A gold nanoshell with a silica inner shell synthesized using liposome templates for doxorubicin loading and near-infrared photothermal therapy

Gold (Au) nanoshells with solid silica cores have great potential for cancer photothermal therapy. However, this nanostructure cannot carry enough drugs. Here, we report a Au nanoshell with a hollow silica core for drug loading and cancer therapy. The silica shells were synthesized using nanoliposome templates, and then Au nanoshells were grown on the outer surface of the silica shells. Transmission-electron and scanning-electron microscopy showed that the Au nanoshells were successfully fabricated, and that the liposome/SiO2/Au core-shell nanocomposites were spherical with a narrow size distribution. Images of several broken spheres, and the fact that hollow templates (liposomes) were used, suggest that the fabricated Au nanoshells were hollow. After doxorubicin (DOX) was incorporated into liposome/SiO2/Au, the DOX-loaded Au nanoshells killed cancer cells with high therapeutic efficacy when irradiated with near-infrared light, suggesting that the Au nanoshells delivered both DOX chemotherapy and photothermal therapy with a synergistic effect

Th17 Cells in Type 1 Diabetes: Role in the Pathogenesis and Regulation by Gut Microbiome

Type 1 diabetes (T1D) is an autoimmune disease which is characterized by progressive destruction of insulin producing pancreatic islet β cells. The risk of developing T1D is determined by both genetic and environmental factors. A growing body of evidence supports an important role of T helper type 17 (Th17) cells along with impaired T regulatory (Treg) cells in the development of T1D in animal models and humans. Alteration of gut microbiota has been implicated to be responsible for the imbalance between Th17 and Treg cells. However, there is controversy concerning a pathogenic versus protective role of Th17 cells in murine models of diabetes in the context of influence of gut microbiota. In this review we will summarize current knowledge about Th17 cells and gut microbiota involved in T1D and propose Th17 targeted therapy in children with islet autoimmunity to prevent progression to overt diabetes

Meta-analysis of driving behavior studies and assessment of factors using structural equation modeling

The aim of this paper is to understand the factors that influence unsafe driving practices by examining published studies that utilized the Theory of Planned Behavior (TPB) to predict driving behavior. To this end, it reviews 42 studies published up to the end of 2021 to evaluate the predictive utility of TPB by employing a meta-analysis and structural equation model. The results indicate that these studies sought to predict 20 distinct driving behaviors (e.g., drink-driving, use of cellphone while driving, aggressive driving) using the original TPB constructs and 43 additional variables. The TPB model with the three original constructs is found to account for 32% intentional variance and 34% behavioral variance. Among the 43 variables researchers have examined in TPB studies related to driving behavior, this study identified the six that are commonly used to enhance the TPB model’s predictive power. These variables are past behavior, self-identity, descriptive norm, anticipated regret, risk perception, and moral norm. When past behavior is added to the original TPB model, it increases the explained variance in intention to 52%. When all six factors are added to the original TPB model, the best model has only four variables (perceived risk, self-identity, descriptive norm, and moral norm); this model increased the explained variance to 48%. The influence of the TPB constructs on intention is modified by behavior category and traffic category. The findings of this paper validate the application of TPB to predict driving behavior. It is the first study to do this through the use of meta-analysis and structural equation modeling