Correlation between macroscopic characteristics and tissue-specific chemical profiling of the root of Salvia miltiorrhiza

Application of PLS-NN model based on mid-infrared spectroscopy in the origin identification of Cornus officinalis

Mid-infrared spectroscopy has been increasingly used as a nondestructive analytical technique in Chinese herbal medicine identification in recent years. In this study, a new chemometric model named as PLS-NN model was proposed based on the mid-infrared spectral data of Cornus officinalis samples from 11 origins. It was realized by combining the partial least squares and neural networks for the identification of the origin of Chinese herbal medicines. First, we extracted features from the spectral data in 3448 bands using the partial least squares method, and extracted 122 components that contained more than 95% of the information. Then, we trained the PLS-NN model by neural network using the extracted components as inputs and the corresponding origin classes as outputs. Finally, based on an external test set, we evaluated the generalization ability of the PLS-NN model using metrics such as accuracy, F1-Score and Kappa coefficient. The results show that the PLS-NN model performs well in all three metrics when compared to models such as Decision trees, Support vector machine, Partial least squares Discriminant analysis, and Naive bayes. The model not only realizes the dimensionality reduction of full-spectrum data and improves the training efficiency of the model, but also has higher accuracy compared with the full-spectrum data model. The PLS-NN model was applied to identify the origin of Cornus officinalis with an accuracy of 91.9%.

Unveiling the spatial distribution and molecular mechanisms of terpenoid biosynthesis in Salvia miltiorrhiza and S. grandifolia using multi-omics and DESI-MSI

Salvia miltiorrhiza and S. grandifolia are rich in diterpenoids and have therapeutic effects on cardiovascular diseases. In this study, the spatial distribution of diterpenoids in both species was analyzed by a combination of metabolomics and mass spectrometry imaging techniques. The results indicated that diterpenoids in S. miltiorrhiza were mainly abietane-type norditerpenoid quinones with a furan or dihydrofuran D-ring and were mainly distributed in the periderm of the roots, e.g. cryptotanshinone and tanshinone IIA. The compounds in S. grandifolia were mainly phenolic abietane-type tricyclic diterpenoids with six- or seven-membered C-rings, and were widely distributed in the periderm, phloem, and xylem of the roots, e.g. 11-hydroxy-sugiol, 11,20-dihydroxy-sugiol, and 11,20-dihydroxy-ferruginol. In addition, the leaves of S. grandifolia were rich in tanshinone biosynthesis precursors, such as 11-hydroxy-sugiol, while those of S. miltiorrhiza were rich in phenolic acids. Genes in the upstream pathway of tanshinone biosynthesis were highly expressed in the root of S. grandifolia, and genes in the downstream pathway were highly expressed in the root of S. miltiorrhiza. Here, we describe the specific tissue distributions and mechanisms of diterpenoids in two Salvia species, which will facilitate further investigations of the biosynthesis of diterpenoids in plant synthetic biology.

Rapid quality evaluation of four kinds of Polygoni Multiflori Radix Praeparata by electronic eye combined with chemometrics

INTRODUCTION

Polygonum multiflorum Thunb., a widely used herbal medicine, has trouble with the hepatic adverse effect. Processing is an effective method to increase potency and reduce the adverse effects of herbal medicines. Polygoni Multiflori Radix Praeparata (PMRP), the decoction pieces processed from raw material, is widely consumed in clinical practice in many countries. The quality control of PMRP has attracted more and more attention worldwide.

OBJECTIVE

A simple and rapid quality evaluation method using an electronic eye (E-eye) combined with chemometrics was proposed for controlling the quality of PMRP.

MATERIALS AND METHODS

The semi-quantitative and quantitative data of 105 major components in 128 batches of PMRP samples obtained by three different analysis instruments were fused to investigate the correlation with the dynamic exterior colour determined by E-eye. The correlation between exterior colour and chemical fusion dataset was investigated by orthogonal partial least squares discriminant analysis (OPLS-DA) and partial least squares regression (PLSR). According to the results of correlation analysis, the color parameters of high-quality PMRP was set.

RESULTS

Correlation studies by chemometrics revealed that the exterior colour depth was significantly correlated with 32 components [variable importance in the projection (VIP) > 1.0, p < 0.05]. The colour parameter of E * ab located in the range of 46.69-51.66 can be used easily, rapidly, and in an environment-friendly way to determine whether the PMRP sample has reached sufficient processing time with good quality.

CONCLUSION

This study adds some scientific information to our understanding of traditional medicine while contributing an alternative method for assessing the quality of other decoction pieces.

Origin identification of Cornus officinalis based on PCA-SVM combined model

Infrared spectroscopy can quickly and non-destructively extract analytical information from samples. It can be applied to the authenticity identification of various Chinese herbal medicines, the prediction of the mixing amount of defective products, and the analysis of the origin. In this paper, the spectral information of Cornus officinalis from 11 origins was used as the research object, and the origin identification model of Cornus officinalis based on mid-infrared spectroscopy was established. First, principal component analysis was used to extract the absorbance data of Cornus officinalis in the wavenumber range of 551~3998 cm-1. The extracted principal components contain more than 99.8% of the information of the original data. Second, the extracted principal component information was used as input, and the origin category was used as output, and the origin identification model was trained with the help of support vector machine. In this paper, this combined model is called PCA-SVM combined model. Finally, the generalization ability of the PCA-SVM model is evaluated through an external test set. The three indicators of Accuracy, F1-Score, and Kappa coefficient are used to compare this model with other commonly used classification models such as naive Bayes model, decision trees, linear discriminant analysis, radial basis function neural network and partial least square discriminant analysis. The results show that PCA-SVM model is superior to other commonly used models in accuracy, F1 score and Kappa coefficient. In addition, compared with the SVM model with full spectrum data, the PCA-SVM model not only reduces the redundant variables in the model, but also has higher accuracy. Using this model to identify the origin of Cornus officinalis, the accuracy rate is 84.8%.

HPLC-DVD combined with chemometrics to analyze the correlation between the Q-marker content and color of Corni Fructus

Although Corni Fructus (CF) is a fruit with great economic value and development potential in medicine and food, too much reliance on personal experience for quality evaluation seriously limits the trading and circulation of CF. In the present study, through the research on the correlation between the chemical composition and the appearance color, a standard colorimetric card related to CF quality was established, which simplified the quality evaluation process and improved the accuracy of the visual evaluation of CF. Firstly, a total of 29 batches of CF from different places were collected. Then, "imread" in the MATLAB software was used to convert the color of all samples into RGB values, and HPLC-DVD was used to measure the content of the main chemical components in CF. Thereafter, the correlation between the content and color was studied by using MLR, BP-ANNs and SVM chemometric tools to screen the Q-marker of CF, which was further confirmed by in vivo and in vitro experiments. Finally, the Q-marker standard colorimetric card with the best fitting degree is established according to the prediction model. Thus, this study provides an auxiliary reference for the color evaluation of CF and a reference for the standardization and quantification of the macro characteristics of traditional Chinese medicine and food.

The Potential Use of Herbal Fingerprints by Means of HPLC and TLC for Characterization and Identification of Herbal Extracts and the Distinction of Latvian Native Medicinal Plants

The growing market of herbal medicines, the increase in international trade in Latvia, and the lack of adequate analytical methods have raised the question of the potential use of herbal fingerprinting methods. In this study, high-performance liquid chromatography (HPLC) and thin layer chromatography (TLC) methods were developed for obtaining chromatographic fingerprints of four taxonomically and evolutionary different medicinal plants (Hibiscus sabdariffa L., Calendula officinalis L., Matricaria recutita L., Achillea millefolium L.). Retention time shifting, principal component analysis (PCA), hierarchical cluster analysis (HCA), and orthogonal projections to latent structures (OPLS) analysis were used to improve and analyze the obtained fingerprints. HPLC data detection at 270 nm was determined superior to 360 nm for the distinction of medicinal plants and used data alignment method significantly increased similarity between samples. Analyzed medicinal plant extracts formed separate, compact clusters in PCA, and the results of HCA correlated with the evolutionary relationships of the analyzed medicinal plants. Herbal fingerprinting using chromatographic analysis coupled with multivariate analysis has a great potential for the identification of medicinal plants as well as for the distinction of Latvian native medicinal plants.

Correlation analysis of physicochemical properties with anti-inflammatory activity of Andrographis paniculata (Burm.f.) Nees based on HPLC-DAD, colorimeter and multivariate statistics: A comprehensive quality evaluation strategy

Andrographis paniculata (Burm.f.) Nees is an essential traditional herbal medicine with various bioactivities in Asian countries. The quality of herbal medicines directly affects its clinical efficacy, so a comprehensive strategy, including color assay, chemical profiles, quantitative analysis, and anti-inflammatory activity assay, is constructed to evaluate the quality of A. paniculata in this paper. Here, 16 batches of commercial A. paniculata were collected, and there were noticeable differences in appearance, chemical compounds, and bioactivity among batches. Principal component analysis (PCA) indicated the color and diterpenoid lactones could be used to classify A. paniculat. And then, correlation analysis found the batches with greener color have higher contents of diterpenoid lactones and more efficient anti-inflammatory activity. Based on the results above, the partial least squares (PLS) regression models were finally established to predict the contents of diterpenoid lactones using the color assay data. All diterpenoid lactones models showed good performance, especially neoandrographolide. Notably, PLS regression models were first used for the nondestructive quantitative analysis of A. paniculata. This comprehensive quality evaluation strategy can theoretically elucidate the relationship between good appearance, high contents of diterpenoid lactones, and superior bioactivity of A. paniculata, which is meaningful for its quality control and evaluation. It also laid a theoretical basis for appearance and bioactivity evaluations of high-quality traditional herbal medicine.

Functional Redox Proteomics Reveal That Salvia miltiorrhiza Aqueous Extract Alleviates Adriamycin-Induced Cardiomyopathy via Inhibiting ROS-Dependent Apoptosis

The anticancer agent adriamycin (ADR) has long been recognized to induce a dose-limiting cardiotoxicity, while Salvia miltiorrhiza (SM) is a Chinese herb widely used for the treatment of cardiovascular disorders and its aqueous extract (SMAE) has shown anticancer as well as antioxidant effects. In the current study, we aimed at investigating the synergistic effect and potent molecular mechanisms of SMAE with a focus on the cardioprotective benefit observed under ADR adoption. Histopathological analysis indicated that SMAE could substantially alleviate cardiomyopathy and cell apoptosis caused by ADR. Meanwhile, the two-dimensional electrophoresis (2-DE) oxyblots demonstrated that SMAE treatment could effectively reduce carbonylation of specific proteins associated with oxidative stress response and various metabolic pathways in the presence of ADR. SMAE application also showed protective efficacy against ADR-mediated H9c2 cell death in a dose-dependent manner without causing any cytotoxicity and significantly attenuated the reactive oxygen species production. Particularly, the simultaneous administration of ADR and SMAE could remarkably suppress the growth of breast cancer cells. We also noticed that there was a marked upregulation of detoxifying enzyme system in the presence of SMAE, and its exposure also contributed to an increase in Nrf2 and HO-1 content as well. SMAE also amended the ERK/p53/Bcl-xL/caspase-3 signaling pathways and the mitochondrial dysfunction, which eventually attribute to apoptotic cathepsin B/AIF cascades. Correspondingly, both the ERK1/2 inhibitor (U0126) and pan-caspase inhibitor (Z-VAD-FMK) could at least partially abolish the ADR-associated cytotoxicity in H9c2 cells. Collectively, these results support that ROS apoptosis-inducing molecule release is closely involved in ADR-induced cardiotoxicity while SMAE could prevent or mitigate the causative cardiomyopathy through controlling multiple targets without compromising the efficacy of chemotherapy.

Distribution Patterns for Bioactive Constituents in Pericarp, Stalk and Seed of Forsythiae Fructus

Forsythiae Fructus (FF) is a widely used folk medicine in China, Japan, and Korea. The distribution of bioactive constituents throughout the fruit segments has rarely been addressed, although mounting evidence suggests that plant secondary metabolites are synthesized and distributed regularly. The phytochemical profiles of three segments of FF (pericarp, stalk and seed) were firstly revealed by liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based quantitative analysis of twenty-one bioactive constituents, including three phenylethanoid glycosides, five lignans, eight flavonoids, and five phenolic acids to explore the spatial distribution of bioactive constituents. Furthermore, the hierarchical clustering analysis (HCA) and one-way analysis of variance (one-way ANOVA) were conducted to visualize and verify the distribution regularity of twenty-one analytes among three segments. The results showed that phytochemical profiles of the three segments were similar, i.e., phenylethanoid glycosides covering the most part were the predominant compounds, followed by lignans, flavonoids and phenolic acids. Nevertheless, the abundance of twenty-one bioactive constituents among three segments was different. Specifically, phenylethanoid glycosides were highly expressed in the seed; lignans were primarily enriched in the stalk; flavonoids were largely concentrated in the pericarp, while the contents of phenolic acids showed no much difference among various segments. The research improves our understanding of distribution patterns for bioactive constituents in FF, and also complements some scientific data for further exploring the quality formation mechanism of FF.