NanoImpact最新文献

Gold nanomaterials (GNMs) have unique optical properties with less antigenicity, and their physicochemical properties have strong relation with an immunological response at bio-interface including antigenicity. An interpretation of this correlation would significantly impact on the clinical and theranostic applications of GNMs. Herein, we studied the effect of GNMs morphology on the cytotoxicity (in-vitro), innate immune responses, hepatotoxicity, and nephrotoxicity (in-vivo studies) using gold nano-cups (GNCs), porous gold nanospheres (PGNSs) and solid gold nano particles (SGNPs) coated with the same ligand to ensure similar surface chemistry. The cytotoxicity was assessed via sulfo-rhodamine B (SRB) assay, and the cytotoxicity data showed that morphological features at nanoscale dimensions like surface roughness and hollowness etc. have a significant impact on cellular viability. The biochemical and histopathological study of liver and kidney tissues also showed that all GNMs did not show any toxicity even at high concentration (100 μL). The relative quantification of cytokine gene expression of TNF-α, IFN-γ, IL-4, 1L-6, and 1L-17 (against each morphology) was checked after in-vivo activation in mice. Among the different nanogold morphologies, PVP stabilized GNCs (PVP-GNCs) showed the highest release of pro-inflammatory cytokines, which might be due to their high surface energy and large surface area for exposure as compared to other nanogold morphologies studied. The pro-inflammatory cytokine release could be suppressed by coating with some anti-inflammatory polymer, i.e., inulin. The in-vitro results of pro-inflammatory (TNF-α, IL-1) cytokines also suggested that all GNMs may induce activation of macrophages and Th1 immune response. The in-vivo activation results showed a decrease in mRNA expression of the cytokines (TNF-α, IFN-γ, IL-4, 1L-6 and 1L-17). Based on these findings, we proposed that the shape and morphology of GNMs control their immune response at nano-bio interface, and it must be considered while designing their role for different biomedical applications like immuno-stimulation and bio-imaging.

Biochar and zeolite have been demonstrated effective to remove heavy metals in soil; however, the effect of combined application of the both materials on the fraction of Cd and soil-plant system are largely unknown. Cd fractions in soil, growth and Cd uptake of Pak Choi were measured after the combined application of biochar (0, 5, 10 and 20 g·kg⁻¹) and nano-zeolite (0, 5, 10, 20 g·kg⁻¹) by pot experiment. Results showed that both single and combined application reduced the exchangeable Cd in soil and improved the plant growth. However, combined application of 20 g·kg⁻¹ biochar with 10 g·kg⁻¹ nano-zeolite showed the strongest effect, with the residual Cd in soil increased by 214% as compared with control. 20 g·kg⁻¹ biochar with 10 g·kg⁻¹ nano-zeolite Mechanic studies showed that this combination enhanced the antioxidant system, with the SOD, CAT and POD activities enhanced by 56.1%, 133.3% and 235.3%, respectively. The oxidative stress was reduced correspondingly, as shown by the reduced MDA contents (by 46.7%). This combination also showed the best efficiency in regulating soil pH, organic matter and soil enzymes thus improving the plant growth. This study suggests that combined application various materials such as biochar and nano-zeolite may provide new strategies for reducing the bioavailability of Cd in soil and thus the accumulation in edible plants.

To supply adequate food, the ongoing and unrestrained administration of nitrogen fertilizer to agricultural fields is polluting the climate and living organisms. On the other hand, the agriculture sector urgently needs a technological upgrade to effectively confront hunger and poverty. Here, we report a rapid synthesis of zinc and magnesium-doped hydroxyapatite-urea nanohybrids for slow release and delivery of nitrogen to wheat and rice crops. Nanohybrids slowly release nitrogen for up to six weeks compared to the burst release of nitrogen from urea, and their use substantially reduces, by at least 3.8 times, ammonia emissions into the environment compared with that of urea fertilizer. A half‑nitrogen dose applied as multi-nutrient complexed nanohybrids maintained crop growth, yield, and nutritional compositions in wheat and subsequent rice crops. Nanohybrids enhanced the wheat crop yield and nitrogen uptake by 22.13% and 58.30%, respectively. The synthesized nitrogen nanohybrids remained in the soil for two continuous crop cycles, reduced ammonia volatilization, and achieved nitrogen delivery to the crops. Additionally, soil dehydrogenase activity (534.55% above control) and urease activities (81.82% above control) suggest that nanohybrids exhibited no adverse impact on soil microorganisms. Our comprehensive study demonstrates the advantages of ‘doping’ as a method for tailoring hydroxyapatite nanoparticles properties for extended agricultural and environmental applications. The use of nanohybrids substantially reduced greenhouse gas emissions and enabled the reduction, by half, of nitrogen inputs into the agricultural fields. This study, therefore, reports a novel nano-enabled platform of engineered hydroxyapatite-urea nanohybrids as a nitrogen fertilizer for efficient nitrogen delivery that results in improved crop growth while minimizing environmental pollution.

Bio-inspired nanoparticles, including metallic, micelles, and polymeric, have been explored as a novel tool in the quest for effective and safe agrochemicals. Although nanoparticles (NPs) are being rapidly investigated for their usefulness in agricultural production and protection, little is known about the behaviour and interaction of oil-in-water micelle nanoparticles or nano-micelles (NM) with plants. We loaded a bio-based resin inherent of tree from the Pinaceae family as active material and produced stable nano-micelles using a natural emulsifier system. Here, we show that foliar-applied nano-micelle can translocate in two dicot plants belonging to diverse families (Coriandrum sativum -Apiaceae and Trigonella foenumgraecum -Fabaceae) via similar mode. Fluorescent-tagged NM (average diameter 11.20nm) showed strong signals and higher intensities as revealed by confocal imaging and exhibited significant adhesion in leaf compared to control. The NM subsequently translocates to other parts of the plants. As observed by SEM, the leaf surface anatomies revealed higher stomata densities and uptake of NM by guard cells; furthermore, larger extracellular spaces in mesophyll cells indicate a possible route of NM translocation. In addition, NM demonstrated improved wetting-spreading as illustrated by contact angle measurement. In a field bioassay, a single spray application of NM offered protection from aphid infestation for at least 9 days. There were no signs of phytotoxicity in plants post-application of NM. We conclude that pine resin-based nano-micelle provides an efficient, safe, and sustainable alternative for agricultural applications.

Background

Nanoparticles have been employed as nanopesticides for pest control in agriculture. However, the harmful effects of their chemical synthesis on human and environmental health have resulted in increased use of green synthetic approaches, including the use of plant extracts. The brown planthopper, Nilaparvata lugens (Stål) (BPH), is a severe pest of rice plants (Oryza sativa L.), especially in Asia. It is usually controlled chemically but has developed resistance against many insecticides.

Results

In this study, we synthesized metallic silver (Ag-NPs) and copper-oxide (CuO-NPs) nanoparticles using the exogenous phytohormone, gibberellic acid (GA₃), as a reducing agent. We then sprayed them separately on rice plants and BPH together and evaluated their effects on the plants and insects. SEM and TEM images showed that the synthesis was successful, indicated by the sizes (25–60 nm), uniform shape and spherical and cubical structures of Ag-NPs, as well as by the rugby sheet-like of CuO-NPs with lateral sizes of 150–340 nm and thickness of 30–70 nm. Independent applications of the nanoparticles and GA₃ on rice plants induced different volatile profiles, of which the highest number emitted was under Ag-NPs, including the highest emission of linalool. Transcriptome analysis showed that Ag-NPs-treated rice plants showed different transcriptome profiles compared to the control, 24 h after treatment, including the upregulation of the linalool synthase gene, genes of plants transcription factors such as WRKY, bHLH and NAC and other genes involved in plant defense responses. In all treatments, the mortality rate of BPH increased with an increase in NPs concentrations over time but was prominent under Ag-NPs treatment. The LC₅₀ values for Ag-NPs and CuO-NPs decreased with an increase in time. Also, the nanoparticles increased the activities of protective enzymes (POD, SOD and CAT), inhibited that of detoxification enzymes (A-CHE, ACP and AKP), and reduced total protein concentrations in the BPH.

Conclusions

These results show that synthesizing nanoparticles using phytohormones may be a safer and environmentally friendly option, which also holds promise for controlling the BPH in rice production.

Recently, microplastics (MPs) have been detected in almost all environmental matrices (water, soil, air, biota). Their presence is of concern due to high environmental persistence and their ability to release or bind pollutants. In light of this, the present work aimed to quantify a poorly studied pollutant category associated with MPs: metals. This analysis was conducted on virgin MPs, used as raw materials in the plastics' production process and on environmental MPs taken from the Ofanto river in Southern Italy. The MP samples were initially grouped for colour, shape and ageing and following mineralised by a microwave digestor. The metals and metalloids Pb, Ba, Sb, Sn, Cd, Mo, Se, Zn, Cu, Ni, Co, Cr, Fe, Mn, Ti, Al, V, Ca, K, Mg, Na were subsequently quantified with ICP-MS. All the analysed elements were found on both types of samples (virgin and environmental MPs), with higher concentrations detected on environmental samples (above 14,400 μg/g⁻¹) rather than on pristine ones (above 5000 μg/g⁻¹). Many of these inorganic compounds are probably adsorbed by the surrounding environment, and others are intentionally added during the plastic production process to improve their properties (e.g. additives). Noticeable differences were detected concerning the metal's distribution and amount observed in the two types of MP particles analysed.

Moreover, trace element concentrations were also linked to the colour and shape of the environmental particles analysed. Most abundant levels of metals were quantified on aged black fragments, followed by coloured and transparent fragments and black pellets. Our concluding remarks underline the role of MPs as a vehicle for the transport of metals, with significant differences between the high abundance of these pollutants examined in our particles collected in a freshwater environment and the significantly lower concentrations revealed previously in marine MPs.

Quasi-SMILES is an extension of the traditional SMILES. The classic SMILES is a way to represent the molecular structure. The quasi-SMILES is a way to describe all eclectic conditions that are able to affect the activity of a substance or a mixture. Nano-QSAR for prediction of toxicity of Nano-mixtures built up using the database on the corresponding experimental data. Models built up for five random splits of available data in training and validation sets are suggested. The Monte Carlo method of optimization is applied to calculate so-called optimal descriptors. The optimization was carried out with two criteria of predictive potential. These are the so-called index of ideality of correlation (IIC) and correlation intensity index (CII). Applying CII gives the better statistical quality of models for toxicity Nano-mixtures towards Daphnia Magna. The statistical quality of the best model follows the determination coefficients 0.987 (training set) and 0.980 (validation set).

The use of in silico tools to investigate the interactions between metal (oxide) nanoparticles (NPs) and plant biological responses is preferred because it allows us to understand molecular mechanisms and improve prediction efficiency by saving time, labor, and cost. In this study, four models (C5.0 decision tree, discriminant function analysis, random forest, and stepwise multiple linear regression analysis) were applied to predict the effect of NPs on rice biomass and yield. Nano-specific descriptors (size-dependent molecular descriptors and image-based descriptors) were introduced to estimate the behavior of NPs in plants to appropriately represent the wide space of NPs. The results showed that size-dependent molecular descriptors (e.g., E-state and connectivity indices) and image-based descriptors (e.g., extension, area, and minimum ferret diameter) were associated with the behavior of NPs in rice. The performance of the constructed models was within acceptable ranges (correlation coefficient ranged from 0.752 to 0.847 for biomass and from 0.803 to 0.905 for yield, while the accuracy ranged from 64% to 77% for biomass and 81% to 89% for yield). The developed model can be used to quickly and efficiently evaluate the impact of NPs under a wide range of experimental conditions and sufficient training data.