The European Union’s REACH regulation: a review of its history and requirements

From Molecular Descriptors to Intrinsic Fish Toxicity of Chemicals: An Alternative Approach to Chemical Prioritization

The European and U.S. chemical agencies have listed approximately 800k chemicals about which knowledge of potential risks to human health and the environment is lacking. Filling these data gaps experimentally is impossible, so in silico approaches and prediction are essential. Many existing models are however limited by assumptions (e.g., linearity and continuity) and small training sets. In this study, we present a supervised direct classification model that connects molecular descriptors to toxicity. Categories can be driven by either data (using k-means clustering) or defined by regulation. This was tested via 907 experimentally defined 96 h LC50 values for acute fish toxicity. Our classification model explained ≈90% of the variance in our data for the training set and ≈80% for the test set. This strategy gave a 5-fold decrease in the frequency of incorrect categorization compared to a quantitative structure-activity relationship (QSAR) regression model. Our model was subsequently employed to predict the toxicity categories of ≈32k chemicals. A comparison between the model-based applicability domain (AD) and the training set AD was performed, suggesting that the training set-based AD is a more adequate way to avoid extrapolation when using such models. The better performance of our direct classification model compared to that of QSAR methods makes this approach a viable tool for assessing the hazards and risks of chemicals.

Cutting-edge computational chemical exposure research at the U.S. Environmental Protection Agency

Exposure science is evolving from its traditional "after the fact" and "one chemical at a time" approach to forecasting chemical exposures rapidly enough to keep pace with the constantly expanding landscape of chemicals and exposures. In this article, we provide an overview of the approaches, accomplishments, and plans for advancing computational exposure science within the U.S. Environmental Protection Agency's Office of Research and Development (EPA/ORD). First, to characterize the universe of chemicals in commerce and the environment, a carefully curated, web-accessible chemical resource has been created. This DSSTox database unambiguously identifies >1.2 million unique substances reflecting potential environmental and human exposures and includes computationally accessible links to each compound's corresponding data resources. Next, EPA is developing, applying, and evaluating predictive exposure models. These models increasingly rely on data, computational tools like quantitative structure activity relationship (QSAR) models, and machine learning/artificial intelligence to provide timely and efficient prediction of chemical exposure (and associated uncertainty) for thousands of chemicals at a time. Integral to this modeling effort, EPA is developing data resources across the exposure continuum that includes application of high-resolution mass spectrometry (HRMS) non-targeted analysis (NTA) methods providing measurement capability at scale with the number of chemicals in commerce. These research efforts are integrated and well-tailored to support population exposure assessment to prioritize chemicals for exposure as a critical input to risk management. In addition, the exposure forecasts will allow a wide variety of stakeholders to explore sustainable initiatives like green chemistry to achieve economic, social, and environmental prosperity and protection of future generations.

Optimized Derivation of Predicted No-Effect Concentrations (PNECs) for Eight Polycyclic Aromatic Hydrocarbons (PAHs) Using HC10 Based on Acute Toxicity Data

For persistent organic pollutants, a concern of environmental supervision, predicted no-effect concentrations (PNECs) are often used in ecological risk assessment, which is commonly derived from the hazardous concentration of 5% (HC₅) of the species sensitivity distribution (SSD). To address the problem of a lack of toxicity data, the objectives of this study are to propose and apply two improvement ideas for SSD application, taking polycyclic aromatic hydrocarbons (PAHs) as an example: whether the chronic PNEC can be derived from the acute SSD curve; whether the PNEC may be calculated by HC₁₀ to avoid solely statistical extrapolation. In this study, the acute SSD curves for eight PAHs and the chronic SSD curves for three PAHs were constructed. The quantity relationship of HC₅s between the acute and chronic SSD curves was explored, and the value of the assessment factor when using HC₁₀ to calculate PNEC was derived. The results showed that, for PAHs, the chronic PNEC can be estimated by multiplying the acute PNEC by 0.1, and the value of the assessment factor corresponding to HC₁₀ is 10. For acenaphthene, anthracene, benzo[a]pyrene, fluoranthene, fluorene, naphthalene, phenanthrene, and pyrene, the chronic PNECs based on the acute HC₁₀s were 0.8120, 0.008925, 0.005202, 0.07602, 2.328, 12.75, 0.5731, and 0.05360 μg/L, respectively.

Economic interests cloud hazard reductions in the European regulation of substances of very high concern

Here we investigate how the conflicts between hazard reduction and economic interests have shaped the regulation of substances of very high concern (SVHCs) under the Authorization program of the European chemical regulation Registration, Evaluation, Authorization, and Restriction of Chemicals (REACH). Since regulation starts with listing SVHCs on the Candidate List, we analyze the relative importance of toxicological properties, economic motivations, and available scientific knowledge on the probability of inclusion on the Candidate List. We find that the most important factor in whether a substance is listed is whether it is being produced in, or imported into, the European Economic Area (EEA), with the regulators less likely to place a substance on the list if it is currently being produced or imported in the EEA. This evidence suggests that regulators have listed chemicals of secondary importance leading to lesser than anticipated hazard reductions, either because production and imports had already ceased before the listing, or because the compound has never been produced or imported in the EEA at all.

The most important variable explaining the regulation of chemical substances of very high concern in the European REACH regulation is not how dangerous a chemical is but the fact that it is not produced nor imported into the European Economic Area.

Deriving freshwater guideline values for neonicotinoid insecticides: Implications for water quality guidelines and ecological risk assessment

The increased use of neonicotinoid insecticides in aquatic environments poses a significant threat to non-target freshwater species. However, the existing water quality guidelines (WQGs) for neonicotinoids mainly focus on imidacloprid, and only a few authoritative institutions have established WQGs for other neonicotinoids. There is a critical need to develop WQGs and conduct ecological risk assessment (ERA) of different neonicotinoids in global freshwater environments. In this study, we derived interim acute and chronic guideline values and acute-to-chronic ratios (ACRs) for six neonicotinoids based on publicly available acute and chronic toxicity data. The exposure concentrations of neonicotinoids were obtained from published literature worldwide, and ERA was conducted for neonicotinoids in global freshwater ecosystems using a tiered approach. The derived chronic guideline values (95% confidence interval (CI), ng/L) were 0.63 (0.02-5.47) for thiacloprid (the lowest) and 16.4 for dinotefuran (the highest). The identified ACRs (95% CI) ranged from 90.9 (47.0-180) to 957 (102-3350), which can be used to extrapolate scarce chronic data from the acute data. Neonicotinoid concentrations in global freshwater were predicted from 10.6 (6.88-23.4) (thiacloprid) to 339 (211-786) ng/L (thiamethoxam). The estimated risk quotients ranged from 3.23 (dinotefuran) to 21.73 (thiacloprid), and the probability of exceeding WQGs ranged from 27.1% (dinotefuran) to 77.1% (thiacloprid). The ERA results indicated that the six neonicotinoids posed negligible acute risks but high chronic risks to global freshwater ecosystems, especially acetamiprid (65.8%) and thiacloprid (28.1%). The key findings of this study provide critical scientific information regarding the ecological risks of long-term neonicotinoid exposure and key insights for policy development and water quality control.

Characterization of Compositional Variability in Petroleum Substances

In the process of registration of substances of Unknown or Variable Composition, Complex Reaction Products or Biological Materials (UVCBs), information sufficient to enable substance identification must be provided. Substance identification for UVCBs formed through petroleum refining is particularly challenging due to their chemical complexity, as well as variability in refining process conditions and composition of the feedstocks. This study aimed to characterize compositional variability of petroleum UVCBs both within and across product categories. We utilized ion mobility spectrometry (IMS)-MS as a technique to evaluate detailed chemical composition of independent production cycle-derived samples of 6 petroleum products from 3 manufacturing categories (heavy aromatic, hydrotreated light paraffinic, and hydrotreated heavy paraffinic). Atmospheric pressure photoionization and drift tube IMS-MS were used to identify structurally related compounds and quantified between- and within-product variability. In addition, we determined both individual molecules and hydrocarbon blocks that were most variable in samples from different production cycles. We found that detailed chemical compositional data on petroleum UVCBs obtained from IMS-MS can provide the information necessary for hazard and risk characterization in terms of quantifying the variability of the products in a manufacturing category, as well as in subsequent production cycles of the same product.

Life stage and endpoint sensitivity differences of fathead minnow (Pimephales promelas) to chemicals with various modes of action

Fish Embryo Acute Toxicity (FET) test was proposed as an alternative to the traditional test methods using larval or adult fish. However, whether fathead minnow (Pimephales promelas) embryo is appropriate for FET remains uncertain. In the present study, ecological threshold of toxicological concern (ecoTTC) values and uncertainty factors (UFs) for each Verhaar et al. category in P. promelas were identified by employing probabilistic ecological risk assessment (PERA) approach with chemical toxicity distributions (CTDs). The sensitivity among different life stages and toxicity among different mode of actions (MOAs) classes were comprehensively compared by CTD comparisons. The results showed that embryo exhibited the less or similar sensitivity compared to larva or adult for Verhaar et al. MOA classes (1-4) while adults were more sensitive, followed by embryo than larval for non-classified chemicals. Considering growth effect as endpoint to class 1, class 3, and non-classified chemicals on P. promelas embryo and larva was more sensitive than mortality. Non-classified chemicals especially inorganic compounds were most toxic to P. promelas embryo for the four concerned Verharr et al. MOA-specific chemical classes. This study also derived uncertainty factors (UFs) as 26.5 (9.8, 109) for embryo-to-larva, 6.26 (3.94, 11.0) for embryo-to-adult, 15.6 (10.1, 36.1) for mortality-to-growth, and 3.03 (1.86, 7.08) for mortality-to-reproduction, which can be applied for extrapolations of life stage-to-life stage and effect-to-effect to reduce the underestimating and overestimating risk by the use of default UF such as 10, 100 or 1000. Our findings are vital for feasibility of FET test of P. promelas for ecotoxicity testing and ecological risk assessment for chemicals with different MOAs.

Towards harmonization of water quality management: A comparison of chemical drinking water and surface water quality standards around the globe

Water quality standards (WQS) set the legal definition for safe and desirable water. WQS impose regulatory concentration limits to act as a jurisdiction-specific legislative risk-management tool. Despite its importance in shaping a universal definition of safe, clean water, little information exists with respect to (dis)similarity of chemical WQS worldwide. Therefore, this paper compares chemical WQS for drinking and surface water matrices in eight jurisdictions representing a global geographic distribution: Australia, Brazil, Canada, China, the European Union, the region of Flanders in Belgium, the United States of America, and South Africa. The World Health Organization's list is used as a reference for drinking water standards. Sørensen-Dice indices (SDI) showed little qualitative similarity in the compounds that are regulated in drinking water (median SDI = 40%) and surface water (median SDI = 33%), indicating that the heterogeneity within a matrix is substantial at the level of the standard. Quantitative similarity for matching standards was higher than the qualitative per Kendall correlation (median = 0.73 and 0.58 for drinking water and surface water respectively), yet variance observed within standards remained inexplicably high for organic compounds. Variations in WQS were more pronounced for organic compounds. Most differences cannot be easily explained from a toxicological or risk-based point-of-view. Historical development, ease of measurement, and (toxicological) knowledge gaps on the risk of a vast number of organic compounds are theorized to be the drivers. Therefore, this study argues for a more tailored, risk-based approach in which standards incorporated into water safety plans are dynamically set for compounds that are persistent and could pose a risk for human health and/or aquatic ecosystems. Global variations in WQS should therefore not necessarily be avoided but rather globally harmonized with enough flexibility to ensure a global, up-to-date definition of safe and desirable water everywhere.

Entrepreneurship in Polymer Chemistry

Launching a startup company is like synthesizing a new molecule. There is a starting point and a general concept for how to achieve the desired end. Known steps may be taken, but a successful synthesis is rarely the result of the original plan and relies on perseverance and creativity. If done well, the starting molecule (idea) gives rise to a new final product (business). Having personally lived these journeys, the authors of this viewpoint distilled their combined experiences into relevant topics for scientific entrepreneurs. This viewpoint is not a how-to guide for launching a startup. Instead, relatable personal insights and potential best practices are shared to catalyze discussions around a topic of growing relevance to both the polymer community and workforce of the future.

Detection of endocrine disrupting chemicals in Danio rerio and Daphnia pulex: Step-one, behavioral screen

Anthropogenic surface and ground water contamination by chemicals is a global problem, and there is an urgent need to develop tools to identify and elucidate biological effects. Contaminants of emerging concern (CECs) are not typically monitored or regulated and those with known or suspected endocrine disrupting potential have been termed endocrine disrupting chemicals (EDCs). Many CECs are known to be neurotoxic (e.g., insecticides) and many are incompletely characterized. Behavioral responses can identify chemicals with neuroactive properties, which can be relevant to EDC mechanisms (e.g., neuroendocrine disturbances). Two freshwater species, Daphnia pulex and Danio rerio, were evaluated for swimming behavior alterations resulting from 24-hr exposure to 9 CECs: triclosan, triclocarban, chlorpyrifos, dieldrin, 4-nonylphenol, bisphenol-A, atrazine, metformin, and estrone. This is the first step in the development of a bioassay for detecting estrogenic and/or anti-androgenic activity with the goal to evaluate complex mixtures of uncharacterized contaminants in water samples. The second step, described in a subsequent report, examines transcriptome alterations following chemical exposure. Significant differences in the swimming behavior response and sensitivity were found across chemicals within a species and across species for a given chemical in this unique optical bioassay system. In the concentration ranges studied, significant behavioral alterations were detected for 6 of 9 CECs for D. pulex and 4 of 9 CECs for D. rerio. These results underscore the utility of this bioassay to identify behavioral effects of sublethal concentrations of CECs before exploration of transcriptomic alterations for EDC detection.

Refining in vitro and in silico neurotoxicity approaches by accounting for interspecies and interindividual differences in toxicodynamics

INTRODUCTION

The process of chemical risk assessment traditionally relies on animal experiments and associated default uncertainty factors to account for interspecies and interindividual differences. To work toward a more precise and personalized risk assessment, these uncertainty factors should be refined and replaced by chemical-specific adjustment factors (CSAFs).

AREAS COVERED

This concise review discusses alternative (in vitro/in silico) approaches that can be used to assess interspecies and interindividual differences in toxicodynamics, ranging from targeted to more integrated approaches. Although data are available on interspecies differences, the increasing use of human-induced pluripotent stem cell (hiPSC)-derived neurons may provide opportunities to also assess interindividual variability in neurotoxicity. More integrated approaches, like adverse outcome pathways (AOPs) can provide a more quantitative understanding of the toxicodynamics of a chemical.

EXPERT OPINION

To improve chemical risk assessment, refinement of uncertainty factors is crucial. In vitro and in silico models can facilitate the development of CSAFs, but still these models cannot always capture the complexity of the in vivo situation, thereby potentially hampering regulatory acceptance. The combined use of more integrated approaches, like AOPs and physiologically based kinetic models, can aid in structuring data and increasing suitability of alternative approaches for regulatory purposes.

Depletion of Boric Acid and Cobalt from Cultivation Media: Impact on Recombinant Protein Production with Komagataella phaffii

The REACH regulation stands for “Registration, Evaluation, Authorization and Restriction of Chemicals” and defines certain substances as harmful to human health and the environment. This urges manufacturers to adapt production processes. Boric acid and cobalt dichloride represent such harmful ingredients, but are commonly used in yeast cultivation media. The yeast Komagataella phaffii (Pichia pastoris) is an important host for heterologous protein production and compliance with the REACH regulation is desirable. Boric acid and cobalt dichloride are used as boron and cobalt sources, respectively. Boron and cobalt support growth and productivity and a number of cobalt-containing enzymes exist. Therefore, depletion of boric acid and cobalt dichloride could have various negative effects, but knowledge is currently scarce. Herein, we provide an insight into the impact of boric acid and cobalt depletion on recombinant protein production with K. phaffii and additionally show how different vessel materials affect cultivation media compositions through leaking elements. We found that boric acid could be substituted through boron leakiness from borosilicate glassware. Furthermore, depletion of boric acid and cobalt dichloride neither affected high cell density cultivation nor cell morphology and viability on methanol. However, final protein quality of three different industrially relevant enzymes was affected in various ways.

In vitro methods for predicting the bioconcentration of xenobiotics in aquatic organisms

The accumulation of anthropogenic chemical substances in aquatic organisms is an immensely important issue from the point of view of environmental protection. In the context of the increasing number and variety of compounds that may potentially enter the environment, there is a need for efficient and reliable solutions to assess the risks. However, the classic approach of testing with fish or other animals is not sufficient. Due to very high costs, significant time and labour intensity, as well as ethical concerns, in vivo methods need to be replaced by new laboratory-based tools. So far, many models have been developed to estimate the bioconcentration potential of chemicals. However, most of them are not sufficiently reliable and their predictions are based on limited input data, often obtained with doubtful quality. The octanol-water partition coefficient is still often used as the main laboratory tool for estimating bioconcentration. However, according to current knowledge, this method can lead to very unreliable results, both for neutral species and, above all, for ionic compounds. It is therefore essential to start using new, more advanced and credible solutions on a large scale. Over the last years, many in vitro methods have been newly developed or improved, allowing for a much more adequate estimation of the bioconcentration potential. Therefore, the aim of this work was to review the most recent laboratory methods for assessing the bioconcentration potential and to evaluate their applicability in further research.

One uncertainty factor does not fit all: Identifying mode of action and species specific acute to chronic ratios for aquatic life

In ecological risk assessment, acute to chronic ratio (ACR) uncertainty factors are routinely applied to acute mortality benchmarks to estimate chronic toxicity thresholds. To investigate variability of aquatic ACRs, we first compiled and compared 56 and 150 pairs of acute and subchronic/chronic growth/reproductive toxicity data for fishes (Pimephales promelas (53), Danio rerio (2), and Oryzias latipes (1)) and the crustacean Daphnia magna, respectively, for 172 chemicals with different modes of action (MOA). We found that there were only significant relationships between P. promelas acute median lethal concentrations and growth lowest-observed effect concentrations for class 1 (nonpolar narcosis) chemicals, though significant relationships were demonstrated for D. magna to all Verhaar et al. MOA classes (Class 1: nonpolar narcosis, Class 2: polar narcosis, Class 3: reactive chemicals, and Class 4: AChE inhibitors and estrogenics). Probabilistic ecological hazard assessment using chemical toxicity distributions was subsequently employed for each MOA class to estimate acute and chronic thresholds, respectively, to identify MOA and species specific ecological thresholds of toxicological concern. Finally, novel MOA and species specific ACRs using both chemical toxicity distribution comparison and individual ACR probability distribution approaches were identified using representative MOA and chemical categories. Our data-driven approaches and newly identified ACR values represent robust alternatives to application of default ACR values, and can also support future research and risk assessment and management activities for other chemical classes when toxicity information is limited for chemicals with specific MOAs within invertebrates and fish.

Overview of REACH: Issues Involved in the Registration of Metals

New European legislation known as REACH (Registration, Evaluation, Authorization and Restriction of Chemicals) was introduced in 2007 to increase the speed at which the health and/or environmental risks of industrial chemicals were being assessed and managed (REACH (EC) No 1907/2006). REACH consolidated earlier chemicals-control statutes and placed the burden of assessing, and identifying the means to manage risks on industry. This paper details the REACH process for controlling and managing hazardous chemicals and challenges encountered in applying the provisions of REACH and the guidance documents available from European Chemical Agency. Special attention is paid to challenges in evaluating potential health risks of metals such as aluminum and aluminum compounds. Lessons learned from over a decade of experience with REACH legislation are also noted.

'All chemical substances are harmful.' public appraisal of uncertain risks of food additives and contaminants

In toxicological health risk assessment, epistemic uncertainties (e.g. about a chemical's intrinsic properties or toxicity) often remain, preventing definitive statements about whether a chemical constitues a risk. In this study, we analyzed public appraisals of uncertain risks of food additives and contaminants. We identified three major characteristics of public appraisal. First, hazard appraisals differed consistently from risk appraisals: respondents were less disturbed by a possible health risk than by the mere presence of the chemical substance in food. Second, while a majority understood that exposure determines whether a chemical constitutes a risk, many respondents thought that all chemicals are equally harmful. This suggests a mismatch between beliefs about exposure and beliefs about toxicity. Finally, the higher people valued certainty about food safety and the less they considered uncertainty about a risk acceptable, the more severe they appraised the presence of the chemical substance in food. This suggests that a mismatch between the level of uncertainty that people expect about food safety and the actual level of scientific uncertainty, affects how people evaluate the presence of chemical substances in food. Following the findings, implications for risk communication are discussed.

Biological activities associated with the volatile compound 2,5-bis(1-methylethyl)-pyrazine

Pyrazines are 1,4-diazabenzene-based volatile organic compounds and known for their broad-spectrum antimicrobial activity. In the present study, we assessed the antimicrobial activity of 2,5-bis(1-methylethyl)-pyrazine, produced by Paenibacillus sp. AD87 during co-culture with Burkholderia sp. AD24. In addition, we were using transcriptional reporter assays in E. coli and mammalian cells to decipher the possible mode of action. Bacterial and mammalian luciferase reporter strains were deployed to elucidate antimicrobial and toxicological effects of 2,5-bis(1-methylethyl)-pyrazine. At high levels of exposure, 2,5-bis(1-methylethyl)-pyrazine exerted strong DNA damage response. At lower concentrations, cell-wall damage response was observed. The activity was corroborated by a general toxicity reporter assay in E. coli ΔampD, defective in peptidoglycan turnover. The maximum E. coli cell-wall stress activity was measured at a concentration close to the onset of the mammalian cytotoxicity, while other adverse outcome pathways, such as the activation of aryl hydrocarbon and estrogenic receptor, the p53 tumour suppressor and the oxidative stress-related Nrf2 transcription factor, were induced at elevated concentrations compared to the response of mammalian cells. Because of its broad-spectrum antimicrobial activity at lower concentrations and the relatively low mammalian toxicity, 2,5-bis(1-methylethyl)-pyrazine is a potential bio-based fumigant with possible applications in food industry, agriculture or logistics.

The California Safer Consumer Products Program: Evaluating a Novel Chemical Policy Strategy

In 2008, California enacted laws to restructure chemical policy and promote green chemistry. Ten years after the passage of California’s green chemistry laws, we assessed their performance through structured interviews with a sample of experts from government, academia, business, and the nonprofit sector. We combined the interviews with a scoping literature review to propose a new ten-point framework for evaluating the effectiveness of a chemical regulatory policy, and we assessed the performance of the California law against this framework. The California program performed well on transparency of the regulatory process; protecting vulnerable populations; placing the primary burden on the manufacturer; breadth of regulatory authority; and advancing the public right-to-know. Areas of weakness include unclear authority to require data on chemical use in products; an inefficient pace of implementation; and limited incentives for innovation. Promoting safer chemicals in products will require additional incentives to protect public health and the environment.

The impact on classifications for carcinogenicity, mutagenicity, reproductive and specific target organ toxicity after repeated exposure in the first ten years of the REACH regulation

The present study primarily aims at informing regulators and policy makers in Europe and examines the evolution of self-classifications and study availability for the endpoints of carcinogenicity, mutagenicity, reproductive toxicity (CMR) and specific target organ toxicity after repeated exposure (STOT RE) for the first ten years of the REACH legislation. Our knowledge on chemical safety keeps increasing due to the registration obligations under REACH, in combination with proactive actions by registrants and regulatory actions by Authorities, which jointly lead to new testing and critical reassessment of existing studies. The improvements become evident by the constant increase in the number of substances that are self-classified by the registrants for human health endpoints. Moreover, there is a slow but steady increase in the number of substances for which there is at least one experimental study available for the human health endpoints in scope of this analysis. However, the increase is slow given the generally limited data availability at the beginning of REACH. Manual examination of about 350 classified substances reveals that the impact of newly generated data and regulatory action by Authorities is greater for reproductive toxicity than for carcinogenicity or mutagenicity, reflecting the strengthening of the information requirements for reproductive toxicity with the introduction of REACH. The results of the study should inform regulators and policy makers at EU and national level in the discussion on potential changes to information requirements or testing strategies under REACH.

Machine Learning of Toxicological Big Data Enables Read-Across Structure Activity Relationships (RASAR) Outperforming Animal Test Reproducibility

Earlier we created a chemical hazard database via natural language processing of dossiers submitted to the European Chemical Agency with approximately 10 000 chemicals. We identified repeat OECD guideline tests to establish reproducibility of acute oral and dermal toxicity, eye and skin irritation, mutagenicity and skin sensitization. Based on 350-700+ chemicals each, the probability that an OECD guideline animal test would output the same result in a repeat test was 78%-96% (sensitivity 50%-87%). An expanded database with more than 866 000 chemical properties/hazards was used as training data and to model health hazards and chemical properties. The constructed models automate and extend the read-across method of chemical classification. The novel models called RASARs (read-across structure activity relationship) use binary fingerprints and Jaccard distance to define chemical similarity. A large chemical similarity adjacency matrix is constructed from this similarity metric and is used to derive feature vectors for supervised learning. We show results on 9 health hazards from 2 kinds of RASARs-"Simple" and "Data Fusion". The "Simple" RASAR seeks to duplicate the traditional read-across method, predicting hazard from chemical analogs with known hazard data. The "Data Fusion" RASAR extends this concept by creating large feature vectors from all available property data rather than only the modeled hazard. Simple RASAR models tested in cross-validation achieve 70%-80% balanced accuracies with constraints on tested compounds. Cross validation of data fusion RASARs show balanced accuracies in the 80%-95% range across 9 health hazards with no constraints on tested compounds.

Impact of obesity and overweight on DNA stability: Few facts and many hypotheses

Health authorities are alarmed worldwide about the increase of obesity and overweight in the last decades which lead to adverse health effects including inflammation, cancer, accelerated aging and infertility. We evaluated the state of knowledge concerning the impact of elevated body mass on genomic instability. Results of investigations with humans (39 studies) in which DNA damage was monitored in lymphocytes and sperm cells, are conflicting and probably as a consequence of heterogeneous study designs and confounding factors (e.g. uncontrolled intake of vitamins and minerals and consumption of different food types). Results of animal studies with defined diets (23 studies) are more consistent and show that excess body fat causes DNA damage in multiple organs including brain, liver, colon and testes. Different molecular mechanisms may cause genetic instability in overweight/obese individuals. ROS formation and lipid peroxidation were found in several investigations and may be caused by increased insulin, fatty acid and glucose levels or indirectly via inflammation. Also reduced DNA repair and formation of advanced glycation end products may play a role but more data are required to draw firm conclusions. Reduction of telomere lengths and hormonal imbalances are characteristic for overweight/obesity but the former effects are delayed and moderate and hormonal effects were not investigated in regard to genomic instability in obese individuals. Increased BMI values affect also the activities of drug metabolizing enzymes which activate/detoxify genotoxic carcinogens, but no studies concerning the impact of these alterations of DNA damage in obese individuals are available. Overall, the knowledge concerning the impact of increased body weight and DNA damage is poor and further research is warranted to shed light on this important issue.

Combining a Deconvolution and a Universal Library Search Algorithm for the Nontarget Analysis of Data-Independent Acquisition Mode Liquid Chromatography-High-Resolution Mass Spectrometry Results

Nontarget analysis is considered one of the most comprehensive tools for the identification of unknown compounds in a complex sample analyzed via liquid chromatography coupled to high-resolution mass spectrometry (LC-HRMS). Due to the complexity of the data generated via LC-HRMS, the data-dependent acquisition mode, which produces the MS² spectra of a limited number of the precursor ions, has been one of the most common approaches used during nontarget screening. However, data-independent acquisition mode produces highly complex spectra that require proper deconvolution and library search algorithms. We have developed a deconvolution algorithm and a universal library search algorithm (ULSA) for the analysis of complex spectra generated via data-independent acquisition. These algorithms were validated and tested using both semisynthetic and real environmental data. A total of 6000 randomly selected spectra from MassBank were introduced across the total ion chromatograms of 15 sludge extracts at three levels of background complexity for the validation of the algorithms via semisynthetic data. The deconvolution algorithm successfully extracted more than 60% of the added ions in the analytical signal for 95% of processed spectra (i.e., 3 complexity levels multiplied by 6000 spectra). The ULSA ranked the correct spectra among the top three for more than 95% of cases. We further tested the algorithms with 5 wastewater effluent extracts for 59 artificial unknown analytes (i.e., their presence or absence was confirmed via target analysis). These algorithms did not produce any cases of false identifications while correctly identifying ∼70% of the total inquiries. The implications, capabilities, and the limitations of both algorithms are further discussed.

Xenobiotic metabolism in the fish hepatic cell lines Hepa-E1 and RTH-149, and the gill cell lines RTgill-W1 and G1B: Biomarkers of CYP450 activity and oxidative stress

The use of fish cell cultures has proven to be an effective tool in the study of environmental and aquatic toxicology. Valuable information can be obtained from comparisons between cell lines from different species and organs. In the present study, specific chemicals were used and biomarkers (e.g. 7-Ethoxyresorufin-O-deethylase (EROD) activity and reactive oxygen species (ROS)) were measured to assess the metabolic capabilities and cytotoxicity of the fish hepatic cell lines Hepa-E1 and RTH-149, and the fish gill cell lines RTgill-W1 and G1B. These cell lines were exposed to β-naphthoflavone (BNF) and benzo[a]pyrene (BaP), the pharmaceutical tamoxifen (TMX), and the organic peroxide tert-butylhydroperoxide (tBHP). Cytotoxicity in gill cell lines was significantly higher than in hepatic cells, with BNF and TMX being the most toxic compounds. CYP1-like associated activity, measured through EROD activity, was only detected in hepatic cells; Hepa-E1 cells showed the highest activity after exposure to both BNF and BaP. Significantly higher levels of CYP3A-like activity were also observed in Hepa-E1 cells exposed to TMX, while gill cell lines presented the lowest levels. Measurements of ROS and antioxidant enzymes indicated that peroxide levels were higher in gill cell lines in general. However, levels of superoxide were significantly higher in RTH-149 cells, where no distinctive increase of superoxide-related antioxidants was observed. The present study demonstrates the importance of selecting adequate cell lines in measuring specific metabolic parameters and provides strong evidence for the fish hepatocarcinoma Hepa-E1 cells to be an excellent alternative in assessing metabolism of xenobiotics, and in expanding the applicability of fish cell lines for in vitro studies.

QSAR models for describing the toxicological effects of ILs against Staphylococcus aureus based on norm indexes

The hazardous potential of ionic liquids (ILs) is becoming an issue of great concern due to their important role in many industrial fields as green agents. The mathematical model for the toxicological effects of ILs is useful for the risk assessment and design of environmentally benign ILs. The objective of this work is to develop QSAR models to describe the minimal inhibitory concentration (MIC) and minimal bactericidal concentration (MBC) of ILs against Staphylococcus aureus (S. aureus). A total of 169 and 101 ILs with MICs and MBCs, respectively, are used to obtain multiple linear regression models based on matrix norm indexes. The norm indexes used in this work are proposed by our research group and they are first applied to estimate the antibacterial toxicity of these ILs against S. aureus. These two models precisely and reliably calculated the IL toxicities with a square of correlation coefficient (R²) of 0.919 and a standard error of estimate (SE) of 0.341 (in log unit of mM) for pMIC, and an R² of 0.913 and SE of 0.282 for pMBC.

Endocrine-disrupting activity of per- and polyfluoroalkyl substances: Exploring combined approaches of ligand and structure based modeling

Exposure to perfluorinated and polyfluoroalkyl substances (PFCs/PFASs), endocrine disrupting halogenated pollutants, has been linked to various diseases including thyroid toxicity in human populations across the globe. PFASs can compete with thyroxine (T4) for binding to the human thyroid hormone transport protein transthyretin (TTR) which may lead to reduce thyroid hormone levels leading to endocrine disrupting adverse effects. Environmental fate and endocrine-disrupting activity of PFASs has initiated several research projects, but the amount of experimental data available for these pollutants is limited. In this study, experimental data for T4-TTR competing potency of 24 PFASs obtained in a radioligand-binding assay were modeled using classification- and regression-based quantitative structure-activity relationship (QSAR) tools with simple molecular descriptors obtained from chemical structure of these compounds in order to identify the responsible structural features and fragments of the studied PFASs for endocrine disruption activity. Additionally, docking studies were performed employing the crystal structure complex of TTR with bound 2', 6'-difluorobiphenyl-4-carboxylic acid (PDB: 2F7I) in order to constitute the receptor model for human TTR. The results corroborate evidence for these binding interactions and indicate multiple high-affinity modes of binding. The developed in silico models therefore advance our understanding of important structural attributes of these chemicals and may provide important information for the design of future synthesis of PFASs as well as may serve as an efficient query tool for virtual screening of large PFAS databases to check their endocrine toxicity profile.

Health risk assessment of exposures to a high molecular weight plasticizer present in automobile interiors

This study provides an exposure and risk assessment of diundecyl phthalate (DUP), a high molecular weight phthalate plasticizer present in automobile interiors. Total daily intake of DUP was calculated from DUP measured in wipe samples from vehicle seats from six automobiles. Four of the vehicles exhibited atypical visible surface residue on the seats. Two vehicles with no visible surface residue were sampled as a comparison. DUP was the predominant organic compound identified in each of the wipes from all seats. A risk assessment of DUP via oral, dermal, and inhalation routes resulting from contact with automobile seats was conducted. The mean, standard deviation, and maximum DUP concentrations on the seats with visible surface residue were 6983 ± 7823 μg/100 cm² and 38300 μg/100 cm², respectively. The mean and 95th percentile of the mean for daily cumulative dose of DUP for all exposure routes for the seats with no visible surface residue ranged from 7 × 10^-4 to 4 × 10^-3 mg/kg-day and from 8 × 10^-4 to 5 × 10^-3 mg/kg-day, respectively. For seats with visible surface residue, cumulative doses ranged from 2 × 10^-3 to 2 × 10^-2 mg/kg-day and from 4 × 10^-3 to 2 × 10^-2 mg/kg-day, respectively. The estimated daily intake (contact or absorbed dose) of DUP from automobile seats were far lower than the NOAELs reported in and derived from animal studies, and are well below the reported Registration, Evaluation, Authorisation and Restriction of Chemicals (REACH) Derived No Effect Levels (DNELs) for the general population. Based on this analysis, using virtually any benchmark for evaluating safety, exposure to DUP via automobile seat covers did not pose a measureable increased health-risk in any population under any reasonably plausible exposure scenario.

Fluid Dynamic Modeling to Support the Development of Flow-Based Hepatocyte Culture Systems for Metabolism Studies

Accurate prediction of metabolism is a significant outstanding challenge in toxicology. The best predictions are based on experimental data from in vitro systems using primary hepatocytes. The predictivity of the primary hepatocyte-based culture systems, however, is still limited due to well-known phenotypic instability and rapid decline of metabolic competence within a few hours. Dynamic flow bioreactors for three-dimensional cell cultures are thought to be better at recapitulating tissue microenvironments and show potential to improve in vivo extrapolations of chemical or drug toxicity based on in vitro test results. These more physiologically relevant culture systems hold potential for extending metabolic competence of primary hepatocyte cultures as well. In this investigation, we used computational fluid dynamics to determine the optimal design of a flow-based hepatocyte culture system for evaluating chemical metabolism in vitro. The main design goals were (1) minimization of shear stress experienced by the cells to maximize viability, (2) rapid establishment of a uniform distribution of test compound in the chamber, and (3) delivery of sufficient oxygen to cells to support aerobic respiration. Two commercially available flow devices – RealBio^® and QuasiVivo^® (QV) – and a custom developed fluidized bed bioreactor were simulated, and turbulence, flow characteristics, test compound distribution, oxygen distribution, and cellular oxygen consumption were analyzed. Experimental results from the bioreactors were used to validate the simulation results. Our results indicate that maintaining adequate oxygen supply is the most important factor to the long-term viability of liver bioreactor cultures. Cell density and system flow patterns were the major determinants of local oxygen concentrations. The experimental results closely corresponded to the in silico predictions. Of the three bioreactors examined in this study, we were able to optimize the experimental conditions for long-term hepatocyte cell culture using the QV bioreactor. This system facilitated the use of low system volumes coupled with higher flow rates. This design supports cellular respiration by increasing oxygen concentrations in the vicinity of the cells and facilitates long-term kinetic studies of low clearance test compounds. These two goals were achieved while simultaneously keeping the shear stress experienced by the cells within acceptable limits.

Integrated decision strategies for skin sensitization hazard

One of the top priorities of the Interagency Coordinating Committee for the Validation of Alternative Methods (ICCVAM) is the identification and evaluation of non-animal alternatives for skin sensitization testing. Although skin sensitization is a complex process, the key biological events of the process have been well characterized in an adverse outcome pathway (AOP) proposed by the Organisation for Economic Co-operation and Development (OECD). Accordingly, ICCVAM is working to develop integrated decision strategies based on the AOP using in vitro, in chemico and in silico information. Data were compiled for 120 substances tested in the murine local lymph node assay (LLNA), direct peptide reactivity assay (DPRA), human cell line activation test (h-CLAT) and KeratinoSens assay. Data for six physicochemical properties, which may affect skin penetration, were also collected, and skin sensitization read-across predictions were performed using OECD QSAR Toolbox. All data were combined into a variety of potential integrated decision strategies to predict LLNA outcomes using a training set of 94 substances and an external test set of 26 substances. Fifty-four models were built using multiple combinations of machine learning approaches and predictor variables. The seven models with the highest accuracy (89-96% for the test set and 96-99% for the training set) for predicting LLNA outcomes used a support vector machine (SVM) approach with different combinations of predictor variables. The performance statistics of the SVM models were higher than any of the non-animal tests alone and higher than simple test battery approaches using these methods. These data suggest that computational approaches are promising tools to effectively integrate data sources to identify potential skin sensitizers without animal testing. Published 2016. This article has been contributed to by US Government employees and their work is in the public domain in the USA.

QSAR modeling for predicting reproductive toxicity of chemicals in rats for regulatory purposes

The experimental determination of multi-generation reproductive toxicity of chemicals involves high costs and a large number of animal studies over a long period of time. Computational toxicology offers possibilities to overcome such difficulties. In this study, we have established ensemble machine learning (EML) based quantitative structure-activity relationship models for predicting the reproductive toxicity potential (LOAEL) of structurally diverse chemicals in accordance with the OECD guidelines. Accordingly, decision tree forest (DTF) and decision tree boost (DTB) QSAR models were developed using a novel dataset composed of the toxicity endpoints for 334 chemicals. Relevant structural features of chemicals responsible for toxicity potential were identified and used in QSAR modeling. The generalization and prediction abilities of the constructed QSAR models were evaluated by internal and external validation procedures and by deriving several stringent statistical criteria parameters. In the test set, the two models (DTF and DTB) yielded R2 of 0.856 and 0.945, between the experimental and predicted endpoint toxicity values. The models were also evaluated for predictive use through the most recent criteria based on root mean squared error (RMSE) and mean absolute error (MAE). The values of various statistical validation coefficients derived for the test data were above their respective threshold limits and thus put a high confidence in this analysis. The applicability domains of the constructed QSAR models were defined using the leverage and standardization approaches. The results suggest that the proposed QSAR models can reliably predict the reproductive toxicity potential of diverse chemicals and can be useful tools for screening new chemicals for safety assessment.

In silico prediction of the developmental toxicity of diverse organic chemicals in rodents for regulatory purposes

The experimental determination of the developmental toxicity potential (LEL) of chemicals is not only tedious, time and resource intensive, but it also involves unethical tests on animals. In this study, we have established quantitative structure activity relationship (QSAR) models for predicting the developmental toxicity potential of chemicals in rodents following the OECD guidelines. Accordingly, decision tree forest (DTF) and decision tree boost (DTB) based local (L-QSAR), global (G-QSAR) and interspecies quantitative structure activity-activity relationship (ISC QSAAR) models were developed for estimating the LEL (lowest effective level) dose of chemicals for developmental toxicity in rats and rabbits. The structural features of chemicals responsible for developmental toxicity in rodents were extracted and used in QSAR/QSAAR analysis. The external predictive power of the developed models was evaluated through the internal and external validation procedures. In test data, the L-QSAR models (DTF, DTB) yielded R2 values of >0.846 (rat) and >0.906 (rabbit), whereas in G-QSAR, the correlation value was >0.870 between the measured and predicted endpoint values. In ISC QSAAR models, the R2 values in test data were 0.830 (DTF) and 0.927 (DTB), respectively. Values of various statistical validation coefficients derived from the test data (except rm2 in DTF based rat L-QSAR and ISC QSAAR models) were above their respective threshold limits, thus putting a high confidence in this analysis. The prediction quality of the developed QSAR/QSAAR models was also assessed using the mean absolute error (MAE) criteria and found good. The applicability domains of the constructed models were defined using the descriptor range, leverage, and standardization approaches. The results suggest that the developed QSAR/QSAAR models can reliably predict the developmental toxicity potential of structurally diverse chemicals in rodents, generating useful toxicity data for risk assessment in humans.

Low potency toxins reveal dense interaction networks in metabolism

BACKGROUND

The chemicals of metabolism are constructed of a small set of atoms and bonds. This may be because chemical structures outside the chemical space in which life operates are incompatible with biochemistry, or because mechanisms to make or utilize such excluded structures has not evolved. In this paper I address the extent to which biochemistry is restricted to a small fraction of the chemical space of possible chemicals, a restricted subset that I call Biochemical Space. I explore evidence that this restriction is at least in part due to selection again specific structures, and suggest a mechanism by which this occurs.

RESULTS

Chemicals that contain structures that our outside Biochemical Space (UnBiological groups) are more likely to be toxic to a wide range of organisms, even though they have no specifically toxic groups and no obvious mechanism of toxicity. This correlation of UnBiological with toxicity is stronger for low potency (millimolar) toxins. I relate this to the observation that most chemicals interact with many biological structures at low millimolar toxicity. I hypothesise that life has to select its components not only to have a specific set of functions but also to avoid interactions with all the other components of life that might degrade their function.

CONCLUSIONS

The chemistry of life has to form a dense, self-consistent network of chemical structures, and cannot easily be arbitrarily extended. The toxicity of arbitrary chemicals is a reflection of the disruption to that network occasioned by trying to insert a chemical into it without also selecting all the other components to tolerate that chemical. This suggests new ways to test for the toxicity of chemicals, and that engineering organisms to make high concentrations of materials such as chemical precursors or fuels may require more substantial engineering than just of the synthetic pathways involved.

Experimental methodology for assessing the environmental fate of organic chemicals in polymer matrices using column leaching studies and OECD 308 water/sediment systems: Application to tire and road wear particles

Automobile tires require functional rubber additives including curing agents and antioxidants, which are potentially environmentally available from tire and road wear particles (TRWP) deposited in soil and sediment. A novel methodology was employed to evaluate the environmental fate of three commonly-used tire chemicals (N-cyclohexylbenzothiazole-2-sulfenamide (CBS), N-(1,3-dimethylbutyl)-N'-phenyl-1,4-phenylenediamine (6-PPD) and 1,3-diphenylguanidine (DPG)), using a road simulator, an artificial weathering chamber, column leaching tests, and OECD 308 sediment/water incubator studies. Environmental release factors were quantified for curing (f(C)), tire wear (f(W)), terrestrial weathering (f(S)), leaching from TRWP (f(L)), and environmental availability from TRWP (f(A)) by liquid chromatography-tandem mass spectroscopy (LC/MS/MS) analyses. Cumulative fractions representing total environmental availability (F(T)) and release to water (FR) were calculated for the tire chemicals and 13 transformation products. F(T) for CBS, DPG and 6-PPD inclusive of transformation products for an accelerated terrestrial aging time in soil of 0.1 years was 0.08, 0.1, and 0.06, respectively (equivalent to 6 to 10% of formulated mass). In contrast, a wider range of 5.5×10(-4) (6-PPD) to 0.06 (CBS) was observed for F(R) at an accelerated age of 0.1 years, reflecting the importance of hydrophobicity and solubility for determining the release to the water phase. Significant differences (p<0.05) in the weathering factor, f(S), were observed when chemicals were categorized by boiling point or hydrolysis rate constant. A significant difference in the leaching factor, f(L), and environmental availability factor, f(A), was also observed when chemicals were categorized by log K(ow). Our methodology should be useful for lifecycle analysis of other functional polymer chemicals.

Short-term fish reproduction assays with methyl tertiary butyl ether with zebrafish and fathead minnow: Implications for evaluation of potential for endocrine activity

The authors report on short-term fish reproduction assays in zebrafish and fathead minnow conducted to examine the potential for methyl tertiary butyl ether (MTBE) to cause effects on the endocrine system. Both studies were performed under good laboratory practice and in accordance with Organisation for Economic Co-operation and Development and US Environmental Protection Agency test guidelines. The results of the first study demonstrated that exposure to a high test concentration (147 mg/L) of MTBE impaired reproductive output of female zebrafish, evident by a reduction in fecundity. Based on the endpoints evaluated in the present study however, there was no supporting evidence to indicate that this effect was caused by disruption of or interaction with the endocrine system. In the second study, fathead minnows exposed to a wider but lower range of test concentrations showed no effects on any reproductive parameter of male or female fish, at the maximum recommended testing concentration of 100 mg/L (62 mg/L measured). The results of these 2 guideline studies indicate that MTBE does not interact with the hypothalamic-pituitary-gonadal axis of zebrafish or fathead minnow.

Predictive QSAR modelling of algal toxicity of ionic liquids and its interspecies correlation with Daphnia toxicity

Predictive toxicology using chemometric tools can be very useful in order to fill the data gaps for ionic liquids (ILs) with limited available experimental toxicity information, in view of their growing industrial uses. Though originally promoted as green chemicals, ILs have now been shown to possess considerable toxicity against different ecological endpoints. Against this background, quantitative structure-activity relationship (QSAR) models have been developed here for the toxicity of ILs against the green algae Scenedesmus vacuolatus using computed descriptors with definite physicochemical meaning. The final models emerged from E-state indices, extended topochemical atom (ETA) indices and quantum topological molecular similarity (QTMS) indices. The developed partial least squares models support the established mechanism of toxicity of ionic liquids in terms of a surfactant action of cations and chaotropic action of anions. The models have been developed within the guidelines of the Organization of Economic Co-operation and Development (OECD) for regulatory QSAR models, and they have been validated both internally and externally using multiple strategies and also tested for applicability domain. A preliminary attempt has also been made, for the first time, to develop interspecies quantitative toxicity-toxicity relationship (QTTR) models for the algal toxicity of ILs with Daphnia toxicity, which should be interesting while predicting toxicity of ILs for an endpoint when the data for the other are available.

Transcriptomic characterization of C57BL/6 mouse embryonic stem cell differentiation and its modulation by developmental toxicants

The Tox21 program calls for transforming toxicology testing from traditional in vivo tests to less expensive and higher throughput in vitro methods. In developmental toxicology, a spectrum of alternative methods including cell line based tests has been developed. In particular, embryonic stem cells (ESCs) have received widespread attention as a promising alternative model for developmental toxicity assessment. Here, we characterized gene expression changes during mouse ESC differentiation and their modulation by developmental toxicants. C57BL/6 ESCs were allowed to differentiate spontaneously and RNA of vehicle controls was collected at 0, 24, 48, 72, 96, 120 and 168 h after embryoid body (EB) formation; RNA of compound-exposed EBs were collected at 24 h. Samples were hybridized to Affymetrix Mouse Gene 2.0 ST Array; using stringent cut-off criteria of Bonferroni-adjusted p<0.05 and fold change >2.0, a total of 1996 genes were found differentially expressed among the vehicle controls at different time points. Gene ontology (GO) analysis showed these regulated genes were mostly involved in differentiation-related processes such as development, morphogenesis, metabolism, cell differentiation, cell organization and biogenesis, embryonic development, and reproduction. Biomarkers of all three germ layers or of their derivative early cell types were identified in the gene list. Principal component analysis (PCA) based on these genes showed that the unexposed vehicle controls appeared in chronological order in the PCA plot, and formed a differentiation track when connected. Cultures exposed to thalidomide, monobutyl phthalate, or valproic acid deviated significantly from the differentiation track, manifesting the capacity of the differentiation track to identify the modulating effects of diverse developmental toxicants. The differentiation track defined in this study may be further exploited as a baseline for developmental toxicity testing, with compounds causing significant deviation from the differentiation track being predicted as potential developmental toxicants.

Reducing aquatic hazards of industrial chemicals: probabilistic assessment of sustainable molecular design guidelines

Basic toxicological information is lacking for the majority of industrial chemicals. In addition to increasing empirical toxicity data through additional testing, prospective computational approaches to drug development aim to serve as a rational basis for the design of chemicals with reduced toxicity. Recent work has resulted in the derivation of a "rule of 2," wherein chemicals with an octanol-water partition coefficient (log P) less than 2 and a difference between the lowest unoccupied molecular orbital and the highest occupied molecular orbital (ΔE) greater than 9 (log P<2 and ΔE >9 eV) are predicted to be 4 to 5 times less likely to elicit acute or chronic toxicity to model aquatic organisms. The present study examines potential reduction of aquatic toxicity hazards from industrial chemicals if these 2 molecular design guidelines were employed. Probabilistic hazard assessment approaches were used to model the likelihood of encountering industrial chemicals exceeding toxicological categories of concern both with and without the rule of 2. Modeling predicted that utilization of these molecular design guidelines for log P and ΔE would appreciably decrease the number of chemicals that would be designated to be of "high" and "very high" concern for acute and chronic toxicity to standard model aquatic organisms and end points as defined by the US Environmental Protection Agency. For example, 14.5% of chemicals were categorized as having high and very high acute toxicity to the fathead minnow model, whereas only 3.3% of chemicals conforming to the design guidelines were predicted to be in these categories. Considerations of specific chemical classes (e.g., aldehydes), chemical attributes (e.g., ionization), and adverse outcome pathways in representative species (e.g., receptor-mediated responses) could be used to derive future property guidelines for broader classes of contaminants.

Brain-derived neurotrophic factor as an indicator of chemical neurotoxicity: an animal-free CNS cell culture model

Recent changes to the legislation on chemicals and cosmetics testing call for a change in the paradigm regarding the current 'whole animal' approach for identifying chemical hazards, including the assessment of potential neurotoxins. Accordingly, since 2004, we have worked on the development of the integrated co-culture of post-mitotic, human-derived neurons and astrocytes (NT2.N/A), for use as an in vitro functional central nervous system (CNS) model. We have used it successfully to investigate indicators of neurotoxicity. For this purpose, we used NT2.N/A cells to examine the effects of acute exposure to a range of test chemicals on the cellular release of brain-derived neurotrophic factor (BDNF). It was demonstrated that the release of this protective neurotrophin into the culture medium (above that of control levels) occurred consistently in response to sub-cytotoxic levels of known neurotoxic, but not non-neurotoxic, chemicals. These increases in BDNF release were quantifiable, statistically significant, and occurred at concentrations below those at which cell death was measureable, which potentially indicates specific neurotoxicity, as opposed to general cytotoxicity. The fact that the BDNF immunoassay is non-invasive, and that NT2.N/A cells retain their functionality for a period of months, may make this system useful for repeated-dose toxicity testing, which is of particular relevance to cosmetics testing without the use of laboratory animals. In addition, the production of NT2.N/A cells without the use of animal products, such as fetal bovine serum, is being explored, to produce a fully-humanised cellular model.

Structure-activity relationship models for rat carcinogenesis and assessing the role mutagens play in model predictivity

We previously demonstrated that fragment based cat-SAR carcinogenesis models consisting solely of mutagenic or non-mutagenic carcinogens varied greatly in terms of their predictive accuracy. This led us to investigate how well the rat cancer cat-SAR model predicted mutagens and non-mutagens in their learning set. Four rat cancer cat-SAR models were developed: Complete Rat, Transgender Rat, Male Rat and Female Rat, with leave-one-out (LOO) validation concordance values of 69%, 74%, 67% and 73%, respectively. The mutagenic carcinogens produced concordance values in the range 69-76% compared with only 47-53% for non-mutagenic carcinogens. As a surrogate for mutagenicity, comparisons between single site and multiple site carcinogen SAR models were analysed. The LOO concordance values for models consisting of 1-site, 2-site and 4+-site carcinogens were 66%, 71% and 79%, respectively. As expected, the proportion of mutagens to non-mutagens also increased, rising from 54% for 1-site to 80% for 4+-site carcinogens. This study demonstrates that mutagenic chemicals, in both SAR learning sets and test sets, are influential in assessing model accuracy. This suggests that SAR models for carcinogens may require a two-step process in which mutagenicity is first determined before carcinogenicity can be accurately predicted.

Analysis of the ecotoxicity data submitted within the framework of the REACH Regulation. Part 2. Experimental aquatic toxicity assays

This paper summarises the aquatic ecotoxicity data submitted in the REACH(1) registration dossiers and disseminated by the European Chemicals Agency (ECHA(2)). The analysis describes both the guidelines and the species mostly used by registrants. Non-OECD guidelines have been extensively used, in particular in covering of fish and aquatic invertebrate studies, but the main concern is that in 22-36% of the cases, depending on the endpoint, no information on the methodological approach and potential equivalences to test guidelines has been provided. As expected, most studies were conducted with those species typically used in laboratory ecotoxicity testing; nevertheless, the database provides a broad range of available species, covering the most relevant taxonomic groups for both freshwater and marine systems, although most are just occasionally used. This species diversity is essential for higher tier testing strategies, including the use of Species Sensitivity Distribution approaches. The assessment suggests that collecting available information has been the main approach used by registrants to fulfil their REACH information requirements for this first REACH registration deadline. Many studies are disclosed for the first time, and all are available through searchable web tools.

Modeling bioconcentration factor (BCF) using mechanistically interpretable descriptors computed from open source tool "PaDEL-Descriptor"

Predictive regression-based models for bioconcentration factor (BCF) have been developed using mechanistically interpretable descriptors computed from open source tool PaDEL-Descriptor ( http://padel.nus.edu.sg/software/padeldescriptor/ ). A data set of 522 diverse chemicals has been used for this modeling study, and extended topochemical atom (ETA) indices developed by the present authors' group were chosen as the descriptors. Due to the importance of lipohilicity in modeling BCF, XLogP (computed partition coefficient) was also tried as an additional descriptor. Genetic function approximation followed by multiple linear regression algorithm was applied to select descriptors, and subsequent partial least squares analyses were performed to establish mathematical equations for BCF prediction. The model generated from only ETA indices shows importance of seven descriptors in model development, while the model generated from ETA descriptors along with XlogP shows importance of four descriptors in model development. In general, BCF depends on lipophilicity, presence of heteroatoms, presence of halogens, fused ring system, hydrogen bonding groups, etc. The developed models show excellent statistical qualities and predictive ability. The developed models were used also for prediction of an external data set available from the literature, and good quality of predictions (R (2) pred = 0.812 and 0.826) was demonstrated. Thus, BCF can be predicted using ETA and XlogP descriptors calculated from open source PaDEL-Descriptor software in the context of aquatic chemical toxicity management.

Stem cells and stem cell-derived tissues and their use in safety assessment

Toxicology has long relied on animal models in a tedious approach to understanding risk of exposure to an uncharacterized molecule. Stem cell-derived tissues can be made in high purity, quality, and quantity to enable a new approach to this problem. Currently, stem cell-derived tissues are primarily "generic" genetic backgrounds; the future will see the integration of various genetic backgrounds and complex three-dimensional models to create truly unique in vitro organoids. This minireview focuses on the state of the art of a number of stem cell-derived tissues and details their application in toxicology.