A global portrait of expressed mental health signals towards COVID-19 in social media space

Globally, the COVID-19 pandemic has induced a mental health crisis. Social media data offer a unique oppor- tunity to track the mental health signals of a given population and quantify their negativity towards COVID-19. To date, however, we know little about how negative sentiments differ across countries and how these relate to the shifting policy landscape experienced through the pandemic. Using 2.1 billion individual-level geotagged tweets posted between 1 February 2020 and 31 March 2021, we track, monitor and map the shifts in negativity across 217 countries and unpack its relationship with COVID-19 policies. Findings reveal that there are important geographic, demographic, and socioeconomic disparities of negativity across continents, different levels of a nation’s income, population density, and the level of COVID-19 infection. Countries with more stringent policies were associated with lower levels of negativity, a relationship that weakened in later phases of the pandemic. This study provides the first global and multilingual evaluation of the public’s real-time mental health signals to COVID-19 at a large spatial and temporal scale. We offer an empirical framework to monitor mental health signals globally, helping international authorizations, including the United Nations and World Health Organi- zation, to design smart country-specific mental health initiatives in response to the ongoing pandemic and future public emergencies

An Exercise Health Simulation Method Based on Integrated Human Thermophysiological Model

Research of healthy exercise has garnered a keen research for the past few years. It is known that participation in a regular exercise program can help improve various aspects of cardiovascular function and reduce the risk of suffering from illness. But some exercise accidents like dehydration, exertional heatstroke, and even sudden death need to be brought to attention. If these exercise accidents can be analyzed and predicted before they happened, it will be beneficial to alleviate or avoid disease or mortality. To achieve this objective, an exercise health simulation approach is proposed, in which an integrated human thermophysiological model consisting of human thermal regulation model and a nonlinear heart rate regulation model is reported. The human thermoregulatory mechanism as well as the heart rate response mechanism during exercise can be simulated. On the basis of the simulated physiological indicators, a fuzzy finite state machine is constructed to obtain the possible health transition sequence and predict the exercise health status. The experiment results show that our integrated exercise thermophysiological model can numerically simulate the thermal and physiological processes of the human body during exercise and the predicted exercise health transition sequence from finite state machine can be used in healthcare

Cloning and molecular characterization of two novel LMW-m type glutenin genes from Triticum spelta L.

Wang R., J. Zhang, F. Luo, N Liu, S. Prodanovic, Y. Yan (2021). Cloning and molecular characterization of two novel LMW-m type glutenin genes from Triticum spelta L.- Genetika, Vol 53, No.1,141 -155. Spelt wheat (Triticum spelta L., 2n=6x=42, AABBDD), as a hexaploid wheat species, is important sources of food and feed in Europe. It also serves as an important genetic resource for improvement of wheat quality and resistance. In this study, two novel m-type low molecularmolecularmolecular molecular glutenin subunit (LMW -GS) genes, named as TsLMW-m1and TsLMW-m2were cloned by allelic specific polymerase chain reaction (AS -PCR) from German spelt wheat cultivars Rochbergers fruher Dinke and Schwabenkorn, respectively. The complete open reading frames (ORFs) of both genes contained contained contained contained contained contained 873 bp encoding 290 amino acid residues, and had typical LMW-GS structural features. Two same deletions with 24 bp at the position of 707-730 bp were present in both genes, while TsLMW-m1had two nonsynonymous single-nucleotide polymorphism (SNP) variations at the positions of 434 bp (C-A transversion) and 857 bp (G-A transition). Phylogenic analysis revealed that both LMW-m genes were closely related to those from wheat A genome, suggesting that both subunits are encoded by the Glu-A3 locus. Secondary structure prediction showed that TsLMW-m1and TsLMW-m2subunits had more α-helices than other wheat LMW-GS including superior quality subunit EU369717, which would benefit to form superior gluten structures and dough properties. The authenticity and expression activity of TsLMW-m1 and TsLMW-m2 genes were verified by prokaryotic expression in E. coli. Our results indicated that two newly cloned TsLMW-m genes could have potential values for wheat quality improvement

Mechanistic Insight Into the Roles of Integrins in Osteoarthritis

Osteoarthritis (OA), one of the most common degenerative diseases, is characterized by progressive degeneration of the articular cartilage and subchondral bone, as well as the synovium. Integrins, comprising a family of heterodimeric transmembrane proteins containing α subunit and β subunit, play essential roles in various physiological functions of cells, such as cell attachment, movement, growth, differentiation, and mechanical signal conduction. Previous studies have shown that integrin dysfunction is involved in OA pathogenesis. This review article focuses on the roles of integrins in OA, especially in OA cartilage, subchondral bone and the synovium. A clear understanding of these roles may influence the future development of treatments for OA