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Within EU FP7 project NANOVALID, the (eco)toxicity of 7 well-characterized engineered nanomaterials (NMs) was evaluated by 15 bioassays in 4 laboratories. The highest tested nominal concentration of NMs was 100 mg/l. The panel of the bioassays yielded the following toxicity order: Ag > ZnO > CuO > TiO2 > MWCNTs > SiO2 > Au. Ag, ZnO and CuO proved very toxic in the majority of assays, assumingly due to dissolution. The latter was supported by the parallel analysis of the toxicity of respective soluble metal salts. The most sensitive tests/species were Daphnia magna (towards Ag NMs, 24-h EC50 = 0.003 mg Ag/l), algae Raphidocelis subcapitata (ZnO and CuO, 72-h EC50 = 0.14 mg Zn/l and 0.7 mg Cu/l, respectively) and murine fibroblasts BALB/3T3 (CuO, 48-h EC50 = 0.7 mg Cu/l). MWCNTs showed toxicity only towards rat alveolar macrophages (EC50 = 15.3 mg/l) assumingly due to high aspect ratio and TiO2 towards R. subcapitata (EC50 = 6.8 mg Ti/l) due to agglomeration of TiO2 and entrapment of algal cells. Finally, we constructed a decision tree to select the bioassays for hazard ranking of NMs. For NM testing, we recommend a multitrophic suite of 4 in vitro (eco)toxicity assays: 48-h D. magna immobilization (OECD202), 72-h R. subcapitata growth inhibition (OECD201), 30-min Vibrio fischeri bioluminescence inhibition (ISO2010) and 48-h murine fibroblast BALB/3T3 neutral red uptake in vitro (OECD129) representing crustaceans, algae, bacteria and mammalian cells, respectively. Notably, our results showed that these assays, standardized for toxicity evaluation of "regular" chemicals, proved efficient also for shortlisting of hazardous NMs. Additional assays are recommended for immunotoxicity evaluation of high aspect ratio NMs (such as MWCNTs).
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http://dx.doi.org/10.1080/17435390.2016.1196251 | DOI Listing |
Driven by eutrophication and global warming, the occurrence and frequency of harmful cyanobacteria blooms (CyanoHABs) are increasing worldwide, posing a serious threat to human health and biodiversity. Early warning enables precautional control measures of CyanoHABs within water bodies and in water works, and it becomes operational with high frequency in situ data (HFISD) of water quality and forecasting models by machine learning (ML). However, the acceptance of early warning systems by end-users relies significantly on the interpretability and generalizability of underlying models, and their operability.
View Article and Find Full Text PDFPest Manag Sci
September 2025
AgResearch Ltd, Tuhiraki, Lincoln, New Zealand.
Background: Conventional weed risk assessments (WRAs) are time-consuming and often constrained by species-specific data gaps. We present a validated, algorithmic alternative, the model, that integrates climatic suitability ( ), weed-related publication frequency (P) and global occurrence data ( ), using publicly available databases and artificial intelligence (AI)-assisted text screening with a large language model (LLM).
Results: The model was tested against independent weed hazard classifications for New Zealand and California.
J Hazard Mater
September 2025
Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Shuangqing RD 18, Beijing 100085, China; University of Chinese Academy of Sciences, Yuquan RD 19 a, Beijing 100049, China. Electronic address:
Epoxiconazole (EPX) is widely applied to control various fungal diseases in crops. However, the toxicological effects of EPX on reptiles remain unknown, especially at the enantiomer level. In this study, lizards were repeatedly exposed to rac-EPX, (+)-EPX, and (-)-EPX at doses of 10 and 100 mg/kg bw for 21 days.
View Article and Find Full Text PDFJ Hazard Mater
September 2025
Department of Civil & Environmental Engineering, National University of Singapore, E1A-07-03, 1 Engineering Drive 2, Singapore 117576, Singapore; NUS Environmental Research Institute, National University of Singapore, 1 Create way, Create Tower, #15-02, Singapore 138602, Singapore.
Antibiotic resistance (AR), driven by antibiotics as emerging pollutants, has become a critical global health threat, jeopardizing both environmental and human health. The persistence and spread of AR in aquatic ecosystems are governed by the intricate interplay between antibiotics, antibiotic resistance genes (ARGs), and antibiotic-resistant bacteria (ARB), which collectively influences its occurrence, transportation, and fate in aquatic ecosystems. However, most assessments focus primarily on antibiotics and ARGs, often relying on single-factor criteria while overlooking critical influence factors such as ARG forms, non-antibiotic chemicals, antibiotic pressure, and microbial competition.
View Article and Find Full Text PDFJ Hazard Mater
August 2025
Department of Environmental Science, Kangwon National University, Chuncheon, Gangwon-do 24341, Republic of Korea; Interdisciplinary Program in Earth Environmental System Science & Engineering, Kangwon National University, Chuncheon, Gangwon-do 24341, Republic of Korea; Gangwon particle pollution res
This study evaluates the oxidative potential (OP) of PM and its chemical drivers across three contrasting environments in South Korea: a residential area, a cement factory, and a charcoal kiln facility. Mass-normalized OP (OPm, reflecting intrinsic particle reactivity) ranged from 9.5 to 13.
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