Cytotoxic and Antitumor Agents from Genus Rubia.

Genus Rubia is widely distributed in almost all regions of the world, with 36 species and 2 varieties in China. Rubia species, such as Rubia cordifolia, have been used in traditional Chinese medicine for the treatment of diseases since ancient times. In recent years, the study of anticancer effects in traditional Chinese medicine has become a popular topic, and some studies have shown that several Rubia species extracts have cytotoxic and antitumor effects, and some of them have been shown to contain specific antitumor agents. Therefore, this review focuses on the cytotoxic and antitumor effects of the chemical constituents contained in Genus Rubia. Summarized 71 types of chemical substances in 5 categories with the effect of cytotoxicity and antitumor, as well as their structures, targets and mechanisms of action.

Stereoconvergent and Enantioselective Synthesis of Z-Homoallylic Alcohols via Nickel-Catalyzed Reductive Coupling of Z/E-1,3-Dienes with Aldehydes.

Stereoconvergent reactions enable the transformation of mixed stereoisomers into well-defined, chiral products─a crucial strategy for handling Z/E-mixed olefins, which are common but challenging substrates in organic synthesis. Herein, we report a stereoconvergent and highly enantioselective method for synthesizing Z-homoallylic alcohols via the nickel-catalyzed reductive coupling of Z/E-mixed 1,3-dienes with aldehydes. This process is enabled by an N-heterocyclic carbene ligand characterized by C2-symmetric backbone chirality and bulky 2,6-diisopropyl N-aryl substituents. Our method achieves excellent stereocontrol over both enantioselectivity and Z-selectivity in a single step, producing chiral Z-homoallylic alcohols that are valuable in natural products and pharmaceuticals.

Comparative evaluation of 16S rRNA primer pairs in identifying nitrifying guilds in soils under long-term organic fertilization and water management.

Compared with 454 sequencing technology, short-read sequencing (e.g., Illumina) technology generates sequences of high accuracy, but limited length (<500 bp). Such a limitation can prove that studying a target gene using a large amplicon (>500 bp) is challenging. The ammonia monooxygenase subunit A (amoA) gene of ammonia-oxidizing archaea (AOA), which plays a crucial part in the nitrification process, is such a gene. By providing a full overview of the community of a functional microbial guild, 16S ribosomal ribonucleic acid (rRNA) gene sequencing could overcome this problem. However, it remains unclear how 16S rRNA primer selection influences the quantification of relative abundance and the identification of community composition of nitrifiers, especially AOA. In the present study, a comparison was made between the performance of primer pairs 338F-806R, 515F-806R, and 515F-907R to a shotgun metagenome approach. The structure of nitrifier communities subjected to different long-term organic matter amendment and water management protocols was assessed. Overall, we observed higher Chao1 richness diversity of soil total bacteria by using 515F-806R compared to 338F-806R and 515F-907R, while higher Pielou's evenness diversity was observed by using 515F-806R and 515F-907R compared to 338F-806R. The studied primer pairs revealed different performances on the relative abundance of Thaumarchaeota, AOB, and NOB. The Thaumarchaeota 16S rRNA sequence was rarely detected using 338F-806R, while the relative abundances of Thaumarchaeota detected using 515F-806R were higher than those detected by using 515F-907R. AOB showed higher proportions in the 338F-806R and 515F-907R data, than in 515F-806R data. Different primers pairs showed significant change in relative proportion of NOB. Nonetheless, we found consistent patterns of the phylotype distribution of nitrifiers in different treatments. Nitrosopumilales (NP) and Nitrososphaerales (NS) clades were the dominant members of the AOA community in soils subject to controlled irrigation, whereas Ca. Nitrosotaleales (NT) and NS clades dominated the AOA community in soils subject to flooding irrigation. Nitrospira lineage II was the dominant NOB phylotype in all samples. Overall, ideal 16S rRNA primer pairs were identified for the analysis of nitrifier communities. Moreover, NP and NT clades of AOA might have distinct environmental adaptation strategies under different irrigation treatments.

Comparative Study of Heavy Metal Blood Serum Level Between Organic and Conventional Farmers in Eastern Taiwan.

Numerous studies have indicated that organic fertilizers (OFer) might contain heavy metals (HMs) that present health risks to organic farmers (OFar). This study compared the concentrations of six HMs (Zn, Ni, Cd, Cu, Pb, Cr) in the blood of two distinct groups of farmers: 30 OFar from a designated organic area in eastern Taiwan, and 74 conventional farmers (CFar) from neighboring non-organic designated regions. The findings revealed that the OFar exhibited higher levels of Zn (1202.70 ± 188.74 µg/L), Cr (0.20 ± 0.09 µg/L), and Ni (2.14 ± 1.48 µg/L) in their blood compared to the CFar (988.40 ± 163.16 µg/L, 0.18 ± 0.15 µg/L, and 0.77 ± 1.23 µg/L), respectively. The disparities in Zn, Cr, and Ni levels were measured at 214.3 µg/L, 0.02 µg/L, and 1.37 µg/L, respectively. Furthermore, among the OFar, those who utilized green manures (GM) displayed significantly elevated blood levels of Zn (1279.93 ± 156.30 µg/L), Cr (0.24 ± 0.11 µg/L), and Ni (1.94 ± 1.38 µg/L) compared to individuals who exclusively employed chemical fertilizers (CFer) (975.42 ± 165.35 µg/L, 0.19 ± 0.16 µg/L, and 0.74 ± 1.20 µg/L), respectively. The differences in Zn, Cr, and Ni levels were measured at 304.51 µg/L, 0.05 µg/L, and 1.20 µg/L, respectively. As a result, OFar should be careful in choosing OFer and avoid those that may have heavy metal contamination.

Two Multidimensional Chromatography/High-Resolution Mass Spectrometry Approaches Enabling the In-Depth Metabolite Characterization Simultaneously from Three Glycyrrhiza Species: Method Development, Comparison, and Integration.

Two offline multidimensional chromatography/high-resolution mass spectrometry systems (method 1: fractionation and online two-dimensional liquid chromatography, 2D-LC; method 2: fractionation and offline 2D-LC) were established to characterize the metabolites simultaneously from three Glycyrrhiza species. Ion exchange chromatography in the first-dimensional (1D) separation was well fractionated between the acidic (mainly triterpenoids) and weakly acidic components (flavonoids). These obtained subsamples got sophisticated separation by the second (2D) and third dimension (3D) of chromatography either by online reversed-phase chromatography × reversed-phase chromatography (RPC × RPC) or offline hydrophilic interaction chromatography × RPC (HILIC × RPC). Orthogonality for the 2D/3D separations reached 0.73 for method 1 and 0.81 for method 2, respectively. We could characterize 1097 compounds from three Glycyrrhiza species based on an in-house library and 33 reference standards, involving 618 by method 1 and 668 by method 2, respectively. They exhibited a differentiated performance and complementarity in identifying the multiple subclasses of Glycyrrhiza components.

Real-time monitoring of glucose metabolism and effects of metformin on HepG2 cells using 13C in-cell NMR spectroscopy.

Metformin is currently a strong candidate antitumor agent for multiple cancers, and has the potential to inhibit cancer cell viability, growth, and proliferation. Metabolic reprogramming is a critical feature of cancer cells. However, the effects of metformin which targets glucose metabolism on HepG2 cancer cells remain unclear. In this study, to explore the effects of metformin on glucose metabolism in HepG2 cells, we conducted real-time metabolomic monitoring of live HepG2 cells treated with metformin using 13C in-cell NMR spectroscopy. Metabolic tracing with U-13C6-glucose revealed that metformin significantly increased the production of 13C-G3P and 13C-glycerol, which were reported to attenuate liver cancer development, but decreased the production of potential oncogenesis-supportive metabolites, including 13C-lactate, 13C-alanine, 13C-glycine, and 13C-glutamate. Moreover, the expression levels of enzymes associated with the measured metabolites were carried out. The results showed that the levels of ALT1, MCT4, GPD2 and MPC1 were greatly reduced, which were consistent with the changes of measured metabolites in 13C in-cell NMR spectroscopy. Overall, our approach directly provides fundamental insights into the effects of metformin on glucose metabolism in live HepG2 cells, and highlights the potential mechanism of metformin, including the increase in production of G3P and glycerol derived from glucose, as well as the inhibition of glucose incorporation into lactate, alanine, glutamate, and glycine.

Spatial Distribution and Characterization of the Small-Molecule Metabolites and In Situ Hydrolyzed Oligosaccharides in the Rhizome of Glycyrrhiza uralensis by Desorption Electrospray Ionization-Mass Spectrometry Imaging and High-Resolution Liquid Chromatography-Mass Spectrometry.

Characterization and spatial distribution studies of the metabolome in plants are crucial for revealing the physiology of plants and developing functional foods. Using the rhizome of Glycyrrhiza uralensis as a case, we integrated desorption electrospray ionization-mass spectrometry imaging (DESI-MSI) and high-resolution liquid chromatography/mass spectrometry approaches aimed at characterizing and locating both the small molecules and the macromolecular polysaccharides. Under the optimal conditions, 21 flavonoids and 12 triterpenoids were detected and characterized in different tissues of the rhizome and another 19 components were characterized exclusively by DESI-MSI. Combined with hydrophilic interaction chromatography/ion mobility-quadrupole time-of-flight mass spectrometry, eight different degrees of polymerization of oligosaccharides (after in situ acid hydrolysis) were characterized from the rhizome of G. uralensis. Majority of these metabolites are located in the cortex, phloem, and medulla, which lays the foundation for understanding the physiology of G. uralensis. The useful information can benefit the sustainable utilization and further development of Glycyrrhiza resource.

Maize-soybean intercropping improved maize growth traits by increasing soil nutrients and reducing plant pathogen abundance.

Introduction: Maize (Zea mays L.)-soybean (Glycine max L.) intercropping has been widely utilized in agricultural production due to its effectiveness in improving crop yield and nutrient use efficiency. However, the responses of maize rhizosphere microbial communities and the plant pathogen relative abundance to maize growth traits in maize-soybean intercropping systems with different chemical nitrogen fertilizer application rates remain unclear. Methods: In this study, a field experiment was conducted, and the bacterial and fungal communities of maize rhizosphere soils in maize-soybean intercropping systems treated with different N fertilization rates were investigated using Illumina NovaSeq sequencing. Maize growth traits, soil physicochemical properties and soil enzyme activities were also examined. Results and discussion: We found that intercropping and N fertilizer treatments strongly influenced soil microbial diversity, structure and function. The PLSPM (partial least squares path modeling) confirmed that soil nutrients directly positively affected maize biomass and that intercropping practices indirectly positively affected maize biomass via soil nutrients, especially NH4+-N. Intercropping agronomic approaches also improved maize growth traits by reducing the plant pathogen abundance, and the relative abundance of the plant pathogen Trichothecium roseum significantly decreased with intercropping treatments compared to monocropping treatments. These results confirmed the benefits of maize-soybean intercropping treatments for agricultural production.

System pharmacology-based determination of the functional components and mechanisms in chronic heart failure treatment: an example of Zhenwu decoction.

Chronic heart failure (CHF) is the primary cause of death among patients with cardiovascular diseases, representing the advanced stage in the development of several cardiovascular conditions. Zhenwu decoction (ZWD) has gained widespread recognition as an efficacious remedy for CHF due to its potent therapeutic properties and absence of adverse effects. Nevertheless, the precise molecular mechanisms underlying its actions remain elusive. This study endeavors to unravel the intricate pharmacological underpinnings of five herbs within ZWD concerning CHF through an integrated approach. Initially, pertinent data regarding ZWD and CHF were compiled from established databases, forming the foundation for constructing an intricate network of active component-target interactions. Subsequently, a pioneering method for evaluating node significance was formulated, culminating in the creation of core functional association space (CFAS). To discern vital components, a novel dynamic programming algorithm was devised and used to determine the core component group (CCG) within the CFAS. Enrichment analysis of the CCG targets unveiled the potential coordinated molecular mechanisms of ZWD, illuminating its capacity to ameliorate CHF by modulating genes and related signaling pathways involved in pathological remodeling. Notable pathways encompass PI3K-Akt, diabetic cardiomyopathy, cAMP and MAPK signaling. Concluding the computational analyses, in vitro experiments were executed to assess the effects of vanillic acid, paradol, 10-gingerol and methyl cinnamate. Remarkably, these compounds demonstrated efficacy in reducing the production of ANP and BNP within isoprenaline-induced AC 16 cells, further validating their potential therapeutic utility. This investigation underscores the efficacy of the proposed model in enhancing the precision and reliability of CCG selection within ZWD, thereby presenting a novel avenue for mechanistic inquiries, compound refinement and the secondary development of TCM herbs.

Metagenomic and network analyses reveal key players in nitrification in upland agricultural soils.

Nitrification, a key step in soil nitrogen cycling, is a biologically mediated process crucial to the ecological environment. However, how nitrifiers drive nitrification under different soil properties and climatic factors at large spatial scales is poorly understood. Here, using metagenomic sequencing and network-based approaches, we identified key nitrifying species of upland agricultural soils in northern China, which spans a wide range of climates and geographic distances. We found that potential nitrification rates (PNRs) varied in different soils and were positively correlated with soil pH (5.42-8.46) and mean annual temperature (MAT) and negatively correlated with the C/N ratio. Network analysis revealed that one module (module 3) was significantly correlated with PNR. In this module, 16 dominant nodes were associated with AOB Nitrosomonas and most nodes were significantly correlated with environmental factors, suggesting that abiotic conditions are important for determining the assembly of these key nitrifiers. Our study advanced the understanding of the key nitrifying populations and their environmental drivers in upland agricultural soil across different soil and climate types.

Exploring the cellular and molecular differences between ovarian clear cell carcinoma and high-grade serous carcinoma using single-cell RNA sequencing and GEO gene expression signatures.

The two most prevalent subtypes of epithelial ovarian carcinoma (EOC) are ovarian clear cell carcinoma (OCCC) and high-grade serous ovarian carcinoma (HGSC). Patients with OCCC have a poor prognosis than those with HGSC due to chemoresistance, implying the need for novel treatment target. In this study, we applied single-cell RNA sequencing (scRNA-seq) together with bulk RNA-seq data from the GEO (Gene Expression Omnibus) database (the GSE189553 dataset) to characterize and compare tumor heterogeneity and cell-level evolution between OCCC and HGSC samples. To begin, we found that the smaller proportion of an epithelial OCCC cell subset in the G2/M phase might explain OCCC chemoresistance. Second, we identified a possible pathogenic OCCC epithelial cell subcluster that overexpresses LEFTY1. Third, novel biomarkers separating OCCC from HGSC were discovered and subsequently validated on a wide scale using immunohistochemistry. Amine oxidase copper containing 1 (AOC1) was preferentially expressed in OCCC over HGSC, while S100 calcium-binding protein A2 (S100A2) was detected less frequently in OCCC than in HGSC. In addition, we discovered that metabolic pathways were enriched in the epithelial compartment of the OCCC samples. In vitro experiments verified that inhibition of oxidative phosphorylation or glycolysis pathways exerted direct antitumor effects on both OCCC and HGSC cells, while targeting glutamine metabolism or ferroptosis greatly attenuated chemosensitivity only in OCCC cells. Finally, to determine whether there were any variations in immune cell subsets between OCCC and HGSC, data from scRNA-seq and mass cytometry were pooled for analysis. In summary, our work provides the first holistic insights into the cellular and molecular distinctions between OCCC and HGSC and is a valuable source for discovering new targets to leverage in clinical treatments to improve the poor prognosis of patients with OCCC.

The impact of digital economy on regional technological innovation capability: An analysis based on China's provincial panel data.

The development of the digital economy in China facilitates the transformation of old and new growth drivers. It can greatly promote the upgrading of technological innovation capacity, realize economies of scale and scope, and constantly promote the generation of new industries and new forms of business with the deep integration of digital economy and traditional industries, thereby promoting the high-quality development of China's economy. This paper uses inter-provincial panel data from 2013 to 2020 and a dynamic spatial Durbin model to quantify the impact of the digital economy on regional technological innovation capability (RTIC). The results show that: (1) the digital economy has positive spatial spillover effect and can boost the province's and neighboring provinces' regional technological innovation capability; (2) regional technological innovation capability has obvious spatial and temporal aggregation effects; (3) the impact of the digital economy on RTIC is mainly short-term effects, and there is regional heterogeneity, with the western region experiencing the highest effects and the eastern region experiencing less. Therefore, it is urgent to accelerate the development speed of the digital economy, grasp the law of dynamic economic development, identify the regional heterogeneity of the digital economy development, and deepen inter-regional digital technology cooperation to comprehensively drive the improvement of regional technological innovation capability.

Element quality indicator: A quality assessment and defect detection method for software requirement specification.

A software requirements specification (SRS) provides a detailed description of the requirements of a software system that is to be developed. The Element Quality Indicator (EQI) is a novel method to detect defects and assess the quality of an SRS. It does not hinge on review guidelines and is based on the SRS element questions extraction method (EQEM). In this study, we optimized the EQI and carried out a systematic and comprehensive experiment to validate and evaluate its effectiveness. The controlled experiment, which included 60 software engineering students, found that 100% of the subjects identified defects in the SRS using EQI. Moreover, the results indicated that the average number of defects detected with EQI was greater than that of the classical review technique - perspective-based reading. Furthermore, the controlled experiment demonstrated that EQI provides a comparatively objective and accurate evaluation of the quality of the SRS and markedly diminishes the bias in understanding software requirements due to the ambiguity of natural language.

Three-dimensional characteristic chromatogram by online comprehensive two-dimensional liquid chromatography: Application to the identification and differentiation of ginseng from herbal medicines to various Chinese patent medicines.

One bottleneck problem in the quality control of traditional Chinese medicine (TCM) is the accurate identification of easily confused herbal medicines from Chinese patent medicine (CPM). Ginseng products derived from the multiple parts (e.g., root/rhizome, leaf, and flower bud) of multiple Panax species (P. ginseng, P. quinquefolius, P. notoginseng, P. japonicus, and P. japonicus var. major) are globally popular; however, their authentication is very challenging. Using online comprehensive two-dimensional liquid chromatography (LC × LC), we propose the concept of a three-dimensional characteristic chromatogram (3D CC) by integrating enhanced LC × LC separation and a contour plot that visualizes the stereoscopic chromatographic peaks and examine its performance in authenticating various ginseng products. Targeted at the resolution of 17 ginsenoside markers, an online LC × LC/UV system with a 56 min analysis time was constructed: a CORTECS UPLC Shield RP 18 column running at 0.1 mL/min for the first-dimensional chromatography and a Poroshell SB-Aq column at 2.0 mL/min in shift gradient mode in the second dimension of separation. In particular, ginsenosides Rg1/Re and Rc/Ra1 were well resolved. According to the presence/absence of stereo peaks consistent with the main ginsenoside markers in the 3D CC and the depth of shade (depending on peak volume), it was feasible to use a single method to identify and distinguish among 12 different ginseng species as the drug materials and the use of ginseng simultaneously from 21 CPMs. Conclusively, a practical solution enabling the accurate identification of easily confused TCMs was provided, covering both the drug materials and the compound preparations.

Comparison of antibiotic-impregnated bone cement coverage versus vacuum sealing drainage in semi-open bone grafting using for tibial fracture with infected bone and soft tissue defect: a retrospective analysis.

OBJECTIVE: To compare antibiotic-impregnated bone cement coverage (bone cement surface technique; BCS-T) versus vacuum sealing drainage (VSD) for tibial fracture with infected bone and soft tissue defect. METHOD: This retrospective analysis compared the clinical outcomes in patients undergoing BCS-T (n = 16) versus VSD (n = 15) for tibial fracture with infected bone and soft tissue defect at the Third Hospital of Hebei Medical University from March 2014 to August 2019. For BCS-T group, osseous cavity was filled with autograft bone graft after debridement, and then the wound was covered with a 3-mm layer of bone cement impregnated with vancomycin and gentamycin. The dressing was changed every day in the first week, and every 2 ~ 3 days in the second week. For VSD group, a negative pressure of -150 ~ -350 mmHg was maintained, and the dressing was changed every 5-7 days. All patients received antibiotics treatment based on bacterial culture results for 2 weeks. RESULTS: The 2 groups did not differ in age, sex and key baseline characteristics, including type of Gustilo-Anderson classification, size of the bone and soft tissue defect, the percentage of primary debridement, bone transport, and the time from injury to bone grafting. The median follow-up was 18.9 months (range:12-40). The time to complete coverage of bone graft by granulation tissue was 21.2 (15.0-44.0) and 20.3 (15.0-24.0) days in the BCS-T and VSD groups, respectively (p = 0.412). The 2 groups also did not differ in wound healing time (3.3 (1.5-5.5) versus 3.2(1.5-6.5) months; p = 0.229) and bone defect healing time (5.4(3.0-9.6) versus 5.9(3.2-11.5) months; p = 0.402). However, the cost of covering material was significantly reduced in the BCS-T group (2071 ± 134 versus 5542 ± 905 yuan; p = 0.026). Paley functional classification at 12 months did not differ between the 2 groups (excellent in 87.5% versus 93.3% in the 2 groups; p = 0.306). CONCLUSION: BCS-T could achieve clinical outcomes similar to VSD in patients receiving bone graft for tibial fracture with infected bone and soft tissue defect, but material cost was significantly reduced. Randomized controlled trials are needed to verify our finding.

Expression of Tryptophan Metabolism Enzymes in Patients with Diffuse Large B-cell Lymphoma and NK/T-cell Lymphoma.

BACKGROUND: Metabolites of tryptophan (Trp) metabolism in the tumor microenvironment play crucial immunosuppressive roles in various cancers. However, the role of Trp metabolism in diffuse large B-cell lymphoma (DLBCL) or natural killer/T-cell lymphoma (NK/TCL) remains unelucidated. METHODS: We investigated the potential role of Trp metabolism in a cohort of 43 patients with DLBCL and 23 with NK/TCL. We constructed tissue microarrays and performed in situ staining of Trp-catabolizing enzymes and PD-L1 using immunohistochemistry (IHC). RESULTS: We observed 14.0% positive staining of IDO1 in DCBCL and 60.9% in NK/TCL; 55.8% of IDO2 in DCBCL and 95.7% in NK/TCL; 79.1% of TDO2 in DCBCL and 43.5% in NK/TCL; 29.7% of IL4I1 in DCBCL and 39.1% in NK/TCL. However, IDO1, IDO2, TDO2, and IL4I1 positivity did not significantly differ between PD-L1+ and PD-L1- biopsy tissue samples of NK/TCL; nonetheless, a positive correlation of IDO1 (r = 0.87, p < 0.001), IDO2 (r = 0.70, p < 0.001), TDO2 (r = 0.63, p < 0.001), and IL4I1 (r = 0.53, p < 0.05) with PD-L1 expression was observed in the TCGA-DLBCL dataset. Finally, immunohistochemical (IHC) analysis revealed the lack of superior prognostic effect with higher expression of Trp enzymes in DLBCL and NK/TCL. Furthermore, IDO1, IDO2, TDO2, and IL4I1 expression, as well as survival rates, did not significantly differ across all groups in the TCGA-DLBCL cohort. CONCLUSION: Collectively, our findings provide novel insights into the enzymes involved in Trp metabolism in DLBCL and NK/TCL and their association with PD-L1 expression, which offers potential strategies to combine Trp-metabolism enzyme inhibitors with anti-PD-L1 or other immunotherapeutic strategies in clinical DLBCL or NK/TCL treatment.

Triterpenoid saponins and C21 steroidal glycosides from Gymnema tingens and their glucose uptake activities.

Four new triterpenoid saponins, tigensides A-D (1-4), and one new C21 steroid, tipregnane A(9), together with six known compounds were isolated from the EtOAc fraction of the roots and stems of Gymnema tingens. The chemical structures of the new compounds were determined based on their spectroscopic data, including IR, UV, NMR, and mass spectrometric analysis. All compounds were isolated for the first time. Compounds 1-11 promoted glucose uptake in the range of 1.12 to 2.52 fold, respectively. Compound 2 showed the most potent glucose uptake, with 2.52 fold enhancement. Additionally, compound 2 showed a medium effect on the GLUT4 translocation activity in L6 cells in further study.

Pseudotargeted Metabolomics Approach Enabling the Classification-Induced Ginsenoside Characterization and Differentiation of Ginseng and Its Compound Formulation Products.

The use of diversified ginseng extracts in health-promoting foods is difficult to differentiate, as they share bioactive ginsenosides among different Panax species (e.g., P. ginseng, P. quinquefolius, P. notoginseng, and P. japonicus) and different parts (e.g., root, leaf, and flower). This work was designed to develop a pseudo-targeted metabolomics approach to discover ginsenoside markers facilitating the precise authentication of ginseng and its use in compound formulation products (CFPs). Versatile mass spectrometry experiments on the QTrap mass spectrometer achieved classified characterization of the neutral, malonyl, and oleanolic acid-type ginsenosides, with 567 components characterized. A pseudo-targeted metabolomics approach by multiple reaction monitoring (MRM) of 262 ion pairs could assist to establish key identification points for 12 ginseng species. The simultaneous detection of 14 markers enabled the identification of ginseng from 15 ginseng-containing CFPs. The pseudo-targeted metabolomics strategy enabled better performance in differentiating among multiple ginseng, compared with the full-scan high-resolution mass spectrometry approach.

A multidimensional chromatography/high-resolution mass spectrometry approach for the in-depth metabolites characterization of two Astragalus species.

To address the chemical complexity is indispensable in a number of research fields. Herb metabolome is typically composed by more than one class of structure analogs produced via different biosynthetic pathways. Multidimensional chromatography (MDC), due to the greatly enhanced separation space, offers the potential solution to comprehensive characterization of herbal metabolites. Here, we presented a strategy, by integrating MDC and quadrupole time-of-flight mass spectrometry (QTOF-MS), to accomplish the in-depth herbal metabolites characterization. Using the metabolome of two Astragalus species (A. membranaceus var. mongholicus,AMM; A. membranaceus, AM) as the case, an off-line three-dimensional liquid chromatography (3D-LC) system was established: hydrophilic interaction chromatography using an XAmide column as the first dimension (1D) for fractionating the total extract, on-line reversed-phase × reversed-phase liquid chromatography separately configuring a CSH Fluoro-Phenyl column and a Cosmocore C18 column as the second dimension (2D) and the third dimension (3D) of chromatography to enable the explicit separation of three well fractionated samples. Moreover, the negative-mode collision-induced dissociation by QTOF-MS under the optimized condition could provide diversified fragments that were useful for the structural elucidation of AMM and AM. An in-house library (composed by 247 known compounds) and comparison with 43 reference standards were utilized to assist more reliable characterization. We could characterize 513 compounds from two Astragalus species (344 from AMM and 323 from AM), including 236 flavonoids, 150 triterpenoids, 18 organic acids, and 109 others. Conclusively, the established MDC approach gained excellent performance favoring the analogs-oriented in-depth characterization of herbal metabolites, but received uncompromising analytical efficiency.