Chemical characterization and comparative analysis of different parts of Cocculus orbiculatus through UHPLC-Q-TOF-MS.

Cocculus orbiculatus (L.) DC. (C. orbiculatus) is a medicinal herb valued for its dried roots with anti-inflammatory, analgesic, diuretic, and other therapeutic properties. Despite its traditional applications, chemical investigations into C. orbiculatus remain limited, focusing predominantly on alkaloids and flavonoids. Furthermore, the therapeutic use of C. orbiculatus predominantly focuses on the roots, leaving the stems, a significant portion of the plant, underutilized. This study employed ultra-high performance liquid chromatography quadrupole time-of-flight mass spectrometry (UHPLC-Q-TOF-MS/MS) with in-house and online databases for comprehensive identification of components in various plant parts. Subsequently, untargeted metabolomics was employed to analyze differences in components across different harvest periods and plant sections of C. orbiculatus, aiming to screen for distinct components in different parts of the plant. Finally, metabolomic analysis of the roots and stems, which contribute significantly to the plant's weight, was conducted using chemometrics, including principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), orthogonal partial least squares discriminant analysis (OPLS-DA), and heatmaps. A total of 113 components, including alkaloids, flavonoids, and organic acids, were annotated across the root, stem, leaf, flower, and fruit, along with numerous previously unreported compounds. Metabolomic analyses revealed substantial differences in components between the root and stem compared to the leaf, flower, and fruit during the same harvest period. PLS-DA and OPLS-DA annotated 10 differentiating components (VIP > 1.5, P < 0.05, FC > 2 or FC < 0.67), with 5 unique to the root and stem, exhibiting lower mass spectrometric responses. This study provided the first characterization of 113 chemical constituents in different parts of C. orbiculatus, laying the groundwork for pharmacological research and advocating for the enhanced utilization of its stem.

Quantitative analysis of six sesquiterpene glycosides from Dendrobium nobile Lindl. under different growth conditions by high-performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry in MRM mode.

INTRODUCTION: The sesquiterpene glycosides (SGs) from Dendrobium nobile Lindl. have immunomodulatory effects. However, there are no studies on the growth conditions affecting its contents and quantitative analysis methods. OBJECTIVE: In the present study, a quantitative analysis method for six SGs from D. nobile was established. We explored which growth conditions could affect the contents of SGs, providing a basis for the cultivation and clinical application of D. nobile. METHODS: Firstly, based on the optimization of mass spectrometry parameters and extraction conditions for six SGs in D. nobile, a method for the determination of the contents of six SGs was established using high-performance liquid chromatography coupled with triple quadrupole tandem mass spectrometry (HPLC-QqQ-MS/MS) in multiple reaction monitoring (MRM) mode. Then, the methodology of the established method was validated. Secondly, the established method was applied to determine the contents of six SGs from 78 samples of D. nobile grown under different growth conditions. Finally, chemometrics analysis was employed to analyze the results and select optimal growth conditions for D. nobile. RESULTS: The results indicated significant variations in the contents of SGs from D. nobile grown under different growth conditions. The primary factors influencing SG contents included age, geographical origin, altitude, and epiphytic pattern. CONCLUSION: Therefore, the established method for determining SG contents from D. nobile is stable. In particular, the SG contents were relatively high in samples of 3-year-old D. nobile grown at an altitude of approximately 500 m on Danxia rocks in Chishui, Guizhou.

Metabolites rapid-annotation in mice by comprehensive method of virtual polygons and Kendric mass loss filtering: A case study of Dendrobium nobile Lindl.

With significant advancements in high-resolution mass spectrometry, there has been a substantial increase in the amount of chemical component data acquired from natural products. Therefore, the rapid and efficient extraction of valuable mass spectral information from large volumes of high-resolution mass spectrometry data holds crucial significance. This study illustrates a targeted annotation of the metabolic products of alkaloid and sesquiterpene components from Dendrobium nobile (D. nobile) aqueous extract in mice serum through the integration of an in-houses database, R programming, a virtual metabolic product library, polygonal mass defect filtering, and Kendrick mass defect strategies. The research process involved initially establishing a library of alkaloids and sesquiterpenes components and simulating 71 potential metabolic reactions within the organism using R programming, thus creating a virtual metabolic product database. Subsequently, employing the virtual metabolic product library allowed for polygonal mass defect filtering, rapidly screening 1705 potential metabolites of alkaloids and 3044 potential metabolites of sesquiterpenes in the serum. Furthermore, based on the chemical composition database of D. nobile and online mass spectrometry databases, 95 compounds, including alkaloids, sesquiterpenes, and endogenous components, were characterized. Finally, utilizing Kendrick mass defect analysis in conjunction with known alkaloids and sesquiterpenes targeted screening of 209 demethylation, methylation, and oxidation products in phase I metabolism, and 146 glucuronidation and glutathione conjugation products in phase II metabolism. This study provides valuable insights for the rapid and accurate annotation of chemical components and their metabolites in vivo within natural products.

Hypoglycemic Effects and Quality Marker Screening of Dendrobium nobile Lindl. at Different Growth Years.

(1) Background: The effect of Dendrobium nobile Lindl. (D. nobile) on hyperglycemic syndrome has only been recently known for several years. Materials of D. nobile were always collected from the plants cultivated in various growth ages. However, regarding the efficacy of D. nobile on hyperglycemic syndrome, it was still unknown as to which cultivation age would be selected. On the other hand, with the lack of quality markers, it is difficult to control the quality of D. nobile to treat hyperglycemic syndrome. (2) Methods: The effects of D. nobile cultivated at year 1 and year 3 were checked on alloxan-induced diabetic mice while their body weight, diet, water intake, and urinary output were monitored. Moreover, levels of glycosylated serum protein and insulin were measured using Elisa kits. The constituents of D. nobile were identified and analyzed by using UPLC-Q/trap. Quality markers were screened out by integrating the data from UPLC-Q/trap into a network pharmacology model. (3) Results: The D. nobile cultivated at both year 1 and year 3 showed a significant effect on hyperglycemic syndrome at the high dosage level; however, regarding the significant level, D. nobile from year 1 showed the better effect. In D. nobile, most of the metabolites were identified as alkaloids and sesquiterpene glycosides. Alkaloids, represented by dendrobine, were enriched in D. nobile from year 1, while sesquiterpene glycosides were enriched in D. nobile from year 3. Twenty one metabolites were differentially expressed between D. nobile from year 1 and year 3. The aforementioned 21 metabolites were enriched to 34 therapeutic targets directly related to diabetes. (4) Conclusions: Regarding the therapy for hyperglycemic syndrome, D. nobile cultivated at year 1 was more recommended than that at year 3. Alkaloids were recommended to be used as markers to control the quality of D. nobile for hyperglycemic syndrome treatment.

The risk factors involved in airway mucus plug in children with ADV Pneumonia.

BACKGROUND: The risk factors for mucus plug in children with adenovirus (ADV) pneumonia. METHODS AND MATERIALS: A retrospective analysis was conducted of children diagnosed ADV pneumonia and underwent fiberoptic bronchoscopy admitted to the Xiamen Children's Hospital from September 2018 to September 2021.The patients were divided into a mucus plug group (39 cases) and a non-mucus plug group (53 cases). The children's data including sex, age, clinical presentation, laboratory test parameters, imaging and bronchoscopic data were collected. The risk factors for the development of airway mucus plug were analysed by multifactorial logistic regression. RESULTS: There were no statistically significant differences in sex, age, fever, hospitalization days, mixed infection, white blood cells (WBC) count, percentage of neutrophils (NE%), C-reactive protein(CRP), and D-dimer (all P > 0.05); Thermal range, procalcitonin (PCT), lactate dehydrogenase (LDH), Pleural effusion and associated decreased breath sounds was significantly higher in mucus plug group than in non-mucus plug group, and the differences were statistically significant (all P < 0.05); multifactorial logistic regression analysis showed that the duration of fever, PCT, and LDH were independent risk factors for the formation of mucus plugs. The critical values of ROC curves were pyroprocedure ≥ 6.5 d, PCT ≥ 0.705 ng/ml and LDH ≥ 478.5 U/L. CONCLUSION: Duration of fever, PCT and LDH levels were the independent risk factors for the formation of an airway mucus plug in children with ADV pneumonia.

Clinical characteristics of severe influenza virus-associated pneumonia complicated with bacterial infection in children: a retrospective analysis.

BACKGROUND: We aimed to investigate the clinical characteristics of severe influenza virus-associated pneumonia complicated with bacterial infection in children. METHODS: We retrospectively analysed data concerning 64 paediatric patients with severe influenza virus-associated pneumonia who had been treated at our hospital. The patients were divided into observation (44 patients) and control (20 patients) groups, based on the presence or absence of concomitant bacterial infection, and clinical data were compared between the groups. RESULTS: The mean age in the observation group was 2.71 ± 1.44 years, 42 (95.45%) were aged ≤ 5 years, and 18 (40.9%) had underlying diseases. The mean age in the control group was 4.05 ± 2.21 years, 13 (65%) were aged ≤ 5 years, and 3 (15%) had underlying diseases. There was a statistically significant difference in patient age and the proportion of patients with underlying diseases (P < 0.05). The observation group had higher duration of fever values, a higher number of patients with duration of fever ≥ 7 days, a higher incidence of gasping, and a higher incidence of seizures/consciousness disturbance, and the differences were statistically significant (P < 0.05). Secondary bacterial infections in the observation group were mainly due to gram-negative bacteria, with Haemophilus influenzae and Moraxella catarrhalis being the most common pathogens. The observation group had a higher proportion of patients treated in the paediatric intensive care unit and a longer hospital stay, and the differences were statistically significant (P < 0.05). CONCLUSION: Severe influenza virus-associated pneumonia complicated with bacterial infection was more common in children aged ≤ 5 years. Younger patients with underlying diseases were more susceptible to bacterial infection (mainly due to gram-negative bacteria). The timely administration of neuraminidase inhibitors and antibiotics against susceptible bacteria is likely to help improve cure rates.

Severe pediatric adenoviral pneumonia combined with invasive pulmonary aspergillosis.

BACKGROUND: This study aimed to analyze the clinical characteristics of severe pediatric adenoviral pneumonia combined with invasive pulmonary aspergillosis. METHODS: We retrospectively analyzed the clinical data of five children clinically diagnosed with severe adenoviral pneumonia combined with invasive pulmonary aspergillosis at Xiamen Children's Hospital. RESULTS: These five children included one boy and four girls, with ages of onset ranging from 8 months and 15 days to 2 years and 2 months. All of them had fever with a mean duration of 11-35 days and cough. Pulmonary imaging was performed, which revealed solid pulmonary opacification in all five children, pleural effusion in two children, and emphysema and multiple small cavity formations in one child. Multiple microbiological tests were performed on the 5 children, and adenovirus was positive in the alveolar lavage fluid for the first time, and aspergillus culture was positive in the second test. On tracheoscopy, the bronchial mucosa was seen to be congested and edematous or pale and eroded; white moss-like material was seen adhering to the tracheal wall or even blocking the airway. The five children were treated with a combination of two or more broad-spectrum antimicrobials, glucocorticoids, and gamma globulins and underwent bronchoscopy. Voriconazole was added in the treatment regimen after the diagnosis of aspergillosis (28-34 days of treatment). Four of the children were discharged in good condition with a mean total length of hospital stay of 17-47 days. The other child leave against medical advice. Follow-up 3-5 months after discharge showed that one child had been cured; two children had developed obliterative bronchiolitis; one child had developed bronchiectasis; and the remaining child who had been discharged spontaneously was not contactable via telephone. CONCLUSIONS: Immune disorders and antibiotic and steroid treatments for adenovirus infection are high-risk factors for secondary invasive pulmonary aspergillosis in children. Prolonged fever and cough are the main manifestations, but which lack specificity, and bronchoscopic mucosal-specific injury evaluation and alveolar lavage fluid culture are helpful in the diagnosis of aspergillosis. The long-term prognosis of severe pediatric adenoviral pneumonia combined with invasive pulmonary aspergillosis maybe poor.

Fatty acid metabolites of Dendrobium nobile were positively correlated with representative endophytic fungi at altitude.

Introduction: Altitude, as a comprehensive ecological factor, regulates the growth and development of plants and microbial distribution. Dendrobium nobile (D. nobile) planted in habitats at different elevations in Chishui city, also shows metabolic differences and endophytes diversity. What is the triangular relationship between altitude, endophytes, and metabolites? Methods: In this study, the diversity and species of endophytic fungi were tested by ITS sequencing and metabolic differences in plants were tested by UPLC-ESI-MS/MS. Elevation regulated the colonization of plant endophytic fungal species and fatty acid metabolites in D. nobile. Results: The results indicate that and high altitude was better for the accumulation of fatty acid metabolites. Therefore, the high-altitude characteristic endophytic floras were screened, and the correlation with fatty acid metabolites of plants was built. The colonization of T. rubrigenum, P. Incertae sedis unclassified, Phoma. cf. nebulosa JZG 2008 and Basidiomycota unclassified showed a significantly positive correlation with fatty acid metabolites, especially 18-carbon-chain fatty acids, such as (6Z,9Z,12Z)-octadeca-6,9,12-trienoic acid, 3,7,11,15-tetramethyl-12-oxohexadeca-2,4-dienoic acid and Octadec-9-en-12-ynoic acid. What is more fascinating is these fatty acids are the essential substrates of plant hormones. Discussion: Consequently, it was speculated that the D. nobile- colonizing endophytic fungi stimulated or upregulated the synthesis of fatty acid metabolites and even some plant hormones, thus affecting the metabolism and development of D. nobile.

Dissecting chemical markers for controlling "Paozhi" method of traditional Chinese medicine with untargeted metabolomics: Vinegar-baked Euphorbia kansui as a case study.

The processing of Traditional Chinese Medicine requires the appropriate parameters, while the specific chemical markers are still absent to obtain the optimized processing. In this study, we used vinegar-baked Euphorbia kansui as a case to dissect the chemical markers for the baking process using untargeted metabolomics. The robust chemical markers were selected based on the three rules, correlation, significant difference, and controllability. All the differential features were categorized based on their mass defects. After the differential analysis, 310 differential compounds were screened out and could be mainly divided into six categories: diacylglycerols and triacylglycerols demonstrated increasing trends with the baking time in the discriminant model, while ingenane-type diterpenes, jatrophane-type diterpenes, fatty acid esters, and fatty acids had decreasing trends. It was unexpected to find that the diterpenes did not correlate with the baking time. Only very few compounds meet the three rules. They were validated with a high-performance liquid chromatography method. Finally, only 13-Hydroxy-9,11-octadecadienoic acid and its isomer 9-Hydroxy-10,12-octadecadienoic acid could be used further to differentiate the commercial vinegar-baked Euphorbia kansui. It would be of interest to evaluate whether these two compounds could be utilized as markers to control more processing methods in future studies.

Identification of Human UDP-Glucuronosyltransferase Involved in Gypensapogenin C Glucuronidation and Species Differences.

Gypensapogenin C (GPC) is one of the important aglycones of Gynostemma pentaphyllum (GP), which is structurally glucuronidated and is highly likely to bind to UGT enzymes in vivo. Due to the important role of glucuronidation in the metabolism of GPC, the UDP-glucuronosyltransferase metabolic pathway of GPC in human and other species' liver microsomes is investigated in this study. In the present study, metabolites were detected using high-performance liquid chromatography-tandem mass spectrometry (LC-MS/MS). The results show that GPC could generate a metabolite through glucuronidation in the human liver microsomes (HLMs). Additionally, chemical inhibitors combined with recombinant human UGT enzymes clarified that UGT1A4 is the primary metabolic enzyme for GPC glucuronidation in HLMs according to the kinetic analysis of the enzyme. Metabolic differential analysis in seven other species indicated that rats exhibited the most similar metabolic rate to that of humans. In conclusion, UGT1A4 is a major enzyme responsible for the glucuronidation of GPC in HLMs, and rats may be an appropriate animal model to evaluate the GPC metabolism.

An improved strategy for identification and annotation of easily in-sourced dissociation diterpene lactones from plant natural products: Taking Andrographis paniculata (Burm. f.) as an example.

RATIONALE: Diterpene lactones (DL) in Andrographis paniculata (AP) are known as "natural antibiotics" for their excellent antibacterial activity. During mass spectrometry (MS) analysis, the hydroxyl groups in the AP DL skeleton are prone to neutral loss of H2 O, producing high in-source fragment peaks and affecting the characterization of these components. METHODS: Mass tags were applied during the MS data acquisition step, and special adduct ion form was used to guide the data processing and characterization steps. Besides, the total number of characterized AP DLs significantly increased when combining the number of neutrally lost H2 O from AP DLs, incorporating information on the diagnostic ions, and adopting molecular networks generated with the Global Natural Products Social Molecular Networking database. RESULTS: Ninety-nine DLs, comprising 6 monohydroxyl groups, 20 dihydroxyl groups, 27 trihydroxy groups, and 46 DLs with more than 3 hydroxyl groups, were characterized from AP. In addition, based on the characteristic fragments in the product ions (C3 H4 , Δm/z = 40.03 Da), it could be assumed that 90 DLs had the C19-OH structure among the identified DLs. The current study provides a new approach for collecting, processing, and characterizing MS analysis of natural DLs prone to in-source fragmentation. CONCLUSIONS: MS characterization of AP DLs was significantly improved, and many potential new compounds were identified in AP. This characterization provides new methods for the purification and identification of AP DLs.

Internet of things-enabled real-time health monitoring system using deep learning.

Smart healthcare monitoring systems are proliferating due to the Internet of Things (IoT)-enabled portable medical devices. The IoT and deep learning in the healthcare sector prevent diseases by evolving healthcare from face-to-face consultation to telemedicine. To protect athletes' life from life-threatening severe conditions and injuries in training and competitions, real-time monitoring of physiological indicators is critical. In this research work, we present a deep learning-based IoT-enabled real-time health monitoring system. The proposed system uses wearable medical devices to measure vital signs and apply various deep learning algorithms to extract valuable information. For this purpose, we have taken Sanda athletes as our case study. The deep learning algorithms help physicians properly analyze these athletes' conditions and offer the proper medications to them, even if the doctors are away. The performance of the proposed system is extensively evaluated using a cross-validation test by considering various statistical-based performance measurement metrics. The proposed system is considered an effective tool that diagnoses dreadful diseases among the athletes, such as brain tumors, heart disease, cancer, etc. The performance results of the proposed system are evaluated in terms of precision, recall, AUC, and F1, respectively.

Arm Movement Analysis Technology of Wushu Competition Image Based on Deep Learning.

In order to improve the recognition accuracy of action poses for athletes in martial arts competitions, it is considered that a single frame pose does not have the temporal features required for sequential actions. Based on deep learning, this paper proposes an image arm movement analysis technology in martial arts competitions. The motion features of the arm are extracted from the bone sequence. Taking human bone motion information as temporal dynamic information, combined with RGB spatial features and depth map, the spatiotemporal features of arm motion data are formed. In this paper, we set up a slow frame rate channel and a fast frame rate channel to detect sequential motion of images. The deep learning model takes 16 frames from each video as samples. The softmax classifier is used to get the classification result of which action category the human action in the video belongs to. The test results show that the accuracy and recall rate of the arm motion analysis technology based on deep learning in martial arts competitions are 95.477% and 92.948%, respectively, with good motion analysis performance.

Authentication of Shenqi Fuzheng Injection via UPLC-Coupled Ion Mobility-Mass Spectrometry and Chemometrics with Kendrick Mass Defect Filter Data Mining.

Nearly 5% of the Shenqi Fuzheng Injection's dry weight comes from the secondary metabolites of Radix codonopsis and Radix astragali. However, the chemical composition of these metabolites is still vague, which hinders the authentication of Shenqi Fuzheng Injection (SFI). Ultra-high performance liquid chromatography with a charged aerosol detector was used to achieve the profiling of these secondary metabolites in SFI in a single chromatogram. The chemical information in the chromatographic profile was characterized by ion mobility and high-resolution mass spectrometry. Polygonal mass defect filtering (PMDF) combined with Kendrick mass defect filtering (KMDF) was performed to screen potential secondary metabolites. A total of 223 secondary metabolites were characterized from the SFI fingerprints, including 58 flavonoids, 71 saponins, 50 alkaloids, 30 polyene and polycynes, and 14 other compounds. Among them, 106 components, mainly flavonoids and saponins, are contributed by Radix astragali, while 54 components, mainly alkaloids and polyene and polycynes, are contributed by Radix codonopsis, with 33 components coming from both herbs. There were 64 components characterized using the KMDF method, which increased the number of characterized components in SFI by 28.70%. This study provides a solid foundation for the authentification of SFIs and the analysis of its chemical composition.

Probiotics for the prevention of atopic dermatitis in infants from different geographic regions: a systematic review and Meta-analysis.

BACKGROUND: Atopic dermatitis (AD) is a common skin disease during infancy, but the preventive effect of probiotics on AD remains unclear. AIM: To evaluate the efficacy of probiotic supplementation for the prevention of AD in infants. METHODS: PubMed, Cochrane Library, and Embase databases were reviewed for relevant randomized controlled trials (RCTs). Two authors independently extracted the data. The primary endpoint was the risk of AD in infants. Risk ratio (RR) and 95% confidence interval (CI) were calculated. RESULTS: A total of 20 related articles including 22 studies were included. A significant reduction in AD risk was revealed for the probiotic group compared to the control group (RR 0.76; 95% CI 0.67-0.87). Subgroup analyses by participant receiving intervention revealed that not only probiotics given to mother (RR 0.70; 95% CI 0.57-0.85) or given to mother and infant (RR 0.76; 95% CI 0.61-0.95) were effective in preventing AD in infants, and probiotics given to infants alone (RR 0.76; 95% CI 0.60-0.96) still effectively decreased the risk of AD. CONCLUSION: Probiotic supplementation reduced the risk of developing AD in infants. Furthermore, probiotic supplementation given to mother or to mother and infant could effectively prevent AD in infants.

In-depth exploration and comparison of chemical constituents from two Lilium species through offline two-dimensional liquid chromatography combined with multimode acquisition of high-resolution mass spectrometry.

Lilium lancifolium and Lilium brownii viridulum were two common cultivars of Lilium in China, which have been used as a source of food in ancient China, and as a traditional herbal medicine in most northern hemispheres countries continues today. However, only a few secondary metabolites in Lilium closely related to human health have been reported. In this research, an offline two-dimensional (HILIC and RP C18) separation system combined with multimode high-resolution mass spectrometry data acquisition was established for in-depth exploration and comparison of the chemical components in Lilium. In total, 331 components were identified, among which phenylpropanoid derivatives and steroidal saponins were the most abundant components. Furthermore, sulfur derivatives and steroidal alkaloids were systematically characterized in Lilium for the first time. These results provided valuable information for in-depth differentiating types of components characterization, which may be applied to assess and improve the edible and medicinal values of Lilium.

Untargeted metabolomics coupled with chemometric analysis deducing robust markers for discrimination of processing procedures: Wine-processed Angelica sinensis as a case study.

Wine-processed Angelica Sinensis is a widely used Chinese medicinal decoction piece in China. However, there are hardly any robust markers indicating the processing procedure of wine-processed Angelica Sinensis, including the amount of rice wine and processing degree. A strategy integrating untargeted metabolomics and chemometric analysis for deducing robust markers was provided and applied to the discrimination of processing procedure. First, 86 compounds were tentatively identified in wine-processed Angelica Sinensis by ultra-high-performance liquid chromatography coupled with quadrupole-time of flight mass spectrometry. Second, 93 potential chemical markers were selected using multivariate analysis, among which nine robust chemical markers were selected by verification with commercial samples. Finally, the effects of processing temperature, time, and amount of rice wine on the three selected chemical markers were investigated through a rapid analytical method. It was demonstrated that both m/z 258.1097 and 238.1189 were positively correlated with the amount of rice wine and processing degree. In summary, this study introduced two candidate processing markers as robust markers for discriminating the processing procedures of wine-processed Angelica sinensis. It also proposed a strategy to provide the reference for the research of other decoction pieces.

Comprehensive feature-based molecular networking and metabolomics approaches to reveal the differences components in Cinnamomum cassia and Cinnamomum verum.

Cinnamon was been a widely used plant in medicinal and spices for a long time and has spread all over the world. However, the differences in the components of the bark from Cinnamomum cassia and Cinnamomum verum, the two most common types of cinnamon, have not been thoroughly investigated. In the present experiment, ultra-high-performance liquid chromatography LTQ-Orbitrap Velos Pro hybrid mass spectrometer-based metabolomics coupled with chemometrics and feature-based molecular networking were employed to dramatically distinguish and annotate Cinnamomum cassia Bark and Cinnamomum verum bark. As a consequence, principal component analysis, orthogonal projection to latent structures discriminates analysis, and heat map analysis demonstrated clear discrimination between the profiles of metabolites in cinnamon. Besides, as the known compounds, proanthocyanidins (cinnamtannin B1 and procyanidin B2) and alkaloids (norboldine, norisoboldine) with variable importance in the projection scores >6, and an unknown alkaloid (formula C24 H33 NO6 ) were selected as the best markers to discriminate cinnamon. Furthermore, large numbers of proanthocyanidins and alkaloids components were identified through feature-based molecular networking for the first time. Our investigation provides new ideas for the discovery of quality markers and identification of unknown components in natural products.

A five-dimensional data collection strategy for multicomponent discovery and characterization in Traditional Chinese Medicine: Gastrodia Rhizoma as a case study.

Establishing the identity of bioactive compounds to control the quality of Traditional Chinese Medicines is made more challenging by the complexity of the metabolite matrix, the existence of isomers, and the range of compound concentration and polarity observed between individual samples of the same plant in a multicomponent preparation. In addition, LC-MS analysis has limited capability for the separation and analysis of potentially important trace compounds and isomers, which hinders the comprehensive metabolite characterization of functional foods and Traditional Natural Medicine. To facilitate and improve the chemical composition characterization and enhance metabolite discernment, a comprehensive strategy was developed which integrates ion mobility mass spectrometry (IMS) with offline two-dimensional liquid chromatography based on hydrophilic interaction chromatography (HILIC) and conventional reversed phase (RP) C18 chromatography. Through application of the HILIC × RP offline 2D-LC approach, trace compounds were enriched and separated promoting a more efficient and detailed analysis of the matrix complexity. Comprehensive non-targeted multidimensional data (Rt1D, Rt2D, MS, CCS and MS/MS) and data-independent-acquisition (DIA) mass data of the metabolites in complex food and drug samples were obtained in the IMS-DIA-MS/MS mode on a Waters-SYNAPT G2-Si mass spectrometer with an ESI source. Through the application of high-efficiency neutral loss (NLs) and diagnostic product ions (DPIs) filter strategies, information from DIA mass data permitted the rapid detection and identification of compounds. The identification coverage of metabolites with low-quality MS/MS data was also improved. In the absence of analytical standards, Collision Cross Section (CCS) prediction and matching strategies based on theoretical chemical structures provided a method to distingish isomers. To demonstrate the efficacy of the technique this comprehensive strategy was applied to the compound characterization of Gastrodia Rhizoma (GR). Characterization of 272 compounds was achieved, including 146 unreported compounds. The results affirm that this comprehensive five-dimensional data collection strategy has the capacity to support the in-depth study of the high level of chemical diversity in Traditional Chinese Medicines.

Research for improvement on the extract efficiency of lignans in traditional Chinese medicines by hybrid ionic liquids: As a case of Suhuang antitussive capsule.

Recently, efficient extraction of natural products from traditional Chinese medicines (TCMs) by green solvents is deemed an essential area of green technology and attracts extensive attentions. In this work, a green protocol for simultaneous ultrasonic-extraction of the native compounds with different polarities of TCMs by using a hybrid ionic liquids (HILs)-water system was reported for the first time. As a case study, three superior ILs (1-ethyl-3-methylimidazolium tetrafluoroborate ([EMIM][BF4]), 1-ethyl-3-methylimidazolium acetate ([EMIM][OAc]), and 1-allyl-3-methylimidazolium chloride ([AMIM]Cl)) were chosen as the compositions of the HILs system, and the TCMs Suhuang antitussive capsule (SH) containing different-polarity lignans was selected. Primarily, an ultra-performance liquid chromatography coupled to triple quadrupole tandem mass spectrometry (UPLC-QqQ-MS/MS) method in the multiple reaction monitoring (MRM) mode was established for qualitative and quantitative analysis of 18 lignans. After majorization by uniform design experiment, the HILs prepared with [AMIM]Cl, [EMIM][BF4], and [EMIM][OAc] at a volume ratio of 1:5:5 could simultaneously extract multi-polarity lignans compared to single IL. Subsequently, the conditions of ultrasonic extraction employing with HILs and traditional organic solvent were optimized by the response surface methodology, respectively. The results indicated that the extract efficiency of the HILs system for target compounds was significantly improved compared with the traditional organic solvent-extraction, i.e. the content of total lignans in ethanol system was up to 47 mg/g, while that in the HILs system was up to 69 mg/g, with an increasing of 47%. Additionally, 1H-NMR and 13C-NMR spectra were used to characterize the hydrogen-bond interactions in the HILs-lignan mixtures. Extraction with the HILs in TCMs is a new application schema of ILs, which not only avoids the use of volatile toxic organic solvents, but also shows the potential to be comprehensively applied for the extraction of bioactive compounds from TCMs.