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Andrographis paniculata is a medicinal plant traditionally used to produce diterpene lactones and flavonoids, which possess various biological activities. Widely distributed in China, India, and other Southeast Asia countries, A. paniculata has become an important economic crop, significantly treating SARS-CoV-2, and is being cultivated on a large scale in southern China. The biosynthesis of active ingredients in A. paniculata are regulated and controlled by genes, but their specific roles are still not fully understood. To further explore the growth regulation factors and utilization of its medicinal parts of this industrial crop, chemical and transcriptome analyses were conducted on the roots, stems, and leaves of A. paniculata to identify the biosynthesis pathways and related candidate genes of the active ingredients. The chemical analysis revealed that the main components of A. paniculata were diterpene lactones and flavonoids, which displayed potential ability to treat SARS-CoV-2 through molecular docking. Moreover, the transcriptome sequencing annotated a total of 40,850 unigenes, including 7962 differentially expressed genes. Among these, 120 genes were involved in diterpene lactone biosynthesis and 60 genes were involved in flavonoid biosynthesis. The expression of diterpene lactone-related genes was the highest in leaves and the lowest in roots, consistent with our content determination results. It is speculated that these highly expressed genes in leaves may be involved in the biosynthesis pathway of diterpenes. Furthermore, two class Ⅰ terpene synthases in A. paniculata transcriptome were also annotated, providing reference for the downstream pathway of the diterpene lactone biosynthesis. With their excellent market value, our experiments will promote the study of the biosynthetic genes for active ingredients in A. paniculata and provide insights for subsequent in vitro biosynthesis.

The flower buds of three Panax species (PGF: P. ginseng; PQF: P. quinquefolius; PNF: P. notoginseng) widely consumed as health tea are easily confused in market circulation. We aimed to develop a green, fast, and easy analysis strategy to distinguish PGF, PQF, and PNF. In this work, fast gas chromatography electronic nose (fast GC e-nose), headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS), and headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) were utilized to comprehensively analyze the volatile organic components (VOCs) of three flowers. Meanwhile, a principal component analysis (PCA) and heatmap were applied to distinguish the VOCs identified in PGF, PQF, and PNF. A random forest (RF) analysis was used to screen key factors affecting the discrimination. As a result, 39, 68, and 78 VOCs were identified in three flowers using fast GC e-nose, HS-GC-IMS, and HS-SPME-GC-MS. Nine VOCs were selected as potential chemical markers based on a model of RF for distinguishing these three species. Conclusively, a complete VOC analysis strategy was created to provide a methodological reference for the rapid, simple, and environmentally friendly detection and identification of food products (tea, oil, honey, etc.) and herbs with flavor characteristics and to provide a basis for further specification of their quality and base sources.

Perilla frutescens was an annual herb considered as one of the “One Root of Medicine and Food”, and it was used widely for food and medical treatment. Its main active ingredients were volatile organic compounds (VOCs), but it was easily affected during drying and storage. The leaves, seeds and stems had shown differences in therapeutic effects, but the underlying reason remained unclear. In the present work, headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) and headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC–MS) were utilized to effectively and comprehensively analyze VOCs of fresh and dried P. frutescens between the leaves, stems and seeds. Meanwhile, chemometric analysis was applied to compare and identify characteristic volatile markers. As a result, 60 VOCs were identified by HS-GC-IMS and 115 VOCs were identified by HS-SPME-GC–MS from P. frutescen. 25 potential volatile markers were selected based on a combination model of orthogonal partial least squares discriminant analysis (OPLS-DA) and random forest (RF). The models could be used to analyze the variation between fresh and dried P. frutescens and distinguish the differences in different parts effectively and comprehensively. It was the first research regarding the method development of HS-GC-IMS and HS-SPME-GC–MS that comprehensively analyzes the VOCs characterization of fresh and dried P. frutescens in different parts and the findings obtained would evaluate the quality and provide a reference for further exploration of the edible and medicinal effects of P. frutescens.

Lasianthus, belonging to Rubiaceae, has been verified to improve clinical syndrome in immune diseases (e.g., hepatitis, nephritis, and rheumatoid arthritis). Both the anti-inflammatory function and chemical composition of Lasianthus vary considerably between different species but few studies focus. So essential it is to explore lasianthus and further search for anti-inflammatory substances. The target of this artical is to analyze the anti-inflammatory activity and chemical composition of lasianthus of different species. And the subsequent active compounds were explored. Primary, the anti-inflammatory activity among seven species of lasianthus (e.g., L. fordii., L. wallichii., L. hookeri C., L. verticillatus., L. sikkimensis., L. appressihirtus., and L. hookeri var) were evaluated by vitro experiments (RAW 264.7 cells). Next, UHPLC/Q-Orbitrap-MS-based metabolomics and the mass defect filter (MDF) algorithm were performed to explore metabolites. In addition, principal component analysis (PCA) was to screen out differential compounds in seven species. Finally, the correlation analysis between activities and composition to rapidly discover the active compounds (compounds were verified pharmacologically). Among the 7 species of lasianthus, the L. fordii. and L. hookeri C indicated the best anti-inflammatory activity. Untargeted metabolomics and MDF show 112 compounds, classified into six dominant types (e.g., flavonoids, phenolic acids, alkaloids, iridoids, coumarins, and anthraquinones). Furthermore, 33 differential metabolites were confirmed by PCA. Then according to correlation analysis and pharmacological validation, 7 compounds IC50＜100 (e.g., scopoletin, asperulosidic acid, chlorogenic acid, ferulic acid, betaine, syringic acid, and emodin) were verified as anti-inflammatory compounds and conduct quantitative analysis. Metabolomics integrated with activities evaluation might be a rapid and effective strategy to explore the active compounds from natural products.

This work was designed to investigate the dynamic changes process of non-volatile organic compounds (n-VOCs) and volatile organic compounds (VOCs) in mulberries during different growth periods using UPLC-Q-Orbitrap-MS, HS-SPME-GC-MS, and HS-GC-IMS. A total of 166 compounds were identified, including 68 n-VOCs and 98 VOCs. Furthermore, principal component analysis (PCA), random forest analysis (RFA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to analyze differences in mulberries at different ripening stages. A total of 74 compounds appeared or disappeared at different ripening periods and 24 compounds were presented throughout the growth process. Quantitative analysis and antioxidant experiments revealed that as the mulberries continued to mature, flavonoids and phenolic acids continued to increase, and the best antioxidant activity occurred from stage IV. Conclusively, an effective strategy was established for analyzing the composition change process during different growth periods, which could assist in achieving dynamic change process analysis and quality control.

IntroductionMachine learning (ML) has gained intensive popularity in various fields, such as disease diagnosis in healthcare. However, it has limitation for single algorithm to explore the diagnosing value of dilated cardiomyopathy (DCM). We aim to develop a novel overall normalized sum weight of multiple-model MLs to assess the diagnosing value in DCM.MethodsGene expression data were selected from previously published databases (six sets of eligible microarrays, 386 samples) with eligible criteria. Two sets of microarrays were used as training; the others were studied in the testing sets (ratio 5:1). Totally, we identified 20 differently expressed genes (DEGs) between DCM and control individuals (7 upregulated and 13 down-regulated).ResultsWe developed six classification ML methods to identify potential candidate genes based on their overall weights. Three genes, serine proteinase inhibitor A3 (SERPINA3), frizzled-related proteins (FRPs) 3 (FRZB), and ficolin 3 (FCN3) were finally identified as the receiver operating characteristic (ROC). Interestingly, we found all three genes correlated considerably with plasma cells. Importantly, not only in training sets but also testing sets, the areas under the curve (AUCs) for SERPINA3, FRZB, and FCN3 were greater than 0.88. The ROC of SERPINA3 was significantly high (0.940 in training and 0.918 in testing sets), indicating it is a potentially functional gene in DCM. Especially, the plasma levels in DCM patients of SERPINA3, FCN, and FRZB were significant compared with healthy control.DiscussionSERPINA3, FRZB, and FCN3 might be potential diagnosis targets for DCM, Further verification work could be implemented.

Acori tatarinowii rhizome (ATR) is a Traditional Chinese Medicine (TCM), which has multiple effects, such as neuroprotective activity, antidepressant and other activity. However, the widespread cultivation of ATR has led to it varying quality. Therefore, it is important to find a method to quickly identify the components of ATR. Headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) and headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC–MS) were applied to analyze and characterize the volatile organic compounds (VOCs) of ATR. 33 VOCs were identified by HS-GC-IMS and 95 VOCs were identified by HS-SPME-GC–MS from 15 batches of ATR. Then, quantification of estragole, methyleugenol, γ-asarone, β-asarone and asarone by gas chromatography-mass spectrometry (GC–MS). The fingerprint of HS-GC-IMS and the heatmap of HS-SPME-GC–MS were established. Which compared differential components of ATR. In addition, principal component analysis (PCA) was performed on the results of both instruments. The VOCs in the ATR were significantly correlated with β-asarone and asarone by PatternHunter analysis. It assisted HS-GC-IMS determine ATR quality. It is the first report regarding the method development of HS-GC-IMS and HS-SPME-GC–MS that targets the VOCs characterization of ATR, and the findings obtained would benefit the quality control and distinguish the complex analytical objects of ATR.

Verbena officinalis Linn. is a kind of traditional Chinese medicine, which has a long history of application and shows good effects on neuroprotection. Therefore, we consider that V. officinalis may be a potential drug for treating Alzheimer’s disease (AD). First, ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) pointed out that the main chemical components in V. officinalis were iridoid glycosides, phenylethanoid glycosides, and flavonoids. These compounds were used for molecular docking and the results showed that these compounds had good anti-AD activity. To explore the biosynthetic pathway of anti-AD components in V. officinalis, UPLC and ultraviolet (UV) spectrophotometry were used for contents determination and the result was leaf > stem > root. At the same time, 92,867 unigenes were annotated in V. officinalis transcriptome; 206, 229, 115 related unigenes were, respectively, annotated in iridoid glycoside, phenylethanoid glycoside, and flavonoid pathway, of which 61, 73, and 35 were differential expression genes. The components had relatively high expression in leaves, which was consistent with the quantitative results. In addition, the tissue distribution particularity of verbenalin may be related to the branching of pathways. Meanwhile transcription factors VoWRKY6 and VoWRKY7 may be involved in the regulation of iridoid glycoside biosynthesis. Further, VoWRKY3, VoWRKY9, and VoWRKY12 may be related to flavonoid biosynthesis. The above research is helpful to explore the biosynthetic pathway of anti-AD components and the regulation mechanism of active components and to further explore the anti-AD effect of V. officinalis.

Lamiophlomis rotata (Benth.) Kudo (L. rotata) belongs to Lamiaceae family, which is an important medicinal plant endemic to Qinghai Tibet Plateau. Traditionally, the whole herb of L. rotata is used for medicine, especially for the treatment of rheumatoid arthritis (RA) in clinical practise. As a result of absolute digging, the plant has a long regeneration cycle after excavation and the damage to plateau grassland ecological environment is difficult to recover. It has been encouraged to use aerial part of the plant with the purpose of protecting environment and maintaning biological diversity. At present, researchers have compared the primary metabolites and iridoids between aerial parts and roots, but there are few reports on the chemical differences and activity comparison of secondary metabolites. In order to characterize the secondary metabolites of different parts, UPLC/Q-Orbitrap-MS was employed to collect data from the extracts of aerial parts and roots, in combination with plant metabolomics technology to screen and quantify differential metabolites. At the same time, network pharmacological analysis with rheumatoid arthritis and immunity as the key words was carried out according to the identification results to clarify the active ingredients of L. rotata in the treatment of RA, so as to speculate the pharmacological effects of aerial parts and roots based on the distribution of active components. A total of 16 potential markers were selected and identified to differentiate two parts. Among them, 8 characteristic flavonoids with similar skeletons were unique in aerial parts, while the other 8 components, including 2 iridoid glycosides and 6 phenylethanoid glycosides, were detected in both aerial parts and roots, but with differentiate contents. Among the predicted 6 active components, there were 5 flavonoids, of which 3 (namely luteolin, apigenin and 2″-acetylastragalin) were still differential metabolites and mainly distributed in the aerial parts. The results revealed that certain flavonoids as potential markers made a distinction between aerial part and root of L. rotata, and were the main active components against RA, which provided a theoretical basis for the aerial parts to replace the whole herbs, and laid a material foundation for further pharmacological research.

Quality evaluation of phytomedicines is limited to small molecules as quality markers, even for herbs with high sugar contents. We established a high-resolution method for distinguishing similar medicinal materials using sugar as quality marker, taking Schisandrae Chinensis Fructus (SCF) and Schisandrae Sphenantherae Fructus (SSF) as an example. High performance liquid chromatography with an evaporative light-scattering detector (HPLC-ELSD), high performance size exclusion chromatography coupled with multi-angle laser light scattering detector and refractive index detector (HPSEC-MALLS-RID) and high performance liquid chromatography with photo-diode array (HPLC-PDA) after 1-phenyl-3-methyl-5-pyrazolone (PMP) pre-column derivatization were used respectively to determine monosaccharide contents, molecular weights and monosaccharide compositions of polysaccharides in this study. The differences of SCF and SSF from ten producing areas were compared by principal component analysis (PCA) and hierarchical cluster analysis (HCA). Results showed that contents of fructose and glucose were similar between SCF and SSF. Molecular weight (Mw) of SCF polysaccharides was ranging from 1.561 × 102 to 6.599 × 102 kDa, and that of SSF polysaccharides was ranging from 8.524 × 102 to 1.7416 × 103 kDa. Schisandra polysaccharides were mainly composed of mannose, galacturonic acid, glucose, galactose and arabinose. Based on PCA and HCA, SCF and SSF from ten different areas were classified into three categories. With great accuracy, sensitivity and stability, the methods established in this study had important reference value for quality evaluation, development and utilization of saccharide components in medicinal materials.

Zingiber corallinum and Zingiber montanum, which belong to the Zingiberaceae family, are traditional Chinese folk medicinal herbs in Guizhou and Yunnan Province of China. They share great similarities in morphology, chemical constituent, and DNA barcoding sequence. The taxonomy of the two Zingiber species is controversial and discrimination of traditional Chinese medicines directly affects the pharmacological and clinical effects. In the present study, we performed a systemic analysis of “super-barcode” and untargeted metabolomics between Z. corallinum and Z. montanum using chloroplast (cp) genome sequencing and gas chromatography-mass spectrometry (GC-MS) analysis. Comparison and phylogenetic analysis of cp genomes of the two Zingiber species showed that the cp genome could not guarantee the accuracy of identification. An untargeted metabolomics strategy combining GC-MS with chemometric methods was proposed to distinguish the Zingiber samples of known variety. A total of 51 volatile compounds extracted from Z. corallinum and Z. montanum were identified, and nine compounds were selected as candidate metabolic markers to reveal the significant difference between Z. corallinum and Z. montanum. The performance of the untargeted metabolomic approach was verified with unknown Zingiber samples. Although the cp genomes could not be used to identify Zingiber species in this study, it will still provide a valuable genomics resource for population studies in the Zingiberaceae family, and the GC-MS based metabolic fingerprint is more promising for species identification and safe application of Z. corallinum and Z. montanum.

The co-elution, pervasive isomers, and frequently occurring in-source fragmentation definitely hinder the comprehensive characterization of the multiple components from traditional Chinese medicine (TCM) by liquid chromatography/mass spectrometry. Herein, a dimension-enhanced strategy, by utilizing an ion mobility quadrupole time-of-flight mass spectrometer coupled to ultra-high performance liquid chromatography (UHPLC/IM-QTOF-MS) with the ability of offering four-dimensional information (retention time, Rt; drift time or collision cross section, CCS; accurate mass of precursors; and accurate MS2 product ions), is presented. Shuanghe Decoction (SHD) is a classic tonifying formula composed of nine herbs, however, little is known to its chemical complexity, hitherto. Good chromatographic separation was achieved on an HSS T3 column, and by the Vion™ IMS-QTOF high-resolution mass spectrometer, data-independent MSE and High-Definition MSE (HDMSE) in both the negative and positive electrospray ionization modes were employed for acquiring the collision-induced dissociation-MS2 data. A self-built database, including 642 known compounds, was established, which assisted to perform the automated peak annotation by UNIFI™. By reference to 55 compounds, totally 236 components were identified or tentatively characterized from SHD with 4D data recorded. The combination of negative and positive modes could yield more information complementary to structural elucidation. Compared with the conventional MSE, HDMSE exhibit of merits in the provision of CCS, better separation and detection those easily co-eluting components, and reduction of the false positives in the identification results. Conclusively, the combination of HDMSE acquisition, in-house library, and UNIFI-facilitated automated peak annotation, renders a potent approach dedicated to deconvoluting the chemical composition of complex systems like TCM formulae.

The pericarps of Zanthoxylum bungeanum (ZBP) and leaves of Zanthoxylum bungeanum (ZBL) are popular spices in China, and they have pharmacological activities as well. In this experiment, the volatile organic compounds (VOCs) of the pericarps of Zanthoxylum bungeanum in Sichuan (SJ) and its leaves (SJY) and the pericarps of Zanthoxylum bungeanum in Shaanxi (SHJ) and its leaves (SHJY) were analyzed by headspace-gas chromatography-ion mobility spectrometry (HS-GC-IMS) and headspace solid phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS). The fingerprint of HS-GC-IMS and the heat maps of HS-SPME-GC-MS were established. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed. The results showed that a total of 95 components were identified, 62 components identified by HS-SPME-GC-MS and 40 components identified by HS-GC-IMS, of which 7 were the same. The analysis found that SJ and SHJ were obviously distinguished, while SJY and SHJY were not. There were considerably fewer VOCs in the leaves than in the pericarps. In the characterization of the VOCs of ZBL and ZBP, the flavor of ZBP was more acrid and stronger, while the flavor of ZBL was lighter and slightly acrid. Thirteen and eleven differential markers were identified by HS-GC-IMS and HS-SPME-GC-MS, respectively. This is helpful in distinguishing between SHJ and SJ, which contributes to their quality evaluation.

Volatile organic compounds (VOCs) are the main chemical components of Schizonepetae Spica (SS), which have positive effects on the quality evaluation of SS. In this study, HS-SPME-GC-MS (headspace solid-phase microextraction-gas chromatography-mass spectrometry) and HS-GC-IMS (headspace-gas chromatography-ion mobility spectrometry) were performed to characterize the VOCs of SS from six different regions. A total of 82 VOCs were identified. In addition, this work compared the suitability of two instruments to distinguish SS from different habitats. The regional classification using orthogonal partial least squares discriminant analysis (OPLS-DA) shows that the HS-GC-IMS method can classify samples better than the HS-SPME-GC-MS. This study provided a reference method for identification of the SS from different origins.

Trimethylamine N-oxide (TMAO), as a gut-derived metabolite, has been found to be associated with enhanced risk for atherosclerosis and cardiovascular disease. We presented a method for targeted profiling of TMAO and betaine in serum and food samples based on a combination of one-step sample pretreatment and proton nuclear magnetic resonance spectroscopy. The key step included a processing of sample preparation using a selective solid-phase extraction column for retention of basic metabolites. Proton signals at δ 3.29 and δ 3.28 were employed to quantify TMAO and betaine, respectively. The developed method was examined with acceptable linear relationship, precision, stability, repeatability, and accuracy. It was successfully applied to detect serum levels of TMAO and betaine in TMAO-fed mice and high-fructose-fed rats and also used to determine the contents of TMAO and betaine in several kinds of food, such as fish, pork, milk, and egg yolk.

The complexity of herbal matrix necessitates the development of powerful analytical strategies to enable comprehensive multicomponent characterization. In this work, targeting the multicomponents from Panax japonicus C.A. Meyer, both data dependent acquisition (DDA) and data-independent high-definition MSE (HDMSE) in the negative electrospray ionization mode were used to extend the coverage of untargeted metabolites characterization by ultra-high-performance liquid chromatography (UHPLC) coupled to a VionTM IM-QTOF (ion-mobility/quadrupole time-of-flight) high-resolution mass spectrometer. Efficient chromatographic separation was achieved by using a BEH Shield RP18 column. Optimized mass-dependent ramp collision energy of DDA enabled more balanced MS/MS fragmentation for mono- to penta-glycosidic ginsenosides. An in-house ginsenoside database containing 504 known ginsenosides and 60 reference compounds was established and incorporated into UNIFITM, by which efficient and automated peak annotation was accomplished. By streamlined data processing workflows, we could identify or tentatively characterize 178 saponins from P. japonicus, of which 75 may have not been isolated from the Panax genus. Amongst them, 168 ginsenosides were characterized based on the DDA data, while 10 ones were newly identified from the HDMSE data, which indicated their complementary role. Conclusively, the in-depth deconvolution and characterization of multicomponents from P. japonicus were achieved, and the approaches we developed can be an example for comprehensive chemical basis elucidation of traditional Chinese medicine (TCM).

The flower buds of three Panax species (PGF: flower bud of P. ginseng; PQF: flower bud of P. quinquefolius; PNF: flower bud of P. notoginseng), widely consumed as healthcare products, are easily confused particularly in the extracts or traditional Chinese medicine (TCM) formulae. We are aimed to develop an untargeted metabolomics approach, by ultra-high performance liquid chromatography/ion mobility-quadrupole time-of-flight mass spectrometry (UHPLC/IM-QTOF-MS) to unveil the chemical markers diagnostic for the differentiation of PGF, PQF, and PNF. Key parameters affecting chromatographic separation and MS detection were optimized in sequence. Forty-two batches of flower bud samples were analyzed in negative high-definition MSE (HDMSE; enabling three-dimensional separations). Efficient metabolomics data processing was performed by Progenesis QI (Waters, Milford, MA, USA), while pattern-recognition chemometrics was applied for species classification and potential markers discovery. Reference compounds comparison, analysis of both HDMSE and targeted MS/MS data, and retrieval of an in-house ginsenoside library, were simultaneously utilized for the identification of discovered potential markers. Satisfactory conditions for metabolite profiling were achieved on a BEH Shield RP18 column and Vion™ IMS-QTOF instrument (Waters; by setting the capillary voltage of 1.0 kV and the cone of voltage 20 V) within 37 min. A total of 32 components were identified as the potential markers, of which Rb3, Ra1, isomer of m-Rc/m-Rb2/m-Rb3, isomer of Ra1/Ra2, Rb1, and isomer of Ra3, were the most important for differentiating among PGF, PQF, and PNF. Conclusively, UHPLC/IM-QTOF-MS-based metabolomics is a powerful tool for the authentication of TCM at the metabolome level.

Chinese medical preparation has complicated chemical constituents. Consequently, the proper quality control methods for these Chinese medical preparations have been great challenges to the traditional Chinese medicine modernization and internationalization. What components should be chosen for quality control is a big challenge in the development of traditional Chinese medicine. A new concept of “Quality Marker” was proposed by Liu et al. to solve this problem and established a new research paradigm for traditional Chinese medicine quality study. Several strategies were proposed by the researchers in traditional Chinese medicine, here, we used Shengmai injection as an example to discuss a strategy for selecting “Quality Markers” of Chinese medical preparation by the components transfer process analysis in the Shengmai injection manufacturing process. Firstly, a total of 87 compounds were identified or partially characterized in shengmai injection. Secondly, referenced to the quality control method in China pharmacopeia and considered the biomarkers in the original medicines and representative components in the manufacturing process, four ginsenosides in Panax ginseng (Hongshen), two compounds in Schisandra chinensis (Wuweizi), and a sugar from Ophiopogon japonicas (Maidong) were quantified. As a result, these seven representative compounds exhibited an acceptable transitivity throughout the Shengmai injection manufacturing process. Finally, combined with the active ingredients, components transfer process analysis, and comprehensive evaluation by “Spider-web” analysis, six compounds were selected as the quality markers for the quality control of Shengmai injection. Through this strategy of optimization for quality markers of Shengmai injection, we found that these six compounds could represent the main bioactive substances and be easily detected in the whole process of production. Furthermore, the quality control method was developed for quality assessment and control of these six quality markers in the Shengmai injection. The total content range of the selected quality markers in the 10 batches of the Shengmai injection is 13.844-22.557 mg/mL.

Russula vinosa Lindbl is a wild edible mushroom that is usually used for original material of food and soup and has rich nutritional value. What are the nutritional ingredients? In order to answer this question, we investigated the chemical constituents of this wild functional food. Six new compounds (1–6), together with nine known ones (7–15), were isolated from R. vinosa. The six new compounds were named as vinosane (1), rulepidadione C (2), (24E)-3,4-seco-cucurbita-4,24-diene-26,29-dioic acid-3-methyl ester (3), (24E)-3,4-seco-cucurbita-4,24-diene-26-oic acid-3-ethyl ester (4), (24E)-3β-hydroxycucurbita-5,24-diene-26,29-dioic acid (5), and (2S,3S,4R,2′R)-2-(2′-hydroxydocosanoylamino)eicosane-1,3,4-triol (6). Their structures were determined based on spectroscopic methods including HR-ESI-MS, 1D, and 2D NMR. Moreover, a cell counting kit-8 (CCK-8 kit) was used to screen for the cytotoxicity of compounds 1–5 and 7–13 on mouse macrophage RAW 264.7 cells. The results showed that compounds 1–5 and 7–13 had no obvious cytotoxicity. In addition, the inhibitory effects on nitric oxide (NO) production in lipopolysaccharide (LPS)-activated mouse macrophage RAW 264.7 cells were evaluated. Compounds 1, 3, 4, 7, 12, and 13 showed moderate inhibitory activity on NO production.

Rationale: Kaixin San (KXS) is a prescription traditional Chinese medicine (TCM) with the effects of "tonifying the kidney and brain" and "improving memory". The volatile organic compounds (VOCs) in KXS could effectively improve senile dementia and depression, but only few studies have focused on the overall characterization of VOCs in KXS and the quantitative study of the main active components. Methods: We have developed a strategy to correlate the results from headspace gas chromatography/ion mobility spectrometry (HS-GC/IMS) and headspace gas chromatography/mass spectrometry (HS-GC/MS) for the comprehensive characterization of VOCs in KXS and the quantitative analysis of the main pharmacodynamic substances. Results: A totsal of 68 low molecular weight VOCs were identified in KXS by HSGC/IMS at room temperature and atmospheric pressure; 117 VOCs were identified and 10 components (isocalamenediol, α-asarone, β-asarone, methyl eugenol, isoeugenol methyl ether, camphor, anethol, 2,4-di-tert-butylphol, linalool, asarylaldehyde) as the quality markers of KXS based on HS-GC/MS. Conclusions: This results from this study provide a foundation for quality control, pharmacodynamic mechanism research and further development of KXS, and provides more convincing data supporting the VOCs of other natural products. [ABSTRACT FROM AUTHOR]