Quality study of animal-derived traditional Chinese medicinal materials based on spectral technology: Calculus bovis as a case.

INTRODUCTION: Calculus bovis (C. bovis) is a typical traditional Chinese medicine (TCM) derived from animals, which has a remarkable curative effect and high price. OBJECTIVES: Rapid identification of C. bovis from different types was realized based on spectral technology, and a rapid quantitative analysis method for the main quality control indicator bilirubin was established. METHODS: We conducted a supervised and unsupervised pattern recognition study on 44 batches of different types of C. bovis by five spectral pretreatment methods. Three variable selection methods were used to extract the essential information, and the partial least squares regression (PLSR) quantitative model of bilirubin by near-infrared (NIR) spectroscopy was constructed. RESULTS: The partial least squares discriminant analysis (PLS-DA) model could achieve 100% accuracy in identifying different types of C. bovis. The R2 of the NIR quantitative model was 0.979, which is close to 1, and the root mean square error of calibration (RMSEC) was 2.3515, indicating the good prediction ability of the model. CONCLUSION: The study was carried out to further improve the basic data of quality control of C. bovis and help the high-quality development of TCM derived from animals.

Identification and determination of different processed products and their extracts of Crataegi Fructus by infrared spectroscopy combined with two-dimensional correlation analysis.

The fruit of Crataegus sp. is known as "Shanzha (SZ)" in China and is widely used in the food, beverage, and traditional Chinese medicine (TCM) industries. SZ usually requires thermal processing to reduce the irritation of its acidity to the gastric mucosa. Different processed products of SZ resulting from thermal processing have different or even opposite functions in clinical applications. In addition, 5-hydroxymethylfurfural (5-HMF) intermediates produced during thermal processing are carcinogenic to humans. Therefore, the aim of this study was to explore a rapid and accurate method by Fourier transform infrared spectroscopy (FT-IR) for the identification of different processed products and the determination of 5-HMF in extracts. In qualitative identification, a three-stage infrared spectroscopy identification method (raw spectra, the second derivative spectra, and two-dimensional correlation (2DCOS) spectra) was developed to distinguish different processed products of SZ step by step. In quantitative determination, partial least squares regression combined with different variable selection methods, especially the 2DCOS method, was applied to determine the 5-HMF content. The results show that temperature-induced 2DCOS synchronous spectra can effectively identify different processed products of SZ by shape, intensity, and position of auto-peaks or cross-peaks, and the variables selected by power spectra from concentration-induced 2DCOS synchronous spectra have better prediction ability for 5-HMF compared to full variables. The above results demonstrate that 2D-COS analysis is a potential tool in qualitative and quantitative analysis, which can improve sample identification accuracy and determination capabilities. This study not only establishes a rapid and accurate method for the identification of different processed products but also provides a practical reference for food safety and the efficient use of TCM.

Nondestructive discrimination of Potentilla anserina L. from different production areas based on near-infrared spectroscopy.

INTRODUCTION: The traditional Chinese medicine (TCM) Potentilla anserina L. can use both as food and medicine. At present, the market mainly depends on experience to identify the species and determine the production areas of P. anserina. To ensure the quality of P. anserina, it is essential to improve the level of quality control. OBJECTIVE: We aimed to establish a rapid and nondestructive discrimination model to identify P. anserina from different production areas by near-infrared spectroscopy. METHODS: The spectra of complete P. anserina medicinal materials and their powder of the same variety from four production areas were collected, and principal component analysis discriminant analysis and partial least squares discriminant analysis (PLS-DA) were conducted based on different pretreatment methods and band selection methods. Then, the spectra of complete medicinal materials were converted into the spectra of medicinal powder for nondestructive identification. RESULTS: The correct recognition rate (CRR) of the PLS-DA discriminant model was the best after spectral preprocessing using autoscaling and competitive adaptive reweighted sampling for band selection. The CRRs of the calibration set and validation set were 100%, the CRRs of the external test set were 95%, 90%, 82%, and 88%, respectively, and the CRRs of the transfer external test set were 84%, 80%, 82%, and 86%, respectively. CONCLUSION: We realized the nondestructive and effective identification of P. anserina from different origins and laid a foundation for the industrialization and upgrading of TCM.

Study on quality analysis of different species of Coptidis rhizome based on fingerprint-effect relationship.

INTRODUCTION: The quality evaluation of Coptidis rhizome (CR) is attributed to the origin and processing method, and this strategy of ignoring the bioactive components usually leads to biased quality analysis, which is difficult to indicate the clinical efficacy. OBJECTIVES: In order to evaluate the quality level of different species of CR, we collected 20 batches of CR and investigated the fingerprint-effect relationship. METHODS: High-performance liquid chromatography (HPLC) fingerprints of CR were established, and the fingerprint-effect relationship was explored using cluster analysis, principal component analysis, Pearson correlation analysis, grey relation analysis, and partial least squares regression. RESULTS: We have identified a total of 10 common peaks (1-10) with similarity scores above 0.96. The study on the relationship between spectra and potency further showed that the contents of peaks 8, 9, and 10 are potential key components. And based on a previous study, a method of one measurement and multiple evaluations of CR was established to achieve the goal of simplifying the analytical process and reducing costs. CONCLUSION: Through a combination of fingerprint analysis, antioxidant activity evaluation, fingerprint-efficacy relationship analysis, and simultaneous quantification of multiple components, a CR quality control index and method have been selected and established, which can also provide a more comprehensive quality evaluation for traditional Chinese medicine.

Application of Rapid Identification and Determination of Moisture Content of Coptidis Rhizoma From Different Species Based on Data Fusion.

BACKGROUND: For thousands of years, traditional Chinese medicine (TCM) has been clinically proven, and doctors have highly valued the differences in utility between different species. OBJECTIVE: This study aims to replace the complex methods traditionally used for empirical identification by compensating for the information loss of a single sensor through data fusion. The research object of the study is Coptidis rhizoma (CR). METHOD: Using spectral optimization and data fusion technology, near infrared (NIR) and mid-infrared (MIR) spectra were collected for CR. PLS-DA (n = 134) and PLSR (n = 63) models were established to identify the medicinal materials and to determine the moisture content in the medicinal materials. RESULTS: For the identification of the three species of CR, the mid-level fusion model performed better than the single-spectrum model. The sensitivity and specificity of the prediction set coefficients for NIR, MIR, and data fusion qualitative models were all higher than 0.95, with an AUC value of 1. The NIR data model was superior to the MIR data model. The results of low-level fusion were similar to those of the NIR optimization model. The RPD of the test set of NIR and low-level fusion model was 3.6420 and 3.4216, respectively, indicating good prediction ability of the model. CONCLUSIONS: Data fusion technology using NIR and MIR can be applied to identify CR species and to determine the moisture content of CR. It provides technical support for the rapid determination of moisture content, with a fast analysis speed and without the need for complex pretreatment methods. HIGHLIGHTS: This study is the first to introduce spectral data fusion technology to identify CR species. Data fusion technology is feasible for multivariable calibration model performance and reduces the cost of manual identification. The moisture content of CR can be quickly evaluated, reducing the difficulty of traditional methods.

A rapid extraction process monitoring of Swertia mussotii Franch. With near infrared spectroscopy.

Swertia mussotii Franch. (SMF), a traditional Tibetan medicine, which has miraculous effect on treating hepatitis diseases. However, there is no research on its entire production process, and invisible production process has seriously hindered the SMF modern development. In this study, principal component analysis (PCA), subtractive spectroscopy, and two-dimensional correlation spectroscopy (2D-COS) were used to explain changes of characteristic groups in the extraction process. Four main characteristic peaks at 1884 nm, 1944 nm, 2246 nm and 2308 nm were identified to describe the changes of molecular structure information of total active components in SMF extraction process. In addition, multi critical quality attributes (CQAs) models were established by near-infrared spectroscopy (NIRS) combined with the total quantum statistical moment (TQSM). The coefficients of determination (R2eval and R2ival) were both greater than 0.99. The ratios of the standard deviation of validation to the standard error of the prediction (RPDe and RPDi) were greater than five. The quantitative model of AUCT could save time on primary data measurement by not requiring determination of indicator components compared with others. In conclusion, these results demonstrated that it was feasible to understand the SMF extraction process through AUCT and characteristic groups. These could realize the visual digital characterization and quality stability of the SMF extraction process.

Molecular and metabolic mechanisms of bufalin against lung adenocarcinoma: New and comprehensive evidences from network pharmacology, metabolomics and molecular biology experiment.

BACKGROUND: This study aims to evaluate the efficacy and therapeutic mechanism of bufalin on lung adenocarcinoma (LUAD) through a comprehensive strategy integrating network pharmacology, metabolomics and molecular biology verification. METHODS: The putative targets of bufalin were discerned from PharmMapper and Swiss Target Prediction database. LUAD-related targets were obtained by target filtering of GeneCard database and data mining of GEO database. PPI network was constructed to screen the core targets, and their clinical significance was assessed through several public databases. GO and KEGG pathway analyses were performed to identify possible enrichment of genes with specific biological themes. Molecular docking and molecular dynamics (MD) simulation were employed to determine the correlation and binding pattern between bufalin and core targets. The potential mechanisms of bufalin acting on LUAD, as predicted by network pharmacology analyses, were experimentally validated using in-vitro and in-vivo models. Finally, the effects of bufalin intervention on metabolite profile and metabolic pathway in LUAD nude mice were investigated by non-targeted metabolomics. RESULTS: 209 bufalin targets and 1082 LUAD-associated targets were harvested, of which 51 intersection targets were identified. 10 core targets including Akt1, STAT3, EGFR, CASP3 and SRC were picked out through network topology analysis, and they had a potent binding activity with bufalin as indicated by molecular docking and MD simulation. Hub module of PPI network was closely related to cell proliferation and apoptosis. GO and KEGG enrichment analyses suggested that bufalin exerted therapeutic effects on LUAD possibly by inhibiting proliferation and promoting apoptosis via PI3K/Akt, FoxO1 and MAPK/ERK pathways, which were confirmed by a series of in-vitro studies as well as HE, TUNEL and Ki-67 staining of tumor tissues. Further metabolomics analysis revealed that bufalin mainly regulated ABC transporter and remodeled AA metabolism, thereby contributing to the treatment of LUAD. CONCLUSION: From molecular and metabolic perspective, the present study not only provided a unique insight into the possible mechanisms of bufalin against LUAD after successfully filtering out associated key target genes, differential endogenous metabolites, and signaling pathways, but also proposed a novel promising therapeutic strategy for LUAD.

An Integrated Strategy to Identify and Quantify the Quality Markers of Xinkeshu Tablets Based on Spectrum-Effect Relationship, Network Pharmacology, Plasma Pharmacochemistry, and Pharmacodynamics of Zebrafish.

Xinkeshu tablets (XKST), a traditional Chinese patent medicine (CPM), have served in the clinical treatment of cardiovascular diseases (CVDs) for decades. However, its pharmacodyamic material basis was still unclear, and the holistic quality control has not been well established due to the lack of systematic research on the quality markers. In this experiment, the heart rate recovery rate of a zebrafish larva was used to evaluate the traditional pharmacological effect of XKST i.e., antiarrhythmic effect. The HPLC fingerprints of 16 batches of XKST samples were obtained, and antiarrhythmic components of XKST were identified by establishing the spectrum-effect relationship between HPLC fingerprints and heart rate recovery rate of zebrafish larva with orthogonal signal correction and partial least squares regression (OSC-PLSR) analysis. The anticardiovascular disease components of XKST were identified by mapping the targets related to CVDs in network pharmacology. The compounds of XKST absorbed and exposed in vivo were identified by ultra-high performance liquid chromatography Q-Exactive high-resolution mass spectrometry (UHPLC-Q-Exactive HRMS). Based on the earlier studies, combined with five principles for identifying quality markers and verified by a zebrafish arrhythmia model, danshensu, salvianolic acid A, salvianolic acid B, daidzein, and puerarin were identified as quality markers of XKST. In total, 16 batches of XKST samples were further quantified with the method established in this study. Our study laid the foundation for the quality control of XKST. The integrated strategy used in the study of XKST could be applied for the identification and quantification of quality markers of other CPMs as well.

Multi critical quality attributes monitoring of Chinese oral liquid extraction process with a spectral sensor fusion strategy.

The traditional Chinese medicine (TCM) extraction process is a complicated dynamic system with many variables and disturbance. Therefore, multi critical quality attributes (CQAs) monitoring is of great significance to understand the whole process. Spectroscopy is a powerful process analytical tool used for process understanding. However, single senor sometimes could not provide comprehensive information. Sensor fusion is a very practical method to overcome this deficiency. In this study, the extraction process of Xiao'er Xiaoji Zhike Oral Liquid (XXZOL) was carried out in pilot scale, where near infrared (NIR) spectroscopy and mid infrared (MIR) spectroscopy were collected to determine the concentrations of seven CQAs (synephrine, arecoline, chlorogenic acid, forsythoside A, naringin, hesperidin and neohesperidin) during extraction process. Based on fused data blocks, fusion partial least squares (PLS) models were established. Two fusion data blocks are obtained from the concatenation of original spectra (low-level data fusion) and the concatenation of characteristic variables based on band selection (mid-level data fusion) respectively. The results indicated that for all seven analytes, the mid-level data fusion models were superior to the single spectral models, with the prediction performance significantly improved. Specifically, the coefficients of determination (Rp2 and Rt2) of NIR, MIR and fusion quantitative models were all higher than 0.95. The relative standard errors of prediction (RSEP) values were all within 10%, except for models of neohesperidin, which were 10.76%, 12.39%, 12.05%, 10.03% for NIR, MIR, low-level and mid-level models respectively. These results demonstrate that it is feasible to monitor the extraction process of Xiao'er Xiaoji Zhike Oral Liquid more accurately and rapidly by fusing NIR and MIR spectroscopy, and the proposed approach also has vital and valuable reference value for the rapid monitoring of the mixed decoction process of other TCM.

Study on the Pharmacokinetic Profiles of Three Ingredients in Qilong Capsules and Their Potential Interactions in Rats by LC-MS/MS.

Qilong capsule (QLC) is a well-known Traditional Chinese Medicine, and it has a long history for the treatment of ischemic stroke. Its major ingredients are saponins, such as paeoniflorin, amygdalin and calycosin-7-glucoside, contributing to vasodilation function. In this study, a simple, rapid and sensitive high-performance liquid chromatography-tandem mass spectrometry method was developed to determine three bioactive ingredients in rat plasma after oral administration of QLC. A simple acetonitrile precipitation method was introduced during the sample preparation. Chromatographic separation was performed on a Shiseido CAPCELL PAC MGIII-C18 column using a gradient elution with acetonitrile and water (0.1% formic acid) as a mobile phase, and the chromatographic separation was 5 min. The methodological evaluation showed that this method had a high sensitivity (the lower limit of quantification was 1 ng/mL for calycosin-7-glucoside, 5 ng/mL for paeoniflorin, 5 ng/mL for amygdalin), satisfactory accuracy (relative error ≤ ±15%) and precision (relative standard deviation ≤15%). Then, the analytical method was applied to the pharmacokinetic study in rats following oral administration of the extracts in QLC. Meanwhile, the pharmacokinetic parameters of complex system in QLC were analyzed and the potential interaction between ingredients was explored. The present quantification method and pharmacokinetic study will provide a meaningful reference for the formulas research of QLC in the treatment of ischemic stroke.

Chromatographic Fingerprinting Based on Column Switching Technology for Quality Evaluation of Tianmeng Oral Liquid.

Separation power was limited when the conventional high-performance liquid chromatography (HPLC) fingerprinting method based on a single column was used to analyze very complex traditional Chinese medicine (TCM) preparations. In this research, a novel HPLC fingerprinting method based on column switching technology by using a single pump was established for evaluating the quality of Tianmeng oral liquid (TMOL). Twelve batches of TMOL samples were used for constructing HPLC fingerprints. Compared with the 16 common peaks in fingerprinting with a single column, 25 common peaks were achieved with two columns connected through a six-way valve. The similarity analysis combined with bootstrap method was applied to determine the similarity threshold, which was 0.992 to distinguish expired samples and unexpired samples. Principal component analysis (PCA) and hierarchical clustering analysis (HCA) were also applied to classify the TMOL samples, and results revealed that expired and unexpired samples are classified into two categories. The HPLC fingerprinting based on column switching technology with better separation power and higher peak capacity could characterize chemical composition information more comprehensively, providing an effective and alternative method to control and evaluate the quality of TMOL, which would offer a valuable reference for other TCM preparations.

Water as a probe to understand the traditional Chinese medicine extraction process with near infrared spectroscopy: A case of Danshen (Salvia miltiorrhiza Bge) extraction process.

Extraction process is not only a critical manufacturing unit but also the initial process of various extracts and preparations. Taking the most extensive Chinese herbal medicine Danshen (Salvia miltziorrhiza Bge) as an example, salvianolic acid B (Sal B) is its main active pharmaceutical ingredient but lacks accurate characterization of the extraction process. As one of process analytical technologies, near-infrared spectroscopy (NIRS) technology has been widely applied for monitoring pharmaceutical extraction process. In most past studies, water spectral information is often eliminated due to its high absorption. However, this study proposed a method of using water spectrum to understand the whole extraction process and to quickly determine the content of Sal B. Principal component analysis (PCA) was first utilized to investigate the whole extraction process, then the reconstructed spectrum based on PCA was established and analyzed by Aquaphotomics, and finally the partial least squares regression (PLSR) quantitative model of Sal B was established. PCA and Aquaphotomics results showed the whole extraction process could be considered as a dynamic change from structure breaker to structure maker, and the dominance of highly H-bonded water structures increases with the extraction time. Also, the Sal B quantitative model with water spectrum showed higher accuracy and stability than other methods, which parameters (RMSEC, RMSECV, RMSEP, R2c, R2cv, R2p, RPD) were 0.2408 mg/mL, 0.2939 mg/mL, 0.2584 mg/mL, 0.9536, 0.9300, 0.9494, 4.6298, respectively, and the paired t-test showed that Sal B content measured by NIR and HPLC methods had no significant differences (p > 0.05). In conclusion, all result indicated that water can be used as a probe to understand the traditional Chinese medicine extraction process with NIRS.

Comprehensive quality evaluation strategy based on non-targeted, targeted and bioactive analyses for traditional Chinese medicine: Tianmeng oral liquid as a case study.

Traditional Chinese medicine (TCM), especially herbal medicine compound preparation, faces great challenges in its quality control due to a myriad of components involved. How to perform quality control of TCM more effectively has been a research topic. In this study, we used Tianmeng oral liquid (TOL) as a case study and developed a comprehensive strategy based on non-targeted, targeted and bioactive analyses for quality evaluation of TOL from different batches. Firstly, a non-targeted fingerprinting analysis was performed by HPLC-DAD and UHPLC-MS/MS. Twenty-five batches of TOL were clearly discriminated by similarity analysis and hierarchical cluster analysis and components were tentatively identified. Secondly, the targeted quantitative methods based on HPLC-DAD and HPLC-MS were applied to simultaneous quantitative determination of five and eight marker compounds, especially toxic component strychnine, respectively. The quantitative data were processed with principal component analysis for differentiating different batches of samples. Finally, we explored the feasibility of establishing a total antioxidant capacity (TAC) model. How to use the peak area instead of the corresponding concentration to determine the antioxidant activity-related compounds was theoretically explained for the first time, which was of great significance for the study of the fingerprint-efficacy relationship. The orthogonal signal correction-partial least squares model was employed to predict the TAC of TOL from their chromatographic fingerprints and identify three potential antioxidant markers. These results demonstrated that the comprehensive strategy from fingerprinting, chemical composition, multiple-component quantification, and antioxidant activity could be applied to quality evaluation of TOL and discrimination of the expired and unexpired samples.

Quality evaluation of traditional Chinese medicines based on fingerprinting.

The usage of traditional Chinese medicines has expanded globally, but the data about authentication, efficacy, and safety is far from sufficient to meet the criteria supporting their use worldwide due to complexity in the composition. Fingerprinting describes integral characterization and reflects interactive aspects of complex components; therefore, it can offer the possibility of evaluating quality of traditional Chinese medicines following the overall principle. Chemometric techniques introduce multivariate analytical methods into fingerprinting to obtain more information that is useful, which is consistent with the holistic thought and plays an important role in research on the substantial basis. In this review, we will start with three aspects to expound the quality evaluation of traditional Chinese medicines based on fingerprints. The analytical techniques used in developing fingerprints including chromatographic methods, spectroscopic methods, and capillary electrophoresis are introduced. Strategies for fingerprints analysis usually based on chemometric methods including unsupervised and supervised pattern recognition are described. Applications of fingerprints for multi-component quantification, quality control, screening of bioactive components, and fingerprint-efficacy relationship study are also outlined. Finally, we propose challenges and future perspectives of fingerprints in quality evaluation to promote the development of modernization and internationalization of traditional Chinese medicines.

Rapid quality evaluation of Shenzhiling oral liquid by attenuated total reflectance-infrared spectroscopy with chemometrics.

In this study, a useful method of Attenuated total reflectance-Fourier transform infrared spectroscopy (ATR-FTIR) combined with chemometrics was proposed for rapid quantification of two-indicator components as well as discrimination of Shenzhiling oral liquid in shelf life and over shelf life. Fifteen batches of samples were employed to construct quantitative and discriminant models. Two ingredients (paeoniflorin and cinnamic acid) for quality control were modeled by partial least square regression (PLSR). The discrimination of samples between in shelf life and over shelf life was carried out by using discriminant analysis (DA). The samples were divided into calibration set and validation set according to batches. Different data pre-processing algorithms such as standard-normal-variate (SNV), multiplicative scatter correction (MSC), Savitzkye-Golay (SG) smoothing with derivative methods were applied to reduce the influence of systematic disturbances. Variable selection methods including correlation coefficient (CC), competitive adaptive reweighted sampling (CARS) and interval partial least squares regression (iPLS) were all performed for optimizing the PLSR models and DA model. The results demonstrated that ATR-FTIR combined with chemometrics could be a rapid, convenient and nondestructive approach to evaluate the quality of Shenziling oral liquid.

Multi-parameters monitoring during traditional Chinese medicine concentration process with near infrared spectroscopy and chemometrics.

As a powerful process analytical technology (PAT) tool, near infrared (NIR) spectroscopy has been widely used in real-time monitoring. In this study, NIR spectroscopy was applied to monitor multi-parameters of traditional Chinese medicine (TCM) Shenzhiling oral liquid during the concentration process to guarantee the quality of products. Five lab scale batches were employed to construct quantitative models to determine five chemical ingredients and physical change (samples density) during concentration process. The paeoniflorin, albiflorin, liquiritin and samples density were modeled by partial least square regression (PLSR), while the content of the glycyrrhizic acid and cinnamic acid were modeled by support vector machine regression (SVMR). Standard normal variate (SNV) and/or Savitzkye-Golay (SG) smoothing with derivative methods were adopted for spectra pretreatment. Variable selection methods including correlation coefficient (CC), competitive adaptive reweighted sampling (CARS) and interval partial least squares regression (iPLS) were performed for optimizing the models. The results indicated that NIR spectroscopy was an effective tool to successfully monitoring the concentration process of Shenzhiling oral liquid.

[Rapid monitoring five components of ethanol precipitation process of Shenzhiling oral solution using near infrared spectroscopy].

To develop a method for the rapid monitoring of five components during the alcohol precipitation process of Shenzhiling oral solution using near infrared spectroscopy(NIRS).The contents of five components detemined by high performance liquid chromatography(HPLC) were used as the reference values, and the NIRS based partial least square regression(PLSR) models were used to monitor the concentrations of paeoniflorin, albiflorin, liquiritin, cinnamic acid and glycyrrhizic acid during the alcohol precipitation process of Shenzhiling oral solution, which were optimized and verified through comparing of different spectral pre-processing and variables selection methods. Determination coefficients(Rcal2 and Rpred2), root mean squares error of prediction (RMSEP), root mean squares error of calibration(RMSEC) and ratiao of performance to deviation(RPD) were applied to evaluate the performance of the models, and the corresponding values were 0.993 3 and 0.997 6, 0.084 9 g•L⁻¹, 0.073 3 g•L⁻¹ and 14.7 for paeoniforin; 0.991 4, 0.992 7, 0.028 1 g•L⁻¹, 0.030 5 g•L⁻¹ and 10.2 for albiforin; 0.955 3, 0.976 1, 0.012 0 g•L⁻¹, 0.012 3 g•L⁻¹ and 5.1 for liquiritin; 0.958 8, 0.990 3, 0.003 89 g•L⁻¹, 0.002 89 g•L⁻¹ and 7.1 for cinnamic acid; 0.982 0, 0.986 3, 0.053 8 g•L⁻¹, 0.059 0 g•L⁻¹, 7.2 for glycyrrhizic acid, respectively. The results indicated that the presented approach was effectively for the quantitative monitoring of the alcohol precipitation process of Shenzhiling oral solution.

A Useful Strategy to Evaluate the Quality Consistency of Traditional Chinese Medicines Based on Liquid Chromatography and Chemometrics.

Evaluation of the batch consistency of traditional Chinese medicines (TCMs) is essential for the promotion of the development and quality control of TCMs. The aim of the present work was to develop a useful strategy via liquid chromatography and chemometrics to evaluate the batch consistency of TCM preparations. Xin-Ke-Shu (XKS) tablet was chosen as a model for this method development. Four types of chromatographic fingerprint approaches were compared by using similarity analysis based on cosine of angel or correlation coefficient. Differences in the fingerprints of 71 batches of XKS tablet were illustrated by hierarchical cluster analysis. Then, Mahalanobis distance was employed for estimating the probability level (P < 0.05) of the differences mentioned above. Additionally, t-test was applied to find out the chromatographic peaks which had significant differences. For XKS tablet, the maximum wavelength fingerprint had the largest range and dispersion degree of similarity as compared with the other three ones. There were two clear clusters in all the batches of samples. And we clearly arrived at the conclusion that higher similarity does not exactly indicate small Mahalanobis distance, while lower similarity indicated larger Mahalanobis distance. Finally, a useful strategy was proposed for evaluation of the batch consistency of XKS tablet.

Fingerprint analysis, multi-component quantitation, and antioxidant activity for the quality evaluation of Salvia miltiorrhiza var. alba by high-performance liquid chromatography and chemometrics.

Salvia miltiorrhiza Bge. var. alba C.Y. Wu and H.W. Li has wide prospects in clinical practice. A useful comprehensive method was developed for the quality evaluation of S. miltiorrhiza var. alba by three quantitative parameters: high-performance liquid chromatography fingerprint, ten-component contents, and antioxidant activity. The established method was validated for linearity, precision, repeatability, stability, and recovery. Principal components analysis and hierarchical clustering analysis were both used to evaluate the quality of the samples from different origins. The results showed that there were category discrepancies in quality of S. miltiorrhiza var. alba samples according to the three quantitative parameters. Multivariate linear regression was adopted to explore the relationship between components and antioxidant activity. Three constituents, namely, danshensu, rosmarinic acid, and salvianolic acid B, significantly correlated with antioxidant activity, and were successfully elucidated by the optimized multivariate linear regression model. The combined use of high-performance liquid chromatography fingerprint analysis, simultaneous multicomponent quantitative analysis, and antioxidant activity for the quality evaluation of S. miltiorrhiza var. alba is a reliable, comprehensive, and promising approach, which might provide a valuable reference for other herbal products in general to improve their quality control.

Rapid discrimination of geographical origin and evaluation of antioxidant activity of Salvia miltiorrhiza var. alba by Fourier transform near infrared spectroscopy.

Radix Salvia miltiorrhiza Bge. var. alba C.Y. Wu and H.W. Li and Radix S. miltrorrhiza belong to the same genus. S. miltiorrhiza var. alba has a unique effectiveness for thromboangiitis besides therapeutical efficay of S. miltrorrhiza. It exhibits antioxidant activity (AA), while its quality and efficacy also vary with geographic locations. Therefore, a rapid and nondestructive method based on Fourier transform near infrared spectroscopy (FT-NIRS) was developed for discrimination of geographical origin and evaluation of AA of S. miltiorrhiza var. alba. The discrimination of geographical origin was achieved by using discriminant analysis and the accuracy was 100%. Partial least squares (PLS) regression was employed to establish the model for evaluation of AA by NIRS. The spectral regions were selected by interval PLS (i-PLS) method. Different pre-treated methods were compared for the spectral pre-processing. The final optimal results of PLS model showed that correlation coefficients in the calibration set (Rc) and the prediction set (Rp), root mean square error of prediction (RMSEP) and residual prediction deviation (RPD) were 0.974, 0.950, 0.163 mg mL(-1) and 2.66, respectively. The results demonstrated that NIRs combined with chemometric methods could be a rapid and nondestructive tool to discriminate geographical origin and evaluate AA of S. miltiorrhiza var. alba. The developed NIRS method might have a potential application to high-throughput screening of a great number of raw S. miltiorrhiza var. alba samples for AA.