ABSTRACT
In the context of COVID-19, people face conditions of great stress and are susceptible to negative emotions such as worry, fear, and doubt. Therefore, the focus of epidemic prevention should be on mental health as well as physical health. It is important to pay attention to people's mental health while mitigating and controlling the epidemic. As an intervention to improve mental health, exercise behavior has attracted increasing attention from scholars due to its convenience and low cost. Therefore, the goal of this paper was to investigate the differences between characteristics related to linguistic expression and mental health indicators among different groups of Weibo users by constructing a Weibo exercise behavior user lexicon to explore the influence of exercise behavior on mental health. This study developed a user dictionary of exercise behavior, classified Sina Weibo users' exercise behavior, and established relevant systems to uncover the expressive characteristics of psychological vocabulary and behavioral vocabulary to explore the differences in expressive features related to psychological and behavioral vocabulary and mental health indicators among users who engage in different forms of exercise behavior during the period of COVID-19. As a result of an analysis of variance (ANOVA) conducted during the COVID-19 epidemic, (1) based on the constructed user lexicon of motion behavior in Weibo, the classification program exhibited good performance;(2) there were significant differences in the expressions of some lexical features among users who exhibited different motor behaviors;and (3) both nonphysical exercise and physical exercise behavior had positive relationships with some mental health indicators, but the mechanism associated with nonphysical exercise requires further exploration. This study provides a scientific online evaluation methodology and support for research concerning exercise and mental health during the COVID-19 epidemic.
ABSTRACT
As an important component of the COVID-19 mRNA vaccines, liposomes play a key role in the efficient protection and delivery of mRNA to cells. Herein, due to the controllable release amplification strategy of liposomes, a reliable and robust single-particle collision electrochemical (SPCE) biosensor was constructed for H9N2 avian influenza virus (H9N2 AIV) detection by combining liposome encapsulation-release strategy with immunomagnetic separation. The liposomes modified with biotin and loaded with platinum nanoparticles (Pt NPs) were used as signal probes for the first time. Biotin facilitated the coupling of biomolecules (DNA or antibodies) through the specific reaction of biotin-streptavidin. Each liposome can encapsulate multiple Pt NPs, which were ruptured under the presence of 1 × PBST (phosphate buffer saline with 0.05% Tween-20) within 2 min, and the encapsulated Pt NPs were released for SPCE experiment. The combination of immunomagnetic separation not only improved the anti-interference capabilities but also avoided the agglomeration of Pt NPs, enabling the SPCE biosensor to realize ultrasensitive detection of 18.1 fg/mL H9N2 AIV. Furthermore, the reliable SPCE biosensor was successfully applied in specific detection of H9N2 AIV in complex samples (chicken serum, chicken liver and chicken lung), which promoted the universality of SPCE biosensor and its application prospect in early diagnosis of diseases.