1.Professor WU Rongzu's Clinical Experience in Treating Irritable Bowel Syndrome with Constipation Using Fuyang Tongmi Decoction (扶阳通秘汤)
Yihao YANG ; Junran ZHU ; Wendi WU ; Liyun JIANG ; Yueqiu DONG ; Yueqing CAI ; Ruibin ZHOU ; Yunjiao XU ;
Journal of Traditional Chinese Medicine 2026;67(10):1049-1051
This paper introduces professor WU Rongzu's clinical experience in using Fuyang Tongmi Decoction (扶阳通秘汤, FTD) to treat irritable bowel syndrome with constipation (IBS-C). It is believed that yang qi depletion, water cold, earth dampness, and wood constraint are the key pathogenesis.The treatment principle is warming water, drying the earth and venting wood, with the basic formula FTD adjusted according to the symptoms. This approach aims to transport the qi movement of the middle jiao (焦) and support the recovery of intestinal function of directing turbidity downward, providing a treatment strategy for IBS-C caused by yang deficiency.
2.A study on post-traumatic stress disorder classification based on multi-atlas multi-kernel graph convolutional network.
Lijun ZHOU ; Hongru ZHU ; Yunfei LIU ; Xian MO ; Jun YUAN ; Changyu LUO ; Junran ZHANG
Journal of Biomedical Engineering 2024;41(6):1110-1118
Post-traumatic stress disorder (PTSD) presents with complex and diverse clinical manifestations, making accurate and objective diagnosis challenging when relying solely on clinical assessments. Therefore, there is an urgent need to develop reliable and objective auxiliary diagnostic models to provide effective diagnosis for PTSD patients. Currently, the application of graph neural networks for representing PTSD is limited by the expressiveness of existing models, which does not yield optimal classification results. To address this, we proposed a multi-graph multi-kernel graph convolutional network (MK-GCN) model for classifying PTSD data. First, we constructed functional connectivity matrices at different scales for the same subjects using different atlases, followed by employing the k-nearest neighbors algorithm to build the graphs. Second, we introduced the MK-GCN methodology to enhance the feature extraction capability of brain structures at different scales for the same subjects. Finally, we classified the extracted features from multiple scales and utilized graph class activation mapping to identify the top 10 brain regions contributing to classification. Experimental results on seismic-induced PTSD data demonstrated that our model achieved an accuracy of 84.75%, a specificity of 84.02%, and an AUC of 85% in the classification task distinguishing between PTSD patients and non-affected subjects. The findings provide robust evidence for the auxiliary diagnosis of PTSD following earthquakes and hold promise for reliably identifying specific brain regions in other PTSD diagnostic contexts, offering valuable references for clinicians.
Humans
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Stress Disorders, Post-Traumatic/diagnostic imaging*
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Neural Networks, Computer
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Algorithms
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Brain/diagnostic imaging*
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Magnetic Resonance Imaging
3.Differences of biological property between glioma stem cells and glioma non-stem cells
Yifan LYU ; Junran LUO ; Guojie JING ; Gang ZHU ; Honghai LUO ; Baisheng LI ; Yituan XIE
Chinese Journal of Neuromedicine 2019;18(3):225-232
Objective To observe the differences of biological property of glioma stem cells (GSCs) and glioma non-stem cells (nGSCs), and their related protein expressions. Methods The proliferations of GSCs1, GSCs2 and nGSCs1 and nGSCs2 were detected by CCK8 after two, 4, 6, 8, 10 and 12 d of culture in vitro. The sensitivities of the cells to temozolomide (TMZ) were detected by CCK8 after 2 d of culture. The adhesion abilities of cells were tested by adhesion assay. Transwell assay was used to detect the migration and invasion abilities of cells. The activity of matrix metalloproteinase-2 (MMP-2) was detected by gelatin zymography. Western blotting and immunofluorescence staining were used to detect the protein expressions of Notchl and epidermal growth factor receptor (EGFR). Results The survival rate of nGSCs1 was significantly higher than that of GSCs1 and the survival rate of nGSCs2 was significantly higher than that of GSCs2 after 4, 6, 8, 10 and 12 d of culture (P<0.05). The inhibitory concentration (IC)50 of TMZ for GSCs1, nGSCs1, GSCs2 and nGSCs2 was (1536.0±17.67) μmol/L, (514.5±13.44) μmol/L, (2543.0±39.87) μmol/L, (889.6±17.43) μmol/L, respectively (P<0.05). Number of GSCs1 adhering to extracellular matrix proteins Fibronectin and Collagen I was significantly larger than that of nGSCs1, and that of GSCs2 was significantly larger than that of nGSCs2 (P<0.05). The number of migrated GSCs112 and 24 h of cultivation was statistically larger than that of nGSCs1, and that of GSCs2 was statistically larger than that of nGSCs2 (P<0.05). The number of invaded GSCs124 and 36 h of cultivation was larger than that of nGSCs1, and that of invaded GSCs2 was larger than that of nGSCs2, with statistical differences (P<0.05). The activity of MMP2 secreted by GSCs1 was significantly higher than that by nGSCs1, and that of MMP2 secreted by GSCs2 was significantly higher than that by nGSCs2 (P<0.05). Western blotting showed that the relative protein expression level of EGFR/Notch1 in GSCs1 was significantly lower than that in nGSCs1, and that in GSCs2 was significantly lower than that in nGSCs2 (P<0.05). The results of immunofluorescence staining were consistent with those of Western blotting; EGFR protein strongly expressed in nGSCs and weakly expressed in GSCs; Notch1 protein strongly expressed in GSCs and weakly expressed in nGSCs. Conclusion As compared with the high-EGFR-expressing and proliferative primary glioma cells, the high-Notch1-expressing glioma stem cells have higher activity level of MMP-2,stronger abilities of adhesion, migration and invasion, which may be contributed to glioma treatment resistance and its occurrence.

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