Health risks caused by exposure to black carbon (BC) and nanoparticles (NP) are well studied, although no standard currently exists for them worldwide. Exposure to children may lead to serious health effects due to their increased vulnerability and longer time spend inside the classrooms, making it important to assess the factors that affect air quality in preschools. Thus, this work aims to evaluate indoor-outdoor (I/O) relationships of NPs in the 10-420 nm range, BC and volatile organic compounds (VOCs) at rural and urban preschools (aged 3-5 years) between May 2016 and July 2017. Factorial analysis was applied to identify the possible emission sources. Prior communalities were estimated by the squared multiple correlations with all other variables. We used the varimax rotation method and the criterion for factor selection was the number of eigenvalues greater than one. check details Results indicate that BC and NP were 4- and 3.2-times higher in urban outdoor caused by traffic emissions, respectively. Highest concentrations occurred during rush hours and during the pickup time of children. In urban school, BC was directly related to accumulation mode (N49-205), while in the rural area, BC was related to local traffic and particles from pulp industries in the regional background. Nucleation mode (N11-36) was related to traffic emissions in urban school, while in the rural school was related with secondary formation of particles. Mean I/O ratios of BC and NP in the urban (0.54; 0.51) and rural (0.71; 0.91) schools, respectively, suggested that their higher concentrations occurred in outdoors. VOCs were higher indoor in urban (I/O = 1.97) and rural (I/O = 2.22) sites, indicating these pollutants are generated inside, regardless of urban or rural sites. These findings suggest the necessity of improving ventilation and commuting styles to lower the exposure of children to air pollutants in and around school environments.Silver nanoparticles (AgNPs) are among the major groups of contaminants of emerging concern for aquatic ecosystems. The massive application of AgNPs relies on the antimicrobial properties of Ag, raising concerns about their potential risk to ecologically important freshwater microbes and the processes they drive. Moreover, it is still uncertain whether the effects of AgNPs are driven by the same mechanisms underlying those of Ag ions (Ag+). We employed transcriptomics to better understand AgNP toxicity and disentangle the role of Ag+ in the overall toxicity towards aquatic fungi. To that end, the worldwide-distributed aquatic fungus Articulospora tetracladia, that plays a central role in organic matter turnover in freshwaters, was selected and exposed for 3 days to citrate-coated AgNPs (∼20 nm) and Ag+ at concentrations inhibiting 20% of growth (EC20). Responses revealed 258 up- and 162 down-regulated genes upon exposure to AgNPs and 448 up- and 84 down-regulated genes under exposure to Ag+. Different gene expression patterns were found after exposure to each silver form, suggesting distinct mechanisms of action. Gene ontology (GO) analyses showed that the major cellular targets likely affected by both silver forms were the biological membranes. GO-based biological processes indicated that AgNPs up-regulated the genes involved in transport, nucleobase metabolism and energy production, but down-regulated those associated with redox and carbohydrate metabolism. Ag+ up-regulated the genes involved in carbohydrate and steroid metabolism, whereas genes involved in localization and transport were down-regulated. Our results showed, for the first time, distinct profiles of gene expression in aquatic fungi exposed to AgNPs and Ag+, supporting different modes of toxicity of each silver form. Also, our results suggest that Ag+ had a negligible role in the toxicity induced by AgNPs. Finally, our study highlights the power of transcriptomics in portraying the stress induced by different silver forms in organisms.The diagnostic modalities for giant cell arteritis (GCA) have evolved significantly in recent years. Among the different diagnostic tools developed, Doppler ultrasound of the temporal arteries, with a sensitivity and specificity reaching 69% and 82%, respectively, is now recognized as superior and, therefore, is a first-line diagnostic tool in GCA. Moreover, with the increasing development of new ultrasound technologies, the accuracy of Doppler ultrasound in GCA seems to be constantly improving. In this article, we describe in detail the scanning technique to perform while realizing Doppler ultrasound of temporal arteries to assess GCA, as well as the diagnostic performance of this tool according to current literature.Kidney transplantation is the best choice for patients with end-stage renal disease. To date, allograft biopsy remains the gold standard for revealing pathologic changes and predicting long-term outcomes. However, the invasive nature of transplant biopsy greatly limits its application. Ultrasound has been a first-line examination for evaluating kidney allografts for a long time. Advances in ultrasound in recent years, especially the growing number of studies in elastography and contrast-enhanced ultrasonography (CEUS), have shed new light on its application in kidney transplantation. Elastography, including strain elastography and shear wave elastography, is used mainly to assess allograft stiffness and, thus, predict renal fibrosis. CEUS has been used extensively in evaluating blood microperfusion, assessing acute kidney injury and detecting different complications after transplantation. Requiring the use of microbubbles also makes CEUS a novel method of gene transfer and drug delivery, enabling promising targeted diagnosis and therapy. In this review, we summarize the advances of elastography and CEUS in kidney transplantation and evaluate their potential efficiency in becoming a better complement to or even substitute for transplant biopsy in the future.The interference of nontarget adulterant on FT-IR-based target adulterant quantitative analysis was explored and a sequential strategy was proposed to improve the prediction accuracy of the quantitative analysis model. Based on the FT-IR data of fish oil adulterated with terrestrial animal lipid, PLS and PLS-DA results show that quantitative analysis modeled by multiple and single adulteration data do not apply to each other; quantitative models based on the fusion of single and multiple adulteration data were established and showed a low quantitative analysis precision (higher RSD); and the sensitivity and specificity of discrimination analysis for multiply and singly adulterated fish oils both all exceed 0.910. To enhance the detection accuracy, a sequential strategy was proposed; identifying singly or multiply adulterated fish oil and then quantifying the content of adulterant was considered an efficient approach.