Chromatographic fingerprinting and related chemometric techniques for quality control of traditional Chinese medicines

Development of chromatographic fingerprint (CF) and related chemometric methods and their applications to quality control of traditional Chinese medicines (TCMs) were discussed. CF is essentially a kind of quality control method for TCMs (or Chinese herbal medicines). Also, it is a quality‐relevant‐data high‐throughput and integral tool to explore chemically the complexity of TCMs. With the help of chemometrics, some difficulties in evaluation and analysis of CFs, such as calculation of information content, peak alignment, pattern analysis, deconvolution of overlapping peaks, etc. could be well solved. To further explore TCMs synergic quality, intensive study of CF coupled with chemometrics will create the possibility to achieve the aim to reveal the working mechanisms of TCMs and to further control and strengthen TCMs' intrinsic quality in a comprehensive manner.     

色谱指纹图谱与中药质量控制

本文综述了近年来色谱指纹图谱研究中多种色谱技术、相关化学计量学方法的发展及其在中药质量控制中的应用,并对中药质量稳定性和有效性的全面评价方法和可行性进行了初步探讨。提出以色谱指纹图谱为核心,依托现代色谱技术、化学计量学和系统生物学方法,建立中药化学成分信息与药效(毒性)信息相关关系的中药质量控制研究策略,深层次揭示中药的内在作用机理,期望真正实现中药质量的可控、安全和有效。     

Chromatographic fingerprints of industrial toluic acids established for their quality control

The chromatographic fingerprints of industrial o-toluic acid, m-toluic acid and p-toluic acid have been established by HPLC-UV detection according to their impurity groups. HPLC separation of all relative substances involved in the groups was developed on a Kromasil C₁₈ column by using methanol-water-NH₄Ac-HAc buffer (100 mM, pH 4.70) 15/65/20 (v/v/v) as the mobile phase at a flow rate of 1.5 mL/min, and detection was operated by UV adsorption at a wavelength of 254 nm. The ultraviolet spectra corresponding to each chromatographic peak were also recorded for further identification of all components. Whether the limits of relative impurities residues in a toluic acid product are qualified or not can be intuitively estimated by analyzing its chromatogram with comparison to the fingerprint. This protocol has successfully provided some Chinese manufacturers with a simple and feasible method for quality control of toluic acids for industrial use.     

Pattern recognition based on fuzzy observations for spectroscopic quality control and chromatographic fingerprinting

The quality of multicomponent samples from one or several groups of samples can be monitored by a pattern recognition method. The method is based on profiles of sample quality, which are obtained by means of a multicomponent analytical technique (e.g., ultraviolet spectroscopy or chromatography), and data reduction is done with the aid of fuzzy set theory. The advantages of the method in cases of overlapping and non-additive signals are outlined for quality control of analgesic tablets by ultraviolet spectroscopy. Its performance in the case of highly uncertain data patterns is demonstrated for classification of protein samples by chromatography.     

Development, optimization and validation of gas chromatographic fingerprinting of Brazilian commercial gasoline for quality control

Three-step development, optimization and validation strategy for GC fingerprints of Brazilian commercial gasoline is described. A suitable chromatographic system was selected first. The following step was to improve acceptable chromatographic resolution with reduced analysis time, which is recommended for routine applications. Optimization was carried out using full three-level factorial designs. Optimal conditions were obtained for flow rate, oven ramps, injection volume and split ratio. Finally, several validation parameters were performed. Therefore, a feasible and reliable fingerprint was established to identify Brazilian commercial gasoline quality. This strategy can also be applied to develop fingerprints for quality control of other fuels.     

A novel approach for LC-MS/MS-based chiral metabolomics fingerprinting and chiral metabolomics extraction using a pair of enantiomers of chiral derivatization reagents

Chiral metabolites are found in a wide variety of living organisms and some of them are understood to be physiologically active compounds and biomarkers. However, the overall analysis of chiral metabolomics is quite difficult due to the high number of metabolites, the significant diversity in their physicochemical properties, and concentration range from metabolite-to-metabolite. To solve this difficulty, we developed a novel approach for chiral metabolomics fingerprinting and chiral metabolomics extraction, which is based on the labeling of a pair of enantiomers of chiral derivatization reagents (i.e., DMT-(S,R)-Pro-OSu and DMT-3(S,R)-Apy) and precursor ion scan chromatography of the derivatives. The multivariate statistics is also required for this strategy. The proposed procedures were evaluated by the detection of a diagnostic marker (i.e., d-lactic acid) using the saliva of diabetic patients. This method was used for the determination of biomarker candidates of chiral amines and carboxyls in Alzheimer's disease (AD) brain homogenates. As the results, l-phenylalanine (L-Phe) and l-lactic acid (L-LA) were identified as the decreased and increased biomarker candidates in the AD brain, respectively. Therefore, the proposed approach seems to be helpful for the determination of non-target chiral metabolomics possessing amines and carboxyls.     

Multiple chromatographic fingerprinting and its application to the quality control of herbal medicines

Recently, chromatographic fingerprinting has become one of the most powerful approaches to quality control of herbal medicines. However, the performance of reported chromatographic fingerprinting constructed by single chromatogram sometimes turns out to be inadequate for complex herbal medicines, such as multi-herb botanical drug products. In this study, multiple chromatographic fingerprinting, which consists of more than one chromatographic fingerprint and represents the whole characteristics of chemical constitutions of the complex medicine, is proposed as a potential strategy in this complicated case. As a typical example, a binary chromatographic fingerprinting of “Danshen Dropping Pill” (DSDP), the best-sold traditional Chinese medicine in China, was developed. First, two HPLC fingerprints that, respectively, represent chemical characteristics of depsides and saponins of DSDP were developed, which were used to construct binary chromatographic fingerprints of DSDP. Moreover, the authentication and validation of the binary fingerprints were performed. Then, a data-level information fusion method was employed to capture the chemical information encoded in two chromatographic fingerprints. Based on the fusion results, the lot-to-lot consistency and frauds can be determined either using similarity measure or by chemometrics approach. The application of binary chromatographic fingerprinting to consistency assessment and frauds detection of DSDP clearly demonstrated that the proposed method was a powerful approach to quality control of complex herbal medicines.     

Carbon nuclear magnetic resonance spectroscopic fingerprinting of commercial gasoline: Pattern-recognition analyses for screening quality control purposes

In this work, the combination of carbon nuclear magnetic resonance (¹³C NMR) fingerprinting with pattern-recognition analyses provides an original and alternative approach to screening commercial gasoline quality. Soft Independent Modelling of Class Analogy (SIMCA) was performed on spectroscopic fingerprints to classify representative commercial gasoline samples, which were selected by Hierarchical Cluster Analyses (HCA) over several months in retails services of gas stations, into previously quality-defined classes. Following optimized ¹³C NMR-SIMCA algorithm, sensitivity values were obtained in the training set (99.0%), with leave-one-out cross-validation, and external prediction set (92.0%). Governmental laboratories could employ this method as a rapid screening analysis to discourage adulteration practices.     

Chromatographic and mass spectrometric fingerprinting analyses of Angelica sinensis (Oliv.) Diels-derived dietary supplements

Angelica sinensis (Oliv.) Diels (“Danggui” in Chinese) is one of the most commonly used traditional Chinese medicines. It has been used to invigorate blood circulation for the treatment of anemia, hypertension, chronic bronchitis, asthma, rheumatism, and cardiovascular diseases. There are a number of A. sinensis-derived dietary supplements in the US markets. However, no study have been conducted to investigate the quality of these dietary supplements. In this paper, high-performance liquid chromatographic and flow-injection mass spectrometric fingerprints were both evaluated to assess the consistency of A. sinensis-derived dietary supplements. Similarity analysis was carried out on the high-performance liquid chromatographic (HPLC) fingerprints. Meanwhile, principal component analysis (PCA) was performed on the data obtained from flow-injection mass spectrometric (FIMS) fingerprints, which can analyze each sample in 2 min, compared with 30 min required for the chromatographic fingerprint. Both methods show significant chemical differences between samples that may be due to differences in growing locations, growing conditions, harvesting times, and/or botanical processing. The loading plots obtained from PCA singled out the discriminatory ions that were responsible for chemical differences of A. sinensis-derived dietary supplements.

Chromatographic multivariate quality control of pharmaceuticals giving strongly overlapped peaks based on the chromatogram profile

In the present paper, the simultaneous quantification of two analytes showing strongly overlapped chromatographic peaks (alpha = 1.02), under the assumption that both available equipment and training of the laboratory staff are basic, is studied. A pharmaceutical preparation (Mutabase) containing two drugs of similar physicochemical properties (amitriptyline and perphenazine) is selected as case of study. The assays are carried out under realistic working conditions (i.e. routine testing laboratories). Uncertainty considerations are introduced in the study. A partial least squares model is directly applied to the chromatographic data (with no previous signal transformation) to perform quality control of the pharmaceutical formulation. Under the adequate protocol, the relative error in prediction of analytes is within the tolerances found in the pharmacopeia (10%). For spiked samples simulating formulation mistakes, the errors found have the same magnitude and sign to those provoked.     

A proficiency test scheme for the quality control of black tea and development of quality control material for internal quality control

A proficiency test (PT) was organized for quality control analysis of black tea. Test materials for the analyses of total content of powder tea, moisture, total ash, acid-insoluble ash, water-soluble ash, alkalinity of water-soluble ash, water extract, crude fiber and caffeine were sent to the participant laboratories (n:43) in 2009. The assigned value, standard deviation of the parameters and z-scores of the participant laboratories were calculated using the data reported by the participants. The percentage of the reported results for analytes was found to be ranged from 67.5 to 100%. Acceptable z-scores were achieved by 80.5–97.5% of the participant laboratories. More than 15% of unacceptable results were obtained for acid-insoluble ash and caffeine analyses. The quality control material for quality control analysis of black tea was developed from the remaining material.     

Chromatographic and electrophoretic approaches for the analysis of protein quality of soy beverages

Furosine, generated by acid hydrolysis of fructosyllysine, an early Maillard reaction product, is a highly valuable indicator of food quality and, more specifically, of food protein quality. Ion pair RP-HPLC and CZE techniques were employed to determine furosine content in beverages based on soymilk (n = 15) and cow's milk supplemented with soy isoflavones (n = 1). The levels of furosine found in the samples ranged from 25.55 +/- 0.18 to 170.72 +/- 10.4 mg/100 g of protein by HPLC and from 28.67 +/- 1.84 to 161.25 +/- 5.78 mg/100 g of protein by CZE. Results obtained by both analytical techniques do not differ significantly (p > 0.05), confirming their feasibility for furosine analysis in soy-based products.     

Capillary electrophoresis fingerprinting coupled with chemometrics to evaluate the quality consistency and predict the antioxidant activity of Sanhuang tablet as part of its quality control

A capillary electrophoresis fingerprint was constructed for Sanhuang tablet, a Chinese traditional patent medicine, that was commonly used in clinical practice, where the isosceles trapezoid method was first applied for the optimization of background electrolyte solution, and the resolution index was performed to assess the experimental conditions; furthermore, a novel linear quantitative fingerprint method was established for accurate qualitative and quantitative discrimination of the test samples from diverse commercial brands. The fingerprint analysis coupled with quantitative determination of two components was employed to elucidate that the quality consistency of the products was relatively good within one manufactory, but poor among different companies for the 30 batches of samples. In addition, the fingerprint–efficacy relationship between chemical components and antioxidant activity in vitro was investigated using partial least squares analysis, and the calibration and prediction of the antioxidant activity of the selected samples via fingerprint data were presented with the desired results. This work illustrates that the proposed fingerprint analysis based on linear quantitative fingerprint method can be applied for the quality evaluation of traditional Chinese medicine and herbal preparations as part of their quality control, and the constructed mathematical model is particularly suitable for depicting the fingerprint–efficacy relationship.     

A flow-injection mass spectrometry fingerprinting method for authentication and quality assessment of Scutellaria lateriflora-based dietary supplements

Scutellaria lateriflora, commonly known as skullcap, is used as an ingredient in numerous herbal products. However, it has been occasionally adulterated/contaminated with Teucrium canadense and/or Teucrium chamaedrys, commonly known as germander, due to the morphological similarities between the two genera. The latter contains hepatotoxic diterpenes. Despite the potential hepatotoxicity introduced by germander contamination, analytical methodologies for the authentication and quality assessment of S. lateriflora-based dietary supplements have not been reported. In this study, a flow-injection/mass spectrometry fingerprinting method in combination with principal component analysis was used to survey S. lateriflora-based dietary supplements sold in the USA.     

基于信息融合的中药多元色谱指纹图谱相似性计算方法

摘要用信息融合算法合并多张色谱指纹图谱, 解决中药多元指纹图谱相似性评价难题, 提出一种多元色谱指纹图谱相似度计算方法. 用该方法先对各单元指纹图谱进行串行或并行象素级信息融合, 再对融合了各指纹峰信息的多元色谱指纹图谱进行相似度评价. 计算机仿真和复方丹参滴丸多元HPLC指纹图谱应用结果表明, 该法能够评价中药多元色谱指纹图谱相似度, 定量表征中成药产品批次间质量波动情况.     

Quantitative NMR for bioanalysis and metabolomics

Over the last several decades, significant technical and experimental advances have made quantitative nuclear magnetic resonance (qNMR) a valuable analytical tool for quantitative measurements on a wide variety of samples. In particular, qNMR has emerged as an important method for metabolomics studies where it is used for interrogation of large sets of biological samples and the resulting spectra are treated with multivariate statistical analysis methods. In this review, recent developments in instrumentation and pulse sequences will be discussed as well as the practical considerations necessary for acquisition of quantitative NMR experiments with an emphasis on their use for bioanalysis. Recent examples of the application of qNMR for metabolomics/metabonomics studies, the characterization of biologicals such as heparin, antibodies, and vaccines, and the analysis of botanical natural products will be presented and the future directions of qNMR discussed.     

Combining network pharmacology with chromatographic fingerprinting and multicomponent quantitative analysis for the quality evaluation of Astragali Radix

Nowadays, cultivated variants and adulterants of Astragali Radix (AR) have flooded the market, causing the quality assurance of AR to be challenging. To address this issue, we combined network pharmacology with chromatographic fingerprinting and multicomponent quantitative analysis for the quality evaluation of AR. Specifically, through network pharmacology, a complete understanding of the active components and pharmacological activities of AR was established. In addition, establishing fingerprint profiles and multicomponent quantitation by high-performance liquid chromatography (HPLC) is convenient and comprehensive, and can more fully reflect the overall situation of the distribution of various chemical components. To evaluate and differentiate AR from different origins, hierarchical cluster analysis and principal component analysis were performed. The result showed that AR acts synergistically through multiple targets and pathways. The content of chemical components in AR from different origins varied significantly. Combining network pharmacology and multicomponent quantification results, astragaloside II and IV and formononetin can be used as quality markers for the quality control of AR. This study provides a comprehensive and reliable strategy for the quality evaluation of AR and identifies its quality markers to ensure the quality of the herb.     

Simple quality assessment approach for herbal extracts using high performance liquid chromatography-UV based metabolomics platform

A lack of adequate or accepted research methodology has been a major obstacle to study herbal medicines. In this study, instead of the prevalent hyphenated chromatographies, common high performance liquid chromatography equipped with ultraviolet detector (HPLC-UV) and multivariate statistical analysis were utilized to assess the qualities of total flavones of sea buckthorn (TFS), an 85% ethanol extract of the sea buckthorn berries. Two complementary HPLC-UV methods were developed, validated and combined to comprehensively determine the ingredients in TFS. Principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) of the combined analytical data showed that the six batches of TFS could be well differentiated. Hierarchical cluster analysis (HCA) using Ward's minimum variance method of the PLS-DA loading matrix demonstrated the known ingredients (quercetin, kaempferol, isorhamnetin, oleanolic acid and ursolic acid) and three unknown ingredients in TFS significantly contributed to the quality differences. A PLS regression model indicated that the results of the present method correlated well with the content of total flavones, which is now the quality control approach of TFS. Results from this study indicated that the proposed method is reliable for the quality reassessment of some widely used herbal extracts.     

Separation strategies for untargeted metabolomics

Metabolomics has rapidly become a profiling technique of choice for biomarker elucidation and molecular diagnostics in addition to studies focused on understanding disease pathogenesis. Key to the success of metabolomics in these areas has been the techniques to separate and analyze the chemically diverse group of compounds comprising the metabolome by using global and untargeted approaches. Untargeted metabolomic efforts have the goal of examining as many metabolites as possible simultaneously and most frequently use an LC/MS-based approach. Here, the importance of LC in an untargeted metabolomic workflow is outlined and separation strategies for optimization are reviewed within the context of these criteria.