目的通过文献挖掘的方法对冠心病气虚血瘀证与气滞血瘀证进行内在生物学区分。方法在MEDLINE数据库中找到与冠心病有关的文献,提取摘要池,通过其对摘要池进行匹配,使用共现的文本挖掘技术挖掘出冠心病气虚血瘀证和气滞血瘀证的分子生物学网络,确定与冠心病气虚血瘀证和气滞血瘀证相关的候选分子指标。最后,应用特征选择的数据挖掘方法遴选出"指标个数少,准确性高"的证候生物学特征诊断模式。结果对利用文献挖掘方法挖掘出的基因数据进行对比、分析,显示气虚血瘀相关集群与内分泌、信号传导、造血细胞系、炎症反应等相关;气滞血瘀相关集群与糖蛋白、含有二硫键的蛋白、G蛋白偶联受体信号传导系统、儿茶酚胺类递质活性调控相关,从而与交感神经调节相关。中医证型的内在生物学特征可以在NEI水平上进行有效的辨识。结论文献挖掘法作为一种新的发现证候生物学指标的方法具有一定的可行性,建议将其进一步扩大到其他证型的研究中,验证该方法的普适性和可靠性。
Objective: To biology distinguish the Qi deficiency blood stasis syndrome and Qi-blood stagnation syndrome in unstable angina pectoris by literature mining technology. Methods: Firstly,the literature about unstable angina pectoris were searched from MEDLINE. Secondly,the molecular indicators were determined from the molecular network,which were through the literature mining in the Qi deficiency blood stasis syndrome and Qi-blood stagnation syndrome. Lastly,the diagnosis pattern of syndrome biological characteristics was determined by the feature selection of literature mining. Results: From the gene indices,there were some indicators related to the Qi deficiency blood stasis syndrome such as endocrine,signal transduction and inflammatory response. Meanwhile,there were some correlation cluster about Qi-blood stagnation syndrome including the glycoprotein,the G protein coupling receptor signal transduction system and catecholamines transmitter activity regulation. The bio-logical characteristics of TCM syndrome can be identified in the NEI. Conclusion: It is proved universality and reliability that literature mining method as a new method for finding syndrome abnormal biological indexes were feasible and further expanded the research to other syndromes.