Yanjiang Qiao

Diagnostic fragment-ion-based and extension strategy coupled to DFIs intensity analysis for identification of chlorogenic acids isomers in Flos Lonicerae Japonicae by HPLC-ESI-MSn

A method of modified diagnostic fragment-ion-based extension strategy (DFIBES) coupled to DFIs (diagnostic fragmentation ions) intensity analysis was successfully established to simultaneously screen and identify the chlorogenic acids (CGAs) in Flos Lonicerae Japonicae (FLJ) by HPLC-ESI-MS(n). DFIs, such as m/z 191 [quinic acid-H](-), m/z 179 [caffeic acid-H](-) and m/z 173 [quinic acid-H-H2O](-) were determined or proposed from the fragmentation patterns analysis of corresponding reference substances for every chemical family of CGAs. A structure extension method was then proposed based on the well-demonstrated fragmentation patterns and was successively applied into the rapid screening of CGAs in FLJ. Considering that substitution isomerism is a common phenomenon, a full ESI-MS(n) fragmentation analysis according to the intensity of DFIs has been performed to identify the CGA isomers. Based on the DFIs and intensity analysis, 41 peaks attributed to CGAs including 4 caffeoylquinic acids (CQA), 7 CQA glycosides, 6 dicaffeoylquinic acids (DiCQA), 10 DiCQA glycosides, 1 tricaffeoylquinic acids (TriCQA), 4p-coumaroylquinic acids (pCoQA), 3 feruloylquinic acids (FQA) and 6 caffeoylferuloylquinic acids (CFQA) were identified preliminarily in a 65-min chromatographic run. It was the first time to systematically report the presence of CGAs in FLJ, especially for CQA glycosides, DiCQA glycosides, TriCQA, pCoQA and CFQA. All the results indicated that the method of developed DFIBES coupled to DFIs analysis was feasible, reliable and universal for screening and identifying the constituents with the same carbon skeletons especially the isomeric compounds from the complex extract of TCMs.

Multivariate detection limits of on-line NIR model for extraction process of chlorogenic acid from Lonicera japonica

A methodology is proposed to estimate the multivariate detection limits (MDL) of on-line near-infrared (NIR) model in Chinese Herbal Medicines (CHM) system. In this paper, Lonicera japonica was used as an example, and its extraction process was monitored by on-line NIR spectroscopy. Spectra of on-line NIR could be collected by two fiber optic probes designed to transmit NIR radiation by a 2mm-flange. High performance liquid chromatography (HPLC) was used as a reference method to determine the content of chlorogenic acid in the extract solution. Multivariate calibration models were carried out including partial least squares regression (PLS) and interval partial least-squares (iPLS). The result showed improvement of model performance: compared with PLS model, the root mean square errors of prediction (RMSEP) of iPLS model decreased from 0.111mg to 0.068mg, and the R(2) parameter increased from 0.9434 to 0.9801. Furthermore, MDL values were determined by a multivariate method using the type of errors and concentration ranges. The MDL of iPLS model was about 14ppm, which confirmed that on-line NIR spectroscopy had the ability to detect trace amounts of chlorogenic acid in L. japonica. As a result, the application of on-line NIR spectroscopy for monitoring extraction process in CHM could be very encouraging and reliable.

UPLC Q-TOF/MS-Based Metabolic Profiling of Urine Reveals the Novel Antipyretic Mechanisms of Qingkailing Injection in a Rat Model of Yeast-Induced Pyrexia

Fever is one of the most common clinical symptoms of many diseases. Qingkailing (QKL) injection is widely used in China as a clinical emergency medicine due to its good antipyretic effects. It is a herbal formula which is composed by eight kinds of traditional Chinese medicines (TCM). As a kind of typical multiple constituents and multiple actions of TCM, it is very difficult to elaborate the antipyretic mechanism by conventional pharmacological method. Metabonomics technique provides beneficial tool for this challenge. In this study, an ultra performance liquid chromatography quadrupole time-of-flight mass spectrometry (UPLC Q-TOF/MS) metabonomics method was developed to explore the changing process of biochemical substances in rats of yeast-induced pyrexia. Partial least squares discriminate analysis (PLS-DA) was used to distinguish the normal control group, the pyrexia model group, and the pyrexia model group treated by QKL injection. The potential biomarkers related to pyrexia were confirmed and identified. MetPA was used to find the possible metabolic pathways. The results indicated that the antipyretic effect of QKL injection on yeast-induced pyrexia rats was performed by repairing the perturbed metabolism of amino acids.

[6]-Gingerol: A Novel AT1 Antagonist for the Treatment of Cardiovascular Disease

Considering the prevalence of cardiovascular disease in public health and the limited validated therapeutic options, this study aimed to find novel compounds targeting the angiotensin II type 1 receptor, accepted as a therapeutic target in cardiovascular disease. A small library consisting of 89 compounds from 39 Chinese herbs was profiled using a cell-based calcium mobilization assay which was developed and characterized for high-throughput screening. [6]-Gingerol derived from Zingiber officinale Roscoe (ginger) was identified as a novel angiotensin II type 1 receptor antagonist, with an IC50 value of 8.173 µM. The hit was further tested by a specificity assay indicating that it had no antagonistic effects on other evaluated GPCRs, such as endothelin receptors. The major ingredient of ginger, [6]-gingerol, could inhibit angiotensin II type 1 receptor activation, which partially clarified the mechanism of ginger regulating blood pressure and strengthening heart in the cardiovascular system.

NIR spectroscopy as a process analytical technology (PAT) tool for monitoring and understanding of a hydrolysis process

The use of near infrared spectroscopy was investigated as a process analytical technology to monitor the amino acids concentration profile during hydrolysis process of Cornu Bubali. A protocol was followed, including outlier selection using relationship plot of residuals versus the leverage level, calibration models using interval partial least squares and synergy interval partial least squares (SiPLS). A strategy of four robust root mean square error of predictions (RMSEP) values have been developed to assess calibration models by means of the desirability index. Furthermore, multivariate quantification limits (MQL) values of the optimum model were determined using two types of error. The SiPLS(3) models for L-proline, L-tyrosine, L-valine, L-phenylalanine and L-lysine provided excellent accuracies with RMSEP values of 0.0915 mg/mL, 0.1605 mg/mL, 0.0515 mg/mL, 0.0586 mg/mL and 0.0613 mg/mL, respectively. The MQL ranged from 90 ppm to 810 ppm, which confirmed that these models can be suitable for most applications.

A novel model selection strategy using total error concept.

Our previous work had proved that accuracy profile theory could be employed as a means of validating one PLS model in Chinese material medica system. In this paper, accuracy profile theory is proposed as a powerful decision tool to demonstrate the prediction performance of multi-model at each concentration level rather than all concentration levels. Partial least square (PLS), interval partial least square (iPLS), backward interval partial least square (BiPLS) and moving window partial least square (MWPLS) were selected to construct visible and near-infrared (vis/NIR) spectroscopy models. Chemometric indicators, i.e., determination coefficient (R(2)), root-mean-square error of prediction (RMSEP) and ratio of performance to inter-quartile (RPIQ), were used to select the optimum model. However, the results clarified that these commonly used indicators could not clearly demonstrate different PLS models ability because these indicators depend on all concentration levels to assess the multi-model. Therefore, total error concept (accuracy profile theory) was introduced to assess the ability of multi-model at each concentration level. Analytical methodology parameters, i.e., linearity, relative bias, uncertainty, repeatability, intermediate precision, lower limit of quantification (LLOQ) and risk, were calculated by accuracy profile theory. Final results showed that model selection strategy which was based on model assessment at every concentration level was more sensitive than the one based on all concentration levels. The analytical procedures involved in this work ensure that model selection strategy using total error concept is coherent.

Multiscale study on the interaction mechanism between ginsenoside biosurfactant and saikosaponin a

Ginsenoside is an important class of saponin biosurfactant that is derived from ginseng. The interactions between ginsenoside Ro, Rb1, and Rg1 with saikosaponin a (SSa) were explored using multiscale methods. The order of interaction strength was found to be Ro>Rb1>Rg1. Ro markedly increased the solubility of SSa; however, Rb1 could only disperse SSa solid in aqueous medium. No significant interaction was observed between Rg1 and SSa. Ro formed vesicles in aqueous medium while Rb1 and Rg1 formed spherical micelles. The differences in the available surface area of the aggregates appear to have some influence on the interactions between ginsenoside and SSa. However, more important effects are related to their chemical structures and interaction energy. According to the molecular simulation results, glucuronic acid linked to Ro molecules significantly reduced the potential energy through its strong electrical attraction to SSa, which contributed greatly to the strong compatibility between them. The greater number of sugars in Rb1, as compared to Rg1, created more binding sites with SSa, thus resulting in stronger interaction between Rb1 with SSa than between Rg1 and SSa. Spherical and worm-like micelles were found to be formed by Rb1 and SSa molecules. This was different from Ro and SSa, which formed vesicles. The formation of worm-like micelles was through the fusion and modification of small spherical micelles. These results may guide in expanding the applications of ginsenoside.

Study on the aconitine-type alkaloids of Radix Aconiti Lateralis and its processed products using HPLC-ESI-MSn

The type and content change of alkaloids of Radix Aconiti Lateralis (Lateral root of Aconitum carmichaeli Debx, an important and popular medicinal herb in Traditional Chinese Medicine) in processing were studied using high performance liquid chromatography-electrospray ionization-multi-stage mass spectrometry (HPLC-ESI-MS(n)). Extract containing alkaloids, which were known to be the main bioactive components of the herb, was prepared by 1% (v/v) hydrochloric acid solution. An HPLC method which can simultaneously separate these alkaloids was established with gradient elution mode. Forty-eight compounds were structurally identified by employing LC-MS(n) techniques; the MS(n) spectra of most alkaloids displayed a characteristic behaviour of loss of CH(3)COOH (60 u), CH(3)OH (32 u), C(6)H(5)COOH (122 u), CO (28 u) and H(2)O (18 u). Among them, the fragmentation ion C6H5COOH (122 u) was reported for the first time. By comparison, 22 compounds were found both in the crude materials and the processed products; 17 alkaloids were only found in the processed products and 9 alkaloids,which existed in crude material, could not be detected after processing. In the process of identification, we found new kinds of alkaloids, with protonated molecules at m/z 452, 468, and 482. We called these compounds dehydra-hypaconine, dehydra-mesaconine, and dehydra-aconine, respectively.

Application of orthogonal space regression to calibration transfer without standards

To transfer a calibration model in cases where the standardization samples are rare or unstable, a method based on orthogonal space regression (OSR) is proposed. It uses virtual standardization spectra to account for response changes between instruments or batches. A comparative study of the proposed OSR, piecewise direct standardization, finite impulse response, orthogonal signal correction, and model updating (MU) was conducted on both pharmaceutical tablet data and chlorogenic acid data. The results of these studies suggest that both the OSR and the MU are superior to the other transfer techniques in terms of root‐mean‐squared error of prediction and ratio of performance to interquartile distance. Moreover, OSR requires no identical standard samples, and it avoids re‐optimizing the transfer models. In conclusion, both the differences among spectra measured on different spectrometers and the differences between different batches can be corrected successfully using the OSR method. Copyright

Characterization of thirty-nine polymethoxylated flavonoids (PMFs) in the branches of Murraya paniculata by HPLC-DAD-ESI-MS/MS

Abstract Aim To investigate the polymethoxylated flavonoids (PMFs) in the branches of Murraya paniculata (L.) Jack. Methods A sensitive HPLC-DAD-ESI-MS/MS method was established to screen PMFs in the branches of M. paniculata based on the analysis of six PMF standards in the positive mode by CID-MS/MS. Results The diagnostic fragmentation pathways for polymethoxylated flavones, polymethoxylated flavanones, polymethoxylated chalcones and PMF glycosides were summarized, respectively. According to the MS fragmentation pathways, 39 PMFs, including 24 flavones, 10 flavanones or chalcones and 5 PMFs glycosides were screened. Conclusion The results indicated that the developed analytical method could be employed as a rapid, effective technique for the chemical screening of PMFs in TCMs extracts.