Phytochemical Analysis最新文献

Introduction: Galls, which are abnormal or protruding tissues, form when insects bite plant cells and serve as evidence for understanding plant-insect interactions.

Objectives: This study is aimed at understanding the interactions between Chrysanthemum species and insects at the metabolomic level and to reveal the metabolic changes induced by insect galls.

Methodology: This study employed liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS), along with multivariate statistics and pathway enrichment, for metabolomic profiling of Chrysanthemum glabriusculum, including gall-infected and gall-free leaves, and reported the gall phenomenon in Chrysanthemum species for the first time.

Results: LC-MS metabolomics analysis identified 105 marker metabolites, with 61 upregulated and 42 downregulated. Organic acids were the most abundant (20.00%), followed by carbohydrates (16.19%) and flavonoids (14.29%). KEGG analysis revealed significant pathway enrichment in flavone and flavonol biosynthesis, the TCA cycle, and galactose metabolism (p < 0.05). GC-MS metabolomics analysis revealed 27 volatile secondary metabolites, predominantly terpenoids (16 types), followed mainly by alcohol (4 types) and ketone compounds (three types). VIP > 1 analysis revealed 13 differentially signature metabolites; gall tissue (CgCa) presented elevated levels of β-phellandrene, camphene, and 1,8-Cineole, whereas γ-Muurolene, α-Farnesene, and Copaene were downregulated in CgCa.

Conclusions: During gall induction, C. glabriusculum plays an important role in energy metabolism through the regulation of key metabolic pathways, such as galactose metabolism and the TCA cycle, and their products; moreover, by regulating the biosynthesis of flavonoids and flavonols and the corresponding accumulation of secondary metabolites (terpenoids, ketones, and alcohols), it defends against insect-induced galls.

The Rhododendri Daurici Folium (RDF) represents the desiccated foliage of Rhododendron dauricum L., belonging to the Rhododendron family. RDF abounds in diverse chemical elements, predominantly flavonoids, volatile oils, phenols, coumarin, and lignans. RDF functions as a cough and expectorant agent, primarily employed in the management of acute and chronic bronchitis and pharyngitis. RDF is also known for its pharmacological properties, including antibacterial, cardiotonic, antihypertensive, and anticancer properties. RDF is frequently utilized as a potent ingredient in Yingshanhong tablets, compound RDF syrup, XiaoKeChuan syrup, and various traditional Chinese medicinal concoctions, and it holds significant importance in clinical settings. This article's data were sourced from publications including PubMed, CNCK, SCI-HUB, Web of Science, Scopus, Chinese Pharmacopoeia, Chinese Dictionary of Traditional Chinese Medicine, Chinese Flora, and associated studies. The present document provides a comprehensive examination of the herbal properties, pharmacological effects, chemical makeup, clinical application, quality assurance, and safety assessments of RDF, serving as a guide for advancing and applying traditional Chinese medicine RDF.

Introduction: The present study focuses on the application of near-infrared (NIR) spectroscopy, combined with mid-infrared (MIR) spectroscopy, to predict the levels of total polyphenols in peanut seed samples, highlighting innovative methodologies and advanced spectroscopic techniques.

Objective: To develop and validate accurate predictive models for quantifying total polyphenols in peanut seeds using NIR and MIR spectroscopy combined with advanced statistical approaches.

Material and methods: Partial least squares (PLS), competitive adaptive reweighted sampling PLS low-level (CARS-PLS Fusion_LL), and mid-level (CARS-PLS Fusion_ML) techniques were employed for model development. The total polyphenols were quantified using a spectrophotometer, and the model's efficacy was evaluated using calibration correlation coefficients (R_c), prediction correlation coefficients (R_p), root mean square error of cross-validation (RMSECV), root mean square error of prediction (RMSEP), and residual predictive deviation (RPD).

Results: The CARS-PLS Fusion_ML Fusion method demonstrated high precision, with determination coefficients for prediction (R_p = 0.9818) and calibration (R_c = 0.9819). The RMSECV and RMSEP were calculated at 1.62 and 1.80, respectively, with an RPD value of 7.36.

Conclusion: In conclusion, a precise method for measuring the amounts of polyphenols in peanut seeds is provided by integrating NIR and MIR spectroscopy with advanced statistical methods. These findings underscore the potential of NIR and MIR spectroscopy, combined with advanced data fusion, for non-destructive, rapid, and cost-effective quantification of total polyphenols in peanuts, offering practical applications in the food industry for quality control and safety assessment.

Objective: An integrated strategy was utilized in this study to comprehensively characterize the chemical composition of Gegen-Qinlian Decoction (GQD).

Methods: The major components of GQD (total flavonoids, total saponins, total alkaloids, carbohydrates, and proteins) were determined firstly using colorimetric methods, while free amino acids and trace elements were analyzed by automatic amino acid analyzer and inductively coupled plasma-mass spectrometry (ICP-MS), respectively. After that, the small-molecule components of GQD were characterized using ultra-high performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (UHPLC-QTOF-MS/MS). Furthermore, a quantitative method was established for 26 representative compounds determination simultaneously using ultra-high performance liquid chromatography coupled with triple-quadrupole linear ion-trap tandem mass spectrometry (UHPLC-QTRAP-MS/MS) in multiple reaction monitoring (MRM) mode.

Results: The accurate content and proportion of the major constituents in GQD were determined for the first time. A total of 230 compounds were characterized from GQD, of which four undescribed alkaloids were identified initially by their tandem mass data analyses based on mass spectral fragmentation pathways of isoquinoline alkaloids. A quantitative method was established to determine 26 representative compounds, and validated through linearity, precision, repeatability, stability, and recovery. The total content of the 26 compounds accounted for 27.81%, of which baicalin being the most abundant was up to 107.26 ± 1 mg/g.

Conclusions: The present study achieved a comprehensive characterization of constituents in GQD, laying the foundation for elucidating the active components, mechanism, and the quality control of GQD, offering a valuable analytical framework for research on other traditional Chinese medicine (TCM) formulas.

Introduction: Fruit-derived medicinal materials (FDMM) are extensively utilized in daily life, yet the market is beset by substantial variety confusion, which undermines consumer rights and well-being. Consequently, accurate identification of these materials is essential for guaranteeing their quality, effectiveness, and safety.

Objectives: This study aimed to combine attenuated total reflection-Fourier transform infrared spectroscopy (ATR-FTIR) and machine learning (ML) techniques to differentiate and identify 55 kinds of FDMM.

Materials and methods: A total of 861 sample batches were collected, with 721 allocated for model establishment and 140 for independent validation. A PLS-DA model alongside nine machine learning algorithms-namely support vector machine (SVM), tree, K-nearest neighbor (KNN), discriminant, ensemble, support vector machine kernel (SVMK), logistic regression kernel (LRK), naive Bayes (NB), and neural network (NN)-were constructed. Considering both accuracy and computational efficiency, the optimal model was selected and evaluated in terms of its accuracy, precision, recall, and F1-score. The optimal model was further validated using 140 newly collected samples to ensure its long-term stability after several months.

Results: Among the 10 classification models, the KNN model showed exceptional classification capability, with all evaluation metric exceeding 0.98. The KNN model was validated by the new 140 samples with a prediction accuracy of 85.7%, confirming its capability in distinguishing most FDMM.

Conclusion: The application of ATR-FTIR technology combined with the robust classification capabilities of ML models enabled rapid and accurate differentiation and identification of 55 FDMM, which contributed to ensuring their quality.

Background: Talinum paniculatum root (pseudo ginseng in Chinese) is a widely distributed medicinal plant material in Asia, Africa, and America. However, its chemistry remains poorly understood nowadays.

Methods: Fresh Talinum paniculatum root was treated for the preparation of a lyophilized aqueous extract. The extract thereafter was subjected to qualitative and quantitative analysis using the library-aided ultra-high-performance liquid chromatography-quadrupole-Exactive-Orbitrap-tandem mass spectrometry (UHPLC-Q-Exactive-Orbitrap-MS/MS) technology.

Results: Based on MS/MS elucidation and comparison with the authentic standards in the library of UHPLC-Q-Exactive-Orbitrap-MS/MS apparatus, 22 compounds were accurately identified. Information retrieval suggested that 18 compounds belonged to "unexcavated" ones, which were found in the plant for the first time. Subsequently, all 22 compounds (including 18 "unexcavated" ones) were further quantified using the corresponding linear regression equations of authentic standards. All 22 compounds exhibited different contents from each other in the quantitative analysis. Particularly, synephrine had the highest content (8.159 ± 1.443 mg/g extract), and α-mangostin showed the lowest content (0.001 ± 0.000 mg/g extract), while chikusetsusaponin Iva displayed a moderate content (0.737 ± 0.274 mg/g extract).

Conclusion: On the basis of these results and relevant principles, synephrine, N-trans-feruloyltyramine, and chikusetsusaponin Iva are recommended as the anti-counterfeiting Q-markers of T. paniculatum root. These findings will help to understand the substance basis of the traditional medicinal functions of T. paniculatum root and to find a suitable quality-control method.

Introduction: Natural products are among the main ingredients of medicinal plants, and strategies that enhance their bioactive profile by elemental supplementation have emerged recently. Manganese is involved in various plant secondary metabolism pathways among different micronutrients.

Objectives: This study investigated the effects of ionic (MnSO₄, MnCl₂), bulk (Mn₂O₃), and nano (Mn₂O₃-NP) manganese forms on Artemisia annua's secondary metabolism. It also studied the influence of the application method (seed priming vs. seed priming + foliar).

Methods: For this purpose, untargeted UHPLC-QTOF-HRMS metabolomics was conducted.

Results: The findings revealed that Mn form and application method significantly influenced the metabolomic profile and secondary metabolite composition of the leaves and inflorescences, regardless of tissue type. Metabolomic profiling using untargeted analysis and multivariate statistical tools (PCA, PLS-DA, and VIP scoring) showed significant variation in bioactive compound accumulation. Mn₂O₃ and MnCl₂ were most effective in enhancing nitrogen-containing compounds, phenylpropanoids, flavonoids, and terpenoids, possibly via ROS-mediated biosynthesis. Mn₂O₃ strongly increased lignans, while Mn₂O₃-NP showed the highest artemisinin accumulation (3.2-3.7 mg g^-1 FW) compared to MnCl₂ and Mn₂O₃ (0.2-1.7 mg g^-1 FW). Key pharmacological metabolites such as vincristine, Momilactone A, and terbinafine were identified by VIP2 analysis.

Conclusion: Mn₂O₃-NP application through seed priming is a promising and cost-effective approach to modulate bioactive metabolite production in Artemisia annua.

Introduction: In this study, apigenin-7-O-β-glucoside (AGL) was isolated from Nepeta nuda; also, rosmarinic acid (RA) was isolated from N. aristata and N. nuda.

Objectives: The aim of this study is to investigate the enzyme inhibitory, DNA protective, and antibacterial effects of AGL and RA isolated from two Nepeta species.

Material and methods: 1D and 2D NMR spectra and an MS chromatogram were recorded to identify AGL and RA. The antibacterial and DNA protection activities, enzyme inhibition, and kinetics investigated of AGL and RA. Molecular interactions, molecular dynamics (MD) simulations, molecular mechanics Poisson-Boltzmann surface area (MM-PBSA) calculations, density functional theory (DFT), molecular electrostatic potential (MEP) analyses, and prediction of activity spectra for substances (PASS) predictions for RA and AGL were investigated for the first time to evaluate the activity results.

Results: In this context, the inhibitory properties of AGL were higher in urease, α-amylase, and tyrosinase, whereas RA has a higher inhibitory activity on lipase, CA, and urease. In addition, AGL and RA showed effective antimicrobial activity against Staphylococcus aureus, while it also was effective DNA and deoxyribose protective activities. The stability of the complex formed by lipase, CA, and urease with RA and by tyrosinase and α-amylase with AGL was determined by MD simulations, and the energy results of RA were evaluated by MM-PBSA analysis. The DFT, MEP analysis, and PASS prediction showed that AGL and RA have a soft structure and can easily exchange electrons.

Conclusion: According to the results obtained from the current study, AGL and RA were explored as a drug model.

Introduction: Gentiana rigescens Franch. (Jianlongdan) and other Gentiana species (Longdan), including G. manshurica, G. scabra, and G. triflora, are valuable medicinal plants used in traditional Chinese medicine. However, their similar appearances and potential for market misidentification necessitate a rapid and accurate identification method.

Objective: This study aimed to develop a rapid identification method using Proofman-LMTIA technology to accurately identify Jianlongdan and prevent misidentification in the market.

Methods: Specific primers and Proofman probes were designed based on the differential region of Internal Transcribed Spacer 2 (ITS2) sequence between Jianlongdan and Longdan. The method's specificity, sensitivity, detection limit, and stability were evaluated, and its applicability to commercial gentian products was tested.

Results: The developed Proofman-LMTIA method demonstrated high specificity and sensitivity for Jianlongdan at an optimal reaction temperature of 56°C, with a detection limit of 10 pg/μL and the ability to identify 0.1% Jianlongdan in mixtures. The method showed good stability and was successfully applied to market samples.

Conclusion: The Proofman ladder-shape melting temperature isothermal amplification (Proofman-LMTIA) method offers a rapid, specific, and cost-effective tool for the authentication of Jianlongdan, crucial for ensuring the quality of herbal medicine and protecting consumers from misidentification and potential adulteration.

Background: Berberis cortex is a typical multi-origin species in Tibetan medicine, with varying medicinal effects among different species. Establishing a rapid and accurate identification method for the major species of Tibetan medicinal B. cortex, including Berberis vernae Schneid. (SY), Berberis diaphana Maxim. (XH), Berberis kansuensis Schneid. (GS), and Berberis dictyophylla Franch. (CHZ), is conducive to the quality control of B. cortex.

Methods: Site-specific PCR visualization using SYBR Green I was developed based on rbcL SNP sites for SY, GS, and CHZ. For XH, which cannot be differentiated through rbcL and other barcoding SNP sites, RAPD-PCR methodology was employed to screen for species-specific sequences. A site-specific amplification visualization system was subsequently developed based on the identified sequence.

Results: The developed site-specific PCR visualization systems demonstrated excellent sensitivity, with all systems capable of detecting genomic DNA at concentrations as low as 100 fg. These systems were employed to analyze 16 batches of actual B. cortex samples. The analysis revealed that four samples were identified as SY, six samples as GS, two samples as CHZ, and three samples as XH. All results were concordant with sequencing data. One remaining negative sample was confirmed through sequencing as adulterated with Phellodendri Chinensis Cortex. Further authentication of 10 batches of Tibetan patent medicines containing B. cortex revealed that 2 batches contained both SY and GS, one batch contained both SY and CHZ, three batches contained exclusively GS, and three batches contained XH.

Conclusion: A site-specific PCR fluorescence visual identification system has been developed for the authentication of four major B. cortex species, enabling accurate identification of botanical origins in both B. cortex crude materials and Berberis-containing Tibetan patent medicines.