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Zeng-Hui Yue,Xin-Qun He,Xiao-Rong Chang,Jian-Ling Yuan,Bao-Sheng Yu,Mi Liu,Ling Fu,Liang Zhang,Li-Chao Shang 사단법인약침학회 2012 Journal of Acupuncture & Meridian Studies Vol.5 No.2
Objective: To explore the mechanism of Toll-like receptor (TLR4) inhibition in the delay of formation of atherosclerosis by herb-partition moxibustion. Method: Seventy-five rabbits were randomly assigned to one of five groups: blank, atherosclerosis (AS) model, direct moxibustion, herb-partition moxibustion, and drug treatment. With the exception of the blank group, all rabbits were given a high-fat diet in addition to immunologic injury to create the AS model. The experiments were carried out for 16 weeks, at which time the aorta was removed from each rabbit. Immunohistochemical methods were used to detect the gray level of the aortic TLR4 to observe the immunologic competence of its antigens. Fluorescent quantitative polymerase chain reaction was used to detect the expression of TLR4 messenger RNA (mRNA) in the aorta. Results: The gray-scale value of TLR4 and the TLR4 mRNA expression significantly decreased (p < 0.05) in the direct moxibustion, herb-partition moxibustion, and drug treatment groups. Furthermore, the effects of the herb-partition moxibustion and drug treatment were superior to those of the direct moxibustion. Conclusion: Herb-partition moxibustion inhibits aortic TLR4 activity and mRNA expression,showing that herb-partition moxibustion delays the formation of atherosclerosis through the inhibition of TLR4 expression.
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EVALUATION OF THE ANTITUMOR ACTIVITY BY CdTe QDs WITH VERBASCOSIDE
XIAO-HUI ZHAO,HUI-LAN YUE,PING LI,XIN ZENG,GEN ZHANG 성균관대학교(자연과학캠퍼스) 성균나노과학기술원 2013 NANO Vol.8 No.3
Cadmium telluride quantum dots (QDs) have received significant attention in biomedical research because of their potential in drug delivery. In this study, the chemotherapeutic agent Verbascoside (VB) was immobilized successfully onto CdTe QDs by covalent bonding between the –OH group of VB and the –COOH group of CdTe QDs. The amount of VB that could be immobilized depended on the concentration of –COOH groups (succinic acid) on the surface of the CdTe QDs. Apoptotic staining, DNA fragmentation and flow cytometry analysis further demonstrated that compared with CdTe QDs or VB treatment alone, the apoptosis rate increased after the treatment of CdTe QDs together with VB (VB–QDs) in HepG2/ADM cells. We observed that VB–QDs treatment could clearly activate apoptosis-related Caspase 3 expression in HepG2/ADM cells. Moreover, our in vivo study indicated that the treatment of VB–QDs effectively inhibited the human hepatoma HepG2/ADM nude mice tumor growth. The increased cell apoptosis rate was closely correlated with the enhanced inhibition of tumor growth in the studied animals. Thus, VB–QDs may serve as a possible alternative for therapeutic approaches for some cancer treatments. In summary, studies have shown that cancer cells are treated by the presence of VB–QDs nanoparticles based on analysis of cell apoptosis.
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Predicting Non Performing Loan of Business Bank with Data Mining Techniques
Wan Jie,Yue Zeng-lei,Yang Dong-hui,ZhangYu,Liu Jiao,Liu Zhi,Liu Jinfu 보안공학연구지원센터 2016 International Journal of Database Theory and Appli Vol.9 No.12
The non-performing loans (NPL) prediction plays an important role in business bank. However, there is still a large gap between the requirement of prediction performance and current techniques. In this paper data mining approaches is used to predict the NPL. Both macroeconomic and bank-specific variables are collected to form the feature set firstly. Based on selected features, the study firstly applies single basic classifiers such as decision tree, k nearest neighbors and support vector machine (SVM) to model the problem of NPL. Bagging and AdaBoost are described in this paper as two different method of multiple classifier fusion, to build prediction models. In this experiment, non-performing loans data with 96 features and 10415 instances of a business bank is collected. F-mean and The Area under the ROC Curve (AUC) are considered as metrics of classification. The results illustrate that multiple classifier fusion algorithms outperform single basic classifier. The model built by multiple classifiers fusion can produce better prediction results. Furthermore, the AdaBoost method performs much better than bagging method in processing NPL.
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Niu, Yu-Ming,Shen, Ming,Li, Hui,Ni, Xiao-Bing,Zhou, Juan,Zeng, Xian-Tao,Leng, Wei-Dong,Wu, Ming-Yue Asian Pacific Journal of Cancer Prevention 2012 Asian Pacific journal of cancer prevention Vol.13 No.8
Objective: Findings for associations between the methylenetetrahydrofolate reductase (MTHFR) A1298C gene polymorphism and head and neck cancer risk have been conflicting. We therefore performed a meta-analysis to derive a more precise relationship. Methods: Ten published case-control studies were collected and odds ratios (ORs) with 95% confidence intervals (CIs) were used to assess the association between MTHFR A1298C polymorphism and head and neck cancer risk. Sensitivity analysis and publication bias assessment also were performed to guarantee the statistical power. Results: Overall, no significant association between MTHFR A1298C polymorphism and head and neck cancer risk was found in this meta-analysis (C vs. A: OR=1.04, 95%CI=0.87-1.25, P=0.668, Pheterogeneity<0.001; CC vs. AA: OR=1.07, 95%CI=0.70-1.65, P=0.748, $P_{heterogeneity}<0.001$; AC vs. AA: OR=1.06, 95%CI=0.88-1.27, P=0.565, $P_{heterogeneity}<0.001$; CC+AC vs. AA: OR=1.06, 95%CI=0.86-1.30, P=0.571, $P_{heterogeneity}<0.001$; CC vs. AA+AC: OR=1.02, 95%CI=0.69-1.52, P=0.910, $P_{heterogeneity}<0.001$). Similar results were also been found in succeeding analysis of HWE and stratified analysis of ethnicity. Conclusion: In conclusion, our meta-analysis demonstrates that MTHFR A1298C polymorphism may not be a risk factor for developing head and neck cancer.
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