Shi Han, Liu Yang, Cui Enuo, Zhao Hai, Gao Wei, Zhu Jian, Yang Dongxiang
Engineering Research Center of Security Technology of Complex Network System, School of Computer Science and Engineering, Northeastern University, Shenyang 110169, China.
School of Information Science and Engineering, Shenyang University of Technology, Shenyang 110870, China.
Evid Based Complement Alternat Med. 2020 Jul 12;2020:6031601. doi: 10.1155/2020/6031601. eCollection 2020.
In the process of treating pro-diseases with acupuncture, traditional Chinese medicine (TCM) doctors may fine-tune acupuncture prescriptions according to different prior experiences. Different prescriptions will affect the efficiency and effect of acupuncture treatment, and even excessive acupoint selection may cause psychological pressure on patients. We still lack an effective means to analyze the meridian system and acupoint specificity to clarify the mapping relationship between acupoints and diseases. Given the inability of modern medical technology to provide effective evidence support for meridians and acupoints, we combined acupuncture theory with network science for an interdisciplinary discussion. In this paper, we constructed a weighted undirected acupoint-disease network (ADN) based on clinical acupuncture prescription literature and proposed a high-specificity key node mining method based on ADN. Combined with the principle of acupoint selection in TCM, the proposed method balanced the contribution of local areas to the network based on the distribution characteristics of meridians and selected 30 key acupoints with high influence on the global topology according to the evaluation index of key nodes. Finally, we compared the proposed method with the other six classical node importance evaluation algorithms in terms of resolution, network loss, and accuracy. The comprehensive results show that the marked key acupoint nodes make outstanding contributions to the connectivity, topological structure, and weighted benefits of the network, and the stability and specificity of the algorithm guarantee the reliability of the key acupoint nodes. We consider that these key acupoints with high centrality in ADN can be used as core acupoints to help researchers explore targeted and high-impact acupoint combinations under resource constraints and optimize existing acupuncture prescriptions.
在运用针灸治疗疾病的过程中，中医医生可能会根据不同的既往经验对针灸处方进行微调。不同的处方会影响针灸治疗的效率和效果，甚至穴位选择过多可能会给患者带来心理压力。我们仍然缺乏一种有效的手段来分析经络系统和穴位特异性，以阐明穴位与疾病之间的映射关系。鉴于现代医学技术无法为经络和穴位提供有效的证据支持，我们将针灸理论与网络科学相结合进行跨学科探讨。在本文中，我们基于临床针灸处方文献构建了一个加权无向穴位-疾病网络（ADN），并提出了一种基于ADN的高特异性关键节点挖掘方法。结合中医选穴原则，该方法根据经络分布特征平衡局部区域对网络的贡献，并根据关键节点评估指标筛选出对全局拓扑有高影响力的30个关键穴位。最后，我们在分辨率、网络损失和准确性方面将所提方法与其他六种经典节点重要性评估算法进行了比较。综合结果表明，所标记的关键穴位节点对网络的连通性、拓扑结构和加权效益做出了突出贡献，算法的稳定性和特异性保证了关键穴位节点的可靠性。我们认为，这些在ADN中具有高中心性的关键穴位可作为核心穴位，帮助研究人员在资源受限的情况下探索有针对性且影响较大的穴位组合，并优化现有的针灸处方。
