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Analysis of volatile oil in Rhizoma Ligustici Chuanxiong-Radix Paeoniae Rubra by gas chromatography-mass spectrometry and chemometric resolution

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Acta Pharmacologica Sinica 2006年第4期27卷 491-498页

作者： Xiao-ru LI Yi-zeng LIANG~2.Fang-qiu GUO College of Chemistry and Chemical Engineering,research center of {2. of traditional chinese medicines,central south university,changsha 410083.china College of Chemistry and Chemical Engineering Research Center of Modernization of Traditional Chinese Medicines Central South University Changsha China

Aim:To analyze the volatile chemical components of the herbal pair RhizomaLigustici Chuanxiong-Radix Paeoniae Rubra(RLC-RPR)and compare them withthose of each of the herbs ***:Gas chromatography-mass spectrom-etry(GC-MS),a chemometric resolution technique using the heuristic evolvinglatent projections(HELP)method,and the overall volume integration methodwere ***:In total,52.38,and 61 volatile chemical components in RLC,RPR,and RLC-RPR essential oils were determined,respectively,accounting for95.14%,95.19%,and 89.68% of the total contents of essential oil of RLC,RPR,andRLC-RPR,*** main volatile chemical components werebutyldienephthalide(2..65%)and ligustilide(50.15%)for RLC;and n-hexadecanoicacid(2..18%),[Z,Z]9,12.octadecadienoic acid(30.11%),2.hydroxy-benzaldehyde(17.08%)for RPR,and butyldienephthalide(14.80%),and ligustilide(38.91%)*** main volatile chemical components of RLC-RPR were almost thesame as those of RLC,but the relative amounts were ***:Thenumber of volatile chemical components in RLC-RPR was almost equal to the sumof the number in the 2.constituent herbs,but the relative amounts were ***,an acid-base reaction takes place during the process of decoctingthe *** data gathered in this study may be helpful for understanding thesynergistic nature of this herb pair in traditional chinese medicine.

关键词： herbal pair Rhizoma Ligustici Chuanxiong-Radix Paeoniae Rubra essential oil gas chromatography-mass spectrometry chemometric resolution method

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高效液相色谱法测定食物中的类胡萝卜素

色谱 2005年第1期23卷 57-62页

作者：卢红梅梁逸曾中南大学化学化工学院中药现代化研究中心湖南长沙410083

综述了用于食物中的类胡萝卜素、类胡萝卜素酯测定的高效液相色谱方法,介绍了样品提取处理方法、色谱分离条件及检测方法。引用文献85篇。

关键词：高效液相色谱法类胡萝卜素食物分析综述

Counter current chromatography numerical simulation

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Counter current chromatography numerical simulation

第十届全国计算(机)化学学术会议

作者： Zhaohui Yang,Bing Wang,Yizeng Liang (College of Chemistry and Chemical Engineering,research center of {2. of chinese medicines, central south university,changsha,410083,People’s Republic of china,)

For measuring a certain solute’s concentration distribution in counter current chromatography tube,a numerical model was suggested for calculation of the retention volume (V) and simulation of ***-Stage ratio(RSR) was introduced to describe retention time;it has positive proportion to the retention time(RSR =(F/V)t,where F is the flow rate;V is the balance mobile phase volume;t is time.).RSR(RSR =[(1-S+ kS)/(1 - S)](1 -1/n), where S is the retention ratio of stationary phase,n is stages number.) is a constant for a specified k value for a large number of stages(k value is defined as the proportion of concentration in the stationary phase and mobile phase).For a certain material,the concentration distribution is a Negative Binomial(x= Cpqx,where x is the concentration for a solute which distribution ratio is k,x is the initial concentration,p=(1-S)/(1-S+kS), q = kS/(1-S+kS)).For some solvent system,the consumed time for the balance of the solvents is very long and the consumption of solvents is costly,solvents reuse became very important,especially for the balanced ***-feed is essential for such a time and money consumed *** numerical model can predict the optimal feed *** influence to the process for the amount of a feeding solute is discussed *** efficiency(E),which was defined as E = n/n(n is stages,which can be measured by the equation n=1/2.qX,where X is the dimensionless concentration.),was introduced to determine the effect to the spectrum by different k values of different components.

关键词： numerical model retention volume row-stage ratio negative binomial multi-feed stage efficiency

A NOVEL 3D MOLECULAR SIMILARITY ALGORITHM BASED ON ENERGY SPECTRUM

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A NOVEL 3D MOLECULAR SIMILARITY ALGORITHM BASED ON ENERGY SP...

40th IUPAC Congress

作者： Wei Liu Jun Xu Shuo Chen Yizeng Liang * research center of {2. of traditional chinese Herb Medicine College of Chemistry and Chemical Engineering central south university changsha 410083 china.

Kernel k-nearest neighbor algorithm as a flexible SAR modeling tool

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Kernel k-nearest neighbor algorithm as a flexible SAR modeli...

中国化学会第2.届学术年会

作者： Dong-Sheng Cao1 Jian-Hua Huang1 Jun Yan1 Qing-Song Xu2.Yi-Zeng Liang*1 1research center of {2. of traditional chinese medicines central south university changsha 410083 P.R.china 2.chool of Mathematical Sciences and Computing Technology central south university changsha 410083 P.R.china research center of {2. of traditional chinese medicines Central South UniversityChangsha 410083 P.R. China School of Mathematical Sciences and Computing Technology Central South UniversityChangsha 410083 P.R. China

A kernel version of k-nearest neighbor algorithm （k-NN） has been developed to model the complex relationship between molecular descriptors and bioactivities of *** k-NN is to perform the original k-NN algorithm by mapping the training samples in the input space into a high-dimensional feature *** can be easily constructed by calculating the distance between samples in the feature space,directly deriving from the simple calculation of the kernel *** developed kernel k-NN is very flexible to deal with complex nonlinear relationship,more importantly;it can also conveniently cope with some non-vectorial data only by the definition of different *** results obtained from several real SAR datasets indicated that the performance of kernel k-NN is comparable to support vector machine *** can be regarded as an alternative modeling technique for several chemical problems including the study of structure-activity relationship （SAR）.The source codes implementing kernel k-NN in R language are freely available at http://***/p/kernelmethods/.

关键词： k-nearest neighbor (k-NN) kernel methods string kernel structure-activity relationship (SAR).

Planning Environmental Impact Assessment Orienting Sustainable Development: Opportunities and Challenges

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chinese Journal of Population,Resources and Environment 2005年第4期3卷 33-39页

作者： Sun Yanjun 1, Chen Xingeng 1, Bao Yun 2. Peng Xiaochun 3 & Gao Changbo 1 1.School of Environmental Science and Engineering, Sun Yat-sen university, Guangzhou 5102.5, china 2. {2. center for Coastal Ocean Science and Technology, Sun Yat-sen university, Guangzhou 5102.5, china 3. south china Institute of Environmental Science, SEPA, Guangzhou 510655, china

Strategic Environmental Assessment is a frontier subject in the field of Environmental Impact Assessment. In the past two decades, especially in recent years, much more importance has been attached to Strategic Environmental Assessment. The Environmental Impact Assessment Law of the P.R. china which was promulgated provides a great opportunity for the development of Planning Environmental Impact Assessment and brings great challenges for the development of traditional Project Environmental Impact Assessment and Planning Environmental Impact Assessment at the same time. In order to promote the implementation of "The EIA Law", the inherent limitations of Project Environmental Impact Assessment must be identified sufficiently and the theory {2. and practice of Planning Environmental Impact Assessment should be strengthened as well. Measures should be taken currently to enforce the operation system. The authors wish to offer a few references to the progress and implementation of Planning Environmental Impact Assessment in china.

关键词： planning environmental impact assessment strategic environmental assessment sustainable development opportunities challenges.

Predicting Drug-Target Interaction Networks by Fusing Drug and Target Kernel Measures

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Predicting Drug-Target Interaction Networks by Fusing Drug a...

中国化学会第2.届学术年会

作者： Dong-Sheng Cao1 Jian-Hua Huang1 Jun Yan1 Nai-Ping Dong1 Qian-Nan Hu4 Shao Liu3 Qing-Song Xu2.Yi-Zeng Liang1 1research center of {2. of traditional chinese medicines central south university changsha 410083 P.R.china 2.chool of Mathematical Sciences and Computing Technology central south university changsha 410083 P.R.china 3Xiangya Hospital central south university changsha 410008 P.R.china 4Key Laboratory of Combinatorial Biosynthesis and Drug Discovery (Wuhan university) Ministry of Education and Wuhan university School of Pharmaceutical Sciences Wuhan 430071 P.R.china research center of {2. of traditional chinese medicines Central South UniversityChangsha 410083 P.R. China Key Laboratory of Combinatorial Biosynthesis and Drug Discovery(Wuhan University)Ministry of Education and Wuhan University School of Pharmaceutical SciencesWuhan 430071 P.R.China Xiangya Hospital Central South University Changsha 410008 P. R. China School of Mathematical Sciences and Computing Technology Central South UniversityChangsha 410083 P.R.China

The identification of interactions between drugs and target proteins plays a key role in the process of genomic drug *** is both consuming and costly to determine drug-target interactions by experiments ***,there is an urgent need to develop new in silico prediction approaches capable of identifying these potential drug-target interactions in a timely manner.A key issue for predicting drug-target interactions is how to represent the interaction relationship between drugs and target proteins by using a certain numeric *** the work,we aim at addressing such an issue by using some basic properties of kernel *** means of different kernel representations,drug similarity can be represented by constructing a drug kernel matrix,and protein similarity a protein kernel *** interactions between drugs and target proteins are represented by some certain combination of drug kernel and target *** can be considered as a new interaction kernel representing complex interaction relationships between drugs and targets,strictly under the framework of basic kernel ***,we redesigned the question as a binary classification one by support vector machines （SVMs） with an interaction kernel as an *** classes of drug-target interaction networks in humans involving enzymes,ion channels,G-protein-coupled receptors （GPCRs） and nuclear receptors,are independently used for establishing predictive models using SVM as their operation engine,with each to predict the interactions between drugs and one of the four protein *** conclusion,the results demonstrate the ability of our proposed method to predict the drug-target interactions.

关键词： drug-target interaction data fusion molecular fingerprint networks genomic drug discovery kernel methods.

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5种大黄蒽醌类衍生物的同时测定及应用

时珍国医国药 2009年第10期20卷 2490-2492页

作者：吕慧英赵晨曦梁逸曾吴海中南大学化学化工学院中药现代化研究中心湖南长沙410083 长沙大学生物工程与环境科学系湖南长沙410003

目的建立同时测定大黄药材中5种蒽醌类衍生物（芦荟大黄素、大黄酸、大黄素、大黄酚和大黄素甲醚）含量的方法,优化大黄蒽醌的超声提取工艺。方法采用反相高效液相法,色谱柱：W aters C18柱（2.0 mm×4.6 mm,5μm）;流动相：甲醇-乙腈-0... 详细信息

目的建立同时测定大黄药材中5种蒽醌类衍生物（芦荟大黄素、大黄酸、大黄素、大黄酚和大黄素甲醚）含量的方法,优化大黄蒽醌的超声提取工艺。方法采用反相高效液相法,色谱柱：W aters C18柱（2.0 mm×4.6 mm,5μm）;流动相：甲醇-乙腈-0.01%磷酸溶液（3∶5∶2.;柱温：2.℃;流速：1.0 m l/m in;检测波长：2.5 nm。结果5种游离蒽醌均具有较宽的线性范围且呈良好的线性关系（R2.0.998 7～0.999 7）,平均回收率为92.79%～99.2.%,日内精密度为0.65%～1.71%,日间精密度为2.52.～3.46%。结论该方法成功应用于大黄活性物质的提取工艺优化,根据所建立的方法测得的5种游离蒽醌含量,确定了大黄蒽醌的最佳超声提取工艺为：以70%乙醇为溶剂、料液比为1∶30（g∶m l）、超声提取2.、每次提取2. m in。

关键词：超声提取大黄 RP-HPLC 蒽醌

均匀设计在蚕蛹虫草和冬虫夏草活性成分分析中的应用

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分析测试学报 2004年第2期23卷 35-37,40页

作者：周枝凤梁逸曾胡芸郭方遒中南大学化学化工学院中药现代研究中心湖南长沙410083

采用均匀实验设计方法快速找到蚕蛹虫草活性成分的高效液相色谱最优分离条件 ;将该优化条件用于蚕蛹虫草和冬虫夏草的水溶性成分的分离取得满意结果 ,并对部分组分进行了定性定量分析 ;均匀实验设计方法可较快找到复杂未知或半未知体系... 详细信息

采用均匀实验设计方法快速找到蚕蛹虫草活性成分的高效液相色谱最优分离条件 ;将该优化条件用于蚕蛹虫草和冬虫夏草的水溶性成分的分离取得满意结果 ,并对部分组分进行了定性定量分析 ;均匀实验设计方法可较快找到复杂未知或半未知体系的色谱分离条件。

关键词：蚕蛹虫草冬虫夏草活性成分成分分析均匀设计高效液相色谱