AD may be an independent risk factor for ischemic stroke, and risk of ischemic stroke increases with AD severity.

Dengue virus (DENV) is one of the major infectious pathogens worldwide. DENV infection is a highly dynamic process. Currently, no antiviral drug is available for treating DENV-induced diseases since little is known regarding how the virus interacts with host cells during infection. Advanced molecular imaging technologies are powerful tools to understand the dynamics of intracellular interactions and molecular trafficking. This study exploited a single-virus particle tracking technology to address whether DENV interacts with autophagy machinery during the early stage of infection. Using confocal microscopy and three-dimensional image analysis, we showed that DENV triggered the formation of green fluorescence protein-fused microtubule-associated protein 1A/1B-light chain 3 (GFP-LC3) puncta, and DENV-induced autophagosomes engulfed DENV particles within 15-min postinfection. Moreover, single-virus particle tracking revealed that both DENV particles and autophagosomes traveled together during the viral infection. Finally, in the presence of autophagy suppressor 3-methyladenine, the replication of DENV was inhibited and the location of DENV particles spread in cytoplasma. In contrast, the numbers of newly synthesized DENV were elevated and the co-localization of DENV particles and autophagosomes was detected while the cells were treated with autophagy inducer rapamycin. Taken together, we propose that DENV particles interact with autophagosomes at the early stage of viral infection, which promotes the replication of DENV.

The formation of different shapes Au–Cu2O core–shell nanoparticles was investigated by in situ liquid cell transmission electron microscopy (LCTEM).

Metal oxides have attracted substantial attention over the years and are commonly used in the semiconductor industry because of their excellent physical and chemical properties. Among the various metal oxides, cuprous oxide (Cu2O) is regarded as a promising material. It is inexpensive, earth-abundant, and nontoxic; therefore, it can be used in catalysis, sensors, solar cells, and p-type semiconductors. However, the redox reaction of Cu2O is still uncertain. The size, morphology, and structure of Cu2O strongly influence its properties. In this work, we developed a new synthesis method of Cu2O that involves reducing the precursor by an electron beam without reducing agent. The growth process of Cu2O nanocubes was observed via in situ liquid cell transmission electron microscopy (in situ LCTEM). The nucleation kinetics, oscillating growth behavior, and redox reaction of the Cu2O nanocubes in the liquid phase were systematically studied. Cu2O exhibited a round shape at the beginning and transformed into a cubic shape afterward. Interestingly, the Cu2O nanocubes grew clearly under long-term observation; however, their diameters increased and fluctuated during the short-term observation. The electron beam not only stimulated the solution to reduce the nanocubes but also caused electron radiation effect to the nanocubes. During the Cu2O growth and dissolution, the cubic shape evolved with specific planes in the {100} family. Our direct observation sheds light on the preparation of Cu2O by a reduction method, extending the study of reaction kinetics and providing a new way to synthesize metal oxides.

With facilitation of advanced technologies, design and application of smart become promising research issues in education. Although it is potential for students to learn geometric in authentic contexts, there were still lack of studies addressing smart learning issue in authentic context for geometry. This study aim to propose an app, called SmartUG, to support students smartly to consolidate geometry understanding and learning through enriching experience of exploring and applying related geometry surrounding. There were four smart mechanisms proposed in SmartUG (direction guidance, learning progress, object recognition and answer feedback) to guide students' measuring and applying geometry smartly and meaningfully in authentic contexts. A total of 83 fifth‐grade students participated in this experiment and were divided into three groups, an experimental group that learned with smart mechanisms, a control group that learned without smart mechanisms and a traditional control group that learning with traditional teaching approach. Basically, experimental group outperformed control group and traditional teaching group in term of geometry ability and estimation ability, which means students benefited from proposed SmartUG. Moreover, students showed positive attitude and high intention to use toward SmartUG. Students should be provided more chances to learn geometry smartly in authentic contexts with SmartUG. It is potential to future studies to implement more smart mechanisms to support students learning in authentic contexts. Moreover, the learning system can get smarter and smarter when the learning system gets more and more input data from students' use.