HPLC fingerprint and UV–Vis spectroscopy coupled with chemometrics for Curcumae radix species discrimination and three bioactive compounds prediction

A comprehensive quality evaluation strategy of Mailuoning oral liquid based on fingerprint, qualitative and quantitative analyses

In order to obtain comprehensive quality evaluation of one traditional Chinese patent medicine of Mailuoning oral liquid (MLN), one smart strategy combined by fingerprint, qualitative and quantitative analyses were carried out in this study. Firstly, the fingerprints of MLN were established by HPLC-UV and HPLC-ELSD, and explained the similarity of twenty-seven batches of MLN by similarity analysis (SA). Secondly, qualitative analysis was performed by high performance liquid chromatography coupled with quadrupole-time-of-flight mass spectrometry (HPLC-QTOF-MS/MS). A total of 60 compounds were identified or tentatively identified based on chemical standards and fragmentation information. Finally, the quantitative method based on UPLC combined with triple quadrupole mass spectrometry (UPLC-QqQ-MS/MS) was developed for the simultaneous determination of 40 target compounds. The results showed that MLN samples of different productive year were clearly discriminated and eight compounds (5-hydroxymethyl-2-furaldehyde, neochlorogenic acid, loganic acid, chlorogenic acid, cryptochlorogenic acid, caffeic acid, isoacteoside, angoroside C) were selected as differential markers for MLN. In a word, this strategy including fingerprint, identification of chemical composition and multiple-component quantification could be well applied to modern quality evaluation of MLN, which could be valuable for the further quality control of more other traditional Chinese patent medicines.

Analysis of genetic and chemical variability of five Curcuma species based on DNA barcoding and HPLC fingerprints

The rhizomes of Curcuma species have a long medicinal history in Asia. In China, Curcuma species mainly be utilized to make pharmaceutical products, including C. phaecocaulis, C. aromatica, C. wenyujin, C. kwangsiensis and C. longa. In this study, twenty-four samples were selected to study the genetic and chemical variability among five Curcuma species. The ITS2 and trnK intron gene fragment were used to identify the five Curcuma species, the differences in chemical composition were computed using the Euclidean distance based on the data of HPLC characteristic peak areas and the content of six key components, and agronomic characteristics were analyzed including morphological and volatile oil characteristics. The ITS2 and trnK intron gene fragment could distinguish the five Curcuma species clearly. The genetic distance between Curcuma species ranged from 0.0085 to 0.0767 based on the data of ITS2 gene sequences with 32 variation sites, and the genetic distance between Curcuma species ranged from 0.0003 to 0.0194 based on the data of trnK intron gene sequences with 39 variation sites. Five Curcuma species showed otherness chemical composition characteristics, with the Euclidean distance ranging from 3.373 to 6.998. The C. longa showed the biggest variation compared with other species, with the Euclidean distance above 6.239. Among the samples of the original plants of Ezhu, the volatile oil yield of W1 was the highest, reached to 105.75 mL per single plant. Among all the samples, J6 showed the highest yield of volatile oil, reached to 149.42 mL per single plant. The results showed that chemical composition similarity of the medicinal plants was the primary proof for the selection of the original plants of the Curcuma medicinal materials. The genetic distance and chemical variability were important references for discovering new medicinal plant resources.

Dual control system for comprehensive evaluation of quality consistency of herbal preparations

This study was undertaken to establish an integrated quality control method based on the fingerprint of different testing instruments and a four-dimensional antioxidant activity profile. Firstly, the comprehensive ratio quantitative fingerprint method was used to rapidly calculate the similarity of GC fingerprint, UV-vis quantized fingerprint, HPLC fingerprint and ATR-FT-IR quantized fingerprint. In addition, a comprehensive evaluation strategy was proposed using the variation coefficient weighting algorithm, incorporating four complementary inputs, to achieve highly accurate analysis. At the same time, multi-markers assay by monolinear method was used for the first time for the quantitative analysis of multiple components. Based on this, the fingerprint-efficacy relationship was investigated, and substances that might be biologically active and the wavelength range of their distribution were predicted using the online-HPLC-DPPH-FIA method in conjunction with a PLS model built from individual and combined data matrices. The results showed that all 20 batches of samples were within 1-3 grades, with good quality consistency. According to index E, the samples' overall antioxidant capacity was also highly correlated with the year of production. The four-dimensional antioxidant activity profile also led to the conclusion that variations in antioxidant characteristics were caused by differences in the concentration and volatility of particular bioactive chemicals. Finally, mid-level data fusion produced better classification results than a single technique, further demonstrating the synergistic effects that may occur when the four types of data were combined. This study demonstrated that the combination of GC, UV-vis, ATR-FT-IR and HPLC can be used for the consistency control of herbal preparations and can elucidate the potential in predicting the antioxidant capacity of herbal preparations.

A highly sensitive method (supercritical fluid chromatography coupled with ion mobility mass spectrometry) for determination of multiple compounds in radix curcumae

A highly sensitive method was developed for simultaneously separating and identifying multiple compounds in radix curcumae. The determination of these compounds was achieved by combining supercritical fluid chromatography with drift tube ion mobility quadrupole time-of-flight MS. Related parameters were optimized: the RX-SIL column was used as the stationary phase, methanol was selected as the organic modifier, back pressure was 120 bar, back temperature was 60°C, the mobile phase flow rate was 1.75 mL/min, the makeup solvent was 0.2% formic acid/methanol with a flow rate of 0.7 mL/min. Under optimal conditions, multipolar compounds were separated. Furthermore, these compounds were identified by the values of collision sectional areas. The established method was verified by related parameters and exhibited good linearity, sensitivity, precision and accuracy. It could be extended to analyze other curcuminoids and sesquiterpenoids in natural products.

Non-Targeted Analytical Technology in Herbal Medicines: Applications, Challenges, and Perspectives

Herbal medicines (HMs) have been utilized to prevent and treat human ailments for thousands of years. Especially, HMs have recently played a crucial role in the treatment of COVID-19 in China. However, HMs are susceptible to various factors during harvesting, processing, and marketing, affecting their clinical efficacy. Therefore, it is necessary to conclude a rapid and effective method to study HMs so that they can be used in the clinical setting with maximum medicinal value. Non-targeted analytical technology is a reliable analytical method for studying HMs because of its unique advantages in analyzing unknown components. Based on the extensive literature, the paper summarizes the benefits, limitations, and applicability of non-targeted analytical technology. Moreover, the article describes the application of non-targeted analytical technology in HMs from four aspects: structure analysis, authentication, real-time monitoring, and quality assessment. Finally, the review has prospected the development trend and challenges of non-targeted analytical technology. It can assist HMs industry researchers and engineers select non-targeted analytical technology to analyze HMs' quality and authenticity.

A hybrid variable selection and modeling strategy for the determination of target compounds in different spectral datasets

In this paper, a hybrid technique is proposed to establish quantitative models for the determination of target compounds in different spectral datasets. The proposed hybrid method is the hybridization of interval partial least squares (iPLS) method with gradient descent (GD) algorithm. Here, the novelty of the proposed method is that the iPLS method is applied to variable selection and the GD algorithm is employed to establish quantitative models based on the selected optimal variables. In the application of the hybrid iPLS-GD method, the factors, i.e., the number of the interval for the iPLS method and the learning rate, the number of iterations for the GD method, that affect the quantitative accuracy of the method are optimized and determined. Then three spectral datasets, including the near-infrared spectroscopy (NIR) dataset, nuclear magnetic resonance (¹H NMR) dataset and excitation-emission matrix fluorescence (EEM) dataset, are used to test and verify the performance of the iPLS-GD method. We compare the hybrid iPLS-GD method with the PLS and iPLS methods from the aspects of modeling ability and predictive ability. The results demonstrated that the iPLS-GD method can be used as an effective and promising tool for the determination of target compounds in complex samples in practice.

Multivariate Statistical Analysis Uncovers Spectrum–Effect Relationship between HPLC Fingerprints and Antioxidant Activity of Saffron

Crocus sativus L. is commonly used as functional food and medicinal herb in traditional Chinese medicine. In this study, the spectrum–effect relationship was established between HPLC fingerprints and in vitro antioxidant activity of saffron to improve the quality evaluation method of saffron. The fingerprints of 21 batches of saffron collected from different regions were assessed, and the data were further analyzed by chemometric methods, including similarity analysis, hierarchical clustering analysis, principal component analysis, and orthogonal partial least squares discriminant analysis. The spectrum–effect relationship between fingerprints and antioxidant effect of saffron was analyzed by grey relational analysis and partial least square methods to figure out the antioxidant component of saffron. Thirteen common peaks of 21 batches of saffron were included in the analysis, and peak 3 (picrocrocin), peak 7 (crocin I), and peak 10 (crocin II) were identified as the main active components responsible for antioxidant efficacy. Besides, a multi-index quality control method was developed for simultaneous determination of these three antioxidant components in saffron. Taken together, this study provided new strategies for the quality control and the development of new bioactive products of saffron in the future.

Rapid discrimination and screening of volatile markers for varietal recognition of Curcumae Radix using ATR-FTIR and HS-GC-MS combined with chemometrics

ETHNOPHARMACOLOGICAL RELEVANCE

Curcumae Radix (Yujin) has a long medicinal use history in China, which is used to cure diseases like jaundice, cholelithiasis caused by dampness-heat of gallbladder and liver, and so on. It comes from the dried tuberous roots of C. kwangsiensis (Guiyujin), C. longa (Huangyujin), C. phaeocaulis (Lvyujin) and C. wenyujin (Wenyujin). Though there are differences in chemical compositions and pharmacological activities among the four species of Yujin, they have not been differentiated well in clinical application due to their similar morphological characterizations.

AIM OF THE STUDY

In this study, the four species of Yujin were rapidly and accurately discriminated. The potential volatile markers for varietal recognition were identified.

MATERIALS AND METHODS

Attenuated total reflection fourier transformed infrared (ATR-FTIR) spectroscopy combined with chemometrics was used to rapidly discriminate the four species of Yujin. Headspace-gas chromatography-mass spectrometry (HS-GC-MS) technology coupled with chemometrics was employed to characterize volatile profiling, differentiate species and select potential markers for varietal recognition of Yujin.

RESULTS

By applying PCA (principal components analysis) and HCA (hierarchical cluster analysis), HS-GC-MS realized complete differentiation of the four species of Yujin, while ATR-FTIR only recognized Guiyuijin. Back propagation neural network (BP-NN), KNN (K-nearest neighbor) and LDA (linear discriminant analysis) models based on spectral data achieved 100% discriminant accuracies. Support vector machines (SVM), KNN and PLS-DA (partial least square discriminant analysis) models based on volatile compounds also realized 100% discriminant accuracies. Additionally, the potential volatile markers for varietal recognition of Yujin were screened using PLS-DA, including 2 for Guiyujin, 6 for Lvyujin, 9 for Wenyujin and 13 for Huangyujin.

CONCLUSIONS

The present study developed reliable methods for the varietal discrimination and volatile compounds characterization of Yujin, which will provide references for its quality control and clinical efficacy.