Dimensional and elemental characterization of environmental nanoparticles is a challenging task that requires the use of a set of complementary analytical methods. Asymmetric flow field-flow fractionation coupled with UV-Vis, multi-angle laser light scattering and ICP-MS detection was applied to study the nanoparticle fraction of a volcanic ash sample, in a Milli-Q water suspension at pH 6.8. It has been shown that the separated by sedimentation nanoparticle fraction of the Klyuchevskoy volcano ash suspension contains 3 polydisperse populations for which size ranges (expressed in gyration radius, rG), hydrodynamic behaviours (evaluated via shape index) and elemental compositions are different. These 3 populations did not dissolve over the 72-h study but aggregated and settled out differently. Thus, the population of particles with gyration radii less then 140 nm (P1), which contained 6% Al2O3 and represented approximately 20% by mass of the nanoparticle fraction, remained in suspension without observable aggregation. The populations P2 and P3, which represented 67% and 13% by mass in the initial suspension, covered the rG range 25-250 nm and contained 17% and 15% Al2O3, respectively. Over time, populations P2 and P3 aggregated and their concentration in suspension at 72 h decreased by approximately 40% compared with the initial suspension. The decrease of these nanoparticle populations occurred either from the beginning of the temporal monitoring (P2) or after 30 h (P3). Aggregation generated a new population (P4) in suspension with rG up to 300 nm and mostly consisting of P2. This population represented only up to 6 to 7% of the nanoparticle fraction and decreased beyond 50 h. As a result, the trace elements present in the nanoparticle fraction and monitored (Cu and La) were also no longer found in the suspension. NVP-TAE684 purchase The results obtained can offer additional insights into the fate of volcanic ash nanoparticles in the environment.The effects of exposure to the herbicide Dicamba (DIC) on tadpoles of two amphibian species, Scinax nasicus and Elachistocleis bicolor, were assessed. Mortality and biochemical sublethal effects were evaluated using acetylcholinesterase (AChE), glutathione S-transferase (GST), glutathione reductase (GR), aspartate aminotransferase (AST), and alanine aminotransferase (ALT) activities and thyroid hormone (T4) levels. The LC50 value at 48h was 0.859 mg L-1 for S. nasicus and 0.221 mg L-1 for E. bicolor tadpoles. After exposure to sublethal DIC concentrations for 48 h, GST activity increased in S. nasicus but significantly decreased in E. bicolor with respect to controls. GR activity decreased only in S. nasicus at all the tested DIC concentrations. AChE activity was significantly inhibited in both S. nasicus and E. bicolor tadpoles at 48 h. DIC also caused significant changes in transamination, as evidenced by an increase in AST and ALT activities in both amphibian species. T4 levels were higher in DIC-treated tadpoles of both species than in controls. The DIC-induced biochemical alterations in glutathione system enzymes and transaminases indicate lesions in liver tissues and cellular function. Moreover, the observed AChE inhibition could lead to the accumulation of acetylcholine, excessively stimulating postsynaptic receptors, and the increase in T4 levels in both species may indicate an overactive thyroid. The commercial DIC formulation showed a high biotoxicity in the two amphibian native species after short-term exposure, controversially differing from the toxicity level indicated in the official fact sheet data. This fact highlights the need for an urgent re-categorization and reevaluation of DIC toxicity in native species.This study increases our understanding of how diet-driven phenotypic plasticity can help non-target aquatic invertebrates deal with chlorpyrifos (CPO) exposure. A bioassay was performed over 6 days with the freshwater shrimp Macrobrachium borellii. Experimental treatments included CPO-treated shrimps (10 μg L-1) were fed with (i) a lipid-rich diet, (ii) a lipid-medium diet, or (iii) a lipid-poor diet. Control shrimps (no CPO exposure) received the same diets as detailed above. Cholinesterases and carboxylesterases were determined as an indicator of CPO exposure. Results showed that diets with a medium-to-high lipid content were important inducers of esterase activity, while shrimps exposed to CPO under a lipid-poor diet showed a significant enzymatic inhibition. This diet-dependent esterase induction suggests that the intake of fatty dietary items mitigates the esterase enzyme inhibition caused by CPO exposure.Rapid environmental microorganism (EM) classification under microscopic images would help considerably identify water quality. Because of the development of artificial intelligence, a deep convolutional neural network (CNN) has become a major solution for image classification. Three popular CNNs, referred to as ResNet50, Vgg16, and Inception-v3, were transferred to identify the EM images present on the Environmental Microorganism Dataset (EMDS), and EMAD was the small dataset, which only has 294 EM images with 21 EM classes. Besides data augmentation, optimizing the fully connected layer of CNN, i.e., both optimally fine-tuned neuron number and dropout rate, was adopted to enhance the performance produced by CNN. The discussions on the causes of the accuracy improved by optimization are also provided. The results showed that the Inception-v3 model obtained 84.9% of the accuracy and performed better than the other two famous CNNs. Also, the implement of data augmentation enhanced the performance of Inception-v3 on EMDS. To add to that, the optimized Inception-v3 model archived 90.5% of the accuracy, and this result demonstrated the improvement effect obtained by using genetic algorithm (GA) to optimize the fully connected layer of the Inception-v3. Therefore, the optimize Inception-v3 with data augmentation process obtained the accuracy of 92.9% and improved almost 21% higher than that obtained from the famous Vgg16. In addition, the optimized Inception-v3 would need less neurons, when compared with that of the optimized Vgg16 possibly. This optimized Inception-v3 could provide a solution to the EM classification in microscope with a digital camera system.