[Quantitative study on the acupoint effects based on complex network analysis: with the examples of the textbook networks formed by and ].

By extracting the acupoint names and their main indications from cases in and , the acupoints and their main indications are represented in a reduced dimension, establishing an "acupoint-indication" linkage. Using complex network detection results (node degree values), the specificity of acupoints was assessed. The small-world characteristics of the "acupoint-indication" network are utilized to analyze the consistency of acupoint selection in acupuncture prescriptions and strategies to avoid redundant acupoints. The results show that the "acupoint-indication" network formed by both texts exhibited an approximate "long-tail" distribution, with a large number of node degree values concentrated between 0 and 4 000, while a few nodes have degree values exceeding 10 000. There are significant differences in the number and distribution of nodes with degree values> 10 000 between the two texts. includes 11 acupoints with multiple edges across the body, whereas contains only 2 such acupoints, located in the lower limbs. Clinically, some acupoints have a broad therapeutic effect and appear in numerous prescriptions. The division of acupoints based on node degree values can coarsely evaluate the body region specificity of acupoints' regulatory effects. The "acupoint-indication" network of has a higher number of edges than that of , which might be related to the different historical contexts of the two texts. In the future, diagnostic and therapeutic patterns with historical continuity can be utilized to optimize acupuncture prescriptions.