scholarly journals HPLC Fingerprint Analysis Combined with Chemometrics for Authentication of Kaempferia galanga from Related Species

2018 ◽  
Vol 16 (3) ◽  
pp. 308 ◽  
Author(s):  
Cahya Septyanti ◽  
Irmanida Batubara ◽  
Mohamad Rafi
Keyword(s):  
Principal Component Analysis ◽  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
Discriminant Analysis ◽  
Related Species ◽  
High Performance ◽  
Principal Component ◽  
Fingerprint Analysis ◽  
Hplc Fingerprint ◽  
Kaempferia Galanga

Fingerprint analysis using high performance liquid chromatography (HPLC) has been developed for authentication of Kaempferia galanga from related species, such as Kaempferia pandurata and K. rotunda. By comparing the fingerprint chromatograms of K. galanga, K. pandurata and K. rotunda, we could identify K. galanga samples and detect adulteration of K. galanga from K. pandurata and K. rotunda by using their marker peaks. We also combined HPLC fingerprint with chemometrics for discrimination the three species and also for authentication of K. galanga. All the three species and K. galanga adulterated with K. pandurata and K. rotunda were discriminated successfully by using principal component analysis (PCA) and discriminant analysis (DA). This result indicates that HPLC fingerprint analysis in combination with PCA (PC1 = 30.06% and PC2 = 34.74%) and DA (DF1 = 94.59% and DF2 = 3.32%) could be used for authentication of K. galanga samples from the related species.

Denaturing high-performance liquid chromatography and principal component analysis for identification of DNA point mutations in breast cancer and lymphoma samples

2018 ◽  
Vol 32 (10) ◽  
pp. e3053
Author(s):  
Yocanxóchitl Perfecto-Avalos ◽  
Raquel Cuevas-Díaz Durán ◽  
Luis Villela ◽  
Alejandro Garcia-Gonzalez ◽  
Ricardo Javier Díaz-Domínguez ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Principal Component Analysis ◽  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
High Performance ◽  
Point Mutations ◽  
Principal Component ◽  
Component Analysis

Establishment and comparative analysis of HPLC fingerprints of deer tissues

2020 ◽  
Vol 60 (10) ◽  
pp. 1343
Author(s):  
Mengjie Yao ◽  
Haiping Zhao ◽  
Xiaoyan Qi ◽  
Yuan Xu ◽  
Wenyuan Liu ◽  
...  
Keyword(s):  
Principal Component Analysis ◽  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
Chinese Medicine ◽  
Traditional Chinese Medicine ◽  
Evaluation System ◽  
High Performance ◽  
Principal Component ◽  
Component Analysis ◽  
Chemometric Methods

Context With the increasing use of velvet antlers (VA) as functional food or traditional Chinese medicine, the quality control has become more and more important. Aims Establish an effective method to provide a way of distinguishing VA from other types of deer tissue. Methods In the present study, 18 samples from three types of deer tissue were analysed on the basis of high-performance liquid chromatography, and a chromatogram of each sample was obtained. Then, these chromatograms were processed using the similarity evaluation system for chromatographic fingerprints of traditional Chinese medicine, to give the fingerprints of three deer tissues. The chemometric methods were used to analyse the fingerprint results, so as to identify the three types of deer tissue. Key results Shared peaks of VA, venison and deer bone were identified using similarity evaluation system. The results showed that, in total, 19 peaks were identified among these three types of deer tissue. Compared with venison, VA lacked three peaks (Numbers 3, 4 and 17); compared with deer bone, VA had six extra peaks (Numbers 2, 5, 8, 9, 14 and 19). The results of chemometric methods showed that different tissue samples could be classified into three categories by using both cluster analysis and principal component analysis. After principal component analysis and partial least-square discrimination analysis, seven peaks were selected, which had significant influence on the classification of VA, venison and deer bone. Conclusions The high-performance liquid-chromatography fingerprints in combination with chemometric methods can be used to effectively distinguish three deer tissue types, namely, VA, venison and deer bone. Implications We believe the method offers a useful tool much needed in the current Chinese velvet market.

scholarly journals Chemical Fingerprint Profiles and Pharmacodynamic Investigation for Quality Evaluation of Moxa Smoke by UHPLC in a Rat Model of Superficial Infection

2021 ◽  
Vol 2021 ◽  
pp. 1-10
Author(s):  
Yanling Wang ◽  
Shengbing Wu ◽  
Leijing Chen ◽  
Guo Xu ◽  
Xiaoxiao Wang ◽  
...  
Keyword(s):  
Aqueous Solution ◽  
Principal Component Analysis ◽  
Wound Healing ◽  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
Rat Model ◽  
High Performance ◽  
Principal Component ◽  
Superficial Infection ◽  
Chromatographic Peaks

Introduction. Moxibustion, a traditional Chinese medicine technique, involves the use of moxa smoke from Folium Artemisia argyi to treat various disorders, especially superficial infections. However, there is a higher health risk for people exposed to high levels of moxa smoke for extended durations. Here, we report the first ultra-high-performance liquid chromatography (UHPLC) fingerprint profiles and pharmacodynamic evaluation of moxa smoke, as well as evaluation of its aqueous solution on a rat model of superficial infection. Methods. A novel method for moxa smoke fingerprint profiling was developed using UHPLC under characteristic wavelength. Chromatographic peaks were further analyzed by ultra-high-performance liquid chromatography quadrupole-time-of-flight mass spectrometry (UHPLC-QTOF/MS). 12 sample batches obtained from various Chinese provinces were then analyzed using similarity evaluation, clustering analysis, and principal component analysis. The pharmacodynamics of moxa smoke and moxa aqueous solution were investigated on a rat model of acute skin wound infection. Results. UHPLC fingerprint profiles of 12 batches of moxa smoke were generated at 270 nm wavelength and 21 chromatographic peaks extracted as common peaks. Similarity between the 12 batches ranged from 0.341 to 0.982. Based on cluster analysis, the 12 batches of moxa smoke samples were clustered into five groups. Principal component analysis showed that the cumulative contribution of the three principal components reached 90.17%. Eigenvalues of the first, second, and third principal components were 10.794, 6.504, and 1.638, respectively. The corresponding variance contribution rates were 51.40%, 30.97%, and 7.80%, respectively. Pharmacological analysis found that wound healing was slow in the model group relative to the mupirocin ointment, moxa smoke, and aqueous moxa smoke solution groups. Histological analysis revealed markedly reduced tissue inflammation in rats treated with moxa smoke or its aqueous solution. Conclusions. Moxa smoke and its aqueous solution significantly promote wound healing upon superficial infection. A novel quality control method for moxa smoke was established and evaluated for the first time. As its main effects are unchanged, the transformation of moxa smoke into aqueous moxa smoke improves safety and is a simple and controllable process.

scholarly journals Species Classification and Quality Assessment of Cangzhu (Atractylodis Rhizoma) by High-Performance Liquid Chromatography and Chemometric Methods

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Yong-Gang Xia ◽  
Bing-You Yang ◽  
Qiu-Hong Wang ◽  
Jun Liang ◽  
Di Wang ◽  
...  
Keyword(s):  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
Discriminant Analysis ◽  
Quality Assessment ◽  
High Performance ◽  
Principal Component ◽  
Chemometric Methods ◽  
Species Classification ◽  
Linear Discriminant

Fast and sensitive high-performance liquid chromatography (HPLC) coupled with chemometric methods was utilized to assist in the quality assessment of Cangzhu (Atractylodis Rhizoma). By comparative analysis of chromatographic profiles, twelve common peaks were selected for multivariate analysis. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) of the chromatographic data demonstrated that 16 batches of Cangzhu samples could be welldifferentiated and categorized into two groups, which were closely related to their species (Atractylodes chinensis and A. lancea). By loading plots of PCA and OPLS-DA, the “common peaks” 2, 10, and 12 were defined as “marker peaks,” which were identified as atractylodinol, (4E,6E,12E)-tetradecatriene-8,10-diyne-1,3-diyl diacetate, and atractylodin, respectively. These three “marker peaks” were then simultaneously quantified for further controlling the quality of Cangzhu, which showed acceptable linearity, both intraday and interday precisions (RSD ≤ 2.30%), repeatability (RSD ≤ 2.82%), and the recoveries of the three analytes in the range of 96.57–100.16%, with RSDs less than 1.46%. Finally, linear discriminant analysis (LDA) was successfully used to build predictive models of the group membership based on the contents of three marker peaks. Results of the present study demonstrated that HPLC-based metabolic profiling coupled with chemometric methods and quantificational determination was a very flexible, reliable, and effective way for homogeneity evaluation and quality assessment of traditional Chinese medicine.

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