人工智能在中医药领域的应用进展及现状思考

人工智能（Artificial Intelligence，AI）的蓬勃兴起为现代社会带来了前所未有的机遇，中医药是中华民族传承千年的文化瑰宝。随着人工智能技术不断在中医药领域的科技创新中崭露头角，二者的融合不断加深，人工智能在中医药领域的发展前景、争议挑战也引发了诸多思考。本文将从人工智能在中医药领域的应用入手，对人工智能辅助中医诊断、智能决策与数据挖掘、健康管理及中草药现代化研究等方面，就近年来国内外研究进展进行总结与分析，以期为AI视域下实现中医药现代化、智能化赋能。     

糖尿病前期中医证型及证素特点分析＊

目的 探讨糖尿病前期的中医证型及证素分布特点。方法 检索中国知网、万方及维普三大数据库中收录的自建库以来有关糖尿病前期证型的临床研究文献，对中医证型进行规范整理，建立数据库，提取证素，运用数据挖掘技术中的关联分析、聚类分析探究证素分布规律。结果 共纳入10篇文献，总有效病例1620例，证型经规范处理后整理为18个，主要证型为脾虚痰湿证。共提取证素13个，主要病位证素为脾，主要病性证素为气虚、湿和痰，关联分析显示脾—湿支持度和置信度最高，聚类分析结果可得到3个聚类组。结论 糖尿病前期病位在脾，气虚、脾、痰、湿是常见证素，临床诊治糖尿病前期应注重从脾论治，需辨证施治。     

阿戈美拉汀联合乙哌立松治疗青年慢性紧张性头痛的疗效分析

目的 探讨阿戈美拉汀联合乙哌立松治疗青年慢性紧张性头痛(Chronictention-typeheadache,CTTH)的疗效及安全性.方法 80例青年慢性紧张性头痛患者依据是否倒班随机分为对照组和治疗组,对照组口服乙哌立松治疗,治疗组在对照组基础上联合阿戈美拉汀治疗,评估2组患者治疗前匹兹堡睡眠量表评分(PSQI)评估治疗6周后两组的头痛疗效以及不良反应.结果 倒班人员的入组前PSQI的总评分、睡眠质量、入睡时间、催眠药物及睡眠障碍因子分高于非倒班人员;治疗组的疗效优于对照组,有统计学意义(P＜0.05);治疗组内,倒班患者疗效优于非倒班患者(P＜0.05).两组不良反应无明显差异.结论 阿戈美拉汀联合乙哌立松治疗慢性紧张性头痛的的疗效确切,安全性高.     

Identification of key genes and pathways in discoid lupus skin via bioinformatics analysis

Discoid lupus erythematosus (DLE) is the most common skin manifestation of lupus; however, the molecular mechanisms underlying DLE remain unknown. Therefore, we aimed to identify key differentially expressed genes (DEGs) in discoid lupus skin and investigate their potential pathways.To identify candidate genes involved in the occurrence and development of the disease, we downloaded the microarray datasets {"type":"entrez-geo","attrs":{"text":"GSE52471","term_id":"52471"}}GSE52471 and {"type":"entrez-geo","attrs":{"text":"GSE72535","term_id":"72535"}}GSE72535 from the Gene Expression Database (GEO). DEGs between discoid lupus skin and normal controls were selected using the GEO2R tool and Venn diagram software (http://bioinformatics.psb.ugent.be/webtools/Venn/). The Database for Annotation, Visualization, and Integrated Discovery (DAVID), Enrichr, and Cytoscape ClueGo were used to analyze the Kyoto Encyclopedia of Gene and Genome pathways and gene ontology. Protein-protein interactions (PPIs) of these DEGs were further assessed using the Search Tool for the Retrieval Interacting Genes version 10.0.Seventy three DEGs were co-expressed in both datasets. DEGs were predominantly upregulated in receptor signaling pathways of the immune response. In the PPI network, 69 upregulated genes were selected. Furthermore, 4 genes (CXCL10, ISG15, IFIH1, and IRF7) were found to be significantly upregulated in the RIG-I-like receptor signaling pathway, from analysis of Enrichr and Cytoscape ClueGo.The results of this study may provide new insights into the potential molecular mechanisms of DLE. However, further experimentation is required to confirm these findings.