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Proper risk assessment of the many new nanoforms (NFs) that are currently being developed and marketed is hindered by constraints in time and resources for testing their fate and (eco) toxicity profile. This problem has also been encountered in conventional chemical risk assessments, where the definition of related chemical groups can facilitate risk assessment for all class members. Whereas grouping and read-across methods are well established, such approaches are in the early stages of development for NFs. In this study, a modeling framework was developed for grouping NFs into distinct classes regarding the contribution of released ions to suspension-induced toxicity. The framework is based on combining dissolution rate constants of NFs with information about the toxicokinetics of the NFs and the dissolution products formed. The framework is exemplified for the specific case of suspension toxicity of metallic NFs (silver and copper). To this end, principles of mixture toxicity and dose-response modeling are integrated to derive threshold values for the key NF properties determining suspension toxicity: size, shape, and chemical composition. The threshold values thus derived offer a possible solution for the high-throughput screening of NFs according to their morphological and compositional properties in a regulatory context.

Evidence grows that standard toxicity testing might underestimate the environmental risk of neurotoxic insecticides. Behavioural endpoints such as locomotion and mobility have been suggested as sensitive and ecologically relevant additions to the standard tested endpoints. Possible interactive effects of chemicals and additional stressors are typically overlooked in standardised testing. Therefore, we aimed to investigate how concurrent exposure to environmental stressors (increased temperature and predation cues) and a nicotinic acetylcholine receptor (nAChR)-modulating insecticide ('sulfoxaflor') impact Chironomus riparius across a range of conventional and non-conventional endpoints. We used a multifactorial experimental design encompassing three stressors, sulfoxaflor (2.0-110 µg/L), predation risk (presence/absence of predatory cues), and elevated temperature (20 °C and 23 °C), yielding a total of 24 distinct treatment conditions. Additional stressors did not change the sensitivity of C. riparius to sulfoxaflor. To assess potential additive effects, we applied an Independent Action (IA) model to predict the impact on eight endpoints, including conventional endpoints (growth, survival, total emergence, and emergence time) and less conventional endpoints (the size of the adults, swimming abilities and exploration behaviour). For the conventional endpoints, observed effects were either lower than expected or well-predicted by the IA model. In contrast, we found greater than predicted effects of predation cues and temperature in combination with sulfoxaflor on adult size, larval exploration, and swimming behaviour. However, in contrast to the non-conventional endpoints, no conventional endpoints detected interactive effects of the neurotoxic insecticide and the environmental stressors. Acknowledging these interactions, increasing ecological context of ecotoxicological test systems may, therefore, advance environmental risk analysis and interpretation as the safe environmental concentrations of neurotoxic insecticides depend on the context of both the test organism and its environment., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Martina G. Vijver reports financial support was provided by European Union. Martina G. Vijver reports financial support was provided by Leiden Bio Science Park. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Despite the pervasive presence of nano- and microplastics (NMPs) in aquatic environments, their movement through food chains remains poorly understood. In this study, we explored the uptake of polystyrene plastics (PSPs) of varying sizes (26, 500, and 4800 nm) in Daphnia magna and their subsequent transfer to the freshwater mysid Limnomysis benedeni, shedding light on the intricate dynamics of NMP transfer in freshwater ecosystems. Our results show that in D. magna the internal concentration of 4800 nm PSPs was 4-10 times higher than that of 26 and 500 nm PSPs, respectively. The uptake rate constants in daphnids decreased in the following order: 4800 nm (2.4 ± 0.5 L/g·h) > 26 nm (1.7 ± 0.4 L/g·h) > 500 nm (0.6 ± 0.1 L/g·h) PSPs. Importantly, only a small fraction (1-5 %) of the PSPs ingested by D. magna was transferred to L. benedeni. Additionally, larger particle sizes were associated with a higher extent of transfer in the food chain. Elimination rate constants in L. benedeni were found to be 0.03 ± 0.03, 0.1 ± 0.2, and 0.2 ± 0.8 per hour for 26, 500, and 4800 nm PSPs, respectively. Fluorescence observations revealed that PSPs were predominantly located in the stomach and intestine of L. benedeni. Furthermore, the calculated trophic transfer factor, based on the mass of particles accumulated in the organisms, was <1 for all PSP treatments. Our results indicate that NMPs can be transferred along the daphnia-mysids food chain, and that there is no evidence of biomagnification along this chain. These findings underscore the importance of understanding particle size effects on NMP transfer and accumulation in aquatic food webs, offering valuable insights for assessing the ecological risks associated with NMP pollution in freshwater ecosystems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Terrestrial systems are a significant sink for plastic contamination, including nano- and microplastics (NMPs). To date, limited information is available about the transfer of NMPs up the food web via trophic transfer, however, concerns about this exposure pathway for invertebrates and higher-level organisms have been raised. We aim to examine and quantify the trophic transfer of europium doped polystyrene nanoplastics (Eu-PS; NPs) within a terrestrial food chain. The uptake of 100 nm spherical Eu-PS particles from water through the roots of the plants to the leaves and finally to garden snails (Cantareus aspersus) was assessed. Lettuce (Lactuca sativa) was cultivated in Hoagland solution spiked with different concentrations of Eu-PS (15, 150 and 1500 μg/L) for three weeks. Then, lettuce shoots were used as food for snails for 19 days at a rate of 1 g of shoots per day. The Eu-PS primarily accumulated in the lettuce roots for all treatments, with a limited transfer to the shoots (only quantifiable in the highest treatment; translocation factor: TF < 1). No detectable levels of Eu-PS were found in the snails' digestive gland; however, the Eu-PS particles were detected in their feces (trophic transfer factor: TFF > 1). Moreover, only limited effects were observed on lettuce biomass by NPs treatments. No effects of the Eu-PS particles on snails were observed, with the exception of a consistent decrease in the shell diameter. Overall, our research illustrates that NPs can be absorbed by plants through their roots, subsequently transported to the shoots. However, our findings show limited transfer of NPs into snail tissues, but direct excretion into their feces. We provide an important insight into the potential transfer within the human food chain., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Laura J. Zantis reports financial support was provided by Horizon Europe. Maria Kazour reports financial support was provided by Horizon Europe. Willie Peijnenburg reports financial support was provided by Horizon Europe. Thijs Bosker reports financial support was provided by Horizon Europe. Martina G. Vijver reports financial support was provided by European Research Council. Frederic Gimbert reports financial support was provided by The French Agency for Ecological Transition. Romain Colpaert reports financial support was provided by The French Agency for Ecological Transition. Romain Colpaert reports financial support was provided by Bourgogne-Franche-Comte Region. Frederic Gimbert reports financial support was provided by Bourgogne-Franche-Comte Region. Thijs Bosker reports financial support was provided by Netherlands Organisation for Health Research and Development. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

The massive production and application of nanomaterials (NMs) have raised concerns about the potential adverse effects of NMs on human health and the environment. Evaluating the adverse effects of NMs by laboratory methods is expensive, time-consuming, and often fails to keep pace with the invention of new materials. Therefore, in silico methods that utilize machine learning techniques to predict the toxicity potentials of NMs are a promising alternative approach if regulatory confidence in them can be enhanced. Previous reviews and regulatory OECD guidance documents have discussed in detail how to build an in silico predictive model for NMs. Nevertheless, there is still room for improvement in addressing the ways to enhance the model representativeness and performance from different angles, such as data set curation, descriptor selection, task type (classification/regression), algorithm choice, and model evaluation (internal and external validation, applicability domain, and mechanistic interpretation, which is key to ensuring stakeholder confidence). This review explores how to build better predictive models; the current state of the art is analyzed via a statistical evaluation of literature, while the challenges faced and future perspectives are summarized. Moreover, a recommended workflow and best practices are provided to help in developing more predictive, reliable, and interpretable models that can assist risk assessment as well as safe-by-design development of NMs.

Agricultural lands have been identified as plastic sinks. One source is plastic mulches, which are a source of micro- and nano-sized plastics in agricultural soils. Because of their persistence, there is now a push towards developing biodegradable plastics, which are designed to undergo (partial) breakdown after entering the environment. Yet, limited research has investigated the impacts of both conventional and biodegradable plastics on distinct plants. Moreover, comparisons among studies are difficult due to differences in experimental design. This study directly compares the effects of artificially weathered conventional polyethylene (PE) and starch-based biodegradable polybutylene adipate terephthalate (PBAT) on four food crops, including two monocots (barley, Hordeum vulgare, and wheat, Triticum aestivum L.) and two dicots (carrot, Daucus carota, and lettuce, Lactuca sativa L.). We investigated the effects of environmentally relevant low, medium, and high (0.01 %, 0.1 %, 1 % w/w) concentrations of PE and starch-PBAT blend on seed germination (acute toxicity), and subsequently on plant growth and chlorophyll through a pot-plant experiment (chronic toxicity). Germination of all species was not affected by both plastics. However, root length was reduced for lettuce and wheat seedlings. No other effects were recorded on monocots. We observed a reduction in shoot length and bud wet weight of carrot seedlings for the highest concentration of PE and starch-PBAT blend. Chronic exposure resulted in a significant decrease in shoot biomass of barley and lettuce. Additionally, a positive increase in the number of leaves of lettuce was observed for both plastics. Chlorophyll content was increased in lettuce when exposed to PE and starch-PBAT blend. Overall, adverse effects in dicots were more abundant than in monocots. Importantly, we found that the biodegradable plastic caused more commonly adverse effects on plants compared to conventional plastic, which was confirmed by a mini-review of studies directly comparing the impact of conventional and biodegradable microplastics., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Laura J. Zantis reports financial support was provided by Horizon Europe. Sylwia Adamczyk reports financial support was provided by Horizon Europe. Sannakajsa M. Velmala reports financial support was provided by Horizon Europe. Bartosz Adamczyk reports financial support was provided by Horizon Europe. Thijs Bosker reports financial support was provided by Horizon Europe. Willie Peijnenburg reports financial support was provided by Horizon Europe. Martina G. Vijver reports financial support was provided by European Research Council. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

A strong need exists for broadly applicable nano-QSARs, capable of predicting toxicological outcomes towards untested species and nanomaterials, under different environmental conditions. Existing nano-QSARs are generally limited to only a few species but the inclusion of species characteristics into models can aid in making them applicable to multiple species, even when toxicity data is not available for biological species. Species traits were used to create classification- and regression machine learning models to predict acute toxicity towards aquatic species for metallic nanomaterials. Afterwards, the individual classification- and regression models were stacked into a meta-model to improve performance. Additionally, the uncertainty and limitations of the models were assessed in detail (beyond the OECD principles) and it was investigated whether models would benefit from the addition of more data. Results showed a significant improvement in model performance following model stacking. Investigation of model uncertainties and limitations highlighted the discrepancy between the applicability domain and accuracy of predictions. Data points outside of the assessed chemical space did not have higher likelihoods of generating inadequate predictions or vice versa. It is therefore concluded that the applicability domain does not give complete insight into the uncertainty of predictions and instead the generation of prediction intervals can help in this regard. Furthermore, results indicated that an increase of the dataset size did not improve model performance. This implies that larger dataset sizes may not necessarily improve model performance while in turn also meaning that large datasets are not necessarily required for prediction of acute toxicity with nano-QSARs., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Nanoplastics can cause severe malformations in chicken embryos. To improve our understanding of the toxicity of nanoplastics to embryos, we have studied their biodistribution in living chicken embryos. We injected the embryos in the vitelline vein at stages 18-19. We injected polystyrene nanoparticles (PS-NPs) tagged with europium- or fluorescence. Their biodistribution was tracked using inductively-coupled plasma mass spectrometry on tissue lysates, paraffin histology, and vibratome sections analysed by machine learning algorithms. PS-NPs were found at high levels in the heart, liver and kidneys. Furthermore, PS-NPs crossed the endocardium of the heart at sites of epithelial-mesenchymal transformation; they also crossed the liver endothelium. Finally, we detected PS-NPs in the allantoic fluid, consistent with their being excreted by the kidneys. Our study shows the power of the chicken embryo model for analysing the biodistribution of nanoplastics in embryos. Such experiments are difficult or impossible in mammalian embryos. These findings are a major advance in our understanding of the biodistribution and tissue-specific accumulation of PS-NPs in developing animals., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

III-V/Silicon tandem solar cells offer one of the most promising avenues for high-efficiency, high-stability photovoltaics. However, a key concern is the potential environmental release of group III-V elements, especially arsenic. To inform long-term policies on the energy transition and energy security, we develop and implement a framework that fully integrates future PV demand scenarios with dynamic stock, emission, and fate models in a probabilistic ecological risk assessment. We examine three geographical scales: local (including a floating utility-scale PV and waste treatment), regional (city-wide), and continental (Europe). Our probabilistic assessment considers a wide range of possible values for over one hundred uncertain technical, environmental, and regulatory parameters. We find that III-V/silicon PV integration in energy grids at all scales presents low-to-negligible risks to soil and freshwater organisms. Risks are further abated if recycling of III-V materials is considered at the panels' end-of-life.

The aim of this study is twofold: i) to determine innovative yet sensitive endpoints for sulfoxaflor and ii) to develop best practices for innovative teaching in ecotoxicology. To this end, a group of 52 MSc students participated in an environmental hackathon, during which they did creative toxicity testing on 5 freshwater invertebrate species: Daphnia magna, Chironomus riparius, Asellus aquaticus, Lymnaea stagnalis, and Anisus vortex. Involving the students in an active learning environment stimulated increased creativity and productivity. In total, 28 endpoints were investigated, including standard endpoints (e.g., mortality) as well as biomechanistic and energy-related endpoints. Despite high variances in the results, likely linked to the limited lab experience of the students and interpersonal differences, a promising set of endpoints was selected for further investigation. A more targeted follow-up experiment focused on the most promising organism and set of endpoints: biomechanistic endpoints of C. riparius larvae. Larvae were exposed to a range of sulfoxaflor concentrations (0.90-67.2 μg/L) for 21 days. Video tracking showed that undulation and swimming were significantly reduced at 11.1 μg sulfoxaflor/L after 9 days of exposure, and an EC 50 = 10.6 μg/L for mean velocities of the larvae in the water phase was found. Biomechanistic endpoints proved much more sensitive than mortality, for which an LC 50 value of 116 μg/L was found on Day 9. Our results show that performing a hackathon with students has excellent potential to find sensitive endpoints that can subsequently be verified using more targeted and professional follow-up experiments. Furthermore, utilising hackathon events in teaching can increase students' enthusiasm about ecotoxicology, driving better learning experiences., (© 2024. The Author(s).)

A suspension of copper oxide nanoparticles (CuO NPs) is a mixture of dissolved and particulate Cu, the relative proportions of which highly depend on the water chemistry. However, the relationship between different proportions of particulate and dissolved Cu and the overall toxicity of CuO NPs is still unknown. This study investigated the response of Chlorella vulgaris to CuO NPs at varying solution pH and at different tannic acid (TA) additions, with a focus on exploring whether and how dissolved and particulate Cu contribute to the overall toxicity of CuO NPs. The results of the exposure experiments demonstrated the involvement of both dissolved and particulate Cu in inducing toxicity of CuO NPs, and the inhibition of CuO NPs on cell density of Chlorella vulgaris was found to be significantly (p < 0.05) alleviated with increased levels of TA and pH (< 8). Using the independent action model, the contribution to toxicity of particulate Cu was found to be enhanced with increasing pH values and TA concentrations. The toxic unit indicator better (R 2 = 0.86, p < 0.001) explained impacts of CuO NPs on micro-algae cells than commonly used mass concentrations (R 2 = 0.27-0.77, p < 0.05) across different levels of pH and TA. Overall, our study provides an additivity-based method to improve the accuracy of toxicity prediction through including contributions to toxicity of both dissolved and particulate Cu and through eliminating the uneven distribution of data due to large variations in total Cu, particulate Cu, dissolved Cu, Cu 2+ activities, Cu-TA complexes and other Cu-complexes concentrations with varying water chemistry conditions., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.)

To date, research on the toxicity and potential environmental impacts of nanomaterials has predominantly focused on relatively simple and single-component materials, whilst more complex nanomaterials are currently entering commercial stages. The current study aimed to assess the long-term and size-dependent (60 and 500 nm) toxicity of a novel core-shell nanostructure consisting of a SiC core and TiO 2 shell (SiC/TiO 2 , 5, 25, and 50 mg L -1 ) to the common model organism Daphnia magna . These novel core-shell nanostructures can be categorized as advanced materials. Experiments were conducted under environmentally realistic feeding rations and in the presence of a range of concentrations of humic acid (0.5, 2, 5, and 10 mg L -1 TOC). The findings show that although effect concentrations of SiC/TiO 2 were several orders of magnitude lower than the current reported environmental concentrations of more abundantly used nanomaterials, humic acid can exacerbate the toxicity of SiC/TiO 2 by reducing aggregation and sedimentation rates. The EC 50 values (mean ± standard error) based on nominal SiC/TiO 2 concentrations for the 60 nm particles were 28.0 ± 11.5 mg L -1 (TOC 0.5 mg L -1 ), 21.1 ± 3.7 mg L -1 (TOC 2 mg L -1 ), 18.3 ± 5.4 mg L -1 (TOC 5 mg L -1 ), and 17.8 ± 2.4 mg L -1 (TOC 10 mg L -1 ). For the 500 nm particles, the EC50 values were 34.9 ± 16.5 mg L -1 (TOC 0.5 mg L -1 ), 24.8 ± 5.6 mg L -1 (TOC 2 mg L -1 ), 28.0 ± 10.0 mg L -1 (TOC 5 mg L -1 ), and 23.2 ± 4.1 mg L -1 (TOC 10 mg L -1 ). We argue that fate-driven phenomena are often neglected in effect assessments, whilst environmental factors such as the presence of humic acid may significantly influence the toxicity of nanomaterials.

Advanced materials comprising multiple metal alloys have made their way into the market. Trimetal-based nanomaterials (TNMs) are an example of advanced materials which have gained significant traction and are now employed in a wide array of products. It is essential to raise the question if the toxicity of advanced nanomaterials like TNMs differs from the joint effects as manifested by exposure to the single component nanoparticles (NPs). To answer this question, a trimetal-based nanomaterial: bismuth cobalt zinc oxide (BiCoZnO) was tested. This TNM had a mass ratio of 90 % ZnO NPs, 7 % Bi 2 O 3 NPs and 3 % Co 3 O 4 NPs. Nanoparticle-exposed lettuce seedlings ( Lactuca sativa L.) showed decreases in relative root elongation (RRE) and biomass production after 21 days of exposure. The 50 % of maximal effective concentration (EC 50 ) value of the TNMs for biomass production was 1.2 mg L -1 when the exposure period was 240 h. This is of the same magnitude as the EC 50 values found for ZnO NPs (EC 50  = 1.5 mg L -1 ) and for the mixture of components NPs (MCNPs) which jointly form the TNMs (EC 50  = 3.7 mg L -1 ) after 10 d of exposure. The inhibition of plant root elongation by the TNMs was partially (65 %) attributed to the release of Zn ions, with the actual concentration of released Zn ions being lower in TNMs compared to the actual concentration of Zn ions in case of ZnO NPs. It is therefore to be concluded that the concentration of Zn ions cannot be used as a direct measure to compare the toxicity between traditional and advanced Zn-related nanomaterials. The EC 50 values could be assessed within a factor of two; which is helpful when developing advanced alloy nanomaterials and assessing prospective the effects of trimetal-based nanomaterials., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2023 The Authors.)

The wide production and use of metallic nanomaterials (MNMs) leads to increased emissions into the aquatic environments and induces high potential risks. Experimentally evaluating the (eco)toxicity of MNMs is time-consuming and expensive due to the multiple environmental factors, the complexity of material properties, and the species diversity. Machine learning (ML) models provide an option to deal with heterogeneous data sets and complex relationships. The present study established an in silico model based on a machine learning properties-environmental conditions-multi species-toxicity prediction model (ML-PEMST) that can be applied to predict the toxicity of different MNMs toward multiple aquatic species. Feature importance and interaction analysis based on the random forest method indicated that exposure duration, illumination, primary size, and hydrodynamic diameter were the main factors affecting the ecotoxicity of MNMs to a variety of aquatic organisms. Illumination was demonstrated to have the most interaction with the other features. Moreover, incorporating additional detailed information on the ecological traits of the test species will allow us to further optimize and improve the predictive performance of the model. This study provides a new approach for ecotoxicity predictions for organisms in the aquatic environment and will help us to further explore exposure pathways and the risk assessment of MNMs.

Only recently there has been a strong focus on the impacts of microplastics on terrestrial crop plants. This study aims to examine and compare the effects of microplastics on two monocotyledonous (barley, Hordeum vulgare and wheat, Triticum aestivum), and two dicotyledonous (carrot, Daucus carota and lettuce, Lactuca sativa) plant species through two complimentary experiments. First, we investigated the effects of low, medium, and high (10 3 , 10 5 , 10 7 particles per mL) concentrations of 500 nm polystyrene microplastics (PS-MPs) on seed germination and early development. We found species-dependent effects on the early development, with microplastics only significantly affecting lettuce and carrot. When acutely exposed during germination, PS-MPs significantly delayed the germination of lettuce by 24%, as well as promoted the shoot growth of carrot by 71% and decreased its biomass by 26%. No effect was recorded on monocot species. Secondly, we performed a chronic (21 d) hydroponic experiment on lettuce and wheat. We observed that PS-MPs significantly reduced the shoot growth of lettuce by up to 35% and increased its biomass by up to 64%, while no record was reported on wheat. In addition, stress level indicators and defence mechanisms were significantly up-regulated in both lettuce and wheat seedlings. Overall, this study shows that PS-MPs affect plant development: impacts were recorded on both germination and growth for dicots, and responses identified by biochemical markers of stress were increased in both lettuce and wheat. This highlights species-dependent effects as the four crops were grown under identical conditions to allow direct comparison. For future research, our study emphasizes the need to focus on crop specific effects, while also working towards knowledge of plastic-induced impacts at environmentally relevant conditions., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interestsLaura J. Zantis reports financial support was provided by Horizon Europe. Sylwia Adamczyk reports financial support was provided by Horizon Europe. Sannakajsa M. Velmala reports financial support was provided by Horizon Europe. Bartosz Adamczyk reports financial support was provided by Horizon Europe. Thijs Bosker reports financial support was provided by Horizon Europe. Martina G. Vijver reports financial support was provided by European Research Council. Willie Peijnenburg reports financial support was provided by Horizon Europe., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Novel nanomaterial-based pesticide formulations are increasingly perceived as promising aids in the transition to more efficient agricultural production systems. The current understanding of potential unintended (eco)toxicological impacts of nano-formulated pesticides is scarce, in particular with regard to (non-target) aquatic organisms and ecosystems. The present study reports the results of a long-term freshwater mesocosm experiment which assessed responses of individual zooplankton taxa and communities to a novel TiO 2 -coated nano-formulation of the fungicide carbendazim. Population- and community trends were assessed and compared in response to the nano-formulation and its constituents applied individually (i.e. nano-sized TiO 2 , carbendazim) and in combination (i.e. nano-sized TiO 2 & carbendazim). Minimal differences were observed between effects induced by the nano-formulation and its active ingredient (i.e. carbendazim) when applied at equivalent nominal test concentrations (4 μg L -1 ). Nano-sized TiO 2 was found to affect zooplankton community trends when applied separately at environmentally realistic concentrations (20 μg L -1 nominal test concentration). However, when nano-sized TiO 2 was applied in combination with carbendazim, nano-sized TiO 2 was found not to alter effects on community trends induced by carbendazim. The findings of the current study provide an extensive and timely addition to the current body of work available on non-target impacts of nano-formulated pesticides., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Research on theoretical prediction methods for the mixture toxicity of engineered nanoparticles (ENPs) faces significant challenges. The application of in silico methods based on machine learning is emerging as an effective strategy to address the toxicity prediction of chemical mixtures. Herein, we combined toxicity data generated in our lab with experimental data reported in the literature to predict the combined toxicity of seven metallic ENPs for Escherichia coli at different mixing ratios (22 binary combinations). We thereafter applied two machine learning (ML) techniques, support vector machine (SVM) and neural network (NN), and compared the differences in the ability to predict the combined toxicity by means of the ML-based methods and two component-based mixture models: independent action and concentration addition. Among 72 developed quantitative structure-activity relationship (QSAR) models by the ML methods, two SVM-QSAR models and two NN-QSAR models showed good performance. Moreover, an NN-based QSAR model combined with two molecular descriptors, namely enthalpy of formation of a gaseous cation and metal oxide standard molar enthalpy of formation, showed the best predictive power for the internal dataset (R 2 test  = 0.911, adjusted R 2 test  = 0.733, RMSE test  = 0.091, and MAE test  = 0.067) and for the combination of internal and external datasets (R 2 test  = 0.908, adjusted R 2 test  = 0.871, RMSE test  = 0.255, and MAE test  = 0.181). In addition, the developed QSAR models performed better than the component-based models. The estimation of the applicability domain of the selected QSAR models showed that all the binary mixtures in training and test sets were in the applicability domain. This study approach could provide a methodological and theoretical basis for the ecological risk assessment of mixtures of ENPs., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)

Over the last years there has been significant research on the presence and effects of plastics in terrestrial systems. Here we summarize current research findings on the effects of nano- and microplastics (NMPs) on terrestrial plants, with the aim to determine patterns of response and sensitive endpoints. We conducted a systematic review (based on 78 studies) on the effects of NMPs on germination, plant growth and biochemical biomarkers. This review highlights that the majority of studies to date have used pristine polystyrene or polyethylene particles, either in a hydroponic or pot-plant setup. Based on these studies we found that effects on plants are widespread. We noted similar responses between and within monocots and dicots to NMPs, except for consistent lower germination seen in dicots exposed to NMPs. During early development, germination and root growth are more strongly affected compared to shoot growth. NMPs induced similar adverse growth effects on plant biomass and length in the most tested plant species (lettuce, wheat, corn, and rice) irrespective of the polymer type and size used. Moreover, biomarker responses were consistent across species; chlorophyll levels were commonly negatively affected, while stress indicators (e.g., ROS or free radicals) and stress respondents (e.g., antioxidant enzymes) were consistently upregulated. In addition, effects were commonly observed at environmentally relevant levels. These findings provide clear evidence that NMPs have wide-ranging impacts on plant performance. However, as most studies have been conducted under highly controlled conditions and with pristine plastics, there is an urgent need to test under more environmentally realistic conditions to ensure the lab-based studies can be extrapolated to the field., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Laura J. Zantis reports financial support was provided by Horizon Europe. Thijs Bosker reports financial support was provided by Horizon Europe. Martina G. Vijver reports financial support was provided by European Research Council. Willie Peijnenburg reports financial support was provided by Horizon Europe. Sara Di Lonardo reports financial support was provided by National Research Council of Italy., (Copyright © 2023 The Authors. Published by Elsevier B.V. All rights reserved.)

Nanomaterials are widespread in the human environment as pollutants, and are being actively developed for use in human medicine. We have investigated how the size and dose of polystyrene nanoparticles affects malformations in chicken embryos, and have characterized the mechanisms by which they interfere with normal development. We find that nanoplastics can cross the embryonic gut wall. When injected into the vitelline vein, nanoplastics become distributed in the circulation to multiple organs. We find that the exposure of embryos to polystyrene nanoparticles produces malformations that are far more serious and extensive than has been previously reported. These malformations include major congenital heart defects that impair cardiac function. We show that the mechanism of toxicity is the selective binding of polystyrene nanoplastics nanoparticles to neural crest cells, leading to the death and impaired migration of those cells. Consistent with our new model, most of the malformations seen in this study are in organs that depend for their normal development on neural crest cells. These results are a matter of concern given the large and growing burden of nanoplastics in the environment. Our findings suggest that nanoplastics may pose a health risk to the developing embryo., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023 The Authors. Published by Elsevier Ltd.. All rights reserved.)

Herein, we investigated to which extent metallic nanoparticles (MNPs) affect the trophic transfer of other coexisting MNPs from lettuce to terrestrial snails and the associated tissue-specific distribution using toxicokinetic (TK) modeling and single-particle inductively coupled plasma mass spectrometry. During a period of 22 days, snails were fed with lettuce leaves that were root exposed to AgNO 3 (0.05 mg/L), AgNPs (0.75 mg/L), TiO 2 NPs (200 mg/L), and a mixture of AgNPs and TiO 2 NPs (equivalent doses as for single NPs). The uptake rate constants ( k u ) were 0.08 and 0.11 kg leaves/kg snail/d for Ag and 1.63 and 1.79 kg leaves/kg snail/d for Ti in snails fed with NPs single- and mixture-exposed lettuce, respectively. The elimination rate constants ( k e ) of Ag in snails exposed to single AgNPs and mixed AgNPs were comparable to the corresponding k u , while the k e for Ti were lower than the corresponding k u . As a result, single TiO 2 NP treatments as well as exposure to mixtures containing TiO 2 NPs induced significant biomagnification from lettuce to snails with kinetic trophic transfer factors (TTF k ) of 7.99 and 6.46. The TTF k of Ag in the single AgNPs treatment (1.15 kg leaves/kg snail) was significantly greater than the TTF k in the mixture treatment (0.85 kg leaves/kg snail), while the fraction of Ag remaining in the body of snails after AgNPs exposure (36%) was lower than the Ag fraction remaining after mixture exposure (50%). These results indicated that the presence of TiO 2 NPs inhibited the trophic transfer of AgNPs from lettuce to snails but enhanced the retention of AgNPs in snails. Biomagnification of AgNPs from lettuce to snails was observed in an AgNPs single treatment using AgNPs number as the dose metric, which was reflected by the particle number-based TTFs of AgNPs in snails (1.67, i.e., higher than 1). The size distribution of AgNPs was shifted across the lettuce-snail food chain. By making use of particle-specific measurements and fitting TK processes, this research provides important implications for potential risks associated with the trophic transfer of MNP mixtures.

Ongoing efforts focus on quantifying plastic pollution and describing and estimating the related magnitude of exposure and impacts on human and environmental health. Data gathered during such work usually follows a receptor perspective. However, Life Cycle Assessment (LCA) represents an emitter perspective. This study examines existing data gathering and reporting approaches for field and laboratory studies on micro- and nanoplastics (MNPs) exposure and effects relevant to LCA data inputs. The outcomes indicate that receptor perspective approaches do not typically provide suitable or sufficiently harmonised data. Improved design is needed in the sampling, testing and recording of results using harmonised, validated and comparable methods, with more comprehensive reporting of relevant data. We propose a three-level set of requirements for data recording and reporting to increase the potential for LCA studies and models to utilise data gathered in receptor-oriented studies. We show for which purpose such data can be used as inputs to LCA, particularly in life cycle impact assessment (LCIA) methods. Implementing these requirements will facilitate proper integration of the potential environmental impacts of plastic losses from human activity (e.g. litter) into LCA. Then, the impacts of plastic emissions can eventually be connected and compared with other environmental issues related to anthropogenic activities., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Chemicals emitted to the environment affect ecosystem health from local to global scale, and reducing chemical impacts has become an important element of European and global sustainability efforts. The present work advances ecotoxicity characterization of chemicals in life cycle impact assessment by proposing recommendations resulting from international expert workshops and work conducted under the umbrella of the UNEP-SETAC Life Cycle Initiative in the GLAM project (Global guidance on environmental life cycle impact assessment indicators). We include specific recommendations for broadening the assessment scope through proposing to introduce additional environmental compartments beyond freshwater and related ecotoxicity indicators, as well as for adapting the ecotoxicity effect modelling approach to better reflect environmentally relevant exposure levels and including to a larger extent chronic test data. As result, we (1) propose a consistent mathematical framework for calculating freshwater ecotoxicity characterization factors and their underlying fate, exposure and effect parameters; (2) implement the framework into the USEtox scientific consensus model; (3) calculate characterization factors for chemicals reported in an inventory of a life cycle assessment case study on rice production and consumption; and (4) investigate the influence of effect data selection criteria on resulting indicator scores. Our results highlight the need for careful interpretation of life cycle assessment impact scores in light of robustness of underlying species sensitivity distributions. Next steps are to apply the recommended characterization framework in additional case studies, and to adapt it to soil, sediment and the marine environment. Our framework is applicable for evaluating chemicals in life cycle assessment, chemical and environmental footprinting, chemical substitution, risk screening, chemical prioritization, and comparison with environmental sustainability targets., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The Safe by Design (SbD) concept aims to ensure the production, use and disposal of materials and products safely. While there is a growing interest in the potential of SbD to support policy commitments, such as the EU Green Deal and the Circular Economy Action Plan in Europe, methodological approaches and practical guidelines on SbD are, however, largely missing. The combined use of Life Cycle Assessment (LCA) and Risk Assessment (RA) is considered suitable to operationalize SbD over the whole life-cycle of a product. Here, we explore the potential of the combined use of LCA and RA at Technological Readiness Level (TRL) 1-6. We perform a review of the literature presenting and/or developing approaches that combine LCA and RA at early stages of product design. We identify that basic early-on-evaluations of safety (e.g., apply lifecycle thinking to assess risk hotspots, avoid use of hazardous chemicals, minimize other environmental impacts from chemicals) are more common, while more complex assessments (e.g., ex-ante LCA, control banding, predictive (eco)toxicology) require specialized expertise. The application of these simplified approaches and guidelines aims to avoid some obvious sources of risks and impacts at early stages. Critical gaps need to be addressed for wider application of SbD, including more studies in the product design context, developing tools and databases containing collated information on risk, greater collaboration between RA/LCA researchers and companies, and policy discussion on the expansion from SbD to Safe and Sustainable by Design (SSbD)., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:Jeroen Guinee and Vrishali Subramanian report financial support was provided by Netherlands Ministry of Infrastructure and Water Management. Carlos F. Blanco reports financial support was provided by Union's Horizon 2020 research and innovation program (Grant agreement No 875637)., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The rapid development of nanomaterials (NMs) and the emergence of new multicomponent NMs will inevitably lead to simultaneous exposure of organisms to multiple engineered nanoparticles (ENPs) at varying exposure levels. Understanding the joint impacts of multiple ENPs and predicting the toxicity of mixtures of ENPs are therefore evidently of importance. We reviewed the toxicity of mixtures of ENPs to a variety of different species, covering algae, bacteria, daphnia, fish, fungi, insects, and plants. Most studies used the independent-action (IA)-based model to assess the type of joint effects. Using co-occurrence networks, it was revealed that 53% of the cases with specific joint response showed antagonistic, 25% synergistic, and 22% additive effects. The combination of nCuO and nZnO exhibited the strongest interactions in each type of joint interaction. Compared with other species, plants exposed to multiple ENPs were more likely to experience antagonistic effects. The main factors influencing the joint response type of the mixtures were (1) the chemical composition of individual components in mixtures, (2) the stability of suspensions of mixed ENPs, (3) the type and trophic level of the individual organisms tested, (4) the biological level of organization (population, communities, ecosystems), (5) the exposure concentrations and time, (6) the endpoint of toxicity, and (7) the abiotic field conditions (e.g., pH, ionic strength, natural organic matter). This knowledge is critical in developing efficient strategies for the assessment of the hazards induced by combined exposure to multiple ENPs in complex environments. In addition, this knowledge of the joint effects of multiple ENPs assists in the effective prediction of hybrid NMs.

Engineered nanomaterials (ENMs) are ubiquitous nowadays, finding their application in different fields of technology and various consumer products. Virtually any chemical can be manipulated at the nano-scale to display unique characteristics which makes them appealing over larger sized materials. As the production and development of ENMs have increased considerably over time, so too have concerns regarding their adverse effects and environmental impacts. It is unfeasible to assess the risks associated with every single ENM through in vivo or in vitro experiments. As an alternative, in silico methods can be employed to evaluate ENMs. To perform such an evaluation, we collected data from databases and literature to create classification models based on machine learning algorithms in accordance with the principles laid out by the OECD for the creation of QSARs. The aim was to investigate the performance of various machine learning algorithms towards predicting a well-defined in vivo toxicity endpoint (Daphnia magna immobilization) and also to identify which features are important drivers of D. magna in vivo nanotoxicity. Results indicated highly comparable model performance between all algorithms and predictive performance exceeding ∼0.7 for all evaluated metrics (e.g. accuracy, sensitivity, specificity, balanced accuracy, Matthews correlation coefficient, area under the receiver operator characteristic curve). The random forest, artificial neural network, and k-nearest neighbor models displayed the best performance but this was only marginally better compared to the other models. Furthermore, the variable importance analysis indicated that molecular descriptors and physicochemical properties were generally important within most models, while features related to the exposure conditions produced slightly conflicting results. Lastly, results also indicate that reliable and robust machine learning models can be generated for in vivo endpoints with smaller datasets., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier Ltd.. All rights reserved.)

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) causes the coronavirus disease-19 (COVID-19) pandemic spread across the world and remains difficult to control. Environmental pollution and habitat conditions do facilitate SARS-CoV-2 transmission as well as increase the risk of exposure to SARS-CoV-2. The coexistence of microplastics (MPs) with SARS-CoV-2 affects the viral behavior in the indoor and outdoor environment, and it is essential to study the interactions between MPs and SARS-CoV-2 because they both are ubiquitously present in our environment. To determine the mechanisms underlying the impact of MPs on SARS-CoV-2, we used molecular dynamic simulations to investigate the molecular interactions between five MPs and a SARS-CoV-2 RNA fragment at temperatures ranging from 223 to 310 K in vacuum and in water. We furthermore compared the interactions of MPs and SARS-CoV-2 RNA fragment to the performance of SARS-CoV-1 and Hepatitis B virus (HBV) RNA fragments in interacting with the MPs. The interaction affinity between the MPs and the SARS-CoV-2 RNA fragment was found to be greater than the affinity between the MPs and the SARS-CoV-1 or HBV RNA fragments, independent of the environmental media, temperature, and type of MPs. The mechanisms of the interaction between the MPs and the SARS-CoV-2 RNA fragment involved electrostatic and hydrophobic processes, and the interaction affinity was associated with the inherent structural parameters (i.e., molecular volume, polar surface area, and molecular topological index) of the MPs monomers. Although the evidence on the infectious potential of SARS-CoV-2 RNA is not fully understood, humans are exposed to MPs via their lungs, and the strong interaction with the gene materials of SARS-CoV-2 likely affects the exposure of humans to SARS-CoV-2., Competing Interests: Declaration of competing interest The authors declare no competing financial interest., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

Recently, the delivery of pesticides through novel controlled-release (nano-)formulations has been proposed intending to reduce (incidental) pesticide translocation to non-target sites. Concerns have however been raised with regards to the potentially enhanced toxicity of controlled-release (nano-)formulations to non-target organisms and ecosystems. We evaluated long-term (i.e. 1 and 3 month-) impacts of a novel controlled-release pesticide formulation (nano-TiO 2 -coated carbendazim) and its individual and combined constituents (i.e. nano-sized TiO 2 and carbendazim) on naturally established freshwater macroinvertebrate communities. In doing so, we simultaneously assessed impacts of nano-sized TiO 2 (nTiO 2 ), currently one of the most used and emitted engineered nanomaterials world-wide. We determined ecological impacts on diversity (i.e. β-diversity), structure (i.e. rank abundance parameters), and functional composition (i.e. feeding guilds & trophic groups) of communities and underlying effects at lower organizational levels (i.e. population dynamics of individual taxa). Freshwater macroinvertebrate communities were negligibly impacted by nTiO 2 at environmentally realistic concentrations. The controlled-release (nano-)formulation significantly delayed release of carbendazim to the water column. Nevertheless, conventional- (i.e. un-coated-) and nTiO 2 -coated carbendazim induced a similar set of adverse impacts at all investigated levels of ecological organization and time points. Our findings show fundamental restructuring of the taxonomic- and functional composition of macroinvertebrate communities as a result of low-level pesticide exposure, and thereby highlight the need for mitigating measures to reduce pesticide-induced stress on freshwater ecosystems., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

The goal of the current study was to quantify the trophic transfer of copper nanoparticles (CuNPs) in a food chain consisting of the microalga Pseudokirchneriella subcapitata as the representative of primary producer, the grazer Daphnia magna, and the omnivorous mysid Limnomysis benedeni. To quantify the size and number concentration of CuNPs in the biota, tissue extraction with tetramethylammonium hydroxide (TMAH) was performed and quantification was done by single particle inductively coupled plasma mass spectrometry (sp-ICP-MS). The bioconcentration factor (BCF) of the test species for CuNPs varied between 10 2 - 10 3 L/kg dry weight when expressing the internal concentration on a mass basis, which was lower than BCF values reported for Cu 2+ (10 3 - 10 4 L/kg dry weight). The particle size of CuNPs determined by sp-ICP-MS ranged from 22 to 40 nm in the species. No significant changes in the particle size were measured throughout the food chain. Moreover, the measured number of CuNPs in each trophic level was in the order of 10 13 particles/kg wet weight. The calculated trophic transfer factor (mass concentration basis) was > 1. This indicates biomagnification of particulate Cu from P. subcapitata to L. benedeni. It was also found that the uptake of particulate Cu (based on the particle number concentration) was mainly from the dietary route rather than from direct aqueous exposure. Furthermore, dietary exposure to CuNPs had a significant effect on the feeding rate of mysid during their transfer from daphnia to mysid and from alga through daphnia to mysid. This work emphasizes the importance of tracing the particulate fraction of metal-based engineered nanoparticles when studying their uptake and trophic transfer., (Copyright © 2022. Published by Elsevier Inc.)

To assess the safety of engineered nanomaterials (ENMs) and to evaluate and improve ENMs' targeting ability for medical application, it is necessary to analyze the fate of these materials in biological media. This protocol presents a workflow that allows researchers to determine, characterize and quantify metal-bearing ENMs (M-ENMs) in biological tissues and cells and quantify their dynamic behavior at trace-level concentrations. Sample preparation methods to enable analysis of M-ENMs in a single cell, a cell layer, tissue, organ and physiological media (e.g., blood, gut content, hemolymph) of different (micro)organisms, e.g., bacteria, animals and plants are presented. The samples are then evaluated using fit-for-purpose analytical techniques e.g., single-cell inductively coupled plasma mass spectrometry, single-particle inductively coupled plasma mass spectrometry and synchrotron X-ray absorption fine structure, providing a protocol that allows comprehensive characterization and quantification of M-ENMs in biological matrices. Unlike previous methods, the protocol uses no fluorescent dyes or radiolabels to trace M-ENMs in biota and enables analysis of most M-ENMs at cellular, tissue and organism levels. The protocols can be applied by a wide variety of users depending on the intended purpose of the application, e.g., to correlate toxicity with a specific particle form, or to understand the absorption, distribution and excretion of M-ENMs. The results facilitate an understanding of the biological fate of M-ENMs and their dynamic behavior in biota. Performing the protocol may take 7-30 d, depending on which combination of methods is applied., (© 2022. Springer Nature Limited.)

Ingested nanomaterials are exposed to many metabolites that are produced, modified, or regulated by members of the enteric microbiota. The adsorption of these metabolites potentially affects the identity, fate, and biodistribution of nanomaterials passing the gastrointestinal tract. Here, we explore these interactions using in silico methods, focusing on a concise overview of 170 unique enteric microbial metabolites which we compiled from the literature. First, we construct quantitative structure-activity relationship (QSAR) models to predict their adsorption affinity to 13 metal nanomaterials, 5 carbon nanotubes, and 1 fullerene. The models could be applied to predict log k values for 60 metabolites and were particularly applicable to 'phenolic, benzoyl and phenyl derivatives', 'tryptophan precursors and metabolites', 'short-chain fatty acids', and 'choline metabolites'. The correlations of these predictions to biological surface adsorption index descriptors indicated that hydrophobicity-driven interactions contribute most to the overall adsorption affinity, while hydrogen-bond interactions and polarity/polarizability-driven interactions differentiate the affinity to metal and carbon nanomaterials. Next, we use molecular dynamics (MD) simulations to obtain direct molecular information for a selection of vitamins that could not be assessed quantitatively using QSAR models. This showed how large and flexible metabolites can gain stability on the nanomaterial surface via conformational changes. Additionally, unconstrained MD simulations provided excellent support for the main interaction types identified by QSAR analysis. Combined, these results enable assessing the adsorption affinity for many enteric microbial metabolites quantitatively and support the qualitative assessment of an even larger set of complex and biologically relevant microbial metabolites to carbon and metal nanomaterials.

Multigenerational toxicity tests provide more sensitive measures of population-level effects than conventional single-generation tests. Particularly for stressors which exhibit slow uptake rates (e.g. nanomaterials), multigenerational tests may also provide a more realistic representation of natural exposure scenarios. To date, the inherently high costs and labor intensity have however limited the use of multigenerational toxicity tests and thereby their incorporation in environmental risk assessment. The aim of the present study was therefore to determine to what extent short(er) term endpoints which are conventionally measured in Daphnia magna toxicity tests hold predictive capacity towards reproduction measured over longer timescales, including multiple generations. To assess this, a case-study was performed in which effects of TiO 2 nanoparticles (0, 0.02, 0.2, 2 and 5 mg L -1 ) on D. magna life-history traits were assessed over five generations. Additionally, it was determined whether offspring derived from exposed parents exhibited sustained adverse effects when rearing them in clean (non-exposed) media after each generation of exposure. The present study showed that although various life-history traits correlate with the total reproductive output in the same- and subsequent generation under non-exposed conditions, these correlations were decoupled in presence of exposure to nTiO 2 . In addition, it was found that nTiO 2 can induce adverse effects on population relevant endpoints at concentrations 1-2 orders of magnitude lower than previously found (i.e. 0.02 mg L -1 ), and close to the range of concentrations occurring in natural freshwater ecosystems., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Screening and prioritization of chemicals is essential to ensure that available evaluation capacity is invested in those substances that are of highest concern. We, therefore, recently developed structural similarity models that evaluate the structural similarity of substances with unknown properties to known Substances of Very High Concern (SVHC), which could be an indication of comparable effects. In the current study the performance of these models is improved by (1) separating known SVHCs in more specific subgroups, (2) (re-)optimizing similarity models for the various SVHC-subgroups, and (3) improving interpretability of the predicted outcomes by providing a confidence score. The improvements are directly incorporated in a freely accessible web-based tool, named the ZZS similarity tool: https://rvszoeksysteem.rivm.nl/ZzsSimilarityTool. Accordingly, this tool can be used by risk assessors, academia and industrial partners to screen and prioritize chemicals for further action and evaluation within varying frameworks, and could support the identification of tomorrow's substances of concern., (© 2022 The Authors. Journal of Computational Chemistry published by Wiley Periodicals LLC.)

Many host-microbiota interactions depend on the recognition of microbial constituents by toll-like receptors of the host. The impacts of these interactions on host health can shape the hosts response to environmental pollutants such as nanomaterials. Here, we assess the role of toll-like receptor 2 (TLR2) signaling in the protective effects of colonizing microbiota against silver nanoparticle (nAg) toxicity to zebrafish larvae. Zebrafish larvae were exposed to nAg for two days, from 3 to 5 days post-fertilization. Using an il1ß-reporter line, we first characterized the accumulation and particle-specific inflammatory effects of nAg in the total body and intestinal tissues of the larvae. This showed that silver gradually accumulated in both the total body and intestinal tissues, yet specifically caused particle-specific inflammation on the skin of larvae. Subsequently, we assessed the effects of microbiota-dependent TLR2 signaling on nAg toxicity. This was done by comparing the sensitivity of loss-of-function zebrafish mutants for TLR2, and each of the TLR2-adaptor proteins MyD88 and TIRAP (Mal), under germ-free and microbially-colonized conditions. Irrespective of their genotype, microbially-colonized larvae were less sensitive to nAg than their germ-free siblings, supporting the previously identified protective effect of microbiota against nAg toxicity. Under germ-free conditions, tlr2, myd88 and tirap mutants were equally sensitive to nAg as their wildtype siblings. However, when colonized by microbiota, tlr2 and tirap mutants were more sensitive to nAg than their wildtype siblings. The sensitivity of microbially-colonized myd88 mutants did not differ significantly from that of wildtype siblings. These results indicate that the protective effect of colonizing microbiota against nAg-toxicity to zebrafish larvae involves TIRAP-dependent TLR2 signaling. Overall, this supports the conclusion that host-microbiota interactions affect nanomaterial toxicity to zebrafish larvae., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

In recent years, various ecotoxicological test guidelines and (technical) guidance documents have been evaluated and updated with regard to their applicability to nanomaterials (NMs). Several of these have currently reached official regulatory status. Ensuring their harmonized implementation with previously recognized methods for ecotoxicity testing of chemicals is a crucial next step towards effective and efficient regulation of NMs. In the present study, we evaluated the feasibility of assessing multigenerational effects in the first generation of offspring derived from exposed Daphnia magna whilst maintaining test conditions in accordance with regulatory test guidelines and guidance documents for NMs. To do so, we integrated the recommendations for ecotoxicological testing of NMs as defined in OECD Guidance Document 317 into an extended long-term D. magna reproduction test method (OECD Test Guideline 211) and assessed effects of two poorly soluble NMs (nTiO 2 and nCeO 2 ). Our results show adverse effects on life-history parameters of D. magna exposed to the selected nanomaterials within the range of reported environmental concentrations. We argue that conforming to OECD test guidelines and accompanying guidance for nanomaterials is feasible when performing D. magna reproduction tests and can minimize unnecessary duplication of similar experiments, even when extensions to the standardized test setup are added., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Safe-and-sustainable-by-design (SSbD) is a concept that takes a systems approach by integrating safety, sustainability, and functionality throughout a product's the life cycle. This paper proposes a framework based on a prospective life cycle assessment for early safety and sustainability assessment. The framework's purpose is to identify environmental sustainability and toxicity hotspots early in the innovation process for future SSbD applicability. If this is impossible, key performance indicators are assessed. Environmental sustainability aspects, such as global warming potential (GWP) and cumulative energy demand (CED), and toxicity aspects, such as human toxicity potential and freshwater ecotoxicity potential, were assessed upon applying the framework on a case study. The case study regarded using nano-titanium dioxide (P25-TiO 2 ) or a modified nano-coated version (Cu 2 O-coated/P25-TiO 2 ) as photocatalysts to produce hydrogen from water using sunlight. Although there was a decrease in environmental impact (GWP and CED), the modified nano-coated version had a relatively higher level of human toxicity and freshwater eco-toxicity. For the presented case study, SSbD alternatives need to be considered that improve the photocatalytic activity but are not toxic to the environment. This case study illustrates the importance of performing an early safety and environmental sustainability assessment to avoid the development of toxic alternatives.

Similarity assessment is one of the means of optimally using scarcely available experimental data on the fate and hazards of nanoforms (NFs) for regulatory purposes. For a set of NFs that are shown to be similar it is allowed in a regulatory context to apply the information available on any of the NFs within the group to the whole set of NFs. Obviously, a proper justification for such a similarity assessment is to be provided. Within the context of exemplifying such a justification, a case study was performed aimed at assessing the similarity of a set of spherical metallic NFs that different with regard to chemical composition (three metals) and particle size (three different sizes). The endpoints of assessment were root elongation and biomass increase of lettuce (Lactuca sativa L.) seedlings and exposure assessment was performed in order to express the actual exposure concentration in terms of time-weighted average particle concentrations. The results of the study show that for the specific endpoints assessed, chemical composition is driving NF toxicity and this is mostly due to impacts on the fate of the NFs. On the other hand, particle size of Cu NFs had a negligible impact on the dose-response relationships for the specific endpoints assessed. It is thus concluded that hazard data available on spherical Cu NF tested in our case can be used to inform on the hazards of any spherical Cu NF within the size range of 25-100 nm, but only applies for the certain endpoints. Also, toxicity data for the Cu 2+ -ion are suited for such a similarity assessment., (Copyright © 2022 The Authors. Published by Elsevier B.V. All rights reserved.)

The European Green Deal outlines ambitions to build a more sustainable, climate neutral, and circular economy by 2050. To achieve this, the European Commission has published the Chemicals Strategy for Sustainability: Towards a Toxic-Free Environment, which provides targets for innovation to better protect human and environmental health, including challenges posed by hazardous chemicals and animal testing. The European project PATROLS (Physiologically Anchored Tools for Realistic nanOmateriaL hazard aSsessment) has addressed multiple aspects of the Chemicals Strategy for Sustainability by establishing a battery of new approach methodologies, including physiologically anchored human and environmental hazard assessment tools to evaluate the safety of engineered nanomaterials. PATROLS has delivered and improved innovative tools to support regulatory decision-making processes. These tools also support the need for reducing regulated vertebrate animal testing; when used at an early stage of the innovation pipeline, the PATROLS tools facilitate the safe and sustainable development of new nano-enabled products before they reach the market., (© 2022 The Authors. Small published by Wiley-VCH GmbH.)

Various modern products have metallic nanoparticles (MNPs) embedded to enhance products performance. Technological advances enable nowadays even multiple hybrid nanoparticles. Consequently, the future co-release of multiple MNPs will inevitably result in the presence of MNP mixtures in the environment. An important question is if the responses of mixtures of MNPs can be dealt with in a similar way as with the responses of biota to mixtures of metal salts. Moreover, natural organic matter (NOM) is an important parameter affecting the behavior and effect of MNPs. Herein, we determined the joint toxicity and accumulation of copper nanoparticles (CuNPs) and zinc oxide nanoparticles (ZnONPs) in Daphnia magna in the absence and presence of Suwannee River natural organic matter (SR-NOM), compared to the joint toxicity and accumulation of corresponding metal salts. The results of toxicity testing showed that the joint toxicity of CuNPs + ZnONPs was greater than the single toxicity of CuNPs or ZnONPs. The joint toxic action of CuNPs + ZnONPs was additive or more-than-additive for D. magna. A similar pattern was found in the toxicity of the mixtures of Cu- and Zn-salts from the literature data. The presence of SR-NOM had no significant impact on the joint toxicity of CuNPs + ZnONPs. The calculated component-specific contribution to overall toxicity indicated that SR-NOM increased the relative contribution of dissolved ions released from the MNPs to the toxicity of the binary mixtures at high-effect concentrations of individual MNPs. Moreover, dissolved Zn-ions released from the ZnONPs were found to dominate the joint toxicity of CuNPs + ZnONPs in the presence of SR-NOM. Furthermore, the results of the accumulation experiment displayed that the presence of SR-NOM significantly enhanced the accumulation of either CuNPs or ZnONPs in D. magna exposed to the MNP mixtures., (Copyright © 2021 Elsevier Ltd. All rights reserved.)