Phytochemical Analysis最新文献

Introduction: Identifying the geographical origin of Gastrodia elata Blume contributes to the scientific and rational utilization of medicinal materials. In this study, infrared spectroscopy was combined with machine learning algorithms to distinguish the origin of G. elata BI.

Objective: Realization of rapid and accurate identification of the origin of G. elata BI.

Materials and methods: Attenuated total reflection Fourier transform infrared (ATR-FTIR) spectra and Fourier transform near-infrared (FT-NIR) spectra were collected for 306 samples of G. elata BI.

Samples: Firstly, a support vector machine (SVM) model was established based on the single-spectrum and the full-spectrum fusion data. To investigate whether feature-level fusion strategy can enhance the model's performance, the sequential and orthogonalized partial least squares discriminant analysis (SO-PLS-DA) model was established to extract and combine two types of spectral features. Next, six algorithms were employed to extract feature variables, SVM model was established based on the feature-level fusion data. To avoid complicated preprocessing and feature extraction processes, a residual convolutional neural network (ResNet) model was established after converting the raw spectral data into spectral images.

Results: The accuracy of the feature-level fusion model is better as compared to the single-spectrum model and the fusion model with full-spectrum, and SO-PLS-DA is simpler than feature-level fusion based on the SVM model. The ResNet model performs well in classification but requires more data to enhance its generalization capability and training effectiveness.

Conclusion: Sequential and orthogonalized data fusion approaches and ResNet models are powerful solutions for identifying the geographic origin of G. elata BI.

Introduction: High-quality nucleic acids are the basis for molecular biology experiments. Traditional RNA extraction methods are not suitable for Eleutherococcus senticosus Maxim.

Objective: To find a suitable method to improve the quality of RNA extracted, we modified the RNA extraction methods of Trizol.

Methodology: Based on the conventional Trizol method, the modified Trizol method 1 and modified Trizol method 2 were used as the control for extraction of RNA from E. senticosus Maxim leaves. The modified Trizol method 1 added β-mercaptoethanol on the conventional Trizol method. After RNA was dissolved, a mixed solution of phenol, chloroform, and isoamyl alcohol was added to denature protein and inhibit the degradation of RNA. The modified Trizol method 2 adds PVPP to grind on the basis of modified Trizol method 1, so as to better remove phenols from leaves, and eliminates the step of incubation at -20°C to reduce extraction time and RNA degradation. Chloroform, CTAB, and CH₃COONa were used instead of a phenol, chloroform, and isoamyl alcohol mixed solution to ensure complete separation of nucleic acid from plant tissues and to obtain high-purity RNA.

Results: The research results showed that the quality of RNA extracted by conventional Trizol method, modified Trizol method 1, was incomplete, accompanied with different degrees of contamination of polysaccharides, polyphenols, and DNA. The modified Trizol method 2 could better extract RNA from E. senticosus Maxim leaves. The ratio of A260/A280 was in the range of 1.8-2.0, and the yield of RNA was the highest, which was 1.68 and 1.15 times compared with that by conventional Trizol method and modified Trizol method 1 extraction, respectively. The reverse transcription cDNA was further tested through PCR with the specific primers. The amplified fragments are displayed in clear and bright bands in accordance with the expected size.

Conclusion: The modified Trizol method 2 could better extract RNA from E. senticosus Maxim leaves. High-quality RNA has more advantages in molecular biology study of E. senticosus Maxim.

Introduction: Veratrum alkaloids have gained attention due to their toxic effects and potential pharmaceutical applications, particularly in cancer and cardiology. Over 200 alkaloids are found in species of the Veratrum genus. The alkaloid composition and concentrations can greatly vary in plants depending on factors like species, plant part, location, season, weather, or nutrients.

Objective: This study aims an analytical approach to analyze and quantify Veratrum alkaloids in different plant parts of Veratrum species. The purpose is to contribute essential alkaloid concentration data for future research on the pharmacological and toxicological aspects of Veratrum alkaloids.

Methods: This study focuses on five Veratrum alkaloids (cevadine, jervine, protoveratrine A, veratramine, and veratridine) in three Veratrum species (Veratrum album L., Veratrum californicum Durand, and Veratrum nigrum L.) collected from four German botanical gardens (Dresden, Leipzig, Marburg, and Schellerhau). A liquid-liquid extraction method and a sensitive high-performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS/MS) method operating in multiple reaction monitoring (MRM) mode were applied for the alkaloid determination.

Results: Quantification revealed varying alkaloid concentrations among plant parts and Veratrum species in the μg/g to mg/g range. Protoveratrine A exhibited the highest content, while veratramine concentrations were generally lower. Especially in fruit, roots and rootstock of Veratrum album L. alkaloid concentrations were significant high.

Conclusion: The developed HPLC-MS/MS method successfully determined Veratrum alkaloid concentrations in plant samples. The study contributes valuable data on Veratrum alkaloid distribution in different species and plant parts, crucial for understanding their potential medicinal and toxicological significance.

Introduction: 2,6-Disubstituted piperidin-3-ols are an important group of piperidine alkaloids found in species such as Senna spectabilis, whose main constituents include cassine and spectaline, compounds with relevant pharmacological activity. The analysis of these compounds is challenging due to the complexity of plant extracts and the absence of chromophores capable of absorbing ultraviolet (UV) radiation.

Objective: This paper presents a new analytical method to separate and quantify the non-UV-absorbing alkaloids present in ethanol extracts from S. spectabilis flowers using capillary zone electrophoresis (CZE) with indirect UV detection.

Methodology: The optimized CZE method employs a background electrolyte containing 60 mM histidine (His), 15 mM α-cyclodextrin, 20% acetonitrile (ACN), and pH-adjusted to 4.7 with acetic acid (AcOH).

Results: The limit of detection (LOD) values was 10.2 and 13.9 mg L^-1 for cassine and spectaline, respectively. For both analytes, the precision data were better than 2% of relative standard deviation (RSD) for migration times and peak areas. To evaluate the applicability of the developed method, ethanolic extracts from S. spectabilis flowers were prepared and analyzed.

Conclusions: Thereby, the method proved to be efficient and complementary to conventional techniques, offering a cost-effective alternative in the quantification of the non-UV-absorbing piperidine alkaloids present in plant extracts.

Introduction: Compound annotation is always a challenging step in metabolomics studies. The molecular networking strategy has been developed recently to organize the relationship between compounds as a network based on their tandem mass (MS2) spectra similarity, which can be used to improve compound annotation in metabolomics analysis.

Objective: This study used Bupleuri Radix from different geographic areas to evaluate the performance of molecular networking strategy for compound annotation in liquid chromatography-mass spectrometry (LC-MS)-based metabolomics.

Methodology: The Bupleuri Radix extract was analyzed by LC-quadrupole time-of-flight MS under MSe acquisition mode. After raw data preprocessing, the resulting dataset was used for statistical analysis, including principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). The chemical makers related to the sample growth place were selected using variable importance in projection (VIP) > 2, fold change (FC) > 2, and p < 0.05. The molecular networking analysis was applied to conduct the compound annotation.

Results: The score plots of PCA showed that the samples were classified into two clusters depending on their growth place. Then, the PLS-DA model was constructed to explore the chemical changes of the samples further. Sixteen compounds were selected as chemical makers and tentatively annotated by the feature-based molecular networking (FBMN) analysis.

Conclusion: The results showed that the molecular networking method fully exploits the MS information and is a promising tool for facilitating compound annotation in metabolomics studies. However, the software used for feature extraction influenced the results of library searching and molecular network construction, which need to be taken into account in future studies.

Introduction: Cordyceps sinensis (CS) is a precious medicinal fungus. Wild CS (WCS) and artificial CS (ACS) are destroyed for their identification using traditional methods, which are time consuming and labor-intensive. Therefore, it is crucial to establish a nondestructive identification method to rapidly screen WCS.

Objective: The aim of this study was to provide technical support for rapid screening of CS and evaluation of its quality. The applicability of the model was improved through model transfer.

Methods: In this study, continuous wavelet transform was used to analyze the differences in moisture content and active components between WCS and ACS from the perspective of characteristic molecular groups. A portable instrument and a laboratory benchtop instrument were used to determine CS spectra. Partial least squares discrimination analysis was conducted for the identification of WCS and ACS while preserving the original shape of CS. Moreover, improved principal component analysis was utilized to transfer the model between the two types of near-infrared spectroscopy (NIRS) instruments.

Results: The results demonstrated that three peaks, at 1443, 1941, and 2183 nm, were characteristic absorption peaks. The model based on NIRS could initially provide rapid differentiation between WCS and ACS. At the same time, the accuracy of the external test set was further improved to over 95% through forward transfer.

Conclusion: Therefore, this method could be used for rapid screening of WCS and provides technical support for the nondestructive identification of CS and initial assessment of CS quality.

Introduction: Baishouwu, derived from Cynanchum auriculatum (CA) Royle ex Wight, Cynanchum bungei (CB) Decne., and Cynanchum wilfordii (CW) (Maxim.) Hemsl., is a valuable traditional Chinese medicine. CA is also recognized as a new food resource by China's National Health Commission. Given the considerable variations in flavor and chemical composition among these species and lack of their qualitative assessments, accurately differentiating between the species constituting Baishouwu is essential.

Objective: To develop a method combining electronic tongue (E-tongue), electronic nose (E-nose), and ultra-performance liquid chromatography-quadrupole-time of flight/mass spectrometry (UPLC-Q-TOF/MS) to differentiate between Baishouwu samples.

Material and methods: Fifteen batches of Baishouwu samples were analyzed using E-tongue, E-nose, and UPLC-Q-TOF/MS. Flavor differences and key differential metabolites were determined through principal component analysis and orthogonal partial least squares discriminant analysis.

Results: E-tongue results revealed umami, sweetness, and richness as the predominant flavors of Baishouwu, with CA having the highest umami response, CW exhibiting the highest bitterness, and CB the highest sweetness. E-nose sensors showed consistent responses across species, with variations in signal strength; W1W and W2W sensors showed the highest response values. A total of 158 and 41 characteristic variables in the positive and negative ion modes, respectively, were selected as candidate differential metabolites, of which 29 and 14 were confirmed through database comparison. Eight critical differential metabolites, including C₂₁ steroids and acetophenone compounds, were identified.

Conclusion: This study presents a strategy for differentiating among the species constituting Baishouwu, providing a basis for broader application and establishing quality standards for these medicinal compounds.

Introduction: Zhen-wu-tang (ZWT) is a traditional Chinese medicine (TCM) formula for the treatment of several kidney diseases. However, due to the complexity of the TCM formula, there is a lack of accurate knowledge of the chemical constituents of ZWT and its bioactive components, as well as in vivo metabolic pathway studies.

Objectives: The chemical composition of ZWT and its bioactive components along with the metabolic pathways were investigated by a combination of chemical profiling and serum pharmacochemistry.

Methods: High-resolution ultra-performance liquid chromatography-quadrupole time-of-flight mass spectrometry was used to identify the chemical components of ZWT and its bioactive components and metabolites in vivo.

Results: As a result, a total of 110 chemical components were identified from ZWT solution, mainly amino acids, alkaloids, gingerols, monoterpene glycosides and terpenoids, and so on. In addition, 24 prototype components and 36 metabolites were detected in rat plasma. Meanwhile, 8 prototype components were detected in rat kidney tissue but no metabolites. Interestingly, 4 of the 28 bioactive components were detected in both plasma and renal tissue, which were atractylenolide III, trimethoxyaconitane, methyl gallate, and paeoniflorin. The metabolic pathways mainly involved Phases I and/or II metabolic reactions such as hydrolysis, oxidation, reduction and hydration, methylation/demethylation, sulphation, glucuronidation, acetylation, and glutathione conjugation.

Conclusion: Overall, the present study has comprehensively elucidated the chemical composition of ZWT and its potential bioactive components and metabolites, which provides a basis for the basic study of its pharmacodynamic substances and a reference for the study of the bioactive components of TCM formulae.

Introduction: Polygalae Radix (PR) is known to relieve toxicity and increase efficiency in various diseases after processing. However, there were few studies for aromatic carboxylic acids (ACAs) due to the limited detection, especially for the metabolites within m/z 100-2000.

Objectives: This study aims to elucidate the whole metabolism of PR with/without licorice (LP), focusing on metabolites within m/z 100-2000 and pharmacodynamics in vivo.

Material and methods: This study was established by the combination of multidimensional ultra-high performance liquid chromatography coupled with a mass spectrometer (UPLC-MS) technology with protein sedimentation method to analyze metabolites in plasma, brain, colon, and stomach contents. Quantitative monitoring ACAs was enhanced with our novel stable isotope derivatization (SILD) technique. And then the pharmacokinetics (PK) study of relatively large metabolites was carried out. A targeted network pharmacology approach was established to avoid false positive results, mapping interactions relevant to Alzheimer's disease (AD), and other conditions.

Results: The 85 polygala metabolites were qualitatively analyzed in plasma, brain, colon, and stomach contents. The 11 types of relatively large metabolites and 8 types of ACAs were quantitatively monitored. Among them, nine types of relatively large metabolites were assessed through PK studies. In targeted network pharmacology, it highlighted the significance of small molecular metabolites, including ACAs et al, which were frequently overlooked. LP may play a more key role mainly through neural active ligand-receptor interaction, AD, and pertussis pathways. These findings have outlined a step-by-step strategy for in-depth research in vivo, laying a foundation for further verification of biological function.

Introduction: Bienertia cycloptera is a species belonging to the Chenopodiaceae family. According to earlier reports, a unique research study on the phytochemistry and biological analysis of that species was conducted.

Objective: This study presents an integrated metabolomics investigation combined with multivariate analysis of various extractive fractions of B. cycloptera aerial parts. This study is the first attempt to explore the anti-inflammatory metabolites from B. cycloptera, showing its significance as a valuable traditional medicine.

Methodology: By comparing retention times, quasi-molecular ions, and MS/MS fragment ions with databases and literature references, metabolite annotation was accomplished using ultra performance liquid chromatography (UPLC)/triple quadrupole mass spectrometry (MS). Moreover, the effects of the studied samples on the gene expression of the four pro-inflammatory cytokines (IL-1β, IL-6, TNF-α, and INF-γ) using polymerase chain reaction (PCR) and comparing their results by those caused by piroxicam were tested to determine their anti-inflammatory efficacy.

Results: Chemical profiling revealed diverse metabolites, with 62 chromatographic peaks identified across various chemical classes. UPLC-MS/MS of different B. cycloptera fractions unveiled distinct chemical profiles. Results showed distinct chemical compositions in each fraction, with petroleum ether fraction enriched in sterols and fatty acids; methylene chloride fraction in alkaloids, sterols, and cardenolides; ethyl acetate fraction in alkaloids, flavonoids, cardenolides, and phenolic acids; and n-butanol fraction in flavonoids, alkaloids, and phenolic acids. Multivariate data analysis illustrated clustering patterns among petroleum ether, methylene chloride, ethyl acetate, and n-butanol fractions. OPLS-DA models were constructed to discern inter-class differences, identifying discriminatory metabolites. In vitro cytotoxicity and anti-inflammatory assays demonstrated the safety and efficacy of B. cycloptera fractions, with significant downregulation of pro-inflammatory markers. Further analysis revealed specific metabolites associated with anti-inflammatory effects, such as p-hydroxybenzoic acid, vanillic acid, tachioside, ferulic acid, staphylionoside D, humilixanthin, bergaptol, vulgaxanthin I, and portulacaxanthin III.

Conclusion: The findings of this study provide valuable insights into the chemical composition and bioactivity of B. cycloptera fractions, suggesting their potential as therapeutic agents and warranting further investigation.