Neurotoxic mechanisms of triclosan: The antimicrobial agent emerging as a toxicant.

Several scientific studies have suggested a link between increased exposure to pollutants and a rise in the number of neurodegenerative disorders of unknown origin. Notably, triclosan (an antimicrobial agent) is used in concentrations ranging from 0.3% to 1% in various consumer products. Recent studies have also highlighted triclosan as an emerging toxic pollutant due to its increasing global use. However, a definitive link is missing to associate the rising use of triclosan and the growing number of neurodegenerative disorders or neurotoxicity. In this article, we present systematic scientific evidence which are otherwise scattered to suggest that triclosan can indeed induce neurotoxic effects, especially in vertebrate organisms including humans. Mechanistically, triclosan affected important developmental and differentiation genes, structural genes, genes for signaling receptors and genes for neurotransmitter controlling enzymes. Triclosan-induced oxidative stress impacting cellular proteins and homeostasis which triggers apoptosis. Though the scientific evidence collated in this article unequivocally indicates that triclosan can cause neurotoxicity, further epidemiological studies may be needed to confirm the effects on humans.

The Threat Posed by Environmental Contaminants on Neurodevelopment: What Can We Learn from Neural Stem Cells?

Exposure to chemicals may pose a greater risk to vulnerable groups, including pregnant women, fetuses, and children, that may lead to diseases linked to the toxicants' target organs. Among chemical contaminants, methylmercury (MeHg), present in aquatic food, is one of the most harmful to the developing nervous system depending on time and level of exposure. Moreover, certain man-made PFAS, such as PFOS and PFOA, used in commercial and industrial products including liquid repellants for paper, packaging, textile, leather, and carpets, are developmental neurotoxicants. There is vast knowledge about the detrimental neurotoxic effects induced by high levels of exposure to these chemicals. Less is known about the consequences that low-level exposures may have on neurodevelopment, although an increasing number of studies link neurotoxic chemical exposures to neurodevelopmental disorders. Still, the mechanisms of toxicity are not identified. Here we review in vitro mechanistic studies using neural stem cells (NSCs) from rodents and humans to dissect the cellular and molecular processes changed by exposure to environmentally relevant levels of MeHg or PFOS/PFOA. All studies show that even low concentrations dysregulate critical neurodevelopmental steps supporting the idea that neurotoxic chemicals may play a role in the onset of neurodevelopmental disorders.

Toxicant-Induced Metabolic Alterations in Lipid and Amino Acid Pathways Are Predictive of Acute Liver Toxicity in Rats.

Liver disease and disorders associated with aberrant hepatocyte metabolism can be initiated via drug and environmental toxicant exposures. In this study, we tested the hypothesis that gene and metabolic profiling can reveal commonalities in liver response to different toxicants and provide the capability to identify early signatures of acute liver toxicity. We used Sprague Dawley rats and three classical hepatotoxicants: acetaminophen (2 g/kg), bromobenzene (0.4 g/kg), and carbon tetrachloride (0.3 g/kg), to identify early perturbations in liver metabolism after a single acute exposure dose. We measured changes in liver genes and plasma metabolites at two time points (5 and 10 h) and used genome-scale metabolic models to identify commonalities in liver responses across the three toxicants. We found strong correlations for gene and metabolic profiles between the toxicants, indicative of similarities in the liver response to toxicity. We identified several injury-specific pathways in lipid and amino acid metabolism that changed similarly across the three toxicants. Our findings suggest that several plasma metabolites in lipid and amino acid metabolism are strongly associated with the progression of liver toxicity, and as such, could be targeted and clinically assessed for their potential as early predictors of acute liver toxicity.

Part 1. Statistical Learning Methods for the Effects of Multiple Air Pollution Constituents.

INTRODUCTION: The United States Environmental Protection Agency (U.S. EPA*) currently regulates individual air pollutants on a pollutant-by-pollutant basis, adjusted for other pollutants and potential confounders. However, the National Academies of Science concluded that a multipollutant regulatory approach that takes into account the joint effects of multiple constituents is likely to be more protective of human health. Unfortunately, the large majority of existing research had focused on health effects of air pollution for one pollutant or for one pollutant with control for the independent effects of a small number of copollutants. Limitations in existing statistical methods are at least partially responsible for this lack of information on joint effects. The goal of this project was to fill this gap by developing flexible statistical methods to estimate the joint effects of multiple pollutants, while allowing for potential nonlinear or nonadditive associations between a given pollutant and the health outcome of interest. METHODS: We proposed Bayesian kernel machine regression (BKMR) methods as a way to simultaneously achieve the multifaceted goals of variable selection, flexible estimation of the exposure-response relationship, and inference on the strength of the association between individual pollutants and health outcomes in a health effects analysis of mixtures. We first developed a BKMR variable-selection approach, which we call component-wise variable selection, to make estimating such a potentially complex exposure-response function possible by effectively using two types of penalization (or regularization) of the multivariate exposure-response surface. Next we developed an extension of this first variable-selection approach that incorporates knowledge about how pollutants might group together, such as multiple constituents of particulate matter that might represent a common pollution source category. This second grouped, or hierarchical, variable-selection procedure is applicable when groups of highly correlated pollutants are being studied. To investigate the properties of the proposed methods, we conducted three simulation studies designed to evaluate the ability of BKMR to estimate environmental mixtures responsible for health effects under potentially complex but plausible exposure-response relationships. An attractive feature of our simulation studies is that we used actual exposure data rather than simulated values. This real-data simulation approach allowed us to evaluate the performance of BKMR and several other models under realistic joint distributions of multipollutant exposure. The simulation studies compared the two proposed variable-selection approaches (component-wise and hierarchical variable selection) with each other and with existing frequentist treatments of kernel machine regression (KMR). After the simulation studies, we applied the newly developed methods to an epidemiologic data set and to a toxicologic data set. To illustrate the applicability of the proposed methods to human epidemiologic data, we estimated associations between short-term exposures to fine particulate matter constituents and blood pressure in the Maintenance of Balance, Independent Living, Intellect, and Zest in the Elderly (MOBILIZE) Boston study, a prospective cohort study of elderly subjects. To illustrate the applicability of these methods to animal toxicologic studies, we analyzed data on the associations between both blood pressure and heart rate in canines exposed to a composition of concentrated ambient particles (CAPs) in a study conducted at the Harvard T. H. Chan School of Public Health (the Harvard Chan School; formerly Harvard School of Public Health; Bartoli et al. 2009). RESULTS: We successfully developed the theory and computational tools required to apply the proposed methods to the motivating data sets. Collectively, the three simulation studies showed that component-wise variable selection can identify important pollutants within a mixture as long as the correlations among pollutant concentrations are low to moderate. The hierarchical variable-selection method was more effective in high-dimension, high-correlation settings. Variable selection in existing frequentist KMR models can incur inflated type I error rates, particularly when pollutants are highly correlated. The analyses of the MOBILIZE data yielded evidence of a linear and additive association of black carbon (BC) or Cu exposure with standing diastolic blood pressure (DBP), and a linear association of S exposure with standing systolic blood pressure (SBP). Cu is thought to be a marker of urban road dust associated with traffic; and S is a marker of power plant emissions or regional long-range transported air pollution or both. Therefore, these analyses of the MOBILIZE data set suggest that emissions from these three source categories were most strongly associated with hemodynamic responses in this cohort. In contrast, in the Harvard Chan School canine study, after controlling for an overall effect of CAPs exposure, we did not observe any associations between DBP or SBP and any elemental concentrations. Instead, we observed strong evidence of an association between Mn concentrations and heart rate in that heart rate increased linearly with increasing concentrations of Mn. According to the positive matrix factorization (PMF) source apportionment analyses of the multipollutant data set from the Harvard Chan School Boston Supersite, Mn loads on the two factors that represent the mobile and road dust source categories. The results of the BKMR analyses in both the MOBILIZE and canine studies were similar to those from existing linear mixed model analyses of the same multipollutant data because the effects have linear and additive forms that could also have been detected using standard methods. CONCLUSIONS: This work provides several contributions to the KMR literature. First, to our knowledge this is the first time KMR methods have been used to estimate the health effects of multipollutant mixtures. Second, we developed a novel hierarchical variable-selection approach within BKMR that is able to account for the structure of the mixture and systematically handle highly correlated exposures. The analyses of the epidemiologic and toxicologic data on associations between fine particulate matter constituents and blood pressure or heart rate demonstrated associations with constituents that are typically associated with traffic emissions, power plants, and long-range transported pollutants. The simulation studies showed that the BKMR methods proposed here work well for small to moderate data sets; more work is needed to develop computationally fast methods for large data sets. This will be a goal of future work.

Part 2. Development of Enhanced Statistical Methods for Assessing Health Effects Associated with an Unknown Number of Major Sources of Multiple Air Pollutants.

A major difficulty with assessing source-specific health effects is that source-specific exposures cannot be measured directly; rather, they need to be estimated by a source-apportionment method such as multivariate receptor modeling. The uncertainty in source apportionment (uncertainty in source-specific exposure estimates and model uncertainty due to the unknown number of sources and identifiability conditions) has been largely ignored in previous studies. Also, spatial dependence of multipollutant data collected from multiple monitoring sites has not yet been incorporated into multivariate receptor modeling. The objectives of this project are (1) to develop a multipollutant approach that incorporates both sources of uncertainty in source-apportionment into the assessment of source-specific health effects and (2) to develop enhanced multivariate receptor models that can account for spatial correlations in the multipollutant data collected from multiple sites. We employed a Bayesian hierarchical modeling framework consisting of multivariate receptor models, health-effects models, and a hierarchical model on latent source contributions. For the health model, we focused on the time-series design in this project. Each combination of number of sources and identifiability conditions (additional constraints on model parameters) defines a different model. We built a set of plausible models with extensive exploratory data analyses and with information from previous studies, and then computed posterior model probability to estimate model uncertainty. Parameter estimation and model uncertainty estimation were implemented simultaneously by Markov chain Monte Carlo (MCMC*) methods. We validated the methods using simulated data. We illustrated the methods using PM2.5 (particulate matter ≤ 2.5 µm in aerodynamic diameter) speciation data and mortality data from Phoenix, Arizona, and Houston, Texas. The Phoenix data included counts of cardiovascular deaths and daily PM2.5 speciation data from 1995-1997. The Houston data included respiratory mortality data and 24-hour PM2.5 speciation data sampled every six days from a region near the Houston Ship Channel in years 2002-2005. We also developed a Bayesian spatial multivariate receptor modeling approach that, while simultaneously dealing with the unknown number of sources and identifiability conditions, incorporated spatial correlations in the multipollutant data collected from multiple sites into the estimation of source profiles and contributions based on the discrete process convolution model for multivariate spatial processes. This new modeling approach was applied to 24-hour ambient air concentrations of 17 volatile organic compounds (VOCs) measured at nine monitoring sites in Harris County, Texas, during years 2000 to 2005. Simulation results indicated that our methods were accurate in identifying the true model and estimated parameters were close to the true values. The results from our methods agreed in general with previous studies on the source apportionment of the Phoenix data in terms of estimated source profiles and contributions. However, we had a greater number of statistically insignificant findings, which was likely a natural consequence of incorporating uncertainty in the estimated source contributions into the health-effects parameter estimation. For the Houston data, a model with five sources (that seemed to be Sulfate-Rich Secondary Aerosol, Motor Vehicles, Industrial Combustion, Soil/Crustal Matter, and Sea Salt) showed the highest posterior model probability among the candidate models considered when fitted simultaneously to the PM2.5 and mortality data. There was a statistically significant positive association between respiratory mortality and same-day PM2.5 concentrations attributed to one of the sources (probably industrial combustion). The Bayesian spatial multivariate receptor modeling approach applied to the VOC data led to a highest posterior model probability for a model with five sources (that seemed to be refinery, petrochemical production, gasoline evaporation, natural gas, and vehicular exhaust) among several candidate models, with the number of sources varying between three and seven and with different identifiability conditions. Our multipollutant approach assessing source-specific health effects is more advantageous than a single-pollutant approach in that it can estimate total health effects from multiple pollutants and can also identify emission sources that are responsible for adverse health effects. Our Bayesian approach can incorporate not only uncertainty in the estimated source contributions, but also model uncertainty that has not been addressed in previous studies on assessing source-specific health effects. The new Bayesian spatial multivariate receptor modeling approach enables predictions of source contributions at unmonitored sites, minimizing exposure misclassification and providing improved exposure estimates along with their uncertainty estimates, as well as accounting for uncertainty in the number of sources and identifiability conditions.

Characteristics of chemosensory disorders--results from a survey.

This survey was undertaken to investigate the nature of chemosensory dysfunction in relation to the underlying cause, severity, and course of the disease and to elucidate their clinical significance. A total of 269 patients (116 men and 149 women) with chemosensory disorders participated in the survey. Approximately 89 % had olfactory loss, either alone or in combination with taste loss and 2 % had gustatory loss alone; 7.4 % had chemosensory distortions. Dysosmia was significantly higher in those on more than four medicines per day (p < 0.02). Most patients (51.6 %) reported sudden onset of symptoms. Self-reported etiologies included: flu/infection (39.4 %), medication intake (13 %), sinusitis (12 %), operation (10.7 %), head-trauma (9.3 %), and not-specified (12.7 %). The most frequent complaint was diminished pleasure from eating followed by a decrease in general quality of life (QoL). Patients with gradual onset of symptoms or long-standing disease complained the least (p < 0.005). Of all etiologies, patients with SND complained the most (p < 0.04). Overall, 18.6 % ate more and 7.3 % ate less, 7.5 % changed their food preferences, and 19 % reported weight gain and 15.8 % weight loss. Haptic feedback was considered more important than visual appeal and acoustic feedback of food. Older patients however valued visual appeal more. When asked directly, 63 % reported having experienced household-mishaps, 58.1 % problems with social communication, 56.8 % reported having changed their sexual behavior and 35.9 % suffered depression. 60.4 % did not cope well with the changes in their lives. Women reported more problems than men, particularly relating to interpersonal communication (64.5 vs. 57.6 %) and mood (47.9 vs. 40.9 %). Women also had more frequent spontaneous recollections of smells (p < 0.02). Chemosensory disorders have a significant impact on QoL. Reduced pleasure from eating is the predominant complaint of patients seeking medical attention. The steeper the onset of symptoms, the worse the ability to cope with changes in daily life. Older patients value the visual appeal, whereas younger patients value the haptic feedback of foods.

Toxicogenomics: the challenges and opportunities to identify biomarkers, signatures and thresholds to support mode-of-action.

Toxicogenomics (TGx) can be defined as the application of "omics" techniques to toxicology and risk assessment. By identifying molecular changes associated with toxicity, TGx data might assist hazard identification and investigate causes. Early technical challenges were evaluated and addressed by consortia (e.g. ISLI/HESI and the Microarray Quality Control consortium), which demonstrated that TGx gave reliable and reproducible information. The MAQC also produced "best practice on signature generation" after conducting an extensive evaluation of different methods on common datasets. Two findings of note were the need for methods that control batch variability, and that the predictive ability of a signature changes in concert with the variability of the endpoint. The key challenge remaining is data interpretation, because TGx can identify molecular changes that are causal, associated with or incidental to toxicity. Application of Bradford Hill's tests for causation, which are used to build mode of action (MOA) arguments, can produce reasonable hypotheses linking altered pathways to phenotypic changes. However, challenges in interpretation still remain: are all pathway changes equal, which are most important and plausibly linked to toxicity? Therefore the expert judgement of the toxicologist is still needed. There are theoretical reasons why consistent alterations across a metabolic pathway are important, but similar changes in signalling pathways may not alter information flow. At the molecular level thresholds may be due to the inherent properties of the regulatory network, for example switch-like behaviours from some network motifs (e.g. positive feedback) in the perturbed pathway leading to the toxicity. The application of systems biology methods to TGx data can generate hypotheses that explain why a threshold response exists. However, are we adequately trained to make these judgments? There is a need for collaborative efforts between regulators, industry and academia to properly define how these technologies can be applied using appropriate case-studies.

Sex ratios in the Arctic--do man-made chemicals matter?

OBJECTIVES: The objective was to analyze the variation of secondary sex ratios across the Arctic and to estimate the time trend. The rationale for this was claims in news media that, in the Arctic, sex ratios have become reduced due to exposure to anthropogenic contaminants in the environment. METHODS: Data was collected from 27 circumpolar jurisdictions from public websites of the eight Arctic countries. Sex ratios at birth were calculated for each jurisdiction and each available year. Linear regression models of the sex ratios across time were fit within each jurisdiction to estimate the change in sex ratio over time. RESULTS: All male:female sex ratios were close to 1.05 with time trends close to 0. In a Bayesian hierarchical model overall sex ratio was estimated at 1.054 (95% confidence interval 1.048, 1.058). The estimate for the 10-year slope across all jurisdictions was 0.0010 (95% confidence interval -0.0021, 0.0046). Separate analyses of indigenous populations in Alaska and Greenland gave similar results and similar sex ratios were found among Greenland Inuit in 1900 and today. CONCLUSIONS: The absence of deviation of the secondary sex ratio in any of the Arctic jurisdictions indicates that the contaminants that are present are not disrupting endocrine systems to the extent that sex ratios are being affected.

Are tolerance processes limiting the responses of Hediste diversicolor to cadmium exposure? A multimarker approach.

Cadmium (Cd) is considered a priority hazardous substance under the European Community Directive 2013/39 due to its ecotoxicity. The ragworm Hediste diversicolor (O.F. Müller, 1776), a common species in estuaries and coastal lagoons, plays an important ecological role in these ecosystems and is a suitable bioindicator of environmental chemical contamination. In this study, H. diversicolor was chosen as an ecotoxicological model with the aim of evaluating the responses to Cd contamination, considering a multi-biomarker approach (mortality, biometry, behaviour, Cd bioaccumulation, oxidative stress and damage, and energy metabolism). Also, the hypothesis of different tolerances resulting in different responses was evaluated, by collecting worms from three systems distinctly impacted by metal contamination (Mondego estuary, Óbidos Lagoon and Sado estuary - Portugal). Animals were exposed under laboratory conditions to cadmium (10, 50 and 100 µg/L), for 10 days. Significant differences were observed in responses amongst worms originating from the different sites. Organisms from the less impacted systems revealed greater effects on mortality, biomass decrease and burrowing behaviour, as well as higher bioaccumulation potential, after exposure to Cd. Biochemical and behaviour impairments were observed as a consequence of Cd exposure, although not in a concentration-dependant manner. The results obtained in this study reinforce the importance of integrating endpoint responses, at the individual and sub-individual levels, to assess potential changes induced by pollutants in the physiological status and fitness of H. diversicolor and help to predict what their ecological consequences might be.

Carveol ameliorates mercury-induced oxidative stress, neuroinflammation, and neurodegeneration in a mouse brain.

BACKGROUND: Mercury compounds are the world's third most hazardous substance. Mercury (II) chloride, also known as mercuric chloride (HgCl2), has been shown to have neurotoxic properties in a variety of forms. In numerous investigations, oxidative stress has been established as a key contributor to HgCl2-induced neurotoxicity. Carveol has been researched as an antioxidant and Nrf2-activator in several studies. This study was conducted to investigate if the carveol could protect mice against HgCl2-induced neuronal damage. METHODS: Mice were exposed to a dose of 0.4 mg/kg of HgCl2 and 20 mg/kg of carveol for 21 days. Animals were then subjected to behavioral evaluation through various methods such as open field test (OFT), elevated plus maze test (EPM), morris-water maze test (MWM), and Y-maze test. RESULTS: Results indicated hippocampal-related behavior anomalies which were improved significantly after carveol treatment. Oxidative stress was accompanied by excessive neuroinflammation, which was demonstrated by elevated levels of inflammatory markers such as TNF-α, p-NFkB, and COX-2, and were measured by Western blot, ELISA, and immunohistochemistry. These elevated levels of inflammatory markers were significantly mitigated upon treatment with carveol. To further investigate the participation of the JNK pathway, we used SP-600125 to inhibit JNK, which enhanced the neuroprotective effects of carveol. Moreover, molecular docking and modeling studies were used to validate these effects. CONCLUSION: Our findings indicate that carveol can inhibit the p-JNK pathway, thereby inhibiting HgCl2-induced apoptosis and downregulating the expression of inflammatory mediators.

Dual-targeted magnetic mesoporous silica nanoparticles reduce brain amyloid-ß burden via depolymerization and intestinal metabolism.

Rationale: Active removal of excess peripheral amyloid-ß (Aß) can potentially treat Alzheimer's disease (AD). However, the peripheral clearance of Aß using an anti-Aß monoclonal antibody (mAb) cannot remove PET-detectable Aß within the brain. This may be due to the inability of mAb to cross the blood-brain barrier (BBB) to degrade insoluble brain Aß plaques and block liver dysfunction. Methods: We developed a dual-targeted magnetic mesoporous silica nanoparticle (HA-MMSN-1F12) through surface-coupled Aß42-targeting antibody 1F12 and CD44-targeting ligand hyaluronic acid (HA). Results: HA-MMSN-1F12 had a high binding affinity toward Aß42 oligomers (Kd = 1.27 ± 0.34 nM) and revealed robust degradation of Aß42 aggregates. After intravenous administration of HA-MMSN-1F12 into ten-month-old APP/PS1 mice for three weeks (4 mg/kg/week), HA-MMSN-1F12 could cross the BBB and depolymerize brain Aß plaques into soluble Aß species. In addition, it also avoided hepatic uptake and excreted captured Aß species through intestinal metabolism, thereby reducing brain Aß load and neuroinflammation and improving memory deficits of APP/PS1 mice. Furthermore, the biochemical analysis showed that HA-MMSN-1F12 did not detect any toxic side effects on the liver and kidney. Thus, the efficacy of HA-MMSN-1F12 is associated with the targeted degradation of insoluble brain Aß plaques, avoidance of non-specific hepatic uptake, and excretion of peripheral Aß through intestinal metabolism. Conclusions: The study provides a new avenue for treating brain diseases by excreting disease-causing biohazards using intestinal metabolism.

Environmental hazard in the aetiology of somatic and germ cell aneuploidy.

Sources of environmental exposures to potentially aneugenic agents are many and include occupational and therapeutic exposures, and exposures associated with lifestyle habits. In this present study, some of these agents and exposure scenarios are discussed that involve potentially large population targets and/or seem to affect chromosome segregation by previously unsuspected mechanisms: metals, possibly acting by epigenetic mechanisms; nano-sized particles that might directly interact with subcellular components of the mitotic and meiotic machineries; cytostatic drugs in healthcare occupations; anticancer therapies potentially affecting the genetic integrity of gametes; continuously increasing electromagnetic field exposures with some sparse evidence of aneugenic activity; endocrine disruptors and their seemingly elusive effects in mouse oocytes, including the first evidence that prenatal exposure could affect meiotic nondisjunction in adult life. Hazards are considered for both somatic cells at risk of neoplastic transformation or tumour progression by chromosome loss and gain and germ cells at risk of heritable aneuploidies associated with spontaneous abortions or genetic diseases. Finally, possible synergistic interactions between environmental exposure and ageing or genetic predisposition are considered that could influence ultimate risks.

Multilevel empirical bayes modeling for improved estimation of toxicant formulations to suppress parasitic sea lamprey in the upper great lakes.

Estimation of extreme quantal-response statistics, such as the concentration required to kill 99.9% of test subjects (LC99.9), remains a challenge in the presence of multiple covariates and complex study designs. Accurate and precise estimates of the LC99.9 for mixtures of toxicants are critical to ongoing control of a parasitic invasive species, the sea lamprey, in the Laurentian Great Lakes of North America. The toxicity of those chemicals is affected by local and temporal variations in water chemistry, which must be incorporated into the modeling. We develop multilevel empirical Bayes models for data from multiple laboratory studies. Our approach yields more accurate and precise estimation of the LC99.9 compared to alternative models considered. This study demonstrates that properly incorporating hierarchical structure in laboratory data yields better estimates of LC99.9 stream treatment values that are critical to larvae control in the field. In addition, out-of-sample prediction of the results of in situ tests reveals the presence of a latent seasonal effect not manifest in the laboratory studies, suggesting avenues for future study and illustrating the importance of dual consideration of both experimental and observational data.

Inhibition of soluble epoxide hydrolase confers cardioprotection and prevents cardiac cytochrome P450 induction by benzo(a)pyrene.

We recently demonstrated that benzo(a)pyrene (BaP) causes cardiac hypertrophy by altering arachidonic acid metabolism through the induction of the expression of CYP ω-hydroxylases and soluble epoxide hydrolase (sEH) enzymes. The inhibition of CYP ω-hydroxylase enzymes partially reversed the BaP-induced cardiac hypertrophy. Therefore, it is important to examine whether the inhibition of sEH also confers cardioprotection. For this purpose, male Sprague-Dawley rats were injected intraperitoneally daily with either the sEH inhibitor 1-(1-methanesulfonyl-piperidin-4-yl)-3-(4-trifluoromethoxy-phenyl)-urea (TUPS; 0.65 mg/kg), BaP (20 mg/kg), or the combination of BaP (20 mg/kg) and TUPS (0.65 mg/kg) for 7 days. Thereafter, the heart, liver, and kidney were harvested, and the heart to body weight ratio was measured. The expression of the hypertrophic markers, sEH, heme oxygenase-1, and CYP450 enzymes was determined. Our results demonstrate that BaP alone significantly induced the expression of sEH and CYP ω-hydroxylases in the heart, liver, and kidney tissues. Treatment with TUPS significantly reversed the BaP-mediated induction of the hypertrophic markers, completely prevented the increase in the heart to body weight ratio, and reduced the BaP-induced CYP1A1, CYP1B1, CYP4F4, and CYP4F5 genes in the heart. The current study demonstrates the cardioprotective effect of sEH inhibitor, TUPS, against BaP-induced cardiac hypertrophy and further confirms the role of sEH and CYP450 enzymes in the development of cardiac hypertrophy.

Developmental exposure of zebrafish to vitamin D receptor acting drugs and environmental toxicants disrupts behavioral function.

Vitamin D receptor (VDR) signaling is important for optimal neurobehavioral development. Disruption of VDR signaling by environmental toxicants during early development might contribute to the etiology of behavioral dysfunction. In the current set of studies, we examined ten compounds known to affect VDR function in vitro for neurobehavioral effects in vivo in zebrafish. Zebrafish embryos were exposed to concentrations of the compounds in their water during the first 5 days post-fertilization. On day 5, the embryos were tested in an alternating light-dark locomotor assay using a computerized video tracking system. We found that most of the compounds produced significant changes in locomotor behavior in exposed zebrafish larvae, although the direction of the effect (i.e., hypo- or hyperactivity) and the sensitivity of the effect to changes in illumination condition varied across the compounds. The nature of the behavioral effects generally corresponded to the effects these compounds have been shown to exert on VDR. These studies lay a foundation for further investigation to determine whether behavioral dysfunction persists into adulthood and if so which behavioral functions are affected. Zebrafish can be useful for screening compounds identified in high throughput in vitro assays to provide an initial test for how those compounds would affect construction and behavioral function of a complex nervous system, helping to bridge the gap between in vitro neurotoxicity assays and mammalian models for risk assessment in humans.

Role of extracellular vesicles in cell-cell communication and inflammation following exposure to pulmonary toxicants.

Extracellular vesicles (EVs) have emerged as key regulators of cell-cell communication during inflammatory responses to lung injury induced by diverse pulmonary toxicants including cigarette smoke, air pollutants, hyperoxia, acids, and endotoxin. Many lung cell types, including epithelial cells and endothelial cells, as well as infiltrating macrophages generate EVs. EVs appear to function by transporting cargo to recipient cells that, in most instances, promote their inflammatory activity. Biologically active cargo transported by EVs include miRNAs, cytokines/chemokines, damage-associated molecular patterns (DAMPs), tissue factor (TF)s, and caspases. Findings that EVs are taken up by target cells such as macrophages, and that this leads to increased proinflammatory functioning provide support for their role in the development of pathologies associated with toxicant exposure. Understanding the nature of EVs responding to toxic exposures and their cargo may lead to the development of novel therapeutic approaches to mitigating lung injury.

Stress biology and hormesis: the Yerkes-Dodson law in psychology--a special case of the hormesis dose response.

This article traces the historical foundations of the Yerkes-Dodson Law from its experimental foundations in the first decade of the 20th century, to its recognition as a generalizable phenomenon in multiple species including humans and to more current attempts to understand its molecular basis within the framework of stress-related biological processes. Within this context, the biological and dose-response characteristics of the Yerkes-Dodson Law are evaluated and compared to the hormesis dose-response model. Based on this evaluation, which includes study design analysis, statistical models of multiple factor/chemical interaction, and a comparative assessment of the quantitative features of these respective dose-response relationships and their molecular foundations, the Yerkes-Dodson Law is shown to represent a special case of the general concept of hormesis illustrating the interaction of two independent study variables, which has typically been observed to be an additive response, although not theoretically restricted to one. The conceptual integration of the Yerkes-Dodson Law within the hormetic dose response framework adds further support for the generalization of the hormesis concept.

Acute sensitivity of the killifish Nothobranchius furzeri to a combination of temperature and reference toxicants (cadmium, chlorpyrifos and 3,4-dichloroaniline).

Aquatic organisms of inland waters are often subjected to a combination of stressors. Yet, few experiments assess mixed stress effects beyond a select group of standard model organisms. We studied the joint toxicity of reference toxicants and increased temperature on the turquoise killifish, Nothobranchius furzeri, a promising model for ecotoxicological research due to the species' short life cycle and the production of drought-resistant eggs. The acute sensitivity of the larval stage (2dph) to three compounds (cadmium, 3,4-dichloroaniline and chlorpyrifos) was tested in combination with a temperature increase of 4 °C, mimicking global warming. Dose-response relationships were used to calculate 96h-LC50 of 0.28 mg/L (24 °C) and 0.39 mg/L (28 °C) for cadmium, 96h-LC50 of 9.75 mg/L (24 °C) and 6.61 mg/L (28 °C) for 3,4-dichloroaniline and 96h-LC50 of 15.4 µg/L (24 °C) and 14.2 µg/L (28 °C) for chlorpyrifos. After 24 h of exposure, the toxicity of all tested compounds was exacerbated under increased temperature. Furthermore, the interaction effect of cadmium and temperature could be predicted by the stress addition model (SAM). This suggests the applicability of the model for fish and at the same time indicates that the model could be suitable to predict effects of temperature-toxicant interactions.

In vitro Cytotoxicity and Genotoxicity Analysis of Ten Tannery Chemicals Using SOS/umu Tests and High-content In vitro Micronucleus Tests.

BACKGROUND: More than 2,000 chemicals have been used in the tannery industry. Although some tannery chemicals have been reported to have harmful effects on both human health and the environment, only a few have been subjected to genotoxicity and cytotoxicity evaluations. OBJECTIVE: This study focused on cytotoxicity and genotoxicity of ten tannery chemicals widely used in China. MATERIALS AND METHODS: DNA-damaging effects were measured using the SOS/umu test with Salmonella typhimurium TA1535/pSK1002. Chromosome-damaging and cytotoxic effects were determined with the high-content in vitro Micronucleus test (MN test) using the human-derived cell lines MGC-803 and A549. CONCLUSION: The cytotoxicity of the ten tannery chemicals differed somewhat between the two cell assays, with A549 cells being more sensitive than MGC-803 cells. None of the chemicals induced DNA damage before metabolism, but one was found to have DNA-damaging effects on metabolism. Four of the chemicals, DY64, SB1, DB71 and RR120, were found to have chromosome-damaging effects. A Quantitative Structure-Activity Relationship (QSAR) analysis indicated that one structural feature favouring chemical genotoxicity, Hacceptor-path3-Hacceptor, may contribute to the chromosome-damaging effects of the four MN-test-positive chemicals.

Environmental toxicants may modulate osteoblast differentiation by a mechanism involving the aryl hydrocarbon receptor.

UNLABELLED: The AHR mediates many of the toxicological effects of aromatic hydrocarbons. We show that AHR expression in osteoblasts parallels the induction of early bone-specific genes involved in maturation. The AHR may not only mediate the effects of toxicants, but with an as yet unidentified ligand, be involved in the differentiation pathways of osteoblasts. INTRODUCTION: Metabolic bone diseases arise as a result of an imbalance in bone cell activities. Recent evidence suggests that environmental toxicants may be contributing factors altering these activities. One candidate molecule implicated in mediating the toxic effects of exogenous compounds is the aryl hydrocarbon receptor (AHR). MATERIALS AND METHODS: Osteoblasts isolated from neonatal rat calvaria were analyzed for AHR expression by quantitative PCR, Western blot, and immunohistochemistry. In addition, AHR activation was evaluated by electromobility gel shift assay and fluorescence microscopy. RESULTS: Our findings showed AHR expression in mature osteoblasts in vivo. The pattern of AHR expression peaks after alkaline phosphatase and before induction of osteocalcin. We first show that AHR functions as a transactivating receptor in osteoblasts, as evidenced by its ligand-dependent migration to the nucleus and its association with known dioxin response elements. AHR activation by 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD) mediated the induction of cytochrome p450 1A1 and cycloxygenase-2 protein levels. This effect could be inhibited by the potent AHR antagonist, 3'4 methoxynitroflavone. Furthermore, lead treatment of osteoblasts upregulates the expression of AHR mRNA and protein levels, supporting a novel mechanism whereby lead in the skeleton may increase the sensitivity of bone cells to toxicant exposure. CONCLUSIONS: These data imply that the AHR mediates the effects of aromatic toxicants on bone and that AHR expression is regulated during osteoblast differentiation.