As a result of ever increasing applications, nanoparticles will eventually end up in the environment. However, currently no common principle has been established to help understand the toxicity of nanoparticles (NPs) across species. Therefore, it is difficult to estimate the potential risks of nanoparticles to untested species in the environment. The authors exposed 4 different sizes of copper nanoparticles (CuNPs) and 1 submicron-sized copper particle to 5 cladoceran species (Daphnia magna, Daphnia pulex, Daphnia galeata, Ceriodaphnia dubia, and Chydorus sphaericus) to investigate whether morphological attributes of species can help to assess the acute toxicity of CuNPs across species. The results showed that rod-shaped CuNPs caused much lower toxicity to all species than spherical CuNPs. Both the particles and ions contributed to the total toxicity of the CuNP suspensions. Moreover, the toxicity caused by particles in 5 different copper suspensions increases with decreasing body length, surface area, and body volume of neonates of 5 cladoceran species. Especially the correlations between body volume of the 5 cladoceran species tested and the corresponding toxicity caused by 5 different CuNPs were statistically significant, and in all cases radj (2) was higher than 0.51 (p < 0.001). The highest correlation was found between body volume and the toxicity of the 78-nm CuNPs (radj (2) = 0.95, p < 0.001). To conclude, the correlations between attributes of cladoceran species and the toxicity of CuNPs reported in the present study evoke the possibility to assess and extrapolate the toxicity of nanoparticles across species with similar attributes.
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http://dx.doi.org/10.1002/etc.3000 | DOI Listing |
Proc Biol Sci
January 2025
Ecosystems and Global Change Group, Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, UK.
Understanding how species adapt to environmental change is necessary to protect biodiversity and ecosystem services. Growing evidence suggests species can adapt rapidly to novel selection pressures like predation from invasive species, but the repeatability and predictability of selection remain poorly understood in wild populations. We tested how a keystone aquatic herbivore, , evolved in response to predation pressure by the introduced zooplanktivore .
View Article and Find Full Text PDFInt J Mol Sci
January 2025
Department of Chemical Engineering, Faculty of Engineering and Science, Universidad de La Frontera, Avenida Francisco Salazar, 01145, P.O. Box 54-D, Temuco 4811230, Chile.
Over recent decades, Northern Patagonia in Chile has seen significant growth in agriculture, livestock, forestry, and aquaculture, disrupting lake ecosystems and threatening native species. These environmental changes offer a chance to explore how anthropization impacts zooplankton communities from a molecular-ecological perspective. This study assessed the anthropogenic impact on by comparing its proteomes from two lakes: Llanquihue (anthropized) and Icalma (oligotrophic).
View Article and Find Full Text PDFMol Ecol
February 2025
Department of Biology, University of Virginia, Charlottesville, Virginia, USA.
Shared polymorphisms, loci with identical alleles across species, are of unique interest in evolutionary biology as they may represent cases of selection maintaining ancient genetic variation post-speciation, or contemporary selection promoting convergent evolution. In this study, we investigate the abundance of shared polymorphism between two members of the Daphnia pulex species complex. We test whether the presence of shared mutations is consistent with the action of balancing selection or alternative hypotheses such as hybridization, incomplete lineage sorting or convergent evolution.
View Article and Find Full Text PDFSci Total Environ
January 2025
School of Pharmacy, Lanzhou University, Lanzhou 730000, China; Hubei Key Laboratory of Environmental and Health Effects of Persistent Toxic Substances, School of Environment and Health, Jianghan University, Wuhan 430056, China. Electronic address:
The study aimed to assess the impacts of ionic liquids (ILs) as innovative alternatives to traditional organic solvents on aquatic environments and human health. Five machine learning methods, including multiple linear regression (MLR), partial least squares regression (PLS), random forest regression (RF), support vector regression (SVR), and extreme gradient boosting (XGBoost), were used to construct the prediction models of the toxicity of ILs to D. magna, D.
View Article and Find Full Text PDFEnviron Sci Technol
January 2025
Centre for Environmental Research and Justice (CERJ), School of Biosciences, The University of Birmingham, Birmingham B15 2TT, U.K.
The assessment and regulation of chemical toxicity to protect human health and the environment are done one chemical at a time and seldom at environmentally relevant concentrations. However, chemicals are found in the environment as mixtures, and their toxicity is largely unknown. Understanding the hazard posed by chemicals within the mixture is critical to enforce protective measures.
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