1.Research on core syndrome of generalized anxiety disorder in traditional Chinese medicine:based on network analysis method
Xue LI ; Hongxiao JIA ; Hong ZHU ; Zhengtian FENG ; Sisi ZHENG ; Ziyao WU ; Yuhang DUAN
Journal of Capital Medical University 2025;46(3):471-478
Objective To analyze the core syndromes of patients with generalized anxiety disorder(GAD),explore the core pathogenesis,and offer innovative perspectives and practical strategies for the traditional Chinese medicine(TCM)diagnosis and treatment of GAD.Methods The basic information of GAD patients was collected,and depression symptoms were evaluated with Hamilton Anxiety Scale to evaluate anxiety symptoms,Hamilton Depression Scale,and the TCM psychiatric and somatic symptoms were evaluated with Traditional Chinese Medicine Symptom Observation Form.Based on the data collected from the Traditional Chinese Medicine symptom observation table,the systematic clustering method was used to cluster the symptoms with a frequency greater than 10%,determine the disease type syndrome and disease location syndrome,and form a syndrome symptom relationship table.According to this table,the traditional Chinese medicine syndrome score of each patient is calculated.The complex network analysis was carried out to evaluate core syndromes and analyze the relationships between core syndromes and psychiatric symptoms and core syndromes and other syndromes.Results A total of 517 patients with GAD were included.There were 81 symptoms with a frequency of more than 10%,including 21 psychological symptoms and 60 physical symptoms.The clustering analysis led to a total of 12 syndromes,including 6 pathological syndromes,namely yin deficiency,heat,phlegm dampness,qi stagnation,blood stasis,and qi deficiency,and 6 disease location syndromes,namely liver,spleen,kidney,gallbladder,stomach,and heart.The results of complex network analysis show that the core pathological syndrome of GAD is kidney,and the core pathological syndrome is yin deficiency.The joint analysis of pathological syndrome and pathological syndrome network suggests that yin deficiency is the core of the integrated network.The relationship between yin deficiency syndrome and various organs is in the order of kidney,spleen,gallbladder,liver,heart,and stomach.The syndrome element of yin deficiency has the highest correlation with being easily frightened,excessive thinking,indecisiveness,repetitive behavior,and groundless worry.The kidney syndrome has the highest correlation with the symptoms such as being easily scared,unfounded worry,repetitive actions,excessive rumination,and restlessness.Conclusion The core pathological pattern of GAD is kidney and the core pathological pattern is yin deficiency.Kidney yin deficiency may be the core pathogenesis of GAD.
2.Research on core syndrome of generalized anxiety disorder in traditional Chinese medicine:based on network analysis method
Xue LI ; Hongxiao JIA ; Hong ZHU ; Zhengtian FENG ; Sisi ZHENG ; Ziyao WU ; Yuhang DUAN
Journal of Capital Medical University 2025;46(3):471-478
Objective To analyze the core syndromes of patients with generalized anxiety disorder(GAD),explore the core pathogenesis,and offer innovative perspectives and practical strategies for the traditional Chinese medicine(TCM)diagnosis and treatment of GAD.Methods The basic information of GAD patients was collected,and depression symptoms were evaluated with Hamilton Anxiety Scale to evaluate anxiety symptoms,Hamilton Depression Scale,and the TCM psychiatric and somatic symptoms were evaluated with Traditional Chinese Medicine Symptom Observation Form.Based on the data collected from the Traditional Chinese Medicine symptom observation table,the systematic clustering method was used to cluster the symptoms with a frequency greater than 10%,determine the disease type syndrome and disease location syndrome,and form a syndrome symptom relationship table.According to this table,the traditional Chinese medicine syndrome score of each patient is calculated.The complex network analysis was carried out to evaluate core syndromes and analyze the relationships between core syndromes and psychiatric symptoms and core syndromes and other syndromes.Results A total of 517 patients with GAD were included.There were 81 symptoms with a frequency of more than 10%,including 21 psychological symptoms and 60 physical symptoms.The clustering analysis led to a total of 12 syndromes,including 6 pathological syndromes,namely yin deficiency,heat,phlegm dampness,qi stagnation,blood stasis,and qi deficiency,and 6 disease location syndromes,namely liver,spleen,kidney,gallbladder,stomach,and heart.The results of complex network analysis show that the core pathological syndrome of GAD is kidney,and the core pathological syndrome is yin deficiency.The joint analysis of pathological syndrome and pathological syndrome network suggests that yin deficiency is the core of the integrated network.The relationship between yin deficiency syndrome and various organs is in the order of kidney,spleen,gallbladder,liver,heart,and stomach.The syndrome element of yin deficiency has the highest correlation with being easily frightened,excessive thinking,indecisiveness,repetitive behavior,and groundless worry.The kidney syndrome has the highest correlation with the symptoms such as being easily scared,unfounded worry,repetitive actions,excessive rumination,and restlessness.Conclusion The core pathological pattern of GAD is kidney and the core pathological pattern is yin deficiency.Kidney yin deficiency may be the core pathogenesis of GAD.
3.CAMU-Net:an improved model for retinal vessel segmentation based on Attention U-Net
Yunfei TANG ; Zhiping DAN ; Zhengtian HONG ; Yonglin CHEN ; Peilin CHENG ; Guo CHENG ; Fangting LIU
Chinese Journal of Medical Physics 2024;41(8):960-968
An improved U-Net model(channel attention module U-Net,CAMU-Net)is proposed to achieve precise segmentation of retinal vessels.CAMU-Net model enhances its understanding of regional features by employing residual enhancement convolution to extract important information from the regions,improves the global feature acquisition capability by introducing feature refinement module to promote feature extraction,realizes precise segmentation by adding channel attention module to capture image features accurately,and enhances its capability to perceive target boundaries and details through a multi-scale feature fusion structure.The ablation study on the DRIVE dataset validates the role of each module in retinal vessel segmentation.The comparison with other mainstream network models on DRIVE and STARE datasets verify that CAMU-Net model is superior to other models.

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