HPLC/MS Fingerprint Analysis of Tangshenosides

Radix codonopsis(党参)，which is derived fromCodonopsis pilosula, C.pilosula subsp. Modesta andC. Tangshen(ChP,2000),has been used as a remedy fora decrease of appetite, psychoneurosis, fatigue, dyspepsiaetc.or as a substitute for Panax ginseng in traditionalChinese medicine. Relating to the constituents of theseherbs, triterpenes, phytosterols, furaldehyde, sesquitesand some phenolic glycosides have been reported, butnone of these compounds seems to be responsible for thebiological activities of this drug. As regards the quality evaluation of Radix Codonopsis, a HPLC analysis of atractylenolide Ⅲ has been described, but this sesquiterpene lactone exists in a very low content and is difficultfor conventional analysis. The determination of polysaccharide also met limitation because of its non-specialization. In this paper, we report the HPLC/MS fingerprintsanalysis of phelolic glycosides from Radix Codonopsis including three species.

A valid evaluation method for UPLC fingerprint analysis and moisture ratio prediction model:application to microwave vacuum drying of Radix isatidis extract

Background:Drying is a necessary component of traditional Chinese medicine extracts.The heating principle of microwave vacuum drying is different from that of the conventional heat method.However,at present,there is paucity of information on the drying process of traditional Chinese medicine extract by microwave vacuum drying,and the results of such process are unclear.Methods:To study the dynamic changes in the chemical characteristics of microwave vacuum drying under different drying conditions,ultrahigh-performance liquid chromatography fingerprint profiles were established using Radix isatidis extract as a model drug and analyzed using similarity analysis,partial least squares-discriminant analysis,and semi-quantitative analysis.In addition,a backpropagation artificial neural network model was developed to predict the moisture ratio of the drying process.Results:Qualitative results showed that the similarity between different drying conditions was greater than 0.95,and 2 amino acid components(peaks 5 and 6)affected by process fluctuations were screened out.The quantitative results showed that the mass concentration of component 1 fluctuated after drying,while that of component 2 increased.The optimal backpropagation artificial neural network model structure used to predict the moisture ratio was 5-4-1,with regression and mean squared error values of 0.996 and 0.0003,respectively,after training,which were well fitted and had a strong approximation ability.Conclusion:Upon comparison of fingerprints and the evaluation of statistical methods,common components of Radix isatidis extract had little variation under different drying conditions,and the selected components provided a reference for the establishment of process evaluation indexes.The establishment of backpropagation artificial neural network provides a theoretical basis for the application of microwave vacuum drying technology and online monitoring of moisture ratio.

Chromatographic fingerprinting and quantitative analysis for the quality evaluation of Xinkeshu tablet

A simple, sensitive and accurate method based on high performance liquid chromato- graphy （HPLC） with diode array detector （DAD） was developed and validated for systematic quality evaluation of one type of traditional Chinese medicine preparations named Xinkeshu （XKS） tablet. In this study, the chromatographic fingerprints of XKS tablet were developed first, 23 peaks were selected as the common peaks to evaluate the similarities among different batches of XKS samples, which were manufactured in a long time span of three years. Additionally, simultaneous quantification of six markers in XKS tablet, including Danshensu, Protocatechuic aldehyde, Puerarin, Daidzin, Salvianolic acid B and Daidzein, was performed. The validation results showed that the developed method was specific, accurate, precise and robust. The preliminary explanation on why a close similarity between fingerprints did not exactly mean similar contents of chemical components in samples was given. The contribution of each chromatographic peak to similarity was also evaluated. The developed method offers an efficient, reliable and practical approach for systematic quality evaluation of XKS tablet.

Fingerprint analysis for the determination of hand origin(right/left)using the axis slant in whorl patterns

Fingerprints are frequently encountered during both civil and criminal investigations.Fingerprints possess numerous characteristics that assist with personal identification.Determining the hand of origin(right or left)for an individual fingerprint would help reduce investigation time and potentially eliminate certain suspects.In this study,we collected a total of 2900 single digit fingerprints from 290 individuals,and the whorl axis slant was examined in the 743 whorl pattern fingerprints(385 from the right hand and 358 from the left hand).A slant towards the right side was present in 81.82%of samples from the right hand,while a slant towards the left side was observed in 80.73%of samples from the left hand.After applying a chi-square test to the dataset,the results were found to be statistically significant for the determination of hand origin.Our results suggest that the whorl axis slant in a fingerprint is indicative of hand origin(right or left).

Chromatographic Fingerprint Analysis of Herbal Medicines

Thin-layer and High Performance Liquid Chromatography of Chinese Drugs Wagner H;Bauer R;Melchart D;Xiao PG;Staudinger A(Eds.) Originally published by Verlag für Ganzheitliche Medizin,Dr.Erich Wühr GmbH,2004 2nd ed.,revised,enlarged,2011,XL,1024 p.376 illus.,100 in color.In 2 volumes, not available separately Hardcover,ISBN

Geographical origin identification of winter jujube(Ziziphus jujuba Dongzao')by using multi-element fingerprinting with chemometrics

Winter jujube(Ziziphus jujuba'Dongzao')is greatly appreciated by consumers for its excellent quality,but brand infringement frequently occurs in the market.Here,we first determined a total of 38 elements in 167 winter jujube samples from the main winter jujube producing areas of China by inductively coupled plasma mass spectrometer(ICP-MS).As a result,16 elements(Mg,K,Mn,Cu,Zn,Mo,Ba,Be,As,Se,Cd,Sb,Ce,Er,Tl,and Pb)exhibited significant differences in samples from different producing areas.Supervised linear discriminant analysis(LDA)and orthogonal projection to latent structures discriminant analysis(OPLS-DA)showed better performance in identifying the origin of samples than unsupervised principal component analysis(PCA).LDA and OPLS-DA had a mean identification accuracy of 87.84 and 94.64%in the testing set,respectively.By using the multilayer perceptron(MLP)and C5.0,the prediction accuracy of the models could reach 96.36 and 91.06%,respectively.Based on the above four chemometric methods,Cd,Tl,Mo and Se were selected as the main variables and principal markers for the origin identification of winter jujube.Overall,this study demonstrates that it is practical and precise to identify the origin of winter jujube through multi-element fingerprint analysis with chemometrics,and may also provide reference for establishing the origin traceability system of other fruits.

Biological Fingerprinting Analysis of Interaction Between Taxoids in Taxus and Microtubule Protein by Microdialysis Coupled with High-performance Liquid Chromatography/Mass Spectrometry for Screening Antimicrotubule Agents

Some natural products, such as traditional Chinese medicines（TCMs）, contain compounds with anticancer activity and have attracted a great interest in recent years as alternative anticancer therapies. A quick and convenient assay for screening antimicrotubule compounds in which in vitro microdialysis/high-performance liquid chromatography （HPLC） is used to monitor the binding of the compounds extracted from TCM Taxus cuspidata Siebold ＆ Zucc（Taxus） to microtubules is reported. It was observed that the extract of Taxus contains at least five compounds which have affinity interaction with microtubules by biological fingerprinting analysis, and they were identified as the taxoids of taxol, baccatin III, 10-deacetylbaccatin Ⅲ（10-DAB）, cephalomannine and 7-epi-10-deacetyltaxol （7-epi-10-DAT） based on the comparison of their high-performance liquid chromatographic/mass spectrometric and UV spectra with those of the standard samples, both assembly-promoting and disassembly-inhibiting characteristics of those compounds were evaluated. It was observed that baccatin Ⅲ and 10-DAB bound to microtubules and the binding degrees were influenced by GTP. Competitive binding behavior of taxol with other four taxoids to microtubules was also investigated.

Qualitative and quantitative evaluation of Flos Puerariae by using chemical fingerprint in combination with chemometrics method

In order to better control the quality of Flos Puerariae(FP),qualitative and quantitative analyses were initially performed by using chemical fingerprint and chemometrics methods in this study.First,the fingerprint of FP was developed by HPLC and the chemical markers were screened out by similarity analysis(SA),hierarchical clustering analysis(HCA),principal components analysis(PCA),and orthogonal partial least squares discriminant analysis(OPLS-DA).Next,the chemical constituents in FP were profiled and identified by HPLC coupled to Fourier transform ion cyclotron resonance mass spectrometry(HPLCFT-ICR MS).Then,the characteristic constituents in FP were quantitatively analyzed by HPLC.As a result,31 common peaks were assigned in the fingerprint and 6 of them were considered as qualitative markers.A total of 35 chemical constituents were detected by HPLC-FT-ICR MS and 16 of them were unambiguously identified by comparing retention time,UV absorption wavelength,accurate mass,and MS/MS data with those of reference standards.Subsequently,the contents of glycitin,genistin,tectoridin,glycitein,genistein,and tectorigenin in 13 batches of FP were detected,ranging from 0.4438 to 11.06 mg/g,0.955 to 1.726 mg/g,9.81 to 57.22 mg/g,3.349 to 41.60 mg/g,0.3576 to 0.989 mg/g,and 2.126 to 9.99 mg/g,respectively.In conclusion,fingerprint analysis in combination with chemometrics methods could discover chemical markers for improving the quality control standard of FP.It is expected that the strategy applied in this study will be valuable for further quality control of other traditional Chinese medicines.

Fingerprint Liveness Detection Based on Multi-Scale LPQ and PCA

Fingerprint authentication system is used to verify users' identification according to the characteristics of their fingerprints.However,this system has some security and privacy problems.For example,some artificial fingerprints can trick the fingerprint authentication system and access information using real users' identification.Therefore,a fingerprint liveness detection algorithm needs to be designed to prevent illegal users from accessing privacy information.In this paper,a new software-based liveness detection approach using multi-scale local phase quantity(LPQ) and principal component analysis(PCA) is proposed.The feature vectors of a fingerprint are constructed through multi-scale LPQ.PCA technology is also introduced to reduce the dimensionality of the feature vectors and gain more effective features.Finally,a training model is gained using support vector machine classifier,and the liveness of a fingerprint is detected on the basis of the training model.Experimental results demonstrate that our proposed method can detect the liveness of users' fingerprints and achieve high recognition accuracy.This study also confirms that multi-resolution analysis is a useful method for texture feature extraction during fingerprint liveness detection.

Study of Depletion and Contamination Profile of Dioxins in Duck Intensive Production

During 2016, following the implementation of a dioxin contamination monitoring in poultry meat (ducks) in a slaughterhouse, a positive sample was found. The investigation identified the wood shavings used as bedding material in the duck farm as the possible source of contamination of these animals. In this episode, contamination profiles of higher and lower concentrations, seem to be very similar, being OCDD, OCDF and 1,2,3,4,6,7,8-HpCDD responsible for 74.4% of the total contamination of those animals. The study revealed a reduction of poultry contamination after the removal of the source of contamination, with an average daily depletion percentage level ranging between 1.43% and 4.35%.

PCDD/F Dioxin Profile of Treated Pinus pinaster Wood

This work describes the treatment of Pinus pinaster wood with four different industrial wood preservatives (two anti-bluing or fungicide and two fungicide/pesticide) and the detection and quantification of the dioxin contamination profile in the wood shavings. The samples were collected from poultry liters during three contamination incidents of poultry meat. Two methods used were, both nonpressure: one by immersing the wood samples in the preservative solution and the other by impregnation of the preservative solution into the wood, with vacuum. It was concluded that there is no difference in terms of contamination profile, caused by the different industrial wood treatment preservative products in study. A clear correlation between the commercial products used in wood treatment and the contamination profile of wood shavings that have been used as bedding material in poultry production was detected.

Evaluation of the physiochemical and metabolite of different region coffee beans by using UHPLC-QE-MS untargeted-metabonomics approaches

Coffee is one of the most important agricultural commodities and has the unique organoleptic characteristics such as strong but not bitter taste,fragrant,oily,and fruity.In this study,an untargeted metabolomics approach based on UHPLC-QE-MS was used to investigate the differences in terms of components of precursor metabolites in coffee beans from 18 producing regions worldwide.Fingerprint analysis,principal component analysis and hierarchical clustering analysis revealed a neat separation among coffee beans.Compounds with high relevance to variance in the projection values in supervised multivariate analysis were selected as important metabolites for the discrimination of coffee samples.In total,10 different families of compounds were considered as potential markers of the coffee beans:3-hydroxycoumarin,4,5-di-O-caffeoylquinic,cryptochlorogenic acid,palmitic amide,linoleamide,arachidic acid,petroselinic acid,trehalose,L-glutamic acid,L-malic acid.The findings presented herein serve as a suitable framework for the design of novel discrimination strategies in food origin tracing.

TANG Li-da

Thin-layer and High Performance Liquid Chromatography of Chinese Drugs Wagner H;Bauer R;Melchart D;Xiao PG;Staudinger A(Eds.) Originally published by Verlag für Ganzheitliche Medizin,Dr.Erich Wühr GmbH,2004 2nd ed.,revised,enlarged,2011,XL,1024 p.376 illus.,100 in color.In 2 volumes, not available separately Hardcover,ISBN 978-3-7091-0762-1

An Active De-anonymizing Attack Against Tor Web Traffic

Tor is pervasively used to conceal target websites that users are visiting. A de-anonymization technique against Tor, referred to as website fingerprinting attack, aims to infer the websites accessed by Tor clients by passively analyzing the patterns of encrypted traffic at the Tor client side. However, HTTP pipeline and Tor circuit multiplexing techniques can affect the accuracy of the attack by mixing the traffic that carries web objects in a single TCP connection. In this paper, we propose a novel active website fingerprinting attack by identifying and delaying the HTTP requests at the first hop Tor node. Then, we can separate the traffic that carries distinct web objects to derive a more distinguishable traffic pattern. To fulfill this goal, two algorithms based on statistical analysis and objective function optimization are proposed to construct a general packet delay scheme. We evaluate our active attack against Tor in empirical experiments and obtain the highest accuracy of 98.64%, compared with 85.95% of passive attack. We also perform experiments in the open-world scenario. When the parameter k of k-NN classifier is set to 5, then we can obtain a true positive rate of 90.96% with a false positive rate of 3.9%.