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Objective A knowledge graph construction pipeline of traditional Chinese medicine(TCM)diagnosis and treatment was designed and applied,aiming at the automatic construction of the"disease-symptom-pathogenesis-and medicine"knowledge graph based on the medical records of famous TCM physicians,to analyze,organize and present medical records efficiently.Methods Firstly,The entity extraction method of medical records combining Deep Learning and Regular Expression was designed to extract disease,symptom,pathogenesis,and TCM entities from unstructured medical records automatically;secondly,entity relationships were defined and the correlations between entities were calculated using HAN method,and then the"entity-relation-entity"triplets were built;the graph database Neo4j and Gephi were used for knowledge storage and visual display separately;Finally,the application was verified in the Medical records of lung cancer treated by the old famous TCM physicians.Results The precision,Recall and F1 of the knowledge extraction model for medical records entities extraction are 88.49%,90.02%and 89.25%,respectively,and each index is better than the comparison methods.A total of 1077 triples are extracted through entity correlation calculation,and the knowledge graph is successfully constructed.It can reflect the relationship between 'disease-symptom-pathogenesis-medicine' in the treatment of lung cancer by the famous specialists of TCM.Conclusion The method in this paper can effectively solve the extraction,organization and expression of clinical medical records of famous TCM physicians,and realize the automatic construction process from the text of medical records to the knowledge graph.Relevant research ideas and methods proposed in this paper could provide a reference for the construction of the diagnosis and treatment knowledge graph of famous TCM physicians based on medical records.
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It has been revealed that hypoxia is dynamic in hypertrophic scars; therefore, we considered that it may have different effects on hypoxia-inducible factor-1α (HIF-1α) and p53 expression. Herein, we aimed to confirm the presence of a teeterboard-like conversion between HIF-1α and p53, which is correlated with scar formation and regression. Thus, we obtained samples of normal skin and hypertrophic scars to identify the differences in HIF-1α and autophagy using immunohistochemistry and transmission electron microscopy. In addition, we used moderate hypoxia in vitro to simulate the proliferative scar, and silenced HIF-1α or p53 gene expression or triggered overexpression to investigate the changes of HIF-1α and p53 expression, autophagy, apoptosis, and cell proliferation under this condition. HIF-1α, p53, and autophagy-related proteins were assayed using western blotting and immunofluorescence, whereas apoptosis was detected using flow cytometry analysis, and cell proliferation was detected using cell counting kit-8 (CCK-8) and 5-bromo-2'-deoxyuridine (BrdU) staining. Furthermore, immunoprecipitation was performed to verify the binding of HIF-1α and p53 to transcription cofactor p300. Our results demonstrated that, in scar tissue, HIF-1α expression increased in parallel with autophagosome formation. Under hypoxia, HIF-1α expression and autophagy were upregulated, whereas p53 expression and apoptosis were downregulated in vitro. HIF-1α knockdown downregulated autophagy, proliferation, and p300-bound HIF-1α, and upregulated p53 expression, apoptosis, and p300-bound p53. Meanwhile, p53 knockdown induced the opposite effects and enhanced HIF-1α, whereas p53 overexpression resulted in the same effects and reduced HIF-1α. Our results suggest a teeterboard-like conversion between HIF-1α and p53, which is linked with scar hyperplasia and regression.
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Humanos , Apoptose , Autofagia , Hipóxia Celular , Fibroblastos/metabolismo , Subunidade alfa do Fator 1 Induzível por Hipóxia/metabolismo , Proteína Supressora de Tumor p53/metabolismoRESUMO
Objective To observe the changes of type 2 diabetes mellitus patients in blood sugar,TC,TG,HDL C,plasma insulin,body mass index(BMI), microalbuminuria,etc before and after moderate intensity exercise training.Methods 28 patients with mean age of 59.0?7.6 years did moderate intensity exercise training for 1~1.5 hours every day for 12 month.At the same time they received the treatment of diet and oral antidiabetic drug com pared with 40 controls without exercise training. Before and after the observing period we measured the values of items above.Results Plasma glucose level , HbAlc,AUCGS(the area under the curve of glucose sugar) and BMI in fat diabetes with training team were obviously decreased compared with those before observation( P 0.05).Conclusion Exercise training can significantly descend blood sugar, insulin resistance and BMI of obese people ,improve lipidmetabolism and ascend insulin sensitivity. So the action of exercise can't be replaced by the diet and oral drug.