3-N-butylphthalide is an ettectwe drug for acute iscemlc stroke. However, its effects on cnromc cerebral ischemia-induced neuronal injury remain poorly understood. Therefore, this study li- gated bilateral carotid art...3-N-butylphthalide is an ettectwe drug for acute iscemlc stroke. However, its effects on cnromc cerebral ischemia-induced neuronal injury remain poorly understood. Therefore, this study li- gated bilateral carotid arteries in 15-month-old rats to simulate chronic cerebral ischemia in aged humans. Aged rats were then intragastrically administered 3-n-butylphthalide. 3-N-butylphtha- lide administration improved the neuronal morphology in the cerebral cortex and hippocampus of rats with chronic cerebral ischemia, increased choline acetyltransferase activity, and decreased malondialdehyde and amyloid beta levels, and greatly improved cognitive function. These findings suggest that 3-n-butylphthalide alleviates oxidative stress caused by chronic cerebral ischemia, improves cholinergic function, and inhibits amyloid beta accumulation, thereby im- proving cerebral neuronal injury and cognitive deficits.展开更多
Objective To study a novel feature extraction method of Chinese materia medica(CMM) fingerprint.Methods On the basis of the radar graphical presentation theory of multivariate,the radar map was used to figure the non-...Objective To study a novel feature extraction method of Chinese materia medica(CMM) fingerprint.Methods On the basis of the radar graphical presentation theory of multivariate,the radar map was used to figure the non-map parameters of the CMM fingerprint,then to extract the map features and to propose the feature fusion.Results Better performance was achieved when using this method to test data.Conclusion This shows that the feature extraction based on radar chart presentation can mine the valuable features that facilitate the identification of Chinese medicine.展开更多
Depression is closely linked to the morphology and functional abnormalities of multiple brain regions; however, its topological structure throughout the whole brain remains unclear. We col- lected resting-state functi...Depression is closely linked to the morphology and functional abnormalities of multiple brain regions; however, its topological structure throughout the whole brain remains unclear. We col- lected resting-state functional MRI data from 36 first-onset unmedicated depression patients and 27 healthy controls. The resting-state functional connectivity was constructed using the Auto- mated Anatomical Labeling template with a partial correlation method. The metrics calculation and statistical analysis were performed using complex network theory. The results showed that both depressive patients and healthy controls presented typical small-world attributes. Compared with healthy controls, characteristic path length was significantly shorter in depressive patients, suggesting development toward randomization. Patients with depression showed apparently abnormal node attributes at key areas in cortical-striatal-pallidal-thalamic circuits. In addition, right hippocampus and right thalamus were closely linked with the severity of depression. We se- lected 270 local attributes as the classification features and their P values were regarded as criteria for statistically significant differences. An artificial neural network algorithm was applied for classification research. The results showed that brain network metrics could be used as an effec- tive feature in machine learning research, which brings about a reasonable application prospect for brain network metrics. The present study also highlighted a significant positive correlation between the importance of the attributes and the intergroup differences; that is, the more sig- nificant the differences in node attributes, the stronger their contribution to the classification. Experimental findings indicate that statistical significance is an effective quantitative indicator of the selection of brain network metrics and can assist the clinical diagnosis of depression.展开更多
在线编程评测系统(Online Judge,OJ)是一种被广泛应用于计算机编程教学与竞赛的代码测评系统。用户在规模庞大的题库中寻找适合当前学习阶段的题目时,往往会感到迷茫。如何为用户推荐合适的题目和规划学习路径,是在线编程测评系统研发...在线编程评测系统(Online Judge,OJ)是一种被广泛应用于计算机编程教学与竞赛的代码测评系统。用户在规模庞大的题库中寻找适合当前学习阶段的题目时,往往会感到迷茫。如何为用户推荐合适的题目和规划学习路径,是在线编程测评系统研发中的一个重要研究课题。传统推荐算法存在可解释性和准确性难以兼顾的问题。文中提出了基于知识图谱与协同过滤混合策略的在线评测系统推荐模型(A Hybrid Programming Task Recommendation Model Based on Knowledge Graph and Collaborative Filtering,HKGCF)。该模型通过推荐与用户当前知识和技能掌握程度相匹配的题目,来帮助用户提升学习效果。文中设计和实现了该模型,并将其集成到了北京航空航天大学在线编程测评系统中,以适应OJ平台特有的交互形式。线上测试和离线测试实验的结果表明,提出的HKGCF模型在准确率和可解释性方面均优于典型传统算法。展开更多
基金supported by Innovation Team Project of Hubei Province 2011 Plans,No.2011JH-2013CXTT06Momentous Scientific Research Funds of Hubei Provincial Education Ministry,No.D20102101Cultivating Funds of Country’s Projects of Hubei University of Medicine,No.2013GPY03
文摘3-N-butylphthalide is an ettectwe drug for acute iscemlc stroke. However, its effects on cnromc cerebral ischemia-induced neuronal injury remain poorly understood. Therefore, this study li- gated bilateral carotid arteries in 15-month-old rats to simulate chronic cerebral ischemia in aged humans. Aged rats were then intragastrically administered 3-n-butylphthalide. 3-N-butylphtha- lide administration improved the neuronal morphology in the cerebral cortex and hippocampus of rats with chronic cerebral ischemia, increased choline acetyltransferase activity, and decreased malondialdehyde and amyloid beta levels, and greatly improved cognitive function. These findings suggest that 3-n-butylphthalide alleviates oxidative stress caused by chronic cerebral ischemia, improves cholinergic function, and inhibits amyloid beta accumulation, thereby im- proving cerebral neuronal injury and cognitive deficits.
基金the National Nature Science Foundation of China (60873121)
文摘Objective To study a novel feature extraction method of Chinese materia medica(CMM) fingerprint.Methods On the basis of the radar graphical presentation theory of multivariate,the radar map was used to figure the non-map parameters of the CMM fingerprint,then to extract the map features and to propose the feature fusion.Results Better performance was achieved when using this method to test data.Conclusion This shows that the feature extraction based on radar chart presentation can mine the valuable features that facilitate the identification of Chinese medicine.
基金supported by the National Natural Science Foundation of China,No.61070077,61170136,61373101,81171290the Natural Science Foundation of Shanxi Province in China,No.2010011020-2,2011011015-4+3 种基金Programs for Science and Technology Social Development of Shanxi Province,No.20130313012-2Science and Technology Projects by Shanxi Provincial Ed-ucation Ministry,No.20121003Youth Fund by Taiyuan University of Technology,No.2012L014Youth Team Fund by Taiyuan University of Technology,No.2013T047
文摘Depression is closely linked to the morphology and functional abnormalities of multiple brain regions; however, its topological structure throughout the whole brain remains unclear. We col- lected resting-state functional MRI data from 36 first-onset unmedicated depression patients and 27 healthy controls. The resting-state functional connectivity was constructed using the Auto- mated Anatomical Labeling template with a partial correlation method. The metrics calculation and statistical analysis were performed using complex network theory. The results showed that both depressive patients and healthy controls presented typical small-world attributes. Compared with healthy controls, characteristic path length was significantly shorter in depressive patients, suggesting development toward randomization. Patients with depression showed apparently abnormal node attributes at key areas in cortical-striatal-pallidal-thalamic circuits. In addition, right hippocampus and right thalamus were closely linked with the severity of depression. We se- lected 270 local attributes as the classification features and their P values were regarded as criteria for statistically significant differences. An artificial neural network algorithm was applied for classification research. The results showed that brain network metrics could be used as an effec- tive feature in machine learning research, which brings about a reasonable application prospect for brain network metrics. The present study also highlighted a significant positive correlation between the importance of the attributes and the intergroup differences; that is, the more sig- nificant the differences in node attributes, the stronger their contribution to the classification. Experimental findings indicate that statistical significance is an effective quantitative indicator of the selection of brain network metrics and can assist the clinical diagnosis of depression.
文摘在线编程评测系统(Online Judge,OJ)是一种被广泛应用于计算机编程教学与竞赛的代码测评系统。用户在规模庞大的题库中寻找适合当前学习阶段的题目时,往往会感到迷茫。如何为用户推荐合适的题目和规划学习路径,是在线编程测评系统研发中的一个重要研究课题。传统推荐算法存在可解释性和准确性难以兼顾的问题。文中提出了基于知识图谱与协同过滤混合策略的在线评测系统推荐模型(A Hybrid Programming Task Recommendation Model Based on Knowledge Graph and Collaborative Filtering,HKGCF)。该模型通过推荐与用户当前知识和技能掌握程度相匹配的题目,来帮助用户提升学习效果。文中设计和实现了该模型,并将其集成到了北京航空航天大学在线编程测评系统中,以适应OJ平台特有的交互形式。线上测试和离线测试实验的结果表明,提出的HKGCF模型在准确率和可解释性方面均优于典型传统算法。