CCIO: A Cross-Chain Interoperability Approach for Consortium Blockchains Based on Oracle.

Cross-chain interoperability can expand the ability of data interaction and value circulation between different blockchains, especially the value interaction and information sharing between industry consortium blockchains. However, some current public blockchain cross-chain technologies or data migration schemes between consortium blockchains need help to meet the consortium blockchain requirements for efficient two-way data interaction. The critical issue to solve in cross-chain technology is improving the efficiency of cross-chain exchange while ensuring the security of data transmission outside the consortium blockchain. In this article, we design a cross-chain architecture based on blockchain oracle technology. Then, we propose a bidirectional information cross-chain interaction approach (CCIO) based on the former architecture, we novelly improve three traditional blockchain oracle patterns, and we combine a mixture of symmetric and asymmetric keys to encrypt private information to ensure cross-chain data security. The experimental results demonstrate that the proposed CCIO approach can achieve efficient and secure two-way cross-chain data interactions and better meet the application needs of large-scale consortium blockchains.

Abnormal methylation of PIK3AP1 was involved in regulating the immune inflammatory response of GES-1 cells induced by Helicobacter pylori.

Gastric epithelial cells (GES-1) stimulated by Helicobacter pylori (H. pylori) would affect the expression of related genes and induce the immune response of the cells. Abnormal methylation of DNA was one of the main causes. The aim of this study was to investigate phosphoinositol-3-kinase adaptor protein 1(PIK3AP1), which was screened from the chip data as an immune gene candidate to against the inflammatory response of cells caused by H. pylori infection. PIK3AP1 plays a key role in PI3K/AKT signaling pathway. The gene chip analysis and experimental results confirmed that PIK3AP1 expression was downregulated and PIK3AP1 promoter was hypermethylated after H. pylori stimulation in GES-1 cells. Meanwhile, the expression level of PIK3AP1 was significantly upregulated after 5-aza-dc treatment, and its expression was higher after 5-aza-dc and H. pylori co-treatment than that of H. pylori treatment but lower than that of 5-aza-dc treatment. Therefore, hypermethylation was the main reason for the down-regulation of PIK3AP1 after H. pylori stimulation. In addition, the intervention of PIK3AP1 inhibited the expression of downstream gene AKT, and suppressing the expression of the immunoinflammatory gene IL-6 in GES-1 cells. Furthermore, the intervention of PIK3AP1 would promote cell proliferation. In summary, hypermethylation of the PIK3AP1 promoter was accompanied by reduction of the expression level of PIK3AP1 in GES-1 cells by H. pylori stimulation. The expression of PIK3AP1, AKT, and IL-6 genes was positively correlated, Meanwhile, the PIK3AP1 can affect the proliferation of GES-1 cells. These results would be helpful to understand the innate immune response function of PIK3AP1 to pathogenic bacterial infection in the stomach.

Graph Reasoning With Supervised Contrastive Learning for Legal Judgment Prediction.

Given the fact descriptions of legal cases, the legal judgment prediction (LJP) problem aims to determine three judgment tasks of law articles, charges, and the term of penalty. Most existing studies have considered task dependencies while neglecting the prior dependencies of labels among different tasks. Therefore, how to make better use of the information on the relation dependencies among tasks and labels becomes a crucial issue. To this end, we transform the text classification problem into a node classification framework based on graph reasoning and supervised contrastive learning (SCL) techniques, named GraSCL. Specifically, we first design a graph reasoning network to model the potential dependency structures and facilitate relational learning under various graph topologies. Then, we introduce the SCL method for the LJP task to further leverage the label relation on the graph. To accommodate the node classification settings, we extend the traditional SCL method to novel variants for SCL at the node level, which allows the GraSCL framework to be trained efficiently even with small batches. Furthermore, to recognize the importance of hard negative samples in contrastive learning, we introduce a simple yet effective technique called online hard negative mining (OHNM) to enhance our SCL approach. This technique complements our SCL method and enables us to control the number and complexity of negative samples, leading to further improvements in the model's performance. Finally, extensive experiments are conducted on two well-known benchmarks, demonstrating the effectiveness and rationality of our proposed SCL approach as compared to the state-of-the-art competitors.

Effect of trimethylamine N-oxide on inflammation and the gut microbiota in Helicobacter pylori-infected mice.

Diet is one of the factors contributing to symptom of Helicobacter pylori (H. pylori) infection. Trimethylamine N-oxide (TMAO), a diet-related microbial metabolite, is associated with inflammatory and metabolic diseases. The aim of this study is to investigate the effects of TMAO intake on inflammation and gut microbiota composition in H. pylori-infected mice via 16S rRNA sequencing and biochemical analyses. The in vitro experiments showed that TMAO not only increased the expression of growth- and metabolism-associated genes and the urease activity of H. pylori, but increased the production of virulence factors. Moreover, TMAO intake increased the production of inflammatory markers and reduced the richness and diversity of the gut microbiota in H. pylori-infected mice. Further analysis showed that TMAO increased the relative abundance of Escherichia_Shigella in H. pylori-infected mice, which had positive correlation with the levels of LPS, CRP, and CXCL1. Collectively, our results suggest that TMAO may aggravate H. pylori-induced inflammation by increasing the viability and virulence of H. pylori and may aggravate inflammation in association with the gut microbiota in H. pylori-infected mice. This study may provide a novel insight into the mechanism for the effect of diet-derived metabolites such as TMAO on H. pylori-induced disease development.