Identification of ginsenosides in roots of Panax ginseng by HPLC-APCI/MS

A new HPLC-APCI/MS method for the identification of ginsenosides has been developed. The analyses were performed on a reversed-phase C-18 column using a binary eluent (acetonitrile and water) under gradient conditions. Although APCI is a high-temperature evaporative process, HPLC-APCI/MS could effectively identify thermo-labile ginsenosides. The [M-H](-) ions and the thermal degradation ions of ginsenosides could be clearly observed under negative and positive ion conditions, respectively, and these were used to identify the molecular masses, the aglycone structures and the sugar groups of ginsenosides. APCI/MS can provide more explicit information than ESI/MS for identifying and distinguishing ginsenosides. Using the HPLC-APCI/MS method, 35 ginsenosides were identified in Panax ginseng. Copyright (C) 2005 John Wiley & Sons, Ltd.

Screening and analysis of bioactive compounds with biofingerprinting chromatogram analysis of traditional Chinese medicines targeting DNA by microdialysis/HPLC

Biofingerprinting chromatogram, analysis, which is defined as the comparison of fingerprinting chromatograms of the extract of traditional Chinese medicines (TCMs) before and after the interaction with biological systems (DNA, protein. cell. etc.), was proposed for screening and analysis of the multiple bioactive compounds in TCMs. A method of microdialysis sampling combined with high performance liquid chromatography (HPLC) was applied to the study of DNA-binding property for the extracts of TCMs. Seven compounds were found to bind to calf thymus DNA (ct-DNA) from the TCMs of Coptis chinensis Franch (Coptis), but only three ones from Phellodendron amurense Rupr. (Phellodendron) and none from Sophoraflavescens Ait. (Sophora) to bind to ct-DNA. respectively. Three of them were identified as berberine, palmatine and jatrorrhizine and their association constants (K) to ct-DNA were determined by microdialysis/HPLC. Competitive binding behaviors of them to ct-DNA were also investigated. © 2005 Elsevier B.V. All rights reserved.

Improved performance of comprehensive two-dimensional HPLC separation of traditional Chinese medicines by using a silica monolithic column and normalization of peak heights

Performance of comprehensive two-dimensional liquid chromatography system is greatly improved than we reported previously by using a silica monolithic column as for the second dimensional separation. Due to the increase of the elution speed on the second dimensional monolithic column, the first dimensional column efficiency and analysis rate can be greatly improved as comparing with conventionally second dimensional column. The developed system was applied to analysis of methanol extraction of two umbelliferae herbs Ligusticum chuanxiong Hort. and Angelica sinensis (Oliv.) Diels by using CN column as for the first dimensional separation and a silica monolithic ODS column for the second dimensional separation, and the obtained three-dimensional chromatograms were treated by normalization of peak heights with the value of the highest peak or setting a certain value using a software written in-house. It was observed that much more peaks for low-abundant components in TCM extract can clearly be detected here than we reported before, due to the large difference for the amount of components in TCMs' extract. With the above improvements in separation performance and data treatment, totally about 120 components in methanol extraction of Rhizoma chuanxiong and 100 in A. sinensis were separated with UV detection within 130 min. This result meant that both the number of peaks detected increase twice but the analysis time decease twice if comparing with the previously reported result. (c) 2005 Published by Elsevier B.V.

Characterization of interaction property of multicomponents in Chinese Herb with protein by microdialysis combined with HPLC

Interaction of traditional Chinese Herb Rhizoma Chuanxiong and protein was studied by microdialysis coupled with high performance liquid chromatography. Compounds in Rhizoma Chuanxiong, such as ferulic acid, senkyunolide A and 3-butylphthalide, were identified by HPLC, HPLC-MS and UV-vis. Microdialysis recoveries and binding degrees of compounds in Rhizoma Chuanxiong with human serum albumin (HSA) and other human plasma protein were determined: recoveries of microdialysis sampling ranged from 36.7 to 98.4% with R.S.D. below 3.1%; while binding to HSA ranged from 0 to 91.5% (0.3 mM HSA) and from 0 to 93.5% (0.6 mM HSA), respectively. Compared with HSA, most of compounds bound to human blood serum more extensively and the results showed that binding of these compounds in Rhizoma Chuanxiong was influenced by pH. Two compounds were found to bind to HSA and human blood serum. their binding degrees were consistent with ferulic acid and 3-butylphthalide, the active compounds in Rhizoma Chuanoxiong. (c) 2005 Elsevier B.V. All rights reserved.

Metabolic Engineering, metabolite profiling and machine learning to investigate the phloem-mobile signal in systemic acquired resistance in tobacco

Draper, J., Darby, R.M., Beckmann, M., Maddison, A.L., Mondhe, M., Sheldrick, C., Taylor, J., Goodacre, R., and Kell, D.B. (2002) Metabolic Engineering, metabolite profiling and machine learning to investigate the phloem-mobile signal in systemic acquired resistance in tobacco. First International Congress on Plant Metabolomics, Wageningen, The Netherlands

Criminal Profiling : A Continuing History

Chapter 1 RAE2008

Load Profiling in Distributed Real-Time Systems

Load balancing is often used to ensure that nodes in a distributed systems are equally loaded. In this paper, we show that for real-time systems, load balancing is not desirable. In particular, we propose a new load-profiling strategy that allows the nodes of a distributed system to be unequally loaded. Using load profiling, the system attempts to distribute the load amongst its nodes so as to maximize the chances of finding a node that would satisfy the computational needs of incoming real-time tasks. To that end, we describe and evaluate a distributed load-profiling protocol for dynamically scheduling time-constrained tasks in a loosely-coupled distributed environment. When a task is submitted to a node, the scheduling software tries to schedule the task locally so as to meet its deadline. If that is not feasible, it tries to locate another node where this could be done with a high probability of success, while attempting to maintain an overall load profile for the system. Nodes in the system inform each other about their state using a combination of multicasting and gossiping. The performance of the proposed protocol is evaluated via simulation, and is contrasted to other dynamic scheduling protocols for real-time distributed systems. Based on our findings, we argue that keeping a diverse availability profile and using passive bidding (through gossiping) are both advantageous to distributed scheduling for real-time systems.