2019
DOI: 10.1186/s12302-019-0268-z
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Evaluation of microbial shifts caused by a silver nanomaterial: comparison of four test systems

Abstract: Background: Before chemicals, pesticides and biocides are registered and approved, their effects on soil microorganisms must be tested, specifically their impact on nitrogen transformation. Following a request from the European Food Safety Authority (EFSA), the Panel on Plant Protection Products and their Residues provided an opinion document evaluating the science behind the risk assessment of plant protection products in the context of soil-dwelling organisms. The EFSA document concludes that the most releva… Show more

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Cited by 9 publications
(4 citation statements)
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“…While characterizing the difference to the control may be similar to determining a no‐effect concentration, some authors have further adapted this into a dose–response format. Hund‐Rinke et al (2019) calculated bacterial community similarity to the control treatment following silver nanoparticle exposure and plotted this against the dose gradient. This enabled a whole‐community‐level view of increasing dissimilarity to the control treatment within increasing dosage of the test material.…”
Section: Discussionmentioning
confidence: 99%
“…While characterizing the difference to the control may be similar to determining a no‐effect concentration, some authors have further adapted this into a dose–response format. Hund‐Rinke et al (2019) calculated bacterial community similarity to the control treatment following silver nanoparticle exposure and plotted this against the dose gradient. This enabled a whole‐community‐level view of increasing dissimilarity to the control treatment within increasing dosage of the test material.…”
Section: Discussionmentioning
confidence: 99%
“…The better prediction performance of the RF model may reflect the modest number of features in the current datasets. The results indicate that there are complex nonlinear relationships between the effect size of NMs and each feature variable, including NM characteristics, soil properties, and exposure conditions (Hund-Rinke et al, 2019;Kim et al, 2013). Although both machine-learning models had acceptable performance, there is room for improvement in accuracy for practical applications.…”
Section: Effective Machine-learning Prediction Of the Effects Of Nms ...mentioning
confidence: 96%
“…With an enrichment of proteobacteria, cytophagales, and spirobacteria, next-generation sequencing demonstrated a shift in the microbial population and variable sensitivity of bacterial groups. Some nitrifiers (nitrosomonadales) were adversely impacted, and this correlated with the reduction of PAO activity [119].…”
Section: Silvermentioning
confidence: 99%
“…The majority of the information that has been published in this field comes from studies about the effects of nanopesticides that are formed of silver on bacteria and microorganisms that are not intended targets. The authors of the reference [119] used biosolids and AgNPs to modify a clayey SiO 2 with low pH (SiO 2 73, Silt 22 and Clay 5%, pH 5.6, and small amounts of organic components) to a target concentration of 0.19 to 15 mg•kg −1 soil (particle size 15 nm). This mixture was kept at 22 • C in the dark for 30 days.…”
Section: Silvermentioning
confidence: 99%