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10. Advances in Helicobacter pylori infection involved in gastric cancer metastasis

Author

XIAO Rong, TAO Shuangfen, CHEN Siyu, ZHENG Leizhen, and ZHU Meiling

Subjects
stomach neoplasm, helicobacter pylori, caga protein, vaca protein, neoplasm metastasis, immune escape, Medicine
Abstract

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.

Published
2023
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12. Research on data query and application of obstacle dataset based on spatio-temporal data model

Author

LAI Xin, LIANG Changsheng, and ZHU Meiling

Subjects
aeronautical information datasets, spatio-temporal data model, aixm, data query, visualization of obstacles, Motor vehicles. Aeronautics. Astronautics, TL1-4050
Abstract

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.

Published
2023
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47. Evaluation of monolithic crystal detector with dual-ended readout utilizing multiplexing method.

Author

Zeng, Xiangtao, Zhang, Zhiming, Li, Daowu, Huang, Xianchao, Wang, Zhuoran, Wang, Yingjie, Zhou, Wei, Wang, Peilin, Zhu, Meiling, Wei, Qing, Gong, Huixing, and Wei, Long

Subjects
CONVOLUTIONAL neural networks, POSITRON emission tomography, MULTIPLEXING, DETECTORS, CRYSTALS
Abstract

Objective. Monolithic crystal detectors are increasingly being applied in positron emission tomography (PET) devices owing to their excellent depth-of-interaction (DOI) resolution capabilities and high detection efficiency. In this study, we constructed and evaluated a dual-ended readout monolithic crystal detector based on a multiplexing method. Approach. We employed two 12 × 12 silicon photomultiplier (SiPM) arrays for readout, and the signals from the 12 × 12 array were merged into 12 X and 12 Y channels using channel multiplexing. In 2D reconstruction, three methods based on the centre of gravity (COG) were compared, and the concept of thresholds was introduced. Furthermore, a light convolutional neural network (CNN) was employed for testing. To enhance depth localization resolution, we proposed a method by utilizing the mutual information from both ends of the SiPMs. The source width and collimation effect were simulated using GEANT4, and the intrinsic spatial resolution was separated from the measured values. Main results. At an operational voltage of 29 V for the SiPM, an energy resolution of approximately 12.5 % was achieved. By subtracting a 0.8 % threshold from the total energy in every channel, a 2D spatial resolution of approximately 0.90 mm full width at half maximum (FWHM) can be obtained. Furthermore, a higher level of resolution, approximately 0.80 mm FWHM, was achieved using a CNN, with some alleviation of edge effects. With the proposed DOI method, a significant 1.36 mm FWHM average DOI resolution can be achieved. Additionally, it was found that polishing and black coating on the crystal surface yielded smaller edge effects compared to a rough surface with a black coating. Significance. The introduction of a threshold in COG method and a dual-ended readout scheme can lead to excellent spatial resolution for monolithic crystal detectors, which can help to develop PET systems with both high sensitivity and high spatial resolution. [ABSTRACT FROM AUTHOR]

Published
2024
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