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- 저자 : Hou Mingxing (검색결과 2 건)
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Shengli Li,Jianan Zhang,Xiaoqun Hou,Yongyi Wang,Tong Li,Zhiming Xu,Feng Chen,Yong Zhou,Weimin Wang,Mingxing Liu 대한신경외과학회 2024 Journal of Korean neurosurgical society Vol.67 No.1
Objective : The spontaneous intracerebral hemorrhage (ICH) remains a significant cause of mortality and morbidity throughout the world. The purpose of this retrospective study is to develop multiple models for predicting ICH outcomes using machine learning (ML). Methods : Between January 2014 and October 2021, we included ICH patients identified by computed tomography or magnetic resonance imaging and treated with surgery. At the 6-month check-up, outcomes were assessed using the modified Rankin Scale. In this study, four ML models, including Support Vector Machine (SVM), Decision Tree C5.0, Artificial Neural Network, Logistic Regression were used to build ICH prediction models. In order to evaluate the reliability and the ML models, we calculated the area under the receiver operating characteristic curve (AUC), specificity, sensitivity, accuracy, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR). Results : We identified 71 patients who had favorable outcomes and 156 who had unfavorable outcomes. The results showed that the SVM model achieved the best comprehensive prediction efficiency. For the SVM model, the AUC, accuracy, specificity, sensitivity, PLR, NLR, and DOR were 0.91, 0.92, 0.92, 0.93, 11.63, 0.076, and 153.03, respectively. For the SVM model, we found the importance value of time to operating room (TOR) was higher significantly than other variables. Conclusion : The analysis of clinical reliability showed that the SVM model achieved the best comprehensive prediction efficiency and the importance value of TOR was higher significantly than other variables.
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Shen Junjie,Yang Zhiwen,Wu Xinlin,Yao Guodong,Hou Mingxing 한국응용생명화학회 2023 Applied Biological Chemistry (Appl Biol Chem) Vol.66 No.-
Objective Gastric cancer (GC) remains a prevailing threat to life. Baicalein exhibits anti-cancer properties. This study estimated the mechanism of baicalein in GC cell apoptosis by mediating endoplasmic reticulum stress (ERS) through the PI3K/AKT pathway. Methods After treatment with different concentrations of baicalein, GC cell (HGC-27 and AGS) viability was detected by MTT assay. AGS cells more sensitive to baicalein treatment were selected as study subjects. The IC50 of baicalein on AGS cells was determined. Colony formation, cell cycle, and apoptosis were detected using crystal violet staining and flow cytometry. Levels of ERS-related and BTG3/PI3K/AKT pathway-related proteins were determined by Western blot. Intracellular Ca2+ level was measured using Fluo-3 AM fluorescence working solution. GC mouse models were established by subcutaneously injecting AGS cells into the right rib and were intragastrically administrated with baicalein. Tumor volume and weight were recorded. Expression of Ki67 in tumor tissues and positive expression of apoptotic cells were detected by immunohistochemistry and TUNEL staining. Results Baicalein inhibited cell proliferation and induced G0/G1 arrest and apoptosis by regulating the cell cycle, and triggered ERS in GC cells. Baicalein impeded the PI3K/AKT pathway by activating BTG3, thereby triggering ERS and inducing apoptosis. BTG3 inhibition reversed baicalein-induced apoptosis and ERS. Baicalein regulated GC cells in a concentration-dependent manner. Moreover, in xenograft mice, baicalein prevented tumor growth, decreased Ki67- positive cells, activated BTG3, and inhibited the PI3K/AKT pathway, thus activating ERS and increasing apoptotic cells. Conclusion Baicalein facilitates GC cell apoptosis by triggering ERS via repression of the PI3K/AKT pathway.
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