Discrimination of turmeric from different origins in China by MRM-based curcuminoid profiling and multivariate analysis

Distinguishing features of Prunus humilis, P. japonica, P. pedunculata seeds and their adulterant based on DNA barcoding, morphological characterization, and chemical profiles

Pruni Semen, the dried ripe seed of Prunus humilis, P. japonica, or P. pedunculata as recorded in the Chinese Pharmacopoeia, has been widely used in pharmaceutical and food industries. The adulteration of the marketed product with morphologically similar plants of the same genus has led to variable product quality and clinical effectiveness. This study systematically investigated the phylogenetic relationships, morphological traits, and chemical profiles of 37 Pruni Semen samples from planting bases, markets, and fields. DNA barcoding could successfully distinguish the genuine and counterfeit Pruni Semen, and the results indicated that there was almost no authentic Pruni Semen available in the market. The samples were divided into "big seed" (P. pedunculata and P. salicina seeds) and "small seed" (P. humilis, P. japonica, P. tomentosa, and P. avium seeds) categories based on morphology results. The notable discrepancy in the chemical characteristics of "big seed" and "small seed" was that "small seeds" were rich in flavonoids and low in amygdalin, whereas "big seeds" were the opposite. Furthermore, principal component analysis and clustered heatmap analysis verified the distinguishing features of "big seed" and "small seed" based on morphological and chemical characteristics. This study suggested that a combination of DNA barcoding and morphological and chemical characteristics can aid in the identification and quality evaluation of authentic and adulterated Pruni Semen. These findings may help standardize Pruni Semen available in the market and protect the rights and interests of customers.

Effects of nanoscale zinc oxide treatment on growth, rhizosphere microbiota, and metabolism of Aconitum carmichaelii

Trace elements play a crucial role in the growth and bioactive substance content of medicinal plants, but their utilization efficiency in soil is often low. In this study, soil and Aconitum carmichaelii samples were collected and measured from 22 different locations, followed by an analysis of the relationship between trace elements and the yield and alkaloid content of the plants. The results indicated a significant positive correlation between zinc, trace elements in the soil, and the yield and alkaloid content of A. carmichaelii. Subsequent treatment of A. carmichaelii with both bulk zinc oxide (ZnO) and zinc oxide nanoparticles (ZnO NPs) demonstrated that the use of ZnO NPs significantly enhanced plant growth and monoester-type alkaloid content. To elucidate the underlying mechanisms responsible for these effects, metabolomic analysis was performed, resulting in the identification of 38 differentially expressed metabolites in eight metabolic pathways between the two treatments. Additionally, significant differences were observed in the rhizosphere bacterial communities, with Bacteroidota and Actinobacteriota identified as valuable biomarkers for ZnO NP treatment. Covariation analysis further revealed significant correlations between specific microbial communities and metabolite expression levels. These findings provide compelling evidence that nanoscale zinc exhibits much higher utilization efficiency compared to traditional zinc fertilizer.

Evaluation of the chemical profile from four germplasms sources of Pruni Semen using UHPLC-LTQ-Orbitrap-MS and multivariate analysis

Pruni Semen, the seed of several unique Prunus plants, is a traditional purgative herbal material. To determine the authentic sources of Pruni Semen, 46 samples from four species were collected and analyzed. Ten compounds including multiflorin A (Mul A), a notable purative compound, were isolated and identified by chemical separation and nuclear magnetic resonance spectroscopy. Seventy-six communal components were identified by ultra-high performance liquid chromatography with linear ion trap-quadrupole Orbitrap mass spectrometry, and acetyl flavonoid glycosides were recognized as characteristic constituents. The flavonoids were distributed in the seed coat and cyanogenic glycosides in the kernel. Based on this, methods for identifying Pruni Semen from different sources were established using chemical fingerprinting, quantitative analysis of the eight principal compounds, hierarchical cluster analysis, principal component analysis, and orthogonal partial least squares discriminant analysis. The results showed that the samples were divided into two categories: one is the small seeds from Prunus humilis (Ph) and Prunus japonica (Pj), and the other is the big seeds from Prunus pedunculata (Pp) and Prunus triloba (Pt). The average content of Mul A was 3.02, 6.93, 0.40, and 0.29 mg/g, while the average content of amygdalin was 18.5, 17.7, 31.5, and 30.9 mg/g in Ph, Pj, Pp, and Pt, respectively. All the above information suggests that small seeds might be superior sources of Pruni Semen. This is the first comprehensive report on the identification of chemical components in Pruni Semen from different species.

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Chemical constituents of Pruni semen from four Prunus species were compared.

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Acetyl flavonoid glycosides were identified as the characteristic components.

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Flavonoids were present in the seed coat and cyanogenic glycosides in the kernel.

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The content of acetyl flavonoid in small seeds is significant higher than those in big ones.

Spectrum-Effect Relationship Between Antioxidant and Anti-inflammatory Effects of Banxia Baizhu Tianma Decoction: An Identification Method of Active Substances With Endothelial Cell Protective Effect

Banxia Baizhu Tianma decoction (BBTD), a six-herb Chinese medicine formula first described approximately 1732 AD, is commonly prescribed for Hypertension with Phlegm-dampness Stagnation (HPDS) as an adjuvant therapy in China. Obesity is an important risk factor for the increasing prevalence of hypertension year by year in China. In Traditional Chinese medicine, obesity is often differentiated as the syndrome of excessive phlegm-dampness.Vascular endothelial cell injury plays an important role in the development and occurrence of HPDS. In this study, the protective effects of 18 batches of BBTD samples from different origins on HUVEC cells were evaluated, including antioxidant and anti-inflammatory activities. Ultrahigh performance liquid chromatography (UPLC) was used to establish fingerprints, and combined with pharmacodynamic indexes, the protective components of BBTD on endothelial cells were analyzed. Antioxidant and anti-inflammatory activities were evaluated by ROS and Hs-CRP models, respectively. Hierarchical cluster analysis (HCA) and Bivariate correlation analysis (BCA) were used to investigate the potential correlation between chemical components and endothelial cell protection. The results indicated that BBTD could reduce ROS and hs-CRP levels in HUVEC cells, and the pharmacological activities in 18 batches of BBTD samples were significantly different. The results of BCA indicated that Gastrodin, Liquiritin, Hesperidin, Isoliquiritin, Hesperetin, and Isoliquiritigenin might be the active constituents to activate ROS and suppress hs-CRP as determined by spectrum-effect relationships. The antioxidant and anti-inflammatory activities of the 6 components at different concentration were verified, and the results showed that all of them had good antioxidant and anti-inflammatory activities in a concentration-dependent manner. This study showed that activity determination and spectral correlation can be used to search for active substances in Chinese medicine formula and provide data support for quality control of Traditional Chinese medicine (TCM).

Machine learning classification of origins and varieties of Tetrastigma hemsleyanum using a dual-mode microscopic hyperspectral imager

A dual-mode microscopic hyperspectral imager (DMHI) combined with a machine learning algorithm for the purpose of classifying origins and varieties of Tetrastigma hemsleyanum (T. hemsleyanum) was developed. By switching the illumination source, the DMHI can operate in reflection imaging and fluorescence detection modes. The DMHI system has excellent performance with spatial and spectral resolutions of 27.8 μm and 3 nm, respectively. To verify the capability of the DMHI system, a series of classification experiments of T. hemsleyanum were conducted. Captured hyperspectral datasets were analyzed using principal component analysis (PCA) for dimensional reduction, and a support vector machine (SVM) model was used for classification. In reflection microscopic hyperspectral imaging (RMHI) mode, the classification accuracies of T. hemsleyanum origins and varieties were 96.3% and 97.3%, respectively, while in fluorescence microscopic hyperspectral imaging (FMHI) mode, the classification accuracies were 97.3% and 100%, respectively. Combining datasets in dual mode, excellent predictions of origin and variety were realized by the trained model, both with a 97.5% accuracy on a newly measured test set. The results show that the DMHI system is capable of T. hemsleyanum origin and variety classification, and has the potential for non-invasive detection and rapid quality assessment of various kinds of medicinal herbs.

Geographic Origin Discrimination of Millet Using Vis-NIR Spectroscopy Combined with Machine Learning Techniques

Millet is a primary food for people living in the dry and semi-dry regions and is dispersed within most parts of Europe, Africa, and Asian countries. As part of the European Union (EU) efforts to establish food originality, there is a global need to create Protected Geographical Indication (PGI) and Protected Designation of Origin (PDO) of crops and agricultural products to ensure the integrity of the food supply. In the present work, Visible and Near-Infrared Spectroscopy (Vis-NIR) combined with machine learning techniques was used to discriminate 16 millet varieties (n = 480) originating from various regions of China. Five different machine learning algorithms, namely, K-nearest neighbor (K-NN), Linear discriminant analysis (LDA), Logistic regression (LR), Random Forest (RF), and Support vector machine (SVM), were used to train the NIR spectra of these millet samples and to assess their discrimination performance. Visible cluster trends were obtained from the Principal Component Analysis (PCA) of the spectral data. Cross-validation was used to optimize the performance of the models. Overall, the F-Score values were as follows: SVM with 99.5%, accompanied by RF with 99.5%, LDA with 99.5%, K-NN with 99.1%, and LR with 98.8%. Both the linear and non-linear algorithms yielded positive results, but the non-linear models appear slightly better. The study revealed that applying Vis-NIR spectroscopy assisted by machine learning technique can be an essential tool for tracing the origins of millet, contributing to a safe authentication method in a quick, relatively cheap, and non-destructive way.

Quantitative proteomics of plasma and liver reveals the mechanism of turmeric in preventing hyperlipidemia in mice

Hyperlipidemia is manifested by abnormal levels of circulating lipids and may lead to various cardiovascular diseases. Studies have demonstrated that turmeric supplemented in food can effectively prevent hyperlipidemia. The aim of this study is to elucidate the underlying mechanism. 27 male C57BL/6J mice were randomly divided into three groups, which were fed with a standard diet, a high-fat diet and a high-fat diet supplemented with turmeric powder (2.0% w/w), respectively. After eight weeks of feeding, turmeric intervention significantly reduced the plasma TC, TG, and LDL-C levels and the LDL-C/HDL-C ratio of mice compared with high-fat diet fed mice. TMT-based proteomic analysis showed that the expression of 24 proteins in mouse plasma and 76 proteins in mouse liver was significantly altered by turmeric, respectively. Bioinformatics analysis showed that differential proteins in the plasma were mainly involved in complement and coagulation cascades and the cholesterol metabolism pathway. The differential proteins in the liver were mainly involved in arachidonic acid metabolism, steroid hormone biosynthesis and the PPAR signaling pathway. Key differential proteins were successfully validated by western blot analysis. This study is the first to reveal the preventive mechanism of turmeric on hyperlipidemia from proteomics. The results showed that dietary turmeric could prevent hyperlipidemia through regulating the expression of proteins in metabolism pathways.

Flavonoid glycosides and other bioactive compounds in Citrus reticulate 'Chachi' peel analysed by tandem mass spectrometry and their changes during storage

The peel of Citrus reticulate 'Chachiennsis' (Chachi) is a well-known functional food with multiple health benefits in Asia. There is an old saying "the longer time Chachi is stored, the better health benefits it has". Is it convincible? What are the critical bioactive compounds in Chachi? To answer these questions, gas chromatography-mass spectrometry (GC-MS) and ultrahigh performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) were used to qualify and quantify the flavonoid glycosides and other bioactive compounds of Chachi with storage time of 5-20 years. Limonene was the representative volatile compound. The level of most volatile compounds decreased along with storage. Sixteen flavonoids glycosides and twenty flavonoids were identified. Nobiletin, hesperitin, tetramethoxy flavone and pentamethoxy flavone were characteristic bioactive compounds for Chachi. Most of them accumulated during 10-year storage, thereafter decreased. Ten years could be the optimal storage time. These results indicated that the old saying should be corrected.

Geographical Discrimination of Curcuma longa L. in Vietnam Based on LC-HRMS Metabolomics

Curcuma longa L. has been used as a food, cosmetic, traditional medicine, and natural dye for a long time in tropical and subtropical regions such as India, China, and Vietnam. Curcuminoids are considered the main bioactive compounds in this plant. This study focuses on metabolites profiling of the rhizome methanolic extract of C longa samples collected in 6 different provinces in Vietnam using liquid chromatography coupled with high-resolution mass spectrometry. The partial least-squares discriminant analysis model was then established to discriminate its metabolomes and identify the chemomarkers that help to distinguish C longa from 6 geographical locations. Consequently, collected samples were segregated into 3 main groups: northern (Lang Son, with typical content of 2 terpenoids), center (Nghe An), and southern highland (Lam Dong, with distinctive profile of 3 curcuminoids). The absolute curcuminoids’ amount was also measured based on the calibration curve of reference standards. The differential metabolites including curcumin, demethoxycurcumin, and bisdemethoxycurcumin were found with the highest range in samples from Lang Son, indicating the excellent quality of turmeric cultivated in this area.

Hydrophilic silicon nanoparticles as a turn-off and colorimetric fluorescent probe for curcuminoids detection in food samples and cell imaging

Hydrophilic fluorescent silicon nanoparticles (SiNPs) with good pH stability, salt-tolerance and anti-photobleaching were for the first time prepared from hydrophobic 3-glycidoxypropyltrimethoxysilane. Employing SiNPs as the fluorescence probe, selective quantification of curcuminoids based on the quenching effect was realized with a linearity of 0.046-7.4 μg/mL and a limit of detection of 17.6 ng/mL. Moreover, in light of fluorescence redshift of SiNPs corresponding to the elevated concentration of curcuminoids, a fluorescence colorimetric method was established based on only one extra probe, i.e. herein SiNPs. Thus, semi-quantification of curcuminoids (0-14.7 μg/mL) was visualized from blue to yellow color. Both the developed quantitative and semi-quantitative probe were successfully applied to determine curcuminoids in various actual food samples. Furthermore, SiNPs possessed low cytotoxicity and succeeded in intracellular curcuminoids imaging. The proposed SiNPs could be a promising fluorescence probe for multiple applications.

Quality markers based on phytochemical analysis and anti-inflammatory screening: An integrated strategy for the quality control of Dalbergia odorifera by UHPLC-Q-Orbitrap HRMS

BACKGROUND

Quality control, key for the clinical application of traditional Chinese medicines (TCMs), should be connected to the authentication and efficacy of TCMs. The heartwood of Dalbergia odorifera has been widely used to treat inflammation-related diseases. However, in the Chinese pharmacopeia, only the total volatile oil, which does not sufficiently reflect the clinical efficacy, is used as a quality control indicator.

PURPOSE

Establishing a "phytochemical-specificity-effectiveness-Q-marker" analytical strategy to improve the quality control of D. odorifera.

METHODS

Combined with biosynthetic pathway analysis, phytochemical compositions identified by UHPLC-Q-Orbitrap HRMS were used to build substantial phytochemical groups and further discover specific Q-markers. Then, lipopolysaccharide-stimulated RAW 264.7 cells were used to screen effective anti-inflammatory ingredients. Finally, a UHPLC-HRMS method was developed and validated to quantify the selected Q-markers in D. odorifera samples.

RESULTS

Along the constructed biosynthetic pathways, 93 phytochemical components were identified in D. odorifera, including 7 chalcones, 13 flavanones, 21 isoflavones, 21 isoflavanones, 3 flavonols, 19 neoflavones, etc. Among them, 31 compounds representing these 6 categories were further evaluated for their anti-inflammatory activities. It revealed that the extract of D. odorifera and nine flavonoids in the noncytotoxic range could alleviated lipopolysaccharide-stimulated inflammation in RAW 264.7 cells by decreasing the production of proinflammatory mediators such as nitric oxide and interleukin-6. Notably, neoflavones, as species-specific components, exhibited superior anti-inflammatory activities among the representative compounds. Finally, 12 Q-markers (butin, liquiritigenin, eriodictyol, melanettin, naringenin, butein, genistein, 4'-hydroxy-4-methoxydalbergione, isoliquiritigenin, 2,4-dihydroxy-5-methoxybenzophenone, medicarpin, and pinocembrin), which reflect specificity and effectiveness, were successfully quantified in 10 batches of samples from different origins. The origins and consistency of D. odorifera could be efficiently discriminated by hierarchical cluster analysis (HCA).

CONCLUSION

The analysis strategy that combines phytochemical analysis with anti-inflammatory screening clarified the therapeutic material basis and discovered Q-markers, which possibly offers a more comprehensive quality assessment of D. odorifera.