Perspectives for integrating human and environmental risk assessment and synergies with socio-economic analysis

Nanotechnology in sustainable agriculture: A double-edged sword

Nanotechnology is a rapidly developing discipline that has the potential to transform the way we approach problems in a variety of fields, including agriculture. The use of nanotechnology in sustainable agriculture has gained popularity in recent years. It has various applications in agriculture, such as the development of nanoscale materials and devices to boost agricultural productivity, enhance food quality and safety, improve the efficiency of water and nutrient usage, and reduce environmental pollution. Nanotechnology has proven to be very beneficial in this field, particularly in the development of nanoscale delivery systems for agrochemicals such as pesticides, fertilizers, and growth regulators. These nanoscale delivery technologies offer various benefits over conventional delivery systems, including better penetration and distribution, enhanced efficacy, and lower environmental impact. Encapsulating agrochemicals in nanoscale particles enables direct delivery to the targeted site in the plant, thereby reducing waste and minimizing off-target effects. Plants are fundamental building blocks of all ecosystems and evaluating the interaction between nanoparticles (NPs) and plants is a crucial aspect of risk assessment. This critical review therefore aims to provide an overview of the latest advances regarding the positive and negative effects of nanotechnology in agriculture. It also explores potential future research directions focused on ensuring the safe utilization of NPs in this field, which could lead to sustainable development. © 2024 Society of Chemical Industry.

Community Health Impacts From Natural Gas Pipeline Compressor Stations

Compressor stations maintain pressure along natural gas pipelines to sustain gas flow. Unfortunately, they present human health concerns as they release chemical pollutants into the air, sometimes at levels higher than national air quality standards. Further, compressor stations are often placed in rural areas with higher levels of poverty and/or minority populations, contributing to environmental justice concerns. In this paper we investigate what chemical pollutants are emitted by compressor stations, the impacts of emitted pollutants on human health, and local community impacts. Based on the information gained from these examinations, we provide the following policy recommendations with the goal of minimizing harm to those affected by natural gas compressor stations: the Environmental Protection Agency (EPA) and relevant state agencies must increase air quality monitoring and data transparency; the EPA should direct more resources to monitoring programs specifically at compressor stations; the EPA should provide free indoor air quality monitoring to homes near compressor stations; the EPA needs to adjust its National Ambient Air Quality Standards to better protect communities and assess cumulative impacts; and decision-makers at all levels must pursue meaningful involvement from potentially affected communities. We find there is substantial evidence of negative impacts to strongly support these recommendations.

Environmental health and risk assessment metrics with special mention to biotransfer, bioaccumulation and biomagnification of environmental pollutants

The environment pollutants, which are landed up in environment because of human activities like urbanization, mining and industrializations, affects human health, plants and animals. The living organisms present in environment are constantly affected by the toxic pollutants through direct contact or bioaccumulation of chemicals from the environment. The toxic and hazardous pollutants are easily transferred to different environmental matrices like land, air and water bodies such as surface and ground waters. This comprehensive review deeply discusses the routes and causes of different environmental pollutants along with their toxicity, impact, occurrences and fate in the environment. Environment health and risk assessment tools that are used to evaluate the harmfulness, exposure of living organisms to pollutants and the amount of pollutant accumulated are explained with help of bio-kinetic models. Biotransfer, toxicity factor, biomagnification and bioaccumulation of different pollutants in the air, water and marine ecosystems are critically addressed. Thus, the presented survey would be collection of correlations those addresses the factors involved in assessing the environmental health and risk impacts of distinct environmental pollutants.

Integrative artificial intelligence models for Australian coastal sediment lead prediction: An investigation of in-situ measurements and meteorological parameters effects

Heavy metals (HMs) such as Lead (Pb) have played a vital role in increasing the sediments of the Australian bay's ecosystem. Several meteorological parameters (i.e., minimum, maximum and average temperature (T_min, T_max and T_avg^oC), rainfall (R_n mm) and their interactions with the other batch HMs, are hypothesized to have high impact for the decision-making strategies to minimize the impacts of Pb. Three feature selection (FS) algorithms namely the Boruta method, genetic algorithm (GA) and extreme gradient boosting (XGBoost) were investigated to select the highly important predictors for Pb concentration in the coastal bay sediments of Australia. These FS algorithms were statistically evaluated using principal component analysis (PCA) Biplot along with the correlation metrics describing the statistical characteristics that exist in the input and output parameter space of the models. To ensure a high accuracy attained by the applied predictive artificial intelligence (AI) models i.e., XGBoost, support vector machine (SVM) and random forest (RF), an auto-hyper-parameter tuning process using a Grid-search approach was also implemented. Cu, Ni, Ce, and Fe were selected by all the three applied FS algorithms whereas the T_avg and R_n inputs remained the essential parameters identified by GA and Boruta. The order of the FS outcome was XGBoost > GA > Boruta based on the applied statistical examination and the PCA Biplot results and the order of applied AI predictive models was XGBoost-SVM > GA-SVM > Boruta-SVM, where the SVM model remained at the top performance among the other statistical metrics. Based on the Taylor diagram for model evaluation, the RF model was reflected only marginally different so overall, the proposed integrative AI model provided an evidence a robust and reliable predictive technique used for coastal sediment Pb prediction.

Costs and benefits of recycling PVC contaminated with the legacy hazardous plasticizer DEHP

Reusing materials is an attractive option for circular economy and can also reduce emissions of greenhouse gases and pollutants. However, recycling raises questions regarding the potential risks to human health or the environment when hazardous legacy chemical additives of materials are also recycled, instead of the recent and less hazardous additives of virgin materials. To address this trade-off, this study developed a model to calculate the total external cost of material supply, considering the health and environmental impacts of all industrial steps (e.g. virgin material production, incineration, and recycling), and the health effects of recycling chemicals present in the material. The model is coupling material flow analysis, life-cycle analysis, and environmental economics to compare different recycling policies. It is applied for all illustrative purposes to soft PVC and DEHP in France. Results show that recycling of materials is in the long-term positive despite the prolongation of the presence of hazardous additives in materials. The time when the recurring environmental benefits of recycling offset the negative impacts on human health of recycling the additives is very sensitive to the health impact of additives. This approach can improve the harmonization between recycling and circular economy policies, and as a framework to confirm the relevance and size treatments to remove additives from materials during recycling.

Quantifying and predicting ecological and human health risks for binary heavy metal pollution accidents at the watershed scale using Bayesian Networks

The accidental leakage of industrial wastewater containing heavy metals from enterprises poses great risks to resident health, social instability, and ecological safety. During 2005-2018, heavy metal mixed pollution accidents comprised approximately 33% of the major environmental ones in China. A Bayesian Networks-based probabilistic approach is developed to quantitatively predict ecological and human health risks for heavy metal mixed pollution accidents at the watershed scale. To estimate the probability distributions of joint ecological exposure once a heavy metal mixed pollution accident occurs, a Copula-based joint exposure calculation method, comprised of a hydro-dynamic model, emergent heavy metal pollution transport model, and the Copula functions, is embedded. This approach was applied to the risk assessment of acute Cr⁶⁺-Hg²⁺ mixed pollution accidents at 76 electroplating enterprises in 24 risk sub-watersheds of the Dongjiang River downstream watershed. The results indicated that nine sub-watersheds created high ecological risks, while only five created high human health risks. In addition, the ecological and human health risk levels were highest in the tributary (the Xizhijiang River), while the ecological risk was more critical in the river network, and the human health risk was more serious in the mainstream of the Dongjiang River. The quantitative risk assessment provides a substantial support to incident prevention and control, risk management, as well as regulatory decision making for electroplating enterprises.

Ecological risk assessment of current-use pesticides in an aquatic system of Shanghai, China

The widespread use of current-use pesticides (CUPs) in modern agriculture has threatened the survival of aquatic organisms. Therefore, the residual levels, spatial distribution, and ecological risk assessment of 18 CUPs are investigated in an aquatic system of Shanghai. The aquatic system focused on a freshwater system that contains particles smaller than 0.45 μm in size, which are easily absorbed by aquatic organisms. The mean values of chlorpyrifos, napropamide, and atrazine were found to be the highest concentration CUPs, and propazine, mevinphos, ametryn, butylate, dichlorvos, ethoprop, and prometryn displayed the most significant positive correlations with each other. The concentration of the ∑₁₈CUPs was higher in the southern areas of Shanghai (generally greater than 100 ng/L), but it was relatively low in the central areas (generally smaller than 75 ng/L). Six important CUPs were identified, and the differences in the concentration contribution rates and contribution amounts among different intensive land-use types were noticeable. The ecological risk in most areas of this aquatic system of Shanghai was high. Chlorpyrifos and butachlor produced the maximum toxic unit (mTU) for daphnid and green algae, respectively, and their toxic unit contribution rates to the entire mixture toxicity were both greater than 50%. This confirms that the mixture toxicity of the CUPs to aquatic organisms in this aquatic system of Shanghai primarily resulted from a few dominant toxic pesticides. However, for each sensitive organism, there will still be a risk contribution of approximately 5%-30% due to other CUPs.

Aquatic ecological risk assessment frameworks in Canada: a case study using a single framework in South Baymouth, Ontario, Canada

Ecological risk assessment (ERA) is used to determine potential effect of human activities and industries on the natural environment. Numerous ERA management approaches exist and vary based on jurisdiction or ecological media. This ERA focused on contaminants within an aquatic ecosystem in sediments and surface water at South Baymouth port facility in Ontario, Canada. Contaminants were evaluated using the Canada-Ontario Decision-Making Framework for Assessment of Great Lakes Contaminated Sediments (COA). Following COA, this study (1) examined historical data from South Baymouth to determine contaminants of potential concern, (2) delineated potential contamination by comparing sediment and surface water concentration data to sediment quality guidelines and water quality guidelines from Canada and from different jurisdictions if Canadian guidelines were unavailable, (3) compared sediment concentrations to reference concentrations, and (4) developed an ERA decision matrix (used to inform management decisions at this aquatic site). Although sediments exhibited negligible potential for ecological risk and required no remedial management action, this case study highlights strengths of using COA for this ERA which included use of iterative and consistent approaches, but also highlights weaknesses which included unclear linkages between cause and effects of aquatic contaminants. Recommendations for future ERAs at contaminated aquatic sites include use of passive samplers and incorporating recent macroecology techniques.

Vision of a near future: Bridging the human health-environment divide. Toward an integrated strategy to understand mechanisms across species for chemical safety assessment

There is a growing recognition that application of mechanistic approaches to understand cross-species shared molecular targets and pathway conservation in the context of hazard characterization, provide significant opportunities in risk assessment (RA) for both human health and environmental safety. Specifically, it has been recognized that a more comprehensive and reliable understanding of similarities and differences in biological pathways across a variety of species will better enable cross-species extrapolation of potential adverse toxicological effects. Ultimately, this would also advance the generation and use of mechanistic data for both human health and environmental RA. A workshop brought together representatives from industry, academia and government to discuss how to improve the use of existing data, and to generate new NAMs data to derive better mechanistic understanding between humans and environmentally-relevant species, ultimately resulting in holistic chemical safety decisions. Thanks to a thorough dialogue among all participants, key challenges, current gaps and research needs were identified, and potential solutions proposed. This discussion highlighted the common objective to progress toward more predictive, mechanistically based, data-driven and animal-free chemical safety assessments. Overall, the participants recognized that there is no single approach which would provide all the answers for bridging the gap between mechanism-based human health and environmental RA, but acknowledged we now have the incentive, tools and data availability to address this concept, maximizing the potential for improvements in both human health and environmental RA.

Role of Physiologically Based Kinetic modelling in addressing environmental chemical mixtures - A review

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The availability and applicability of Physiologically Based Kinetic (PBK) models for mixtures is reviewed.

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PBK models can support risk assessment of mixtures by incorporating the toxicokinetic processes.

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Quantitative structure-activity relationship (QSAR) models can be used to fill data gaps in PBK modelling.

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PBK models for mixtures can be improved by including various types of interactions.

The role of Physiologically Based Kinetic (PBK) modelling in assessing mixture toxicology has been growing for the last three decades. It has been widely used to investigate and address interactions in mixtures. This review describes the current state-of-the-art of PBK models for chemical mixtures and to evaluate the applications of PBK modelling for mixtures with emphasis on their role in chemical risk assessment. A total of 35 mixture PBK models were included after searching web resources (Scopus, PubMed, Web of Science, and Google Scholar), screening for duplicates, and excluding articles based on eligibility criteria. Binary mixtures and volatile organic compounds accounted for two-thirds of the chemical mixtures identified. The most common exposure route and modelled system were found to be inhalation and rats respectively. Twenty two (22) models were for binary mixtures, 5 for ternary mixtures, 3 for quaternary mixtures, and 5 for complex mixtures. Both bottom-up and top-down PBK modelling approaches are described. Whereas bottom-up approaches are based on a series of binary interactions, top-down approaches are based on the lumping of mixture components. Competitive inhibition is the most common type of interaction among the various types of mixtures, and usually becomes a concern at concentrations higher than environmental exposure levels. It leads to reduced biotransformation that either means a decrease in the amount of toxic metabolite formation or an increase in toxic parent chemical accumulation. The consequence is either lower or higher toxicity compared to that estimated for the mixture based on the additivity principle. Therefore, PBK modelling can play a central role in predicting interactions in chemical mixture risk assessment.

Environmental hazard and risk assessment of thiochemicals. Application of integrated testing and intelligent assessment strategies (ITS) to fulfil the REACH requirements for aquatic toxicity

REACH requires information on hazardous properties of substances to be generated avoiding animal testing where possible. It is the objective of the present case study with thiochemicals to extract as much information as possible from available experimental data with fish, daphnia and algae and to fill data gaps for analogues to be registered under REACH in 2018. Based on considerations of chemical similarity and common mode of action (MOA) the data gaps regarding the aquatic toxicity of the thiochemicals were largely closed by trend analysis ("category approach") and read-across within the same group, for example, thioglycolates or mercaptopropionates. Among 16 thiochemicals to be registered by 2018 there are only 2 substances with sufficient data. 36 data gaps for 14 thiochemicals were identified. Most of the required data (>60%) could be estimated by in silico methods. Only 14 tests (6 algae, 6 daphnia, 1 limit fish test and 1 acute fish test) were proposed. When the results of these tests are available it has to be discussed whether 2 further fish (limit) tests are required. For two substances (exposure-based) waiving was suggested. The relatively high toxicity of the thiochemicals is manifested in low predicted no-effect concentrations (PNECs). Only preliminary predicted environmental concentrations (PECs) could be derived for the thiochemicals for which a risk assessment has to be performed (production rate >10 t/y). The preliminary PEC/PNEC ratios indicate no risk for the aquatic compartment at the production site. PECs due to down-stream use must not exceed the estimated PNECs.

Mapping Exposure to Multi-Pollutants Using Environmental Biomonitors-A Multi-Exposure Index

Atmosphere is a major pathway for transport and deposition of pollutants in the environment. In industrial areas, organic compounds are released or formed as by-products, such as polychlorinated dibenzo-p-dioxins and dibenzofurans (PCDD/F's). Inorganic chemical elements, including lead and arsenic, are also part of the pollutants mixture, and even in low concentrations may potentially be toxic and carcinogenic. However, assessing the spatial pattern of their deposition is difficult due to high spatial and temporal heterogeneity. Lichens have been used as biomonitors of atmospheric deposition, because these organisms encompass greater spatial detail than air monitoring stations and provide an integration of overall pollution. Based upon the ability of lichens to concentrate pollutants such as PCDD/F and chemical elements, the main objectives of this study were to develop a new semi-quantitative multi-pollutant toxicity exposure index (TEQ-like), derived from risk estimates, in an attempt to correlate several atmospheric pollutants to human exposure levels. The actual pollutant concentrations were measured in the environment, from biomonitors (organisms that integrate multi-pollutants), enabling interpolation and mapping of contaminant deposition within the region. Thus, the TEQ-like index provides a spatial representation not from absolute accumulation of the different pollutants, but from the accumulation weighted by their relative risk. The assessment of environmental human exposure to multi-pollutants through atmospheric deposition may be applied to industries to improve mitigation processes or to health stakeholders to target populations for a comprehensive risk assessment, epidemiological studies, and health recommendations.

Chemical alternatives assessment of different flame retardants - A case study including multi-walled carbon nanotubes as synergist

Flame retardants (FRs) are a diverse group of chemicals used as additives in a wide range of products to inhibit, suppress, or delay ignition and to prevent the spread of fire. Halogenated FRs (HFRs) are widely used because of their low impact on other material properties and the low loading levels necessary to meet the required flame retardancy. Health and environmental hazards associated with some halogenated FRs have driven research for identifying safer alternatives. A variety of halogen-free FRs are available on the market, including organic (phosphorus and nitrogen based chemicals) and inorganic (metals) materials. Multi-walled carbon nanotubes (MWCNT) have been demonstrated to act as an effective/synergistic co-additive in some FR applications and could thereby contribute to reducing the loading of FRs in products and improving their performance. As part of the FP7 project DEROCA we carried out a chemical alternatives assessment (CAA). This is a methodology for identifying, comparing and selecting safer alternatives to chemicals of concern based on criteria for categorising human and environmental toxicity as well as environmental fate. In the project we assessed the hazard data of different halogen-free FRs to be applied in 5 industrial and consumer products and here we present the results for MWCNT, aluminium diethylphosphinate, aluminium trihydroxide, N-alkoxy hindered amines and red phosphorus compared to the HFR decabromodiphenylether. We consulted the REACH guidance, the criteria of the U.S.-EPA Design for Environment (DfE) and the GreenScreen® Assessment to assess and compare intrinsic properties affecting the hazard potential. A comparison/ranking of exposure reference values such as Derived No Effect Levels (DNELs) showed that FRs of concern are not identified by a low DNEL. A comparison based on hazard designations according to the U.S.-EPA DfE and GreenScreen® for human health endpoints, aquatic toxicity and environmental fate showed that the major differences between FRs of concern and their proposed alternatives are the potential for bioaccumulation and CMR (carcinogenic, mutagenic or reprotoxic) effects. As most alternatives are inorganic chemicals, persistence (alone) is not a suitable criterion. From our experiences in carrying out a CAA we conclude: i) REACH registration dossiers provide a comprehensive source of hazard information for an alternative assessment. It is important to consider that the presented data is subject to changes and its quality is variable. ii) Correct identification of the chemicals is crucial to retrieve the right data. This can be challenging for mixtures, reaction products or nanomaterials or when only trade names are available. iii) The quality of the data and the practice on how to fill data gaps can have a huge impact on the results and conclusions. iv) Current assessment criteria have mainly been developed for organic chemicals and create challenges when applied to inorganic solids, including nanomaterials. It is therefore crucial to analyse and report uncertainties for each decision making step.

Combined ecotoxicological risk assessment in the frame of European authorization of pesticides

Organisms are frequently exposed to mixtures of chemical contaminants in the environment, causing a potential "cocktail effect", or combined effect. The joint action of different molecules with similar or different modes of action could result in a potentially unlimited number of additives, synergistic or antagonistic combinations. Since the large number of contaminants makes it impossible to perform ecotoxicity tests for each potential mixture, a robust approach for prospective environmental risk assessment of chemical mixtures is needed. A number of recent publications by the European Commission and the authorities in charge prove the increasing interest that is spreading in the European community towards the topic of the assessment of chemical mixtures. The current EU regulation for Plant Protection Products authorization (Reg. 1107/2009 EC) explicitly requires the evaluation of the potential combined effects of active substances. We reviewed current methods and limitations of mixture assessment of pesticides (7 fungicides and 4 herbicides) through the analysis of the approaches adopted to investigate possible risks for different non-target organisms. The Concentration Addition (CA) approach was the most used approach to predict multiple toxicity to non-target organisms. The guidance for birds and mammals first introduced standard procedures to assess the multiple toxicity based on on CA concept. The recent aquatic EFSA guidance introduced some requirements to evaluate potential mixture toxicity, while the current guidance requirements for terrestrial organisms still lack clear indications on how to conduct the assessment. Moreover, new indications come from the draft guidance for the assessment of terrestrial plants and in-soil organisms. However, the approval and implementation of these new guidelines are still at a developmental stage. Some final considerations are drawn on the future possibilities to improve risk assessment procedures so as to identify harmful effects of pesticides mixtures on non-target organisms.

Toxicokinetic models and related tools in environmental risk assessment of chemicals

Environmental risk assessment of chemicals for the protection of ecosystems integrity is a key regulatory and scientific research field which is undergoing constant development in modelling approaches and harmonisation with human risk assessment. This review focuses on state-of-the-art toxicokinetic tools and models that have been applied to terrestrial and aquatic species relevant to environmental risk assessment of chemicals. Both empirical and mechanistic toxicokinetic models are discussed using the results of extensive literature searches together with tools and software for their calibration and an overview of applications in environmental risk assessment. These include simple tools such as one-compartment models, multi-compartment models to physiologically-based toxicokinetic (PBTK) models, mostly available for aquatic species such as fish species and a number of chemical classes including plant protection products, metals, persistent organic pollutants, nanoparticles. Data gaps and further research needs are highlighted.

Perspectives for integrating human and environmental exposure assessments

Integrated Risk Assessment (IRA) has been defined by the EU FP7 HEROIC Coordination action as "the mutual exploitation of Environmental Risk Assessment for Human Health Risk Assessment and vice versa in order to coherently and more efficiently characterize an overall risk to humans and the environment for better informing the risk analysis process" (Wilks et al., 2015). Since exposure assessment and hazard characterization are the pillars of risk assessment, integrating Environmental Exposure assessment (EEA) and Human Exposure assessment (HEA) is a major component of an IRA framework. EEA and HEA typically pursue different targets, protection goals and timeframe. However, human and wildlife species also share the same environment and they similarly inhale air and ingest water and food through often similar overlapping pathways of exposure. Fate models used in EEA and HEA to predict the chemicals distribution among physical and biological media are essentially based on common properties of chemicals, and internal concentration estimations are largely based on inter-species (i.e. biota-to-human) extrapolations. Also, both EEA and HEA are challenged by increasing scientific complexity and resources constraints. Altogether, these points create the need for a better exploitation of all currently existing data, experimental approaches and modeling tools and it is assumed that a more integrated approach of both EEA and HEA may be part of the solution. Based on the outcome of an Expert Workshop on Extrapolations in Integrated Exposure Assessment organized by the HEROIC project in January 2014, this paper identifies perspectives and recommendations to better harmonize and extrapolate exposure assessment data, models and methods between Human Health and Environmental Risk Assessments to support the further development and promotion of the concept of IRA. Ultimately, these recommendations may feed into guidance showing when and how to apply IRA in the regulatory decision-making process for chemicals.

A critical review of frameworks used for evaluating reliability and relevance of (eco)toxicity data: Perspectives for an integrated eco-human decision-making framework

Considerable efforts have been invested so far to evaluate and rank the quality and relevance of (eco)toxicity data for their use in regulatory risk assessment to assess chemical hazards. Many frameworks have been developed to improve robustness and transparency in the evaluation of reliability and relevance of individual tests, but these frameworks typically focus on either environmental risk assessment (ERA) or human health risk assessment (HHRA), and there is little cross talk between them. There is a need to develop a common approach that would support a more consistent, transparent and robust evaluation and weighting of the evidence across ERA and HHRA. This paper explores the applicability of existing Data Quality Assessment (DQA) frameworks for integrating environmental toxicity hazard data into human health assessments and vice versa. We performed a comparative analysis of the strengths and weaknesses of eleven frameworks for evaluating reliability and/or relevance of toxicity and ecotoxicity hazard data. We found that a frequent shortcoming is the lack of a clear separation between reliability and relevance criteria. A further gaps and needs analysis revealed that none of the reviewed frameworks satisfy the needs of a common eco-human DQA system. Based on our analysis, some key characteristics, perspectives and recommendations are identified and discussed for building a common DQA system as part of a future integrated eco-human decision-making framework. This work lays the basis for developing a common DQA system to support the further development and promotion of Integrated Risk Assessment.

Chemical and Hormonal Effects on STAT5b-Dependent Sexual Dimorphism of the Liver Transcriptome

The growth hormone (GH)-activated transcription factor signal transducer and activator of transcription 5b (STAT5b) is a key regulator of sexually dimorphic gene expression in the liver. Suppression of hepatic STAT5b signaling is associated with lipid metabolic dysfunction leading to steatosis and liver cancer. In the companion publication, a STAT5b biomarker gene set was identified and used in a rank-based test to predict both increases and decreases in liver STAT5b activation status/function with high (≥ 97%) accuracy. Here, this computational approach was used to identify chemicals and hormones that activate (masculinize) or suppress (feminize) STAT5b function in a large, annotated mouse liver and primary hepatocyte gene expression compendium. Exposure to dihydrotestosterone and thyroid hormone caused liver masculinization, whereas glucocorticoids, fibroblast growth factor 15, and angiotensin II caused liver feminization. In mouse models of diabetes and obesity, liver feminization was consistently observed and was at least partially reversed by leptin or resveratrol exposure. Chemical-induced feminization of male mouse liver gene expression profiles was a relatively frequent phenomenon: of 156 gene expression biosets from chemically-treated male mice, 29% showed feminization of liver STAT5b function, while <1% showed masculinization. Most (93%) of the biosets that exhibited feminization of male liver were also associated with activation of one or more xenobiotic-responsive receptors, most commonly constitutive activated receptor (CAR) or peroxisome proliferator-activated receptor alpha (PPARα). Feminization was consistently associated with increased expression of peroxisome proliferator-activated receptor gamma (Pparg) but not other lipogenic transcription factors linked to steatosis. GH-activated STAT5b signaling in mouse liver is thus commonly altered by diverse chemicals, and provides a linkage between chemical exposure and dysregulated gene expression associated with adverse effects on the liver.

Stakeholder consultations and opportunities for integrating socio-behavioural factors into the pesticide risk analysis process

The pesticide risk analysis process is well regulated in the EU, especially in relation to placing on the market authorisation procedures, but in order to avoid risks for human health and environment in the use phase, information on how these substances are employed and on socio-behavioural factors that can influence the exposure have to be taken into account. To better explore reasons about the gap between risk assessment and risk management, within the EU FP7 Health and Environmental Risks: Organisation, Integration and Cross-fertilisation of Scientific Knowledge (HEROIC) project, a stepwise stakeholder's consultation process was developed using a mixed approach in two different phases (survey and roundtable). We elicited stakeholder views regarding factors that could limit the pesticide risk assessment phase linked on how the knowledge is produced and the way the data are used in risk management and in risk communication, also taking into account qualitative factors such as responsibility, trust and behaviours, which could have impact on risk assessment policies. Activities deployed indicate that some changes and interaction are needed to better define the problems at the formulation stage, and the type of information risk assessor has to provide, to better inform risk manager in addressing different societal needs, to strengthen the credibility of the process of risk assessment and improve the effectiveness of policies. Integrations between disciplines may initially increase the complexity but in turn will provide a better and more useful estimation of the risk, reinforce transparency and drive a more efficient use of risk management resources.

Investigation of the Verhaar scheme for predicting acute aquatic toxicity: improving predictions obtained from Toxtree ver. 2.6

Assessment of the potential of compounds to cause harm to the aquatic environment is an integral part of the REACH legislation. To reduce the number of vertebrate and invertebrate animals required for this analysis alternative approaches have been promoted. Category formation and read-across have been applied widely to predict toxicity. A key approach to grouping for environmental toxicity is the Verhaar scheme which uses rules to classify compounds into one of four mechanistic categories. These categories provide a mechanistic basis for grouping and any further predictive modelling. A computational implementation of the Verhaar scheme is available in Toxtree v2.6. The work presented herein demonstrates how modifications to the implementation of Verhaar between version 1.5 and 2.6 of Toxtree have improved performance by reducing the number of incorrectly classified compounds. However, for the datasets used in this analysis, version 2.6 classifies more compounds as outside of the domain of the model. Further amendments to the classification rules have been implemented here using a post-processing filter encoded as a KNIME workflow. This results in fewer compounds being classified as outside of the model domain, further improving the predictivity of the scheme. The utility of the modification described herein is demonstrated through building quality, mechanism-specific Quantitative Structure Activity Relationship (QSAR) models for the compounds within specific mechanistic categories.

Screening a mouse liver gene expression compendium identifies modulators of the aryl hydrocarbon receptor (AhR)

The aryl hydrocarbon receptor (AhR) is a ligand-activated transcription factor that mediates the biological and toxic effects of 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), dioxin-like compounds (DLC) as well as some drugs and endogenous tryptophan metabolites. Short-term activation of AhR can lead to hepatocellular steatosis, and chronic activation can lead to liver cancer in mice and rats. Analytical approaches were developed to identify biosets in a genomic database in which AhR activity was altered. A set of 63 genes was identified (the AhR gene expression biomarker) that was dependent on AhR for regulation after exposure to TCDD or benzo[a]pyrene and includes the known AhR targets Cyp1a1 and Cyp1b1. A fold-change rank-based test (Running Fisher's test; p-value ≤ 10(-4)) was used to evaluate the similarity between the AhR biomarker and a test set of 37 and 41 biosets positive or negative, respectively for AhR activation. The test resulted in a balanced accuracy of 95%. The rank-based test was used to identify factors that activate or suppress AhR in an annotated mouse liver/mouse primary hepatocyte gene expression database of ∼ 1850 comparisons. In addition to the expected activation of AhR by TCDD and DLC, AhR was activated by AP20189 and phenformin. AhR was suppressed by phenobarbital and 1,4-Bis[2-(3,5-dichloropyridyloxy)] benzene (TCPOBOP) in a constitutive activated receptor (CAR)-dependent manner and pregnenolone-16α-carbonitrile in a pregnane X receptor (PXR)-dependent manner. Inactivation of individual genes in nullizygous models led to AhR activation (Pxr, Ghrhr, Taf10) or suppression (Ahr, Ilst6st, Hnf1a). This study describes a novel screening strategy for identifying factors in mouse liver that perturb AhR in a gene expression compendium.

White paper on the promotion of an integrated risk assessment concept in European regulatory frameworks for chemicals

The vision of a sustainable and safe use of chemicals to protect human health, preserve the environment and maintain the ecosystem requires innovative and more holistic approaches to risk assessment (RA) in order to better inform decision making. Integrated risk assessment (IRA) has been proposed as a solution to current scientific, societal and policy needs. It is defined as the mutual exploitation of environmental risk assessment (ERA) for human health risk assessment (HHRA) and vice versa in order to coherently and more efficiently characterize an overall risk to humans and the environment for better informing the risk analysis process. Extrapolating between species which are relevant for HHRA and ERA requires a detailed understanding of pathways of toxicity/modes of action (MoA) for the various toxicological endpoints. Significant scientific advances, changes in chemical legislation, and increasing environmental consciousness have created a favourable scientific and regulatory environment to develop and promote the concept and vision of IRA. An initial proof of concept is needed to foster the incorporation of IRA approaches into different chemical sectorial regulations and demonstrate their reliability for regulatory purposes. More familiarity and confidence with IRA will ultimately contribute to an overall reduction in in vivo toxicity testing requirements. However, significant progress will only be made if long-term support for MoA-related research is secured. In the short term, further exchange and harmonization of RA terminology, models and methodologies across chemical categories and regulatory agencies will support these efforts. Since societal values, public perceptions and cultural factors are of increasing importance for the acceptance of risk analysis and successful implementation of risk mitigation measures, the integration of socio-economic analysis and socio-behavioural considerations into the risk analysis process may help to produce a more effective risk evaluation and consideration of the risks and benefits associated with the use of chemicals.

Identification of chemical modulators of the constitutive activated receptor (CAR) in a gene expression compendium

The nuclear receptor family member constitutive activated receptor (CAR) is activated by structurally diverse drugs and environmentally-relevant chemicals leading to transcriptional regulation of genes involved in xenobiotic metabolism and transport. Chronic activation of CAR increases liver cancer incidence in rodents, whereas suppression of CAR can lead to steatosis and insulin insensitivity. Here, analytical methods were developed to screen for chemical treatments in a gene expression compendium that lead to alteration of CAR activity. A gene expression biomarker signature of 83 CAR-dependent genes was identified using microarray profiles from the livers of wild-type and CAR-null mice after exposure to three structurally-diverse CAR activators (CITCO, phenobarbital, TCPOBOP). A rank-based algorithm (Running Fisher’s algorithm (p-value ≤ 10^-4)) was used to evaluate the similarity between the CAR biomarker signature and a test set of 28 and 32 comparisons positive or negative, respectively, for CAR activation; the test resulted in a balanced accuracy of 97%. The biomarker signature was used to identify chemicals that activate or suppress CAR in an annotated mouse liver/primary hepatocyte gene expression database of ~1850 comparisons. CAR was activated by 1) activators of the aryl hydrocarbon receptor (AhR) in wild-type but not AhR-null mice, 2) pregnane X receptor (PXR) activators in wild-type and to lesser extents in PXR-null mice, and 3) activators of PPARα in wild-type and PPARα-null mice. CAR was consistently activated by five conazole fungicides and four perfluorinated compounds. Comparison of effects in wild-type and CAR-null mice showed that the fungicide propiconazole increased liver weight and hepatocyte proliferation in a CAR-dependent manner, whereas the perfluorinated compound perfluorooctanoic acid (PFOA) increased these endpoints in a CAR-independent manner. A number of compounds suppressed CAR coincident with increases in markers of inflammation including acetaminophen, concanavalin A, lipopolysaccharide, and 300 nm silica particles. In conclusion, we have shown that a CAR biomarker signature coupled with a rank-based similarity method accurately predicts CAR activation. This analytical approach, when applied to a gene expression compendium, increased the universe of known chemicals that directly or indirectly activate CAR, highlighting the promiscuous nature of CAR activation and signaling through activation of other xenobiotic-activated receptors.

Identification of modulators of the nuclear receptor peroxisome proliferator-activated receptor α (PPARα) in a mouse liver gene expression compendium

The nuclear receptor family member peroxisome proliferator-activated receptor α (PPARα) is activated by therapeutic hypolipidemic drugs and environmentally-relevant chemicals to regulate genes involved in lipid transport and catabolism. Chronic activation of PPARα in rodents increases liver cancer incidence, whereas suppression of PPARα activity leads to hepatocellular steatosis. Analytical approaches were developed to identify biosets (i.e., gene expression differences between two conditions) in a genomic database in which PPARα activity was altered. A gene expression signature of 131 PPARα-dependent genes was built using microarray profiles from the livers of wild-type and PPARα-null mice after exposure to three structurally diverse PPARα activators (WY-14,643, fenofibrate and perfluorohexane sulfonate). A fold-change rank-based test (Running Fisher’s test (p-value ≤ 10^-4)) was used to evaluate the similarity between the PPARα signature and a test set of 48 and 31 biosets positive or negative, respectively for PPARα activation; the test resulted in a balanced accuracy of 98%. The signature was then used to identify factors that activate or suppress PPARα in an annotated mouse liver/primary hepatocyte gene expression compendium of ~1850 biosets. In addition to the expected activation of PPARα by fibrate drugs, di(2-ethylhexyl) phthalate, and perfluorinated compounds, PPARα was activated by benzofuran, galactosamine, and TCDD and suppressed by hepatotoxins acetaminophen, lipopolysaccharide, silicon dioxide nanoparticles, and trovafloxacin. Additional factors that activate (fasting, caloric restriction) or suppress (infections) PPARα were also identified. This study 1) developed methods useful for future screening of environmental chemicals, 2) identified chemicals that activate or suppress PPARα, and 3) identified factors including diets and infections that modulate PPARα activity and would be hypothesized to affect chemical-induced PPARα activity.

Methods for assigning confidence to toxicity data with multiple values--Identifying experimental outliers

The assessment of data quality is a crucial element in many disciplines such as predictive toxicology and risk assessment. Currently, the reliability of toxicity data is assessed on the basis of testing information alone (adherence to Good Laboratory Practice (GLP), detailed testing protocols, etc.). Common practice is to take one toxicity data point per compound - usually the one with the apparently highest reliability. All other toxicity data points (for the same experiment and compound) from other sources are neglected. To show the benefits of incorporating the "less reliable" data, a simple, independent, statistical approach to assess data quality and reliability on a mathematical basis was developed. A large data set of toxicity values to Aliivibrio fischeri was assessed. The data set contained 1813 data points for 1227 different compounds, including 203 identified as non-polar narcotic. Log KOW values were calculated and non-polar narcosis quantitative structure-activity relationship (QSAR) models were built. A statistical approach to data quality assessment, which is based on data outlier omission and confidence scoring, improved the linear QSARs. The results indicate that a beneficial method for using large data sets containing multiple data values per compound and highly variable study data has been developed. Furthermore this statistical approach can help to develop novel QSARs and support risk assessment by obtaining more reliable values for biological endpoints.

A comprehensive estimation of the economic effects of meteorological services based on the input-output method

Concentrating on consuming coefficient, partition coefficient, and Leontief inverse matrix, relevant concepts and algorithms are developed for estimating the impact of meteorological services including the associated (indirect, complete) economic effect. Subsequently, quantitative estimations are particularly obtained for the meteorological services in Jiangxi province by utilizing the input-output method. It is found that the economic effects are noticeably rescued by the preventive strategies developed from both the meteorological information and internal relevance (interdependency) in the industrial economic system. Another finding is that the ratio range of input in the complete economic effect on meteorological services is about 1 : 108.27–1 : 183.06, remarkably different from a previous estimation based on the Delphi method (1 : 30–1 : 51). Particularly, economic effects of meteorological services are higher for nontraditional users of manufacturing, wholesale and retail trades, services sector, tourism and culture, and art and lower for traditional users of agriculture, forestry, livestock, fishery, and construction industries.