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Nanotechnology is identified as a key enabling technology due to its potential to contribute to economic growth and societal well-being across industrial sectors. Sustainable nanotechnology requires a scientifically based and proportionate risk governance structure to support innovation, including a robust framework for environmental risk assessment (ERA) that ideally builds on methods established for conventional chemicals to ensure alignment and avoid duplication. Exposure assessment developed as a tiered approach is equally beneficial to nano-specific ERA as for other classes of chemicals. Here we present the developing knowledge, practical considerations and key principles need to support exposure assessment for engineered nanomaterials for regulatory and research applications.The operationalization and improvement of environmental exposure assessment models for engineered nanomaterials can build on ten emerging principles relating to their release pathways, waste handling, transformations, influence of the properties on reactions and role that organisms can play in their fate and transport.

Depending on the environmental compartment, plastics are subjected to various stressors, including UV light, water, microbial exudates (enzymes), and temperature. Among these, stress on plastics from photo-chemical processes was identified as a leading exposure pathway of plastics, e.g., in the atmosphere or on the water surface. While the focus of earlier studies mainly was on deterioration of the chemical and mechanical properties, more recent studies demonstrate how photo-oxidation leads to fragmentation and release of secondary micro- and nanoplastic fragments, as well as low-molecular weight species. These studies tend to focus on a single exposure condition and a limited number of polymer types. Therefore, this study focuses on systematically evaluating the influence of temperature and relative humidity during simulated UV exposure on the fragmentation and degradation of five types of pristine microplastic powders: polypropylene, low density polyethylene, polyamide 6, high impact polystyrene and thermoplastic polyurethane. We quantified the dose-dependent release of water-soluble organics, as well as secondary micro- and nanoplastics (including their particle size distributions) and found that the polymer identity dictated the type and quantity of species released rather than the aging protocol. With this systematic assessment the generated data can be used in mechanistic microplastic fragmentation models to determine fragmentation rates and fragment size distributions.

Greenhouse whitefly ( Trialeurodes vaporariorum ) is a major global pest, causing direct damage to plants and transmitting viral plant diseases. Management of  T. vaporariorum is problematic because of widespread pesticide resistance, and many greenhouse growers rely on biological control agents to regulate  T. vaporariorum populations. However, these are often slow and vary in efficacy, leading to subsequent application of chemical insecticides when pest populations exceed threshold levels. Combining chemical and biological pesticides has great potential but can result in different outcomes, from positive to negative interactions. In this study, we evaluated co-applications of the entomopathogenic fungi (EPF) Beauveria bassiana and Cordyceps farinosa and the chemical insecticide spiromesifen in laboratory bioassays. Complex interactions between the EPFs and insecticide were described using an ecotoxicological mixtures model, the MixTox analysis. Depending on the EPF and chemical concentrations applied, mixtures resulted in additivity, synergism, or antagonism in terms of total whitefly mortality. Combinations of B. bassiana and spiromesifen, compared to single treatments, increased the rate of kill by 5 days. Results indicate the potential for combined applications of EPF and spiromesifen as an effective integrated pest management strategy and demonstrate the applicability of the MixTox model to describe complex mixture interactions.

This Guidance document describes harmonised risk assessment methodologies for combined exposure to multiple chemicals for all relevant areas within EFSA's remit, i.e. human health, animal health and ecological areas. First, a short review of the key terms, scientific basis for combined exposure risk assessment and approaches to assessing (eco)toxicology is given, including existing frameworks for these risk assessments. This background was evaluated, resulting in a harmonised framework for risk assessment of combined exposure to multiple chemicals. The framework is based on the risk assessment steps (problem formulation, exposure assessment, hazard identification and characterisation, and risk characterisation including uncertainty analysis), with tiered and stepwise approaches for both whole mixture approaches and component‐based approaches. Specific considerations are given to component‐based approaches including the grouping of chemicals into common assessment groups, the use of dose addition as a default assumption, approaches to integrate evidence of interactions and the refinement of assessment groups. Case studies are annexed in this guidance document to explore the feasibility and spectrum of applications of the proposed methods and approaches for human and animal health and ecological risk assessment. The Scientific Committee considers that this Guidance is fit for purpose for risk assessments of combined exposure to multiple chemicals and should be applied in all relevant areas of EFSA's work. Future work and research are recommended. This publication is linked to the following EFSA Supporting Publications article: http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2019.EN-1589/full, http://onlinelibrary.wiley.com/doi/10.2903/sp.efsa.2019.EN-1602/full

Pollinators in agricultural landscapes can be exposed to mixtures of pesticides and environmental pollutants. Existing mixture toxicity modelling approaches, such as the models of concentration addition and independent action and the mechanistic DEBtox framework have been previously shown as valuable tools for understanding and ultimately predicting joint toxicity. Here we apply these mixture models to investigate the potential to interpret the effects of semi-chronic binary mixture exposure for three bee species: Apis mellifera, Bombus terrestris and Osmia bicornis within potentiation and mixture toxicity experiments. In the potentiation studies, the effect of the insecticide dimethoate with added propiconazole fungicide and neonicotinoid insecticide clothianidin with added tau-fluvalinate pyrethroid acaricide showed no difference in toxicity compared to the single chemical alone. Clothianidin toxicity showed a small scale, but temporally conserved increase in exposure conducted in the presence of propiconazole, particularly for B. terrestris and O. bicornis, the latter showing a near three-fold increase in clothianidin toxicity in the presence of propiconazole. In the mixture toxicity studies, the dominant response patterns were of additivity, however, binary mixtures of clothianidin and dimethoate in A. mellifera, B. terrestris and male O. bicornis there was evidence of a predominant antagonistic interaction. Given the ubiquitous nature of exposures to multiple chemicals, there is an urgent need to consider mixture effects in pollinator risk assessments. Our analyses suggest that current models, particularly those that utilise time-series data, such as DEBtox, can be used to identify additivity as the dominant response pattern and also those examples of interactions, even when small-scale, that may need to be taken into account during risk assessment.

Background The 'exposome' represents the accumulation of all environmental exposures across a lifetime. Top-down strategies are required to assess something this comprehensive, and could transform our understanding of how environmental factors affect human health. Metabolic profiling (metabonomics/metabolomics) defines an individual's metabolic phenotype, which is influenced by genotype, diet, lifestyle, health and xenobiotic exposure, and could also reveal intermediate biomarkers for disease risk that reflect adaptive response to exposure. We investigated changes in metabolism in volunteers living near a point source of environmental pollution: a closed zinc smelter with associated elevated levels of environmental cadmium. Methods High-resolution 1 H NMR spectroscopy (metabonomics) was used to acquire urinary metabolic profiles from 178 human volunteers. The spectral data were subjected to multivariate and univariate analysis to identify metabolites that were correlated with lifestyle or biological factors. Urinary levels of 8-oxo-deoxyguanosine were also measured, using mass spectrometry, as a marker of systemic oxidative stress. Results Six urinary metabolites, either associated with mitochondrial metabolism (citrate, 3-hydroxyisovalerate, 4-deoxy-erythronic acid) or one-carbon metabolism (dimethylglycine, creatinine, creatine), were associated with cadmium exposure. In particular, citrate levels retained a significant correlation to urinary cadmium and smoking status after controlling for age and sex. Oxidative stress (as determined by urinary 8-oxo-deoxyguanosine levels) was elevated in individuals with high cadmium exposure, supporting the hypothesis that heavy metal accumulation was causing mitochondrial dysfunction. Conclusions This study shows evidence that an NMR-based metabolic profiling study in an uncontrolled human population is capable of identifying intermediate biomarkers of response to toxicants at true environmental concentrations, paving the way for exposome research.

Nanosafety assessment, which seeks to evaluate the risks from exposure to nanoscale materials, spans materials synthesis and characterisation, exposure science, toxicology, and computational approaches, resulting in complex experimental workflows and diverse data types. Managing the data flows, with a focus on provenance (who generated the data and for what purpose) and quality (how was the data generated, using which protocol with which controls), as part of good research output management, is necessary to maximise the reuse potential and value of the data. Instance maps have been developed and evolved to visualise experimental nanosafety workflows and to bridge the gap between the theoretical principles of FAIR (Findable, Accessible, Interoperable and Re-usable) data and the everyday practice of experimental researchers. Instance maps are most effective when applied at the study design stage to associate the workflow with the nanomaterials, environmental conditions, method descriptions, protocols, biological and computational models to be used, and the data flows arising from study execution. Application of the InstanceMaps tool (described herein) to research workflows of increasing complexity is presented to demonstrate its utility, starting from (i) documentation of a nanomaterial’s synthesis, functionalisation, and characterisation, over (ii) assessment of a nanomaterial’s transformations in complex media, (iii) description of the culturing of ecotoxicity model organisms Daphnia magna and their use in standardised tests for nanomaterials ecotoxicity assessment, and (iv) visualisation of complex workflows in human immunotoxicity assessment using cell lines and primary cellular models, to (v) the use of the instance map approach for the coordination of materials and data flows in complex multipartner collaborative projects and for the demonstration of case studies. Finally, areas for future development of the instance map approach and the tool are highlighted.

In ecotoxicology, the state of the art for effect assessment of chemical mixtures is through multiple dose—response analysis of single compounds and their combinations. Investigating whether such data deviate from the reference models of concentration addition and/or independent action to identify overall synergism or antagonism is becoming routine. However, recent data show that more complex deviation patterns, such as dose ratio—dependent deviation and dose level—dependent deviation, need to be addressed. For concentration addition, methods to detect such deviation patterns exist, but they are stand‐alone methods developed separately in literature, and conclusions derived from these analyses are therefore difficult to compare. For independent action, hardly any methods to detect such deviations from this reference model exist. This paper describes how these well‐established mixture toxicity principles have been incorporated in a coherent data analysis procedure enabling detection and quantification of dose level—and dose ratio—specific synergism or antagonism from both the concentration addition and the independent action models. Significance testing of which deviation pattern describes the data best is carried out through maximum likelihood analysis. This analysis procedure is demonstrated through various data sets, and its applicability and limitations in mixture research are discussed.

A wealth of studies has investigated how chemical sensitivity is affected by temperature, however, almost always under different constant rather than more realistic fluctuating regimes. Here we compared how the nematode Caenorhabditis elegans responds to copper at constant temperatures (8-24°C) and under fluctuation conditions of low (±4°C) and high (±8°C) amplitude (averages of 12, 16, 20°C and 16°C respectively). The DEBkiss model was used to interpret effects on energy budgets. Increasing constant temperature from 12-24°C reduced time to first egg, life-span and population growth rates consistent with temperature driven metabolic rate change. Responses at 8°C did not, however, accord with this pattern (including a deviation from the Temperature Size Rule), identifying a cold stress effect. High amplitude variation and low amplitude variation around a mean temperature of 12°C impacted reproduction and body size compared to nematodes kept at the matching average constant temperatures. Copper exposure affected reproduction, body size and life-span and consequently population growth. Sensitivity to copper (EC50 values), was similar at intermediate temperatures (12, 16, 20°C) and higher at 24°C and especially the innately stressful 8°C condition. Temperature variation did not increase copper sensitivity. Indeed under variable conditions including time at the stressful 8°C condition, sensitivity was reduced. DEBkiss identified increased maintenance costs and increased assimilation as possible mechanisms for cold and higher copper concentration effects. Model analysis of combined variable temperature effects, however, demonstrated no additional joint stressor response. Hence, concerns that exposure to temperature fluctuations may sensitise species to co-stressor effects seem unfounded in this case.

Nanomaterials (NMs) can interact with the innate immunity of organisms. It remains, however, unclear whether these interactions can compromise the immune functioning of the host when faced with a disease threat. Co-exposure with pathogens is thus a powerful approach to assess the immuno-safety of NMs. In this paper, we studied the impacts of in vivo exposure to a biocidal NM on the gut microbiome, host immune responses, and susceptibility of the host to a bacterial challenge in an earthworm. Eisenia fetida were exposed to CuO-nanoparticles in soil for 28 days, after which the earthworms were challenged with the soil bacterium Bacillus subtilis. Immune responses were monitored by measuring mRNA levels of known earthworm immune genes. Effects of treatments on the gut microbiome were also assessed to link microbiome changes to immune responses. Treatments caused a shift in the earthworm gut microbiome. Despite these effects, no impacts of treatment on the expression of earthworm immune markers were recorded. The methodological approach applied in this paper provides a useful framework for improved assessment of immuno-safety of NMs. In addition, we highlight the need to investigate time as a factor in earthworm immune responses to NM exposure.