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| 1 | Effect of Yizhitongxuan decoction on learning and memory ability,Gαq/11 expression and Na^+-K^+-ATP enzyme activity in rat models of Alzheimer's Disease显示文摘OBJECTIVE: To study the effects of Yizhitongxuan decoction on learning and memory abilities, Gαq/11expression and Na+-K+-ATPenzymeactivityin rat models of Alzheimer's disease(AD) caused by injecting Aβ25-35 into the hippocampus.METHODS: Ninety male Wistar rats(age ≥10 months)were selected and injected with Aβ25-35 into their hippocampi to establish model animals,which were randomly divided into six groups including a sham-operated group(blank group), a model group, a donepezil HCL group(Western Medicinegroup),and ahigh/general/dilute concentrations of Yizhitongxuan decoction groups(TCMⅠⅡⅢgroup).The Morris watermaze was used to examine the learning and memory abilities of rats in each group by place navigation and spatial probe tests.Then, the rats were sacrificed to collect the hippocampi for biochemical tests, using western blotting to detect the expression of Gαq/11 and an ultramicro Na+-K+-ATP enzyme kit to measure Na+-K+-ATP enzyme activity.RESULTS:Yizhitongxuan decoction improved model rats' learning and memory abilities, and increased the expression of Gαq/11 in the hippocampus and the level of Na+-K+-ATP enzyme activity in braintissue.CONCLUSION: Yizhitongxuan decoction could improve model rats' learning and memory abilities,and had a regulating effect on the expression of Gαq/11and Na+-K+-ATP enzyme activity. | Jing Teng Zhexue Xu Jing Zhang Jingmin Li | 2014 | Journal of Traditional Chinese Medicine2014，34，4： | 3 |
| 2 | Mining class outliers:concepts,algorithms and applications in CRM显示文摘 | HE Zengyou XU Xiaofei HUANG Zhexue | 2004 | Expert Systems with Applications2004，27，4： | 1 |
| 3 | FP-outlier: frequent pattern based outlier detection 显示文摘 | HE Zengyou XU Xiaofei HUANG Joshua Zhexue | 2005 | Computer Science rind Information System2005，2，1： | 1 |
| 4 | Maintainability-based facility layout optimum design of ship cabin显示文摘 | Xu Luo Yongmin Yang Zhexue Ge Xisen Wen Fengjiao Guan | 2015 | International Journal of Production Research2015，，3： | 1 |
| 5 | FP-outli- er : Frequent pattern based outlier detection 显示文摘 | He Zengyou Xu Xiaofei Huang Zhexue | 2005 | Computer Science and Information Systems2005，2，1： | 1 |
| 6 | A feature group weighting method for subspace clustering of high-dimensional data显示文摘 | Xiaojun Chen Yunming Ye Xiaofei Xu Joshua Zhexue Huang | 2011 | Pattern Recognition2011，，： | 1 |
| 7 | Observation points classifier ensemble for high-dimensional imbalanced classification显示文摘In this paper,an Observation Points Classifier Ensemble(OPCE)algorithm is proposed to deal with High-Dimensional Imbalanced Classification(HDIC)problems based on data processed using the Multi-Dimensional Scaling(MDS)feature extraction technique.First,dimensionality of the original imbalanced data is reduced using MDS so that distances between any two different samples are preserved as well as possible.Second,a novel OPCE algorithm is applied to classify imbalanced samples by placing optimised observation points in a low-dimensional data space.Third,optimization of the observation point mappings is carried out to obtain a reliable assessment of the unknown samples.Exhaustive experiments have been conducted to evaluate the feasibility,rationality,and effectiveness of the proposed OPCE algorithm using seven benchmark HDIC data sets.Experimental results show that(1)the OPCE algorithm can be trained faster on low-dimensional imbalanced data than on high-dimensional data;(2)the OPCE algorithm can correctly identify samples as the number of optimised observation points is increased;and(3)statistical analysis reveals that OPCE yields better HDIC performances on the selected data sets in comparison with eight other HDIC algorithms.This demonstrates that OPCE is a viable algorithm to deal with HDIC problems. | Yulin He Xu Li Philippe Fournier‐Viger Joshua Zhexue Huang Mianjie Li Salman Salloum | 2023 | CAAI Transactions on Intelligence Technology2023，8，2： | 0 |
| 8 | The gut microbiome and microbial metabolites in acute myocardial infarction显示文摘Emerging evidence has highlighted the role of gut microbiome in human health.However,the integrative role of gut microbiome and microbial metabolites in acute myocardial infarction(AMI)remains unclear.The current study profiles the microbial community through 16S rRNA gene sequencing and shotgun metagenomic sequencing and measures fecal short-chain fatty acids and circulating choline pathway metabolites among 117 new-onset AMI cases and 78 controls.Significant microbial alternations are observed in AMI patients compared with controls(P=0.001).The abundances of nine species(e.g.,Streptococcus salivarius and Klebsiella pneumoniae)are positively associated,and one species(Roseburia hominis)is inversely associated with AMI status and severity.A gut microbial score at disease onset is associated with the risk of major adverse cardiovascular events in 3.2 years(hazard ratio[95%CI]:2.01[1.04-4.24])in AMI patients.The molar proportions of fecal acetate and butyrate are higher,and the circulating levels of choline and carnitine are lower in AMI patients than in controls.In addition,disease classifiers show that AMI cases and controls have a more distinct pattern in taxonomical composition than in pathways or metabolites.Our findings suggest that microbial composition and functional potentials are associated with AMI status and severity. | Chenglin Liu Zhonghan Sun Shalaimaiti Shali Zhendong Mei Shufu Chang Hanjun Mo Lili Xu Yanni Pu Huihui Guan Guo-Chong Chen Qibin Qi Zhexue Quan Ji Qi Kang Yao Yuxiang Dai Yan Zheng Junbo Ge | 2022 | Journal of Genetics and Genomics2022，49，6： | 0 |
| 9 | Diffusion tensor imaging fiber tracking with reliable tracking orientation and flexible step size显示文摘We propose a method of reliable tracking orientation and flexible step size fiber tracking. A new directional strategy was defined to select one optimal tracking orientation from each directional set, which was based on the single-tensor model and the two-tensor model. The directional set of planar voxels contained three tracking directions: two from the two-tensor model and one from the single- tensor model. The directional set of linear voxels contained only one principal vector. In addition, a flexible step size, rather than fixable step sizes, was implemented to improve the accuracy of fiber tracking. We used two sets of human data to assess the performance of our method; one was from a healthy volunteer and the other from a patient with low-grade glioma. Results verified that our method was superior to the single-tensor Fiber Assignment by Continuous Tracking and the two-tensor eXtended Streamline Tractography for showing detailed images of fiber bundles. | Xufeng Yao Manning Wang Xinrong Chen Shengdong Nie Zhexu Li Xiaoping Xu Xuelong Zhang Zhijian Song | 2013 | Neural Regeneration Research2013，8，16： | 0 |
| 10 | A novel observation points‐based positive‐unlabeled learning algorithm显示文摘In this study,an observation points‐based positive‐unlabeled learning algorithm(hence called OP‐PUL)is proposed to deal with positive‐unlabeled learning(PUL)tasks by judiciously assigning highly credible labels to unlabeled samples.The proposed OP‐PUL algorithm has three components.First,an observation point classifier ensemble(OPCE)algorithm is constructed to divide unlabeled samples into two categories,which are temporary positive and permanent negative samples.Second,a temporary OPC(TOPC)is trained based on the combination of original positive samples and permanent negative samples and then the permanent positive samples that are correctly classified with TOPC are retained from the temporary positive samples.Third,a permanent OPC(POPC)is finally trained based on the combination of original positive samples,permanent positive samples and permanent negative samples.An exhaustive experimental evaluation is conducted to validate the feasibility,rationality and effectiveness of the OP‐PUL algorithm,using 30 benchmark PU data sets.Results show that(1)the OP‐PUL algorithm is stable and robust as unlabeled samples and positive samples are increased in unlabeled data sets and(2)the permanent positive samples have a consistent probability distribution with the original positive samples.Moreover,a statistical analysis reveals that POPC in the OP‐PUL algorithm can yield better PUL performances on the 30 data sets in comparison with four well‐known PUL algorithms.This demonstrates that OP‐PUL is a viable algorithm to deal with PUL tasks. | Yulin He Xu Li Manjing Zhang Philippe Fournier‐Viger Joshua Zhexue Huang Salman Salloum | 2023 | CAAI Transactions on Intelligence Technology2023，8，4： | 0 |
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