation of risks from higher doses in southwest Taiwan to arsenic water exposures >10µg/L for more than one-third of a lifetime. By contrast, for all study subjects, relative risks predicted for one-half of lifetime exposure to 50µg/L were just above the upper 95% CI on the SRRE. Thus, results from low-exposure studies, particularly for never smokers, were statistically inconsistent with predicted risk based on high-dose extrapolation. Additional studies that better characterize tobacco use and stratify analyses of arsenic and bladder cancer by smoking status are necessary to further examine risks of arsenic exposure for smokers.

PPARs and Metabolic Syndrome.

Peroxisome proliferator-activated receptors (PPARs) exert versatile biological effects, notably in energy metabolism. During the last two decades, numerous studies have demonstrated that PPARs act as pivotal regulators of metabolic syndrome, a series of disorders in energy utilization and storage that are implicated with type 2 diabetes, diabetic nephropathy, and cardiovascular diseases, to mention a few. PPARα and PPARγ are the molecular targets of a number of marketed drugs for the treatment of these diseases, and accumulating evidence suggested PPARβ/δ as a potential therapeutic drug target as well. Although energy metabolism and metabolic syndrome are the most intensively studied domain of PPARs, it has not been addressed specifically in any issue of PPAR Research ever since its launch. Here, we gathered 3 reviews and 5 research articles that encompass metabolic syndrome and its complications. M. Aprile et al. tackled the subject of PPARγ and human adipogenesis in their research article. Rather than focusing on canonical PPARγ transcripts, authors largely emphasized on the critical contribution of PPARγ dominant negative isoforms to adipogenesis and their implied potential role in pathological conditions. In addition, a novel of PPARγ dominant negative transcript, γ1ORF4, was first identified in this study. In regard to nonalcoholic fatty liver diseases, the hepatic expression of the metabolic syndrome, M. Sharif et al. conducted a thorough analysis of previously published data about the steatogenic role of PPARγ and summarized two probable PPARγ ligand-dependent toxicological modes of action: (i) activation of PPARγ in hepatocytes and (ii) inhibition in adipocytes. Two papers, one review and a research article, by Z. Jia and Y. Sun et al., appraised the role of PPARγ in diabetic nephropathy (DN). Their comprehensive review summarized the limitations of traditional PPARγ agonists, addressed the advantages of newly developed PPARγ agonists, and rendered new insights into the therapeutic potential of PPARγ agonists in the treatment of DN, while the research article suggested that a combination of PPARγ agonists with COX-2/PGE2 inhibitors may be an alternative way of dealing with DN. In another research article, J. Jin et al. analyzed the correlation between PPAR gene polymorphisms and pediatric primary nephrotic syndrome (PNS) by comparing children with PNS against healthy subjects. They found that PPARγ (Pro12Ala) and PGC-1α (Gly482Ser) polymorphisms are associated with abnormal insulin and triglyceride metabolism in pediatric PNS patients, suggesting that these polymorphisms may be relevant to the prognosis of this chronic disease. The knowledge of the role of PPARα in metabolic disorder-associated cardiovascular diseases was well recognized in this special issue. Z. Jia et al.'s research article asserted the involvement of HMGB1 (high mobility group box 1) in the protective effect of PPARα in cardiac hypertrophy and provided a novel approach to study the pathogenesis of cardiac hypertrophy. Although most studies showed that PPARα activation confers protection against atherogenesis, the intriguing possibility that PPARα might foster atherogenesis is also considered. In this current issue, M. Vechoropoulos et al. found that PPARα mediates the proatherogenic effect of chronic nitric oxide synthesis inhibition and this effect is independent of blood pressure and serum lipids alterations. These data further shaped the view that the role of PPARα in atherosclerosis needs to be reevaluated. Lastly, in the review article “PPARs Integrate the Mammalian Clock and Energy Metabolism,” we collected recent findings about the role of PPARs in biological clocks. This brand new function of PPARs bridges energy metabolism with circadian rhythm whose relationship has been known for long time, but not well understood. We summarized the circadian function of three PPAR subtypes one by one and concluded that the abnormality of PPARs and circadian rhythm could impinge on each other and thus leads to metabolic disorders. Further investigation of PPARs in this field will give us a new perspective on the therapeutic advances in the treatment of metabolic ailments. In conclusion, this special issue is packed with intriguing novel breakthroughs and insights into PPARs and metabolic syndrome. We hope that these advances will generate more interest from the scientific community in better understanding of the role of PPARs in metabolic syndrome and associated complications. Lihong Chen Zhanjun Jia Guangrui Yang

Modeling and analysis of personal exposures to VOC mixtures using copulas

Environmental exposures typically involve mixtures of pollutants, which must be understood to evaluate cumulative risks, that is, the likelihood of adverse health effects arising from two or more chemicals. This study uses several powerful techniques to characterize dependency structures of mixture components in personal exposure measurements of volatile organic compounds (VOCs) with aims of advancing the understanding of environmental mixtures, improving the ability to model mixture components in a statistically valid manner, and demonstrating broadly applicable techniques. We first describe characteristics of mixtures and introduce several terms, including the mixture fraction which represents a mixture component's share of the total concentration of the mixture. Next, using VOC exposure data collected in the Relationship of Indoor Outdoor and Personal Air (RIOPA) study, mixtures are identified using positive matrix factorization (PMF) and by toxicological mode of action. Dependency structures of mixture components are examined using mixture fractions and modeled using copulas, which address dependencies of multiple variables across the entire distribution. Five candidate copulas (Gaussian, t, Gumbel, Clayton, and Frank) are evaluated, and the performance of fitted models was evaluated using simulation and mixture fractions. Cumulative cancer risks are calculated for mixtures, and results from copulas and multivariate lognormal models are compared to risks calculated using the observed data. Results obtained using the RIOPA dataset showed four VOC mixtures, representing gasoline vapor, vehicle exhaust, chlorinated solvents and disinfection by-products, and cleaning products and odorants. Often, a single compound dominated the mixture, however, mixture fractions were generally heterogeneous in that the VOC composition of the mixture changed with concentration. Three mixtures were identified by mode of action, representing VOCs associated with hematopoietic, liver and renal tumors. Estimated lifetime cumulative cancer risks exceeded 10−3 for about 10% of RIOPA participants. Factors affecting the likelihood of high concentration mixtures included city, participant ethnicity, and house air exchange rates. The dependency structures of the VOC mixtures fitted Gumbel (two mixtures) and t (four mixtures) copulas, types that emphasize tail dependencies. Significantly, the copulas reproduced both risk predictions and exposure fractions with a high degree of accuracy, and performed better than multivariate lognormal distributions. Copulas may be the method of choice for VOC mixtures, particularly for the highest exposures or extreme events, cases that poorly fit lognormal distributions and that represent the greatest risks.

A Genomics-Based Analysis of Relative Potencies of Dioxin-Like Compounds in Primary Rat Hepatocytes

Toxic equivalency factors (TEFs) for dioxin-like compounds are largely based on relative potency (REP) values derived from biochemical endpoints such as enzyme activity. As of yet, REPs based on gene expression changes have not been accounted for in the TEF values. In this study, primary rat hepatocytes were treated for 24h with 11 concentrations of 2,3,7,8-tetrachlorodibenzo-p-dioxin, 2,3,4,7,8-pentachlorodibenzofuran (4-PeCDF), or 2,3,7,8-tetrachlorodibenzofuran (TCDF) ranging from 0.00001 to 100 nM. Differential changes in gene expression were analyzed using analysis of variance to assess the relative contributions of concentration, congener, and the interaction between concentration and congener for each gene. A total of 3283 genes showed significant changes with concentration (false discovery rate < .05 and fold-change ± 1.5 in at least 1 concentration for 1 congener). Among these genes, 399 were significant for both concentration and congener effects indicating parallel concentration-response curves with significant differences in potency. Only 8 genes showed a significant concentration and congener interaction term indicating a minority of genes show nonparallel dose-response curves among the 3 congeners. Benchmark dose (BMD) modeling was used to derive BMD values for induced individual genes and signaling pathways. The REP values for 4-PeCDF and TCDF were generally 3- to 5-fold lower than the World Health Organization (WHO) TEF values on both a gene and pathway basis. These findings suggest that the WHO TEF values may possibly overpredict the potency of these polychlorinated dibenzofuran congeners and demonstrate the importance of identifying functional pathways relevant to the toxicological modes of action for establishing pertinent REPs.

Application of metabolomics in vitro for identification of toxicological modes of action

Application of metabolomics in vitro for identification of toxicological modes of action