HIT 2.0: an enhanced platform for Herbal Ingredients' Targets.

Literature-described targets of herbal ingredients have been explored to facilitate the mechanistic study of herbs, as well as the new drug discovery. Though several databases provided similar information, the majority of them are limited to literatures before 2010 and need to be updated urgently. HIT 2.0 was here constructed as the latest curated dataset focusing on Herbal Ingredients' Targets covering PubMed literatures 2000-2020. Currently, HIT 2.0 hosts 10 031 compound-target activity pairs with quality indicators between 2208 targets and 1237 ingredients from more than 1250 reputable herbs. The molecular targets cover those genes/proteins being directly/indirectly activated/inhibited, protein binders, and enzymes substrates or products. Also included are those genes regulated under the treatment of individual ingredient. Crosslinks were made to databases of TTD, DrugBank, KEGG, PDB, UniProt, Pfam, NCBI, TCM-ID and others. More importantly, HIT enables automatic Target-mining and My-target curation from daily released PubMed literatures. Thus, users can retrieve and download the latest abstracts containing potential targets for interested compounds, even for those not yet covered in HIT. Further, users can log into 'My-target' system, to curate personal target-profiling on line based on retrieved abstracts. HIT can be accessible at http://hit2.badd-cao.net.

An integrated chemical characterization based on FT-NIR, GC-MS and LC-MS for the comparative metabolite profiling of wild and cultivated agarwood.

Agarwood is a well-known and precious traditional Chinese medicine, has been widely applied as drugs and spices for century. The large demand for this material has deeply stimulated the emergence of numerous cultivated products. However, it is difficult to distinguish wild agarwood from cultivated agarwood, and the chemical composition difference between them is not clear. In this study, an integrated method of Fourier transform near-infrared (FT-NIR), gas chromatography-mass spectrometry (GC-MS) and ultraperformance liquid chromatography Quadrupole-Exactive Orbitrap tandem mass spectrometry (UHPLC-Q-Exactive Orbitrap/MS) was developed to explore chemical variation between wild and cultivated agarwood in combination with multivariate statistical analysis. Twenty-four wild and cultivated agarwood samples were collected from different regions. FT-NIR profiles were used to obtain the holistic metabolic characterization in combination with principal component analysis (PCA). A total of seventy-six and seventy-nine metabolites, including volatile components and 2-(2-phenethyl) chromones derivatives, were successfully identified by GC-MS and UHPLC-Q-Exactive Orbitrap/MS, respectively. Thereafter, the orthogonal-partial least square method-discriminant analysis (OPLS-DA) and variable importance in the projection (VIP) were used to screen potential characteristic chemical components (VIP > 1) in wild and cultivated agarwood, respectively. Finally, eight key chemical markers were putatively identified by two techniques to distinguish agarwood from different origins, which can be found that sesquiterpenes, aromatics, terpenoids, 2-(2-phenylethyl) chromones of the flidersia type (FTPECs) and tetrahydro-2-(2-phenylethyl) chromones (THPECs) are the most important metabolites. Summary, this research presented a comprehensive metabolomic variation between wild and cultivated agarwood on the basis of a multi-technology platform, which laid a foundation for distinguishing the two ecotypes of agarwood and was conducive to the quality control of this resource.

Antioxidative role of Traditional Chinese Medicine in Parkinson's disease.

ETHNOPHARMACOLOGICAL RELEVANCE: Neuroprotective Traditional Chinese Medicine (TCM) has been practiced in alternative medicine from early days. TCM-derived neuroprotective compounds, such as Chrysin, Cannabidiol, Toonasinoids, and ß-asaron, exert significant effectiveness's towards Parkinson's disease (PD). Further, these neuroprotective TCM showed antioxidative, anti-inflammatory, anti-tumor, anti-septic, analgesic properties. Recent research showed that the reduction in the reactive oxygen species (ROS) decreased the α-synuclein (α-syn) toxicity and enhanced the dopaminergic neuron regenerations, the main hallmarks of PD. Therefore, the neuroprotective effects of novel TCM due to its antiradical activities needed deep investigations. AIMS OF THE STUDY: This review aims to enlighten the neuroprotective TCM and its components with their antioxidative properties to the scientific community for future research. METHOD: The relevant information on the neuroprotective TCM was gathered from scientific databases (PubMed, Web of Science, Google Scholar, ScienceDirect, SciFinder, Wiley Online Library, ACS Publications, and CNKI). Information was also gained from MS and Ph.D. thesis, books, and online databases. The literature cited in this review dates from 2001 to June 2, 0201. RESULTS: Novel therapies for PD are accessible, mostly rely on Rivastigmine and Donepezil, offers to slow down the progression of disease at an early stage but embraces lots of disadvantages. Researchers are trying to find a potential drug against PD, which is proficient at preventing or curing the disease progress, but still needed to be further identified. Oxidative insult and mitochondrial dysfunction are thought to be the main culprit of neurodegenerations. Reactive oxygen species (ROS) are the only causative agent in all interactions, leading to PD, from mitochondrial dysfunctions, α-syn aggregative toxicity, and DA neurons degenerations. It is evident from the redox balance, which seems an imperative therapeutic approach against PD and was necessary for the significant neuronal activities. CONCLUSION: Our study is explaining the newly discovered TCM and their neuroprotective and antioxidative properties. But also bring up the possible treatment approaches against PD for future researchers.

The antihypertensive potential of flavonoids from Chinese Herbal Medicine: A review.

With the coming of the era of the aging population, hypertension has become a global health burden to be dealt with. Although there are multiple drugs and procedures to control the symptoms of hypertension, the management of it is still a long-term process, and the side effects of conventional drugs pose a burden on patients. Flavonoids, common compounds found in fruits and vegetables as secondary metabolites, are active components in Chinese Herbal Medicine. The flavonoids are proved to have cardiovascular benefits based on a plethora of animal experiments over the last decade. Thus, the flavonoids or flavonoid-rich plant extracts endowed with anti-hypertension activities and probable mechanisms were reviewed. It has been found that flavonoids may affect blood pressure in various ways. Moreover, despite the substantial evidence of the potential for flavonoids in the control of hypertension, it is not sufficient to support the clinical application of flavonoids as an adjuvant or core drug. So the synergistic effects of flavonoids with other drugs, pharmacokinetic studies, clinical trials and the safety of flavonoids are also incorporated in the discussion. It is believed that more breakthrough studies are needed. Overall, this review may shed some new light on the explicit recognition of the mechanisms of anti-hypertension actions of flavonoids, pointing out the limitations of relevant research at the current stage and the aspects that should be strengthened in future researches.

A Network Pharmacology Study to Uncover the Multiple Molecular Mechanism of the Chinese Patent Medicine Toujiequwen Granules in the Treatment of Corona Virus Disease 2019 (COVID-19).

Since the outbreak of the novel corona virus disease 2019 (COVID-19) at the end of 2019, specific antiviral drugs have been lacking. A Chinese patent medicine Toujiequwen granules has been promoted in the treatment of COVID-19. The present study was designed to reveal the molecular mechanism of Toujiequwen granules against COVID-19. A network pharmacological method was applied to screen the main active ingredients of Toujiequwen granules. Network analysis of 149 active ingredients and 330 drug targets showed the most active ingredient interacting with many drug targets is quercetin. Drug targets most affected by the active ingredients were PTGS2, PTGS1, and DPP4. Drug target disease enrichment analysis showed drug targets were significantly enriched in cardiovascular diseases and digestive tract diseases. An "active ingredient-target-disease" network showed that 57 active ingredients from Toujiequwen granules interacted with 15 key targets of COVID-19. There were 53 ingredients that could act on DPP4, suggesting that DPP4 may become a potential new key target for the treatment of COVID-19. GO analysis results showed that key targets were mainly enriched in the cellular response to lipopolysaccharide, cytokine activity and other functions. KEGG analysis showed they were mainly concentrated in viral protein interaction with cytokine and cytokine receptors and endocrine resistance pathway. The evidence suggests that Toujiequwen granules might play an effective role by improving the symptoms of underlying diseases in patients with COVID-19 and multi-target interventions against multiple signaling pathways related to the pathogenesis of COVID-19.

Add-On Chinese Medicine for Coronavirus Disease 2019 (ACCORD): A Retrospective Cohort Study of Hospital Registries.

Chinese medicine (CM) was extensively used to treat COVID-19 in China. We aimed to evaluate the real-world effectiveness of add-on semi-individualized CM during the outbreak. A retrospective cohort of 1788 adult confirmed COVID-19 patients were recruited from 2235 consecutive linked records retrieved from five hospitals in Wuhan during 15 January to 13 March 2020. The mortality of add-on semi-individualized CM users and non-users was compared by inverse probability weighted hazard ratio (HR) and by propensity score matching. Change of biomarkers was compared between groups, and the frequency of CMs used was analyzed. Subgroup analysis was performed to stratify disease severity and dose of CM exposure. The crude mortality was 3.8% in the semi-individualized CM user group and 17.0% among the non-users. Add-on CM was associated with a mortality reduction of 58% (HR = 0.42, 95% CI: 0.23 to 0.77, [Formula: see text] = 0.005) among all COVID-19 cases and 66% (HR = 0.34, 95% CI: 0.15 to 0.76, [Formula: see text] = 0.009) among severe/critical COVID-19 cases demonstrating dose-dependent response, after inversely weighted with propensity score. The result was robust in various stratified, weighted, matched, adjusted and sensitivity analyses. Severe/critical patients that received add-on CM had a trend of stabilized D-dimer level after 3-7 days of admission when compared to baseline. Immunomodulating and anti-asthmatic CMs were most used. Add-on semi-individualized CM was associated with significantly reduced mortality, especially among severe/critical cases. Chinese medicine could be considered as an add-on regimen for trial use.

Herbal plants coordinate COVID-19 in multiple dimensions - An insight analysis for clinically applied remedies.

The use of multipronged measures, including traditional Chinese medicine (TCM), has greatly increased in response to the COVID-19 pandemic, and we found the use of TCM and is positively correlated with the regional cure rate in China (R=0.77, P<10-5). We analyzed 185 commonly administered TCM recipes comprised of 210 herbs nationwide to reveal mechanistic insight. Eight out of the 10 most commonly used herbs showed anti-coronavirus potential by intersecting with COVID-19 targets. Intriguingly, 17 compounds from the 5 most commonly used herbs were revealed to have direct anti-SARS-CoV-2 potential by docking with the two core structures [CoV spike (S) glycoprotein (6SVB) and CoV 3CL hydrolase (6LU7)]. Seven reported COVID-19 drugs served as positive controls; among them, retionavir (-7.828 kcal/mol) and remdesivir (-8.738 kcal/mol) performed best with 6VSB and 6LU7, respectively. The top candidate was madreselvin B (6SVB: -8.588 kcal/mol and 6LU7: -9.017 kcal/mol), an appreciable component of Flos Lonicerae. Eighty-six compounds from 22 unlisted herbs were further identified among 2,042 natural compounds, completing our arsenal for TCM formulations. The mechanisms have been implicated as multifactorial, including activation of immunoregulation (Th2, PPAR and IL10), suppression of acute inflammatory responses (IL-6, IL-1α/ß, TNF, COX2/1, etc.), enhancement of antioxidative activity (CAT and SOD1), and modulation of apoptosis (inhibited CASP3). It is of interest to understand the biological mechanisms of TCM recipes. We then analyzed 18 representative remedies based on molecular targets associated with 14 medical conditions over the disease course, e.g., pyrexia, coughing, asthenia, lymphopenia, cytokine storm, etc. The significant level of coherence (SLC) revealed, in part, the potential uses and properties of corresponding TCMs. Thus, herbal plants coordinate to combat COVID-19 in multiple dimensions, casting a light of hope before effective vaccines are developed.

Quality grade classification of China commercial moxa floss using electronic nose: A supervised learning approach.

Moxa floss is the primary material used in moxibustion, an important traditional Chinese medicine therapy that uses ignited moxa floss to apply heat to the body for disease treatment. Till date, there is no available data regarding quality control of different grades of moxa floss. The objectives of this study were to explore the probative value of the electronic nose (e-nose) in differentiating different quality grades of commercial moxa floss sold in China, and to investigate if data mining techniques could be used to optimize the sensor array while retaining classification accuracy of the samples. The e-nose with 12 metal oxide semiconductor type sensors was used to analyze the odor profiles of 15 commercial moxa floss samples of different quality grades. Feature selection algorithms using principal component analysis (PCA) and BestFirst (BC) coupled with correlation-based feature subset selection (CfsSubsetEval) method were used to obtain the most efficient feature subsets. Results for the BC feature selection method identified 3 optimized sensors (S2, S6, and S11), suggesting that aromatic compounds relate more to the identification of the samples. Radial basis function (RBF), multilayer perceptron (MLP), and random forests (RF) performed well in discriminating the samples, retaining prediction accuracies above 85%, which achieved cost-effectiveness and operational simplicity, while retaining prediction accuracy. The e-nose could be a rapid and nondestructive method for objective preliminary classification of quality grades of moxa floss and may be used for future studies related to moxa products safety and quality.

A Semantic Analysis and Community Detection-Based Artificial Intelligence Model for Core Herb Discovery from the Literature: Taking Chronic Glomerulonephritis Treatment as a Case Study.

The Traditional Chinese Medicine (TCM) formula is the main treatment method of TCM. A formula often contains multiple herbs where core herbs play a critical therapeutic effect for treating diseases. It is of great significance to find out the core herbs in formulae for providing evidences and references for the clinical application of Chinese herbs and formulae. In this paper, we propose a core herb discovery model CHDSC based on semantic analysis and community detection to discover the core herbs for treating a certain disease from large-scale literature, which includes three stages: corpus construction, herb network establishment, and core herb discovery. In CHDSC, two artificial intelligence modules are used, where the Chinese word embedding algorithm ESSP2VEC is designed to analyse the semantics of herbs in Chinese literature based on the stroke, structure, and pinyin features of Chinese characters, and the label propagation-based algorithm LILPA is adopted to detect herb communities and core herbs in the herbal semantic network constructed from large-scale literature. To validate the proposed model, we choose chronic glomerulonephritis (CGN) as an example, search 1126 articles about how to treat CGN in TCM from the China National Knowledge Infrastructure (CNKI), and apply CHDSC to analyse the collected literature. Experimental results reveal that CHDSC discovers three major herb communities and eighteen core herbs for treating different CGN syndromes with high accuracy. The community size, degree, and closeness centrality distributions of the herb network are analysed to mine the laws of core herbs. As a result, we can observe that core herbs mainly exist in the communities with more than 25 herbs. The degree and closeness centrality of core herb nodes concentrate on the range of [15, 40] and [0.25, 0.45], respectively. Thus, semantic analysis and community detection are helpful for mining effective core herbs for treating a certain disease from large-scale literature.

Exploration of the mechanism of traditional Chinese medicine by AI approach using unsupervised machine learning for cellular functional similarity of compounds in heterogeneous networks, XiaoErFuPi granules as an example.

'Polypharmacology' is usually used to describe the network-wide effect of a single compound, but traditional Chinese medicine (TCM) has a polypharmacological effect naturally based on the 'multi-components, multi-targets and multi-pathways' principle. It is a challenge to investigate the polypharmacology mechanism of TCM with multiple components. In this study, we used XiaoErFuPi (XEFP) granules as an example to describe an unsupervised learning strategy for polypharmacology research of TCM and to explore the mechanism of XEFP polypharmacology against multifactorial disease function dyspepsia (FD). Unsupervised clustering of compounds based on similarity evaluation of cellular function fingerprints showed that compounds of TCM without similar targets and chemical structure could also exert similar therapeutic effects on the same disease, as different targets participate in the same pathway closely associated with the pathological process. In this study, we proposed an unsupervised machine learning strategy for exploring the polypharmacology-based mechanism of TCM, utilizing hierarchical clustering based on cellular functional similarity, to establish a connection from the chemical clustering module to cellular function. Meanwhile, FDA-approved drugs against FD were used as references for the mechanism of action (MoA) of FD. First, according to the compound-compound network built by the similarity of cellular function of XEFP compounds and FDA-approved FD drugs, the possible therapeutic function of TCM may represent a known mechanism of FDA-approved drugs. Then, as unsupervised learning, hierarchical clustering of TCM compounds based on cellular function fingerprint similarity could help to classify the compounds into several modules with similar therapeutic functions to investigate the polypharmacology effect of TCM. Furthermore, the integration of quantitative omics data of TCM and approved drugs (from LINCS datasets) provides more quantitative evidence for TCM therapeutic function consistency with approved drugs. A spasmolytic activity experiment was launched to confirm vanillic acid activity to repress smooth muscle contraction; vanillic acid was also predicted to be active compound of XEFP, supporting the accuracy of our strategy. In summary, the approach proposed in this study provides a new unsupervised learning strategy for polypharmacological research investigating TCM by establishing a connection between the compound functional module and drug-activated cellular processes shared with FDA-approved drugs, which may elucidate the unique mechanism of traditional medicine using FDA-approved drugs as references, facilitate the discovery of potential active compounds of TCM and provide new insights into complex diseases.

The role played by traditional Chinese medicine in preventing and treating COVID-19 in China.

Traditional Chinese medicine (TCM), an ancient system of alternative medicine, played an active role in the prevention and control of COVID-19 in China. It improved the clinical symptoms of patients, reduced the mortality rate, improved the recovery rate, and effectively relieved the operating pressure on the national medical system during critical conditions. In light of the current global pandemic, TCM-related measures might open up a new channel in the control of COVID-19 in other countries and regions. Here, we summarize the TCM-related measures that were widely used in China, including TCM guidelines, the Wuchang pattern, mobile cabin hospitals, integrated treatment of TCM and modern medicine for critical patients, and non-medicine therapy for convalescent patients, and describe how TCM effectively treated patients afflicted with the COVID-19. Effective TCM therapies could, therefore, be recommended and practiced based on the existing medical evidence from increased scientific studies.

Simultaneous determination of 20 bioactive components in Chuanxiong Rhizoma from different production origins in Sichuan province by ultra-high-performance liquid chromatography coupled with triple quadrupole mass spectrometry combined with multivariate statistical analysis.

Chuanxiong Rhizoma is a commonly used in traditional Chinese medicine. Chuanxiong Rhizoma is widely distributed in Sichuan province, China, including the cities of Dujiangyan, Pengzhou, Meishan, Qionglai, and Shifang. However, reports on the comparisons of quality of Chuanxiong Rhizoma of different production origins are limited. Therefore, an ultra-HPLC with triple quadrupole MS method was developed for the determination of 20 bioactive components (12 aromatic acids and eight phthalides) in 36 samples from different production origins and further assessed its quality. The contents of these 20 constituents of samples were analyzed by hierarchical cluster analysis and orthogonal partial least squares discrimination analysis; the result indicated that Chuanxiong Rhizoma of different production origins had some differences. Thirteen constituents of quality difference markers were acquired by variable importance for the project. Furthermore, the sum of the contents of these quality difference markers was different from various production origins of Chuanxiong Rhizoma. Meanwhile, Z-ligustilide and senkyunolide A as main constituents of quality difference markers, the rate of various production origins of Chuanxiong Rhizoma was different. This study provides a foundation for the quality assessment of Chuanxiong Rhizoma.

Identification of Tibetan medicine Dida based on DNA barcoding.

The purpose of this study was to test the ability of DNA barcoding to identify the herbal raw trade of Tibetan medicine Dida in China. A reference database for plant-material DNA barcodes was successfully constructed and used to identify 36 commercially samples of Dida collected from Southwest China. The ITS sequence was amplified from these samples and the efficiency of the PCR amplification of ITS was 100%. The DNA sequencing results revealed that 3 samples (8.3%) were authenticated as Swertia chirayita, 2 sequences (5.6%) were authenticated as Swertia mussotii, 3 sequences (8.3%) were authenticated as Swertia ciliata, as recorded in the Tibetan Pharmacopeia. The other samples were authenticated as adulterants and all of them originated from common plants belonging to Saxifraga, Swertia and Halenia. This result indicates Dida pieces that are available in the market have complex origins and may indicate a potential safety issue and DNA barcoding is a convenient tool for market supervision.

A Rapid and Nondestructive Approach for the Classification of Different-Age Citri Reticulatae Pericarpium Using Portable Near Infrared Spectroscopy.

Citri Reticulatae Pericarpium (CRP), has been used in China for hundreds of years as a functional food and medicine. However, some short-age CRPs are disguised as long-age CRPs by unscrupulous businessmen in order to obtain higher profits. In this paper, a rapid and nondestructive method for the classification of different-age CRPs was established using portable near infrared spectroscopy (NIRS) in diffuse reflectance mode combination with appropriate chemometric methods. The spectra of outer skin and inner capsule of CRPs at different storage ages were obtained directly without destroying the samples. Principal component analysis (PCA) with single and combined spectral pretreatment methods was used for the classification of different-age CRPs. Furthermore, the data were pretreated with the PCA method, and Fisher linear discriminant analysis (FLD) with optimized pretreatment methods was discussed for improving the accuracy of classification. Data pretreatment methods can be used to eliminate the noise and background interference. The classification accuracy of inner capsule is better than that of outer skin data. Furthermore, the best results with 100% prediction accuracy can be obtained with FLD method, even without pretreatment.

Rapid and intelligent discrimination of Notopterygium incisum and Notopterygium franchetii by infrared spectroscopic fingerprints and electronic olfactory fingerprints.

This preliminary research evaluated mid-infrared (MIR) spectroscopy, near-infrared (NIR) spectroscopy and electronic nose (E-nose) for the rapid identification of Notopterygium incisum and Notopterygium franchetii, which were both approved sources of Notopterygii Rhizoma et Radix (Chinese Pharmacopoeia, 2015) but possessed different chemical compositions and pharmacological activities. At the level of single variables, MIR showed quite a few discriminating peaks in the regions of 3000-2800 cm-1 (the stretching bands of CH), 1770-1670 cm-1 (the stretching bands of CO), and 1400-1200 cm-1 (the bending bands of CH and the stretching bands of CO). Meanwhile, NIR only showed an intuitive discriminating peak near 4736 cm-1 (the combination band of OH and CO stretching modes). E-nose response signals of N. incisum and N. franchetii were significant different (p < 0.05) on four sensors, i.e., LY2/LG, LY2/GH, LY2/gCT and LY2/gCTI. Using the infrared spectra or E-nose sensor responses as fingerprints, support vector machine (SVM) models can provide good recognition accuracy (100% for MIR and NIR models, 92.9% for E-nose model). This research indicated the feasibility of MIR, NIR and E-nose for the accurate, rapid, cheap and green identification of N. incisum and N. franchetii, which was desirable to assure the authenticity, efficacy and safety of related herb materials and products.

A chemometric modeling-free near infrared barcode strategy for smart authentication and geographical origin discrimination of Chinese ginseng.

With the growing interest in alternative medicine, handy identification and differentiation of herbal medicines are becoming increasingly important. Here we report a chemometric modeling-free near infrared (NIR) barcode strategy for the smart identification and geographical origin discrimination of Chinese ginseng. The novel strategy demands the transformation of Chinese ginseng (standard and sample) NIR spectra into a barcode representation through assigning zero intensity to every NIR peak except the peaks having intensities greater than average peak intensity. Meanwhile, for Chinese ginseng standard NIR barcode, barcoding condition such as padding size was carefully optimized. It has been demonstrated that the padding size for each bar in the barcode is 8 cm-1. By comparing the percentage of nonzero overlap between Chinese ginseng standard barcode and sample barcodes, eight batches of samples (including Chinese ginseng, American ginseng and counterfeit) were successfully identified with 100% accuracy, respectively. Interestingly, the discrimination of the origin of ginsengs from three provinces (Jilin, Liaoning and Heilongjiang) of Northeastern China was achieved utilizing NIR barcode method. Two characteristic bars at 7750 and 8250 cm-1 were inspected in the ginseng sample from Jilin province, two specific bars at 6780 and 7015 cm-1 were displayed in the ginseng sample from Liaoning province and three distinct bars at 6560, 6910 and 7995 cm-1 were monitored in the ginseng sample from Heilongjiang province. The results indicate that the proposed method will be greatly expanded and applied as an inspecting platform for the on-site analysis and valid identification of Chinese ginseng in herbal markets by a handheld spectrometer or barcode scanner.

Screen for Potential Candidate Alternatives of Sargentodoxa cuneata from Its Six Adulterants Based on Their Phenolic Compositions and Antioxidant Activities.

Daxueteng, the liana stem of Sargentodoxa cuneata, is a widely used Traditional Chinese Medicine facing the overflow of its commercial adulterants. A method for discriminating adulterants and screening potential candidate alternatives of S. cuneata was thus established. Total phenols and flavonoids of S. cuneata and its six adulterants and their abilities to scavenge DPPH• and ABTS•+, to absorb peroxyl radicals (ORAC), and to inhibit AAPH-induced supercoiled plasmid DNA strand scission were comprehensively assessed. Polygonum cuspidatum and Bauhinia championii, two of the six adulterants of S. cuneate, shared considerably higher antioxidant activities as well as phenolic contents and, therefore, were considered as potential candidate alternatives. Phenolic compositions of the two potential candidate alternatives and S. cuneata itself were further determined by UPLC-QTOF-MS/MS. Totally 38 phenolics, including four hydroxybenzoic acids, two tyrosols, two caffeoylquinic acids, seven flavanol or its oligomers, two lignans, three hydroxycinnamic acids, six stilbenes, seven anthraquinones, and five flavanones were determined from three species. Furthermore, contents of different phenolic categories were semi-quantified and the major antioxidant contributors of S. cuneata and the two potential candidate alternatives were subsequently determined. It is concluded that tyrosols and caffeoylquinic acids were unique categories making great antioxidant contributions in S. cuneata and thus were considered as effective biomarkers in distinguishing its potential candidate alternatives.

[Application of numerical taxonomy in study of Dao-di herbs and their producing areas].

As a treasure of traditional Chinese medicine culture,Dao-di herbs are famous for their high quality and good effect.However,traditional characteristics of Dao-di herbs and their producing areas are mostly confined to qualitative description,lacking objective evaluation indicators. Numerical taxonomy,which uses mathematical methods to improve the research of taxonomy from qualitative description to quantitative comprehensive analysis,is objective and accurate,so is widely used in the field of biology and medicine.This paper reviews the concept and main research fields of numerical taxonomy,and summarizes its application status and development prospects in the study of Dao-di herbs and characteristics of production areas,in order to lay the foundation for the objectification and standardization of Dao-di herbs.

[Research and development thought on biopharmaceutics classification system of Chinese materia medica].

The biopharmaceutics classification system( BCS) is a scientific framework or method for classifying drugs based on drug solubility and permeability,which can be used to provide drug bioavailability-absorption correlation analysis. Based on the characteristics of multi-component and multi-target of traditional Chinese medicine( TCM) as well as the concept,method and technology of BCS,the research group proposed biopharmaceutics classification system of Chinese materia medica( CMMBCS) and carried out research and data accumulation of classical prescriptions. Based on the previous research results,further development ideas under the CMMBCS concept and framework were further proposed in this study. In the course of research,the influence of the intermediate links of the complex interactions of the multi-component environment was omitted,and the component absorption studies on the main clinical effects of prescription ingredients were directly concerned,or the components and data were reversely extracted from the aspects of metabolism,pharmacodynamic pathways and absorption principles. Studies were conducted from two aspects( single component and compound prescription) to comprehensively evaluate the absorption properties of TCM compound. In the research path,the different ways in which Chinese medicine could exert its efficacy were fully considered,and CMMBCS classification and establishment rules were clarified mainly by focusing on the absorption pathway into the blood. Specifically,the network pharmacology and molecular docking technology were used to screen the compound index components of TCM; the absorption rules were studied by the physiologically based pharmacokinetic models and the absorption parameters of CMMBCS were calculated by reverse reasoning. Then the CMMBCS classification of TCM prescription was corrected by studying the efficacy or absorption pathway. In this paper,the theoretical framework and research methodology of CMMBCS were systematically improved based on the establishment of CMMBCS basic theory,the supplementary of drug-oriented research ideas and the application of modern mature Chinese medicine methodology.