Modification and completion of geological structure knowledge graph based on pattern matching.

As a knowledge representation method, knowledge graph is widely used in intelligent question answering systems and recommendation systems. At present, the research on knowledge graph mainly focuses on information query and retrieval based on knowledge graph. In some domain knowledge graphs, specific subgraph structures (patterns) have specific physical meanings. Aiming at this problem, this paper proposes a method and framework of knowledge graph pattern mining based on gat. Firstly, the patterns with specific physical meaning were transformed into subgraph structures containing topological structures and entity attributes. Secondly, the subgraph structure of the pattern is regarded as the query graph, and the knowledge graph is regarded as the data graph, so that the problem is transformed into an approximate subgraph matching problem. Then, the improved relational graph attention network is used to fuse the adaptive edge deletion mechanism to realize the approximate subgraph matching of subgraph structure and attribute, so as to obtain the best matching subgraph. The proposed method is trained in an end-to-end manner. The approximate subgraph matching is realized on the existing data set, and the research work of key pattern mining of complex geological structure knowledge graph is carried out.

Construction of knowledge constraints: a case study of 3D structural modeling.

The uncertainty of structural interpretation complicates the practical production and application of data-driven complex geological structure modeling technology. Intelligent structural modeling excavates and extracts structural knowledge from structural interpretation through human-machine collaboration and combines structural interpretation to form a new model of complex structural modeling guided by knowledge. Specifically, we focus on utilizing knowledge rule reasoning technology to extract topological semantic knowledge from interpretive data and employ knowledge inference to derive structural constraint information from complex geological structure models, thus effectively constraining the 3D geological structure modeling process. To achieve this, we develop a rule-based knowledge inference system that derives theoretical models consistent with expert cognition from interpretive data and prior knowledge. Additionally, we represent the extracted knowledge as a topological semantic knowledge graph, which facilitates computer recognition and allows estimation of intersection lines during 3D geological modeling, resulting in the creation of accurate models. The applicability of our proposed method to various complex geological structures is validated through application tests using real-world data. Furthermore, our method effectively supports the realization of intelligent structure modeling in real working area.

SPH7854, a gut-limited RORγt antagonist, ameliorates TNBS-induced experimental colitis in rat.

Multiple lines of evidence suggest that Retinoic Acid Related Orphan Nuclear Receptor gamma t (RORγt) is a potent therapeutic target for inflammatory bowel disease (IBD). However, systemic blockade of RORγt easily leads to thymic lymphoma and aberrant liver function. Therefore, the development of gut-limited RORγt antagonists may lead to the development of innovative IBD therapeutics that improve safety and retain effectiveness. We discovered SPH7854, a potent and selective RORγt antagonist. The effect of SPH7854 on the differentiation of T helper 1 (Th1)/Th17/regulatory T (Treg) cells was evaluated in mouse and human primary cells. SPH7854 (2-(4-(ethylsulfonyl)phenyl)-N- (6-(2-methyl-2-(pyridin-2-yl) propanoyl)pyridin-3-yl)acetamide) dose-dependently inhibited interleukin-17A (IL-17A) secretion from mouse CD4 + T cells and human peripheral blood mononuclear cells (PBMC). Additionally, SPH7854 strongly suppressed Th17 cell differentiation and considerably promoted Treg cell differentiation while slightly affected Th1 cell differentiation from mouse CD4 + T cells. The pharmacokinetic (PK) studies indicated that SPH7854 was restricted to the gut: the bioavailability and maximal plasma concentration of SPH7854 after oral administration (6 mg/kg) were 1.24 ± 0.33 % and 4.92 ± 11.81 nM, respectively, in rats. Strikingly, oral administration of SPH7854 (5 mg/kg and 15 mg/kg) twice daily significantly alleviated 2, 4, 6-trinitrobenzensulfonic acid (TNBS)-induced colitis in rats. SPH7854, especially at 15 mg/kg, significantly alleviated symptoms and improved macroscopic signs and microscopic structure in rat colitis, with decreased colonic mucosal levels of IL-17A, IL-6, tumor necrosis factor α (TNFα), monocyte chemoattractant protein-1 (MCP-1) and myeloperoxidase (MPO). These evidences indicated that blockade of RORγt activity via a gut-limited antagonist may be an effective and safe therapeutic strategy for IBD treatment.