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Gastric cancer is a common cancer of the gastrointestinal tract, highly occurring in East and Southeast Asian. Roughly more than 50% of the population is exposed to Helicobacter pylori (H. pylori) infection worldwide. H. pylori infection is one of the risk factors for gastric cancer and is strongly associated with the development of gastric cancer. The association between H. pylori infection and metastasis of gastric cancer is still inconclusive but has made some progress. For one thing, H. pylori is colonized in the gastric mucosa. The effect of its key virulence factors, VacA and CagA proteins, keeps H. pylori alive in the stomach for a long time and makes it possible for H. pylori to promote the proliferation, epithelial-mesenchymal transition and metastasis of gastric cancer cells. For another, the tumor microenvironment is the site of interaction between host immune system and tumor. By interfering with the effect of tumor cells and immune cells, enhancing the formation of an acidic and hypoxic environment and altering the differentiation of cells in the tumor microenvironment, H. pylori infection can strengthen immune escape and then facilitate the metastasis of gastric cancer. H. pylori infection has become a global public health problem, and its influence on the evolution of gastric cancer cannot be disregarded. The review addresses the correlation between H. pylori infection and gastric cancer metastasis through both key virulence factors and tumor microenvironment. It will provide reference for clinical and basic research in gastric cancer.

The obstacle dataset is a kind of aeronautical information dataset based on the aeronautical information exchange model (AIXM) specification proposed by International Civil Aviation Organization (ICAO) under the aviation intelligence management(AIM) system.The query of the obstacle dataset can directly affect the airport clearance assessment and flight procedure design.Based on the analysis of the temporal and spatial attributes of the obstacle dataset, an obstacle dataset query method based on temporal point and spatial location is proposed by using the spatio-temporal data model and AIXM specification to solve the query problem of the obstacle dataset.The obstacle query and visualization system is constructed, and the random experiments and example applications are designed to verify the feasibility and reliability of the query method.The results show that according to the method,the obstacles that impact on the airport clearance and flight procedure design can be extracted, and the flight procedure designers' situation awareness of the airport obstacle distribution can be enhanced.

Osteoporosis and degenerative endocrine diseases are some of the major causes of disability in the elderly. The feedback loop in the endocrine system works to control the release of hormones and maintain the homeostasis of metabolism, thereby regulating the function of target organs. The breakdown of this feedback loop results in various endocrine and metabolic disorders, such as osteoporosis, type II diabetes, hyperlipidemia, etc. The direct regulation of redox homeostasis is one of the most attractive strategies to redress the imbalance of the feedback loop. The biophysical regulation of redox homeostasis can be achieved through engineered dynamic hydrogel niches, with which cellular mechanics and redox homeostasis are intrinsically connected. Mechanotransduction-dependent redox signaling is initiated by cell surface protein assemblies, cadherins for cell–cell junctions, and integrins for cell–ECM interactions. In this review, we focused on the biophysical regulation of redox homeostasis via the tunable cell–ECM interactions in the engineered dynamic hydrogel niches. We elucidate processes from the rational design of the hydrogel matrix to the mechano-signaling initiation and then to the redox response of the encapsulated cells. We also gave a comprehensive summary of the current biomedical applications of this strategy in several degenerative endocrine disease models. [ABSTRACT FROM AUTHOR]