The conventional Hill equation model is suitable to fit dose-response data obtained from performing (eco)toxicity assays. Models based on quasi-quantitative structure-activity relationships (QSARs)... Show moreThe conventional Hill equation model is suitable to fit dose-response data obtained from performing (eco)toxicity assays. Models based on quasi-quantitative structure-activity relationships (QSARs) to estimate the Hill coefficient ( n H ) ${n}_{{\rm{H}}})$ were developed with the aim of predicting the response of the invertebrate species Daphnia magna to exposure to metal-based nanomaterials. Descriptors representing the pristine properties of nanoparticles and media conditions were coded to a quasi-simplified molecular input line entry system and correlated to experimentally derived values of n H ${n}_{{\rm{H}}}$. Monte Carlo optimization was used to model the set of n H ${n}_{{\rm{H}}}$ values, and the model was trained on the basis of reported dose-response relationships of 60 data sets (n = 367 individual response observations) of 11 metal-based nanomaterials as obtained from 20 literature reports. The model simulates the training data well, with only 2.3% deviation between experimental and modeled response data. The technique was employed to predict the dose-response relationships of 15 additional data sets (n = 72 individual observations) not included in model development of seven metal-based nanomaterials from 10 literature reports, with an average error of 3.5%. Combining the model output with either the median effective concentration value or any other known effect level as obtained from experimental data allows the prediction of full dose-response curves of D. magna immobilization. This model is an accurate screening tool that allows the determination of the shape and slope of dose-response curves, thereby greatly reducing experimental effort in case of novel advanced metal-based nanomaterials or the prediction of responses in altered exposure media. This screening model is compliant with the 3Rs (replacement, reduction, and refinement) principle, which is embraced by the scientific and regulatory communities dealing with nano-safety. Environ Toxicol Chem 2022;00:1-12. (c) 2022 The Authors. Environmental Toxicology and Chemistry published by Wiley Periodicals LLC on behalf of SETAC. Show less
For the soluble metallic nanoparticles (NPs), which forms (particles [NP(particle)] vs. dissolved ions [NP(ion)]) are the main cause of toxicity of the NP suspension (NP(total)) remains uncertain.... Show moreFor the soluble metallic nanoparticles (NPs), which forms (particles [NP(particle)] vs. dissolved ions [NP(ion)]) are the main cause of toxicity of the NP suspension (NP(total)) remains uncertain. In the present study, soybean was exposed to Cu NPs in a hydroponic system to determine how natural organic matter (NOM; 10 mg/l) and concentration of Cu NP(total) (2-50 mg/l) affect the relative contributions of Cu NP(particle) and Cu NP(ion) to the overall toxicity. We found that NOM mitigated the phytotoxicity of Cu NP(particle) more significantly than that of Cu salt. When no NOM was added, Cu NP(particle) rather than Cu NP(ion) was the main contributor to the observed toxicity regardless of the concentration of Cu NP(total). However, NOM tended to reduce the relative contribution of Cu NP(particle) to the toxicity of Cu NP(total). Especially at a low concentration of Cu NP(total) (2 mg/l), the toxicity of Cu NP(total) mainly resulted from Cu NP(ion) in the presence of NOM (accounting for >= 70% of the overall toxicity). This might be attributable to the combined effects of increased dissolution of Cu NPs and steric-electrostatic hindrance between Cu NP(particle) and the soybean roots caused by NOM. Fulvic acids (FAs) tended to reduce the role of Cu NP(particle) in the overall toxicity more effectively than humic acids (HAs), which might partially be due to the higher extent of Cu NP dissolution on FA treatment than in HA treatment. Our results suggest that because of the relatively low metallic NP concentration and the presence of NOM in natural water, NP(ion) are likely problematic, which can inform management and mitigation actions. Environ Toxicol Chem 2021;00:1-11. (c) 2021 SETAC Show less
Jasperse, L.; Levin, M.; Rogers, K.; Perkins, C.; Bosker, T.; Griffitt, R.J.; ... ; De Guise, S. 2019
Corrigendum to:Jasperse L, Levin M, Rogers K, Perkins C, Bosker T, Griffitt RJ, Sepúlveda MS, De Guise S. 2019. Transgenerational effects of polycyclic aromatic hydrocarbon exposure on sheepshead... Show moreCorrigendum to:Jasperse L, Levin M, Rogers K, Perkins C, Bosker T, Griffitt RJ, Sepúlveda MS, De Guise S. 2019. Transgenerational effects of polycyclic aromatic hydrocarbon exposure on sheepshead minnows (Cyprinodon variegatus). Environ Toxicol Chem 38:638‐649.DOI: 10.1002/etc.4340. Show less
Jasperse, L.; Levin, M.; Rogers, K.; Perkins, C.; Bosker, T.; Griffitt, R.J.; ... ; Guise, S. de 2019
Ecosystem quality is an important area of protection in life cycle impact assessment (LCIA). Chemical pollution has adverse impacts on ecosystems at the global scale. To improve methods for... Show moreEcosystem quality is an important area of protection in life cycle impact assessment (LCIA). Chemical pollution has adverse impacts on ecosystems at the global scale. To improve methods for assessing ecosystem impacts, the Life Cycle Initiative hosted at the United Nations Environment Programme established a task force to evaluate the state-of-the-science in modelling chemical exposure of organisms and resulting ecotoxicological effects for use in LCIA. Outcome of the task force work will be global guidance and harmonization by recommending changes to the existing practice in exposure and effect modelling in ecotoxicity characterization. These changes reflect the current science and ensure stability of recommended practice. Recommendations must work within the needs of LCIA in terms of (a) operating on information from any inventory reporting chemical emissions with limited spatiotemporal information, (b) applying best estimates rather than conservative assumptions to ensure unbiased comparison with results for other impact categories, and (c) yielding results that are additive across substances and life cycle stages and allow a quantitative expression of damage to the exposed ecosystem. Here, we report the current framework as well as discuss research questions identified in a roadmap. Primary research questions relate to the approach for ecotoxicological effect assessment, the need to clarify the method's scope and interpretation of its results, the need to consider additional environmental compartments and impact pathways, and the relevance of effect metrics other than the currently applied geometric mean of toxicity effect data across species. Because they often dominate ecotoxicity results in LCIA, metals pose a specific focus, which includes consideration of their possible essentiality and changes in environmental bioavailability. We conclude with a summary of key questions along with preliminary recommendations to address them as well as open questions that require additional research efforts. This article is protected by copyright. All rights reserved. Show less
