Specific targeted quantification combined with non-targeted metabolite profiling for quality evaluation of Gastrodia elata tubers from different geographical origins and cultivars

Identification of geographical origins of Gastrodia elata Blume based on multisource data fusion

INTRODUCTION

Identifying the geographical origin of Gastrodia elata Blume contributes to the scientific and rational utilization of medicinal materials. In this study, infrared spectroscopy was combined with machine learning algorithms to distinguish the origin of G. elata BI.

OBJECTIVE

Realization of rapid and accurate identification of the origin of G. elata BI.

MATERIALS AND METHODS

Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectra and Fourier transform near-infrared (FT-NIR) spectra were collected for 306 samples of G. elata BI.

SAMPLES

Firstly, a support vector machine (SVM) model was established based on the single-spectrum and the full-spectrum fusion data. To investigate whether feature-level fusion strategy can enhance the model's performance, the sequential and orthogonalized partial least squares discriminant analysis (SO-PLS-DA) model was established to extract and combine two types of spectral features. Next, six algorithms were employed to extract feature variables, SVM model was established based on the feature-level fusion data. To avoid complicated preprocessing and feature extraction processes, a residual convolutional neural network (ResNet) model was established after converting the raw spectral data into spectral images.

RESULTS

The accuracy of the feature-level fusion model is better as compared to the single-spectrum model and the fusion model with full-spectrum, and SO-PLS-DA is simpler than feature-level fusion based on the SVM model. The ResNet model performs well in classification but requires more data to enhance its generalization capability and training effectiveness.

CONCLUSION

Sequential and orthogonalized data fusion approaches and ResNet models are powerful solutions for identifying the geographic origin of G. elata BI.

Rapid authentication of variants of Gastrodia elata Blume using near-infrared spectroscopy combined with chemometric methods

The variety is one of the most important factors to generate difference of chemical compositions, which unavoidably influences the quality of natural medicine. Thus, simple and rapid authentication of different variants has great academic and practical significance. In this study, the goal was achieved with the help of near infrared spectroscopy (NIR) and chemometrics by using Gastrodia elata Blume as an example. A total of 540 samples including two classes of variants and their forms were investigated as a whole. The mean spectra of samples of each class and their 2-D synchronous correlation spectra were simultaneously applied to discover the difference of chemical characteristics. After hybrid pre-processing of the first and second derivative combined with Savitzky-Golay and Norris filtering, partial least squares discrimination analysis (PLS-DA) on the basis of latent variable projection was used to assess the feasibility for classification. The results show higher prediction accuracy in both internal test set and external prediction set. In order to further improve the robustness for modeling, three methods for wavelength selection were comprehensively compared to optimize PLS-DA models, including variable importance in the projection (VIP), random frog (RF), and Monte Carlo uninformative variable elimination (MC-UVE). The prediction accuracy of combination of the 2nd derivative, Norris, MC-UVE and PLS-DA achieved to 99.11% and 98.89% corresponding to the internal test set and external prediction set, respectively. The strategies proposed in this work perform effectiveness for rapid and accurate authentication of variants of plants with high chemical complexity.

Bioactivity Profiling and Quantification of Gastrodin in Gastrodia elata Cultivated in the Field versus Facility via Hyphenated High-Performance Thin-Layer Chromatography

Gastrodia elata (Orchidaceae) is native to mountainous areas of Asia and is a plant species used in traditional medicine for more than two thousand years. The species was reported to have many biological activities, such as neuroprotective, antioxidant, and anti-inflammatory activity. After many years of extensive exploitation from the wild, the plant was added to lists of endangered species. Since its desired cultivation is considered difficult, innovative cultivation methods that can reduce the costs of using new soil in each cycle and at the same time avoid contamination with pathogens and chemicals are urgently needed on large scale. In this work, five G. elata samples cultivated in a facility utilizing electron beam-treated soil were compared to two samples grown in the field concerning their chemical composition and bioactivity. Using hyphenated high-performance thin-layer chromatography (HPTLC) and multi-imaging (UV/Vis/FLD, also after derivatization), the chemical marker compound gastrodin was quantified in the seven G. elata rhizome/tuber samples, which showed differences in their contents between facility and field samples and between samples collected during different seasons. Parishin E was also found to be present. Combining HPTLC with on-surface (bio)assays, the antioxidant activity and inhibition of acetylcholinesterase as well as the absence of cytotoxicity against human cells were demonstrated and compared between samples.

Biogenic Solution Map Based on the Definition of the Metabolic Correlation Distance between 4-Dimensional Fingerprints

Accurate discrimination and classification of unknown species are the basis to predict its characteristics or applications to make correct decisions. However, for biogenic solutions that are ubiquitous in nature and our daily lives, direct determination of their similarities and disparities by their molecular compositions remains a scientific challenge. Here, we explore a standard and visualizable ontology, termed "biogenic solution map", that organizes multifarious classes of biogenic solutions into a map of hierarchical structures. To build the map, a novel 4-dimensional (4D) fingerprinting method based on data-independent acquisition data sets of untargeted metabolomics is developed, enabling accurate characterization of complex biogenic solutions. A generic parameter of metabolic correlation distance, calculated based on averaged similarities between 4D fingerprints of sample groups, is able to define "species", "genus", and "family" of each solution in the map. With the help of the "biogenic solution map", species of unknown biogenic solutions can be explicitly defined. Simultaneously, intrinsic correlations and subtle variations among biogenic solutions in the map are accurately illustrated. Moreover, it is worth mentioning that samples of the same analyte but prepared by alternative protocols may have significantly different metabolic compositions and could be classified into different "genera".

Identification and quality evaluation of Chinese rice wine using UPLC-PDA-QTOF/MS with dual-column separation

BACKGROUND

Chinese rice wine (CRW) is a well-known drink and functional food that is used in traditional Chinese medicine. However, there is still a lack of quality control and evaluation methods for CRWs.

PURPOSE

The study aimed to establish a new method that can serve both as quality control and evaluation method and, as well as an identification method for CRWs.

METHOD

Compound identification in different CRW samples and determination of uracil, xanthine, uridine, adenine, guanosine, 5-hydroxymethylfurfural, and adenosine contents from 29 CRW samples from 14 brands were performed using UPLC-PDA/TOF-MS. The dual-column chromatographic separation of CRW was performed using CORTECS T3 coupled to HSS T3. The optimal mobile phase consisted of water with 0.1% formic acid, 40 mM ammonium acetate, and methanol: acetonitrile (2:1). Furthermore, to compare the UPLC fingerprints between CRWs of different brands, a similarity analysis was performed to classify the CRW samples. Finally, network pharmacology and in vitro efficacy and toxicity tests were used to investigate the biological function of the seven components and CRWs.

RESULTS

A total of 55 compounds were unambiguously or tentatively identified. Among them, nucleoside, pyrimidines and purines were reported in CRW for the first time. The seven components were successfully determined, and their contents showed large variations among different brands of CRW, which was consistent with the results of the chromatographic fingerprint similarities. The results of in vitro efficacy and toxicity tests indicated that CRWs and seven components had obvious protective effect on H9c2 cell injury induced by the H₂O₂ model. Network pharmacology analysis showed that these seven compounds might be the main active components of CRW that promote blood circulation and ventilation.

CONCLUSION

This study revealed that dual-column chromatographic separation is an effective method for quantitative and chromatographic fingerprint analyzes of complex samples, and seven compounds can be used for the quality evaluation and control of CRWs.

Fast identification of the geographical origin of Gastrodia elata using excitation-emission matrix fluorescence and chemometric methods

Geographical origin is an important factor affecting the quality of traditional Chinese medicine. In this paper, the identification of geographical origin of Gastrodia elata was performed by using excitation-emission matrix fluorescence and chemometric methods. Firstly, excitation-emission matrix (EEM) fluorescence spectra of Gastrodia elata samples from different geographical origins were obtained. And then three chemometric methods, including multilinear partial least squares discriminant analysis (N-PLS-DA), unfold partial least squares discriminant analysis (U-PLS-DA), and k-nearest neighbor (kNN) method, were applied to build discriminant models. Finally, 45 Gastrodia elata samples could be differentiated from each other by these classification models according to their geographical origins. The results showed that all models obtained good classification results. Compared with the N-PLS-DA and U-PLS-DA, kNN got more accurate and reliable classification results and could identify Gastrodia elata samples from different geographical origins with 100% accuracy on the training and test set. Therefore, the proposed method was available for easily and quickly distinguishing the geographical origin of Gastrodia elata, which can be considered as a promising alternative method for determining the geographic origin of other traditional Chinese medicines.

Discovery of Quality Markers of Nucleobases, Nucleosides, Nucleotides and Amino Acids for Chrysanthemi Flos From Different Geographical Origins Using UPLC-MS/MS Combined With Multivariate Statistical Analysis

Nucleobases, nucleosides, nucleotides and amino acids, as crucial nutrient compositions, play essential roles in determining the flavor, function and quality of Chrysanthemi Flos. The quality of Chrysanthemi Flos from different geographical origins is uneven, but there have been no reports about the screening of their quality markers based on nutritional ingredients. Here, we developed a comprehensive strategy integrating ultra performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry (UPLC-MS/MS) and multivariate statistical analysis to explore quality markers of Chrysanthemi Flos from different geographical origins and conduct quality evaluation and discrimination of them. Firstly, a fast, sensitive, and reliable UPLC-MS/MS method was established for simultaneous quantification 28 nucleobases, nucleosides, nucleotides and amino acids of Chrysanthemi Flos from nine different regions in China. The results demonstrated that Chrysanthemi Flos from nine different cultivation regions were rich in the above 28 nutritional contents and their contents were obvious different; however, correlation analysis showed that altitude was not the main factor for these differences, which required further investigation. Subsequently, eight crucial quality markers for nine different geographical origins of Chrysanthemi Flos, namely, 2'-deoxyadenosine, guanosine, adenosine 3',5'-cyclic phosphate (cAMP), guanosine 3',5'-cyclic monophosphate (cGMP), arginine, proline, glutamate and tryptophan, were screened for the first time using partial least squares discriminant analysis (PLS-DA) and the plot of variable importance for projection (VIP). Moreover, a hierarchical clustering analysis heat map was employed to intuitively clarify the distribution of eight quality markers in the nine different regions of Chrysanthemi Flos. Finally, based on the contents of selected eight quality markers, support vector machines (SVM) model was established to predict the geographical origins of Chrysanthemi Flos, which yielded excellent prediction performance with an average prediction accuracy of 100%. Taken together, the proposed strategy was suitable to discover the quality markers of Chrysanthemi Flos and could be used to discriminate its geographical origin.

An integrated strategy toward comprehensive characterization and quantification of multiple components from herbal medicine: An application study in Gelsemium elegans

Objective

To develop a powerful integrated strategy based on liquid chromatography coupled with mass spectrometry (LC-MS) systems for the comprehensive characterization and quantification of multiple components of herbal medicines.

Methods

Firstly, different mobile phase additives, analysis time, and MS acquisition modes were orthogonally tested with liquid chromatography coupled with quadrupole time-of-flight mass spectrometry (LC-QTOF/MS) in order to detect as many components of Gelsemium elegans as possible with high peak intensity. Secondly, several data mining strategies, including database searching, diagnostic ion filtering and neutral loss filtering, were utilized to perform chemical profiling. Subsequently, this study focused on the quantification and validation of the performance of a liquid chromatography-triple mass spectrometry (LC-QqQ/MS) assay based on derivative multiple reaction monitoring (DeMRM).

Results

A total of 147 components from G. elegans were characterized, among them 116 nontarget components were reported for the first time. A sensitive and reproducible LC-QqQ/MS method was successfully developed and validated for the simultaneous relative quantification of 41 components of G. elegans. This LC-QqQ/MS method was then applied to compare the contents of components in the roots, stems and leaves.

Conclusion

The present integrated strategy would significantly contribute to chemical studies on herbal medicine, and its utility could be extended to other research fields, such as metabolomics, quality control, and pharmacokinetics.

Near-Infrared Spectroscopy as a Process Analytical Technology Tool for Monitoring the Steaming Process of Gastrodiae rhizoma with Multiparameters and Chemometrics

Steaming is a vital unit operation in traditional Chinese medicine (TCM), which greatly affects the active ingredients and the pharmacological efficacy of the products. Near-infrared (NIR) spectroscopy has already been widely used as a strong process analytical technology (PAT) tool. In this study, the potential usage of NIR spectroscopy to monitor the steaming process of Gastrodiae rhizoma was explored. About 10 lab scale batches were employed to construct quantitative models to determine four chemical ingredients and moisture change during the steaming process. Gastrodin, p-hydroxybenzyl alcohol, parishin B, and parishin A were modeled by different multivariate calibration models (SMLR and PLS), while the content of the moisture was modeled by principal component regression (PCR). In the optimized models, the root mean square errors of prediction (RMSEP) for gastrodin, p-hydroxybenzyl alcohol, parishin B, parishin A, and moisture were 0.0181, 0.0143, 0.0132, 0.0244, and 2.15, respectively, and correlation coefficients (R _p ²) were 0.9591, 0.9307, 0.9309, 0.9277, and 0.9201, respectively. Three other batches' results revealed that the accuracy of the model was acceptable and that was specific for next drying step. In addition, the results demonstrated the method was reliable in process performance and robustness. This method holds a great promise to replace current subjective color judgment and time-consuming HPLC or UV/Vis methods and is suitable for rapid online monitoring and quality control in the TCM industrial steaming process.

Assessing Geographical Origin of Gentiana Rigescens Using Untargeted Chromatographic Fingerprint, Data Fusion and Chemometrics

Gentiana rigescens Franchet, which is famous for its bitter properties, is a traditional drug of chronic hepatitis and important raw materials for the pharmaceutical industry in China. In the study, high-performance liquid chromatography (HPLC), coupled with diode array detector (DAD) and chemometrics, were used to investigate the chemical geographical variation of G. rigescens and to classify medicinal materials, according to their grown latitudes. The chromatographic fingerprints of 280 individuals and 840 samples from rhizomes, stems, and leaves of four different latitude areas were recorded and analyzed for tracing the geographical origin of medicinal materials. At first, HPLC fingerprints of underground and aerial parts were generated while using reversed-phase liquid chromatography. After the preliminary data exploration, two supervised pattern recognition techniques, random forest (RF) and orthogonal partial least-squares discriminant analysis (OPLS-DA), were applied to the three HPLC fingerprint data sets of rhizomes, stems, and leaves, respectively. Furthermore, fingerprint data sets of aerial and underground parts were separately processed and joined while using two data fusion strategies (“low-level” and “mid-level”). The results showed that classification models that are based OPLS-DA were more efficient than RF models. The classification models using low-level data fusion method built showed considerably good recognition and prediction abilities (the accuracy is higher than 99% and sensibility, specificity, Matthews correlation coefficient, and efficiency range from 0.95 to 1.00). Low-level data fusion strategy combined with OPLS-DA could provide the best discrimination result. In summary, this study explored the latitude variation of phytochemical of G. rigescens and developed a reliable and accurate identification method for G. rigescens that were grown at different latitudes based on untargeted HPLC fingerprint, data fusion, and chemometrics. The study results are meaningful for authentication and the quality control of Chinese medicinal materials.

A high-throughput metabolomics approach for the comprehensive differentiation of four Pulsatilla Adans herbs combined with a nontargeted bidirectional screen for rapid identification of triterpenoid saponins

Pulsatilla Adans (PSA) herbs (Ranunculaceae) have been widely used in traditional medicine in China and other countries. However, the authentication and quality control of PSA herbs have always been a challenging task due to their similar morphological characteristics and the diversity of the multiple components that exist in the complicated matrix. Herein, a novel integrated strategy combining UHPLC/Q-Orbitrap-MS techniques with chemometrics analysis is proposed for the discrimination of PSA materials. We developed a comprehensive method integrating a nontargeted bidirectionally screened (NTBDS) MS data set and a targeted extraction peak area analysis for the characterization of triterpenoid saponins of PSA from different species. After that, partial least-squares discriminant analysis (PLS-DA) was performed on the obtained MS data set and the parameter variable importance for the projection (VIP) value and P value were employed to screen the valuable MS features to discriminate PSA from different species. In addition, the receiver operating characteristic (ROC) curve is used to verify the reliability of MS features. Finally, heatmap visualization was employed to clarify the distribution of the identified triterpenoid saponins, and four medicinal species of PSA were successfully differentiated. Additionally, 34 constituents were reported in PSAs for the first time, 81 triterpenoid saponins were identified as differential components, and 12 chemical ingredients were characterized as potential chemical markers to differentiate the four officinal PSA herbs. This is the first time that the differences in different PSA herbs have been observed systematically at the chemical level. The results suggested that using the identified characteristic components as chemical markers to identify different PSA herbs was effective and viable. This method provides promising perspectives in the analysis and identification of the ingredients of Chinese herbal medicines, and the identification of similar herbs from the same species.

Comparison of Bioactive Compounds and Antioxidant Activities of Maclura tricuspidata Fruit Extracts at Different Maturity Stages

Maclura tricuspidata fruit contains various bioactive compounds and has traditionally been used in folk medicine and as valuable food material in Korea. The composition and contents of bioactive compounds in the fruit can be influenced by its maturity stages. In this study, total phenol, total flavonoid, individual polyphenolic compounds, total carotenoids and antioxidant activities at four maturity stages of the fruit were determined. Polyphenolic compounds were analyzed using high-pressure liquid chromatography-quadrupole time-of-flight mass spectrometry (HPLC-QTOF-MS) and HPLC. Among 18 polyphenolic compounds identified in this study, five parishin derivatives (gastrodin, parishin A, B, C, E) were positively identified for the first time in this plant. These compounds were also validated and quantified using authentic standards. Parishin A was the most abundant component, followed by chlorogenic acid, gastrodin, eriodictyol glucoside, parishin C, parishin E and parishin B. The contents of all the polyphenolic compounds were higher at the immature and premature stages than at fully mature and overmature stages, while total carotenoid was found to be higher in the mature and overmature stages. Overall antioxidant activities by three different assays (DPPH, ABTS, FRAP) decreased as maturation progressed. Antioxidant properties of the fruit extract are suggested to be attributed to the polyphenols.

Discrimination of Gastrodia elata from Different Geographical Origin for Quality Evaluation Using Newly-Build Near Infrared Spectrum Coupled with Multivariate Analysis

Discrimination of Gastrodia elata (G. elata) geographical origin is of great importance to pharmaceutical companies and consumers in China. this paper focuses on the feasibility of near infrared spectrum (NIRS) combined multivariate analysis as a rapid and non-destructive method to prove its fit for this purpose. Firstly, 16 batches of G. elata samples from four main-cultivation regions in China were quantified by traditional HPLC method. It showed that samples from different origins could not be efficiently differentiated by the contents of four phenolic compounds in this study. Secondly, the raw near infrared (NIR) spectra of those samples were acquired and two different pattern recognition techniques were used to classify the geographical origins. The results showed that with spectral transformation optimized, discriminant analysis (DA) provided 97% and 99% correct classification for the calibration and validation sets of samples from discriminating of four different main-cultivation regions, and provided 98% and 99% correct classifications for the calibration and validation sets of samples from eight different cities, respectively, which all performed better than the principal component analysis (PCA) method. Thirdly, as phenolic compounds content (PCC) is highly related with the quality of G. elata, synergy interval partial least squares (Si-PLS) was applied to build the PCC prediction model. The coefficient of determination for prediction (R_p²) of the Si-PLS model was 0.9209, and root mean square error for prediction (RMSEP) was 0.338. The two regions (4800 cm⁻¹–5200 cm⁻¹, and 5600 cm⁻¹–6000 cm⁻¹) selected by Si-PLS corresponded to the absorptions of aromatic ring in the basic phenolic structure. It can be concluded that NIR spectroscopy combined with PCA, DA and Si-PLS would be a potential tool to provide a reference for the quality control of G. elata.

Comprehensive quality evaluation and comparison of Angelica sinensis radix and Angelica acutiloba radix by integrated metabolomics and glycomics

Angelica radix (Danggui in Chinese) used in China and Japan is derived from two species of Angelica, namely Angelica sinensis and Angelica acutiloba, respectively. The differences in quality between A. sinensis radix (ASR) and A. acutiloba radix (AAR) should be therefore investigated to guide the medicinal and dietary applications of these two species. Secondary metabolites and carbohydrates have been demonstrated to be the two major kinds of bioactive components of Danggui. However, previously, quality comparison between ASR and AAR intensively concerned secondary metabolites but largely overlooked carbohydrates, thus failing to include or take into consideration an important aspect of the holistic quality of Danggui. In this study, untargeted/targeted metabolomics and glycomics were integrated by multiple chromatography-based analytical techniques for qualitative and quantitative characterization of secondary metabolites and carbohydrates in Danggui so as to comprehensively evaluate and compare the quality of ASR and AAR. The results revealed that not only secondary metabolites but also carbohydrates in ASR and AAR were different in type and amount, which should collectively contribute to their quality difference. By providing more comprehensive chemical information, the research results highlighted the need to assess characteristics of both carbohydrates and secondary metabolites for overall quality evaluation and comparison of ASR and AAR.

Novel Strategies Using Total Gastrodin and Gastrodigenin, or Total Gastrodigenin for Quality Control of Gastrodia elata

Gastrodia elata Blume (G. elata), a traditional Chinese medicine, is widely used for treatment of various neuro dysfunctions. However, its quality control is still limited to the determination of gastrodin. In the present study, two novel strategies based on quantitative evaluation of total gastrodin and gastrodigenin with base hydrolysis and total gastrodigenin with base-enzymatic hydrolysis followed by HPLC-FLD were put forward and successfully applied to evaluate the quality of 47 batches of G. elata from eight localities. Meanwhile, a systematic comparison of the novel strategy with the multiple markers and the Pharmacopeia method was performed. The results showed that the parishins category could be completely hydrolyzed to gastrodin by sodium hydroxide solution, and gastrodin could further utterly hydrolyze to gastrodigenin with β-d-glucosidase buffer solution. The contents of total gastrodin and gastrodigenin ranged from 1.311% to 2.034%, and total gastrodigenin from 0.748% to 1.120% at the eight localities. From the comparison, we can conclude that the two novel strategies can comprehensively reveal the characteristics of overall active ingredients in G. elata for quality control. The present study provides a feasible and credible strategy for the quality control of G. elata, suggesting a revision of the latest Chinese Pharmacopoeia or European Pharmacopoeia methods for the modernization of G. elata use.

A practical protocol for comprehensive evaluation of sulfur-fumigation of Gastrodia Rhizoma using metabolome and health risk assessment analysis

Gastrodia Rhizoma is one of the most heavily sulfur-fumigated edible and medical herbs in the marketplace. We developed a practical protocol using an ultra-performance liquid chromatography coupled with quadrupole time-of-flight-MS^E (UPLC/QTOF-MS^E)-based metabolome and health risk assessment model to identify characteristic sulfur-fumigated markers, dissect chemical transformation mechanisms, and control the quality of sulfur-fumigated Gastrodia Rhizoma. Two sulfur-containing p-hydroxybenzyl products, one sulfur-containing disaccharide, one glycolipid, and two phospholipids were selected and identified as markers based on multivariate statistical analysis. In particular, the sulfur-containing markers p-hydroxybenzyl hydrogen sulfite and trace p-mercaptobenzyl hydrogen sulfate were positively correlated with the active major phenolics. Moreover, a practical index the time of the minimum content was useful for evaluating the extent of the sulfur-fumigation under different weight ratios of the sulfur to herbal materials (1:20, 1:40, and 1:80). Ultimately, the 1:40 ratio within 1h of sulfur-fumigation was considered as safe and efficient for herb quality preservation under the maximum residue limit of 750mg/kg. This study shows that the practical protocol-based discriminated markers and practical limits can be applied to quality assurance of sulfur-fumigation and non-fumigation Gastrodia Rhizoma and other edible or medical materials.

Untargeted metabolite analysis-based UHPLC-Q-TOF-MS reveals significant enrichment of p-hydroxybenzyl dimers of citric acids in fresh beige-scape Gastrodia elata (Wutianma)

In order to comprehensively elucidate the chemical biosynthesis process of the beige-scape Gastrodia elata Blume (Wutianma) as a traditional herbal medicines, the untargeted analysis-based UHPLC-PDA-ESI-Q-TOF-MS reveals the metabolites ranging from the skeletons to novel dimers of citric acids in fresh and dried immature/mature stem tubers. Interestingly, two novel types of dimers for citric acids with the anhydride groups at sn-1 and/or sn-5 were discovered in fresh samples. Moreover, the classical mono- versus novel di-mers, and the aglycons versus the glycosides could be easily discriminated by signature fragmentation patterns and some novel adduct ions. The heat map of contents demonstrated more p-hydroxybenzyl metabolites than gastroxyl ones were determined in fresh Wutianma revealing a significant specificity with the lack of the sufficient gastrodin and gastroxyl products in biosynthetic pathway.

A New Strategy for Quality Evaluation and Identification of Representative Chemical Components in Polygonum multiflorum Thunb

Polygonum multiflorum Thunb. (HSW) is widely used as herb medicine and health food additive. Recently, a series of HSW-induced hepatotoxicities have been reported and many studies have been carried out to investigate it. But contradictory conclusions were drawn that might be caused by the inconsistent quality of market decoction pieces. Therefore, the HSW decoction pieces quality was evaluated with a developed novel method in the paper. 25 batches of raw HSW (RHSW) and 21 batches of processed HSW (PHSW) samples were purchased from different provinces of China. HPLC determination was performed to identify and detect the contents of 16 chemical compounds in herbal material. Fingerprint similarity was analyzed using chromatography information and the results showed that most herbs were in good similarity. Then, a comprehensive evaluation strategy based on principal component analysis with representative quality control indicators was developed to evaluate the quality of HSW samples. And the rationality of the developed method was verified by HCA analysis. The results showed that the herb from Dabashan, Sichuan Province, no matter RHSW or PHSW had the best quality. Different representative components were selected for RHSW or PHSW decoction pieces which might be caused by the chemical reaction during processing. And most PHSW were unqualified according to the requirement of Chinese Pharmacopeia which might take the responsibility for the toxicity of HSW.