Identification of sedative-hypnotic compounds shared by five medicinal Polyporales mushrooms using UPLC-Q-TOF-MS/MS-based untargeted metabolomics.

BACKGROUND: Five Polyporales mushrooms, namely Amauroderma rugosum, Ganoderma lucidum, G. resinaceum, G. sinense and Trametes versicolor, are commonly used in China for managing insomnia. However, their active components for this application are not fully understood, restricting their universal recognition. PURPOSE: In this study, we aimed to identify sedative-hypnotic compounds shared by these five Polyporales mushrooms. STUDY DESIGN AND METHODS: A UPLC-Q-TOF-MS/MS-based untargeted metabolomics, including OPLS-DA (orthogonal projection of potential structure discriminant analysis) and OPLS (orthogonal projections to latent structures) analysis together with mouse assays, were used to identify the main sedative-hypnotic compounds shared by the five Polyporales mushrooms. A pentobarbital sodium-induced sleeping model was used to investigate the sedative-hypnotic effects of the five mushrooms and their sedative-hypnotic compounds. RESULTS: Ninety-two shared compounds in the five mushrooms were identified. Mouse assays showed that these mushrooms exerted sedative-hypnotic effects, with different potencies. Six triterpenes [four ganoderic acids (B, C1, F and H) and two ganoderenic acids (A and D)] were found to be the main sedative-hypnotic compounds shared by the five mushrooms. CONCLUSION: We for the first time found that these six triterpenes contribute to the sedative-hypnotic ability of the five mushrooms. Our novel findings provide pharmacological and chemical justifications for the use of the five medicinal mushrooms in managing insomnia.

Ginsenoside Rg3 in combination with artesunate overcomes sorafenib resistance in hepatoma cell and mouse models.

Background: Sorafenib is effective in treating hepatoma, but most patients develop resistance to it. STAT3 signaling has been implicated in sorafenib resistance. Artesunate (ART) and 20(R)-ginsenoside Rg3 (Rg3) have anti-hepatoma effects and can inhibit STAT3 signaling in cancer cells. This study aimed to evaluate the effects of Rg3 in combination with ART (Rg3-plus-ART) in overcoming sorafenib resistance, and to examine the involvement of STAT3 signaling in these effects. Methods: Sorafenib-resistant HepG2 cells (HepG2-SR) were used to evaluate the in vitro anti-hepatoma effects of Rg3-plus-ART. A HepG2-SR hepatoma-bearing BALB/c-nu/nu mouse model was used to assess the in vivo anti-hepatoma effects of Rg3-plus-ART. CCK-8 assays and Annexin V-FITC/PI double staining were used to examine cell proliferation and apoptosis, respectively. Immunoblotting was employed to examine protein levels. ROS generation was examined by measuring DCF-DA fluorescence. Results: Rg3-plus-ART synergistically reduced viability of, and evoked apoptosis in HepG2-SR cells, and suppressed HepG2-SR tumor growth in mice. Mechanistic studies revealed that Rg3-plus-ART inhibited activation/phosphorylation of Src and STAT3 in HepG2-SR cultures and tumors. The combination also decreased the STAT3 nuclear level and induced ROS production in HepG2-SR cultures. Furthermore, over-activation of STAT3 or removal of ROS diminished the anti-proliferative effects of Rg3-plus-ART, and removal of ROS diminished Rg3-plus-ART's inhibitory effects on STAT3 activation in HepG2-SR cells. Conclusions: Rg3-plus-ART overcomes sorafenib resistance in experimental models, and inhibition of Src/STAT3 signaling and modulation of ROS/STAT3 signaling contribute to the underlying mechanisms. This study provides a pharmacological basis for developing Rg3-plus-ART into a novel modality for treating sorafenib-resistant hepatoma.

Chrysoeriol suppresses hyperproliferation of rheumatoid arthritis fibroblast-like synoviocytes and inhibits JAK2/STAT3 signaling.

BACKGROUND: Fibroblast-like synoviocytes (FLS) have cancer cell-like characteristics, such as abnormal proliferation and resistance to apoptosis, and play a pathogenic role in rheumatoid arthritis (RA). Hyperproliferation of RA-FLS that can be triggered by the activation of interleukin-6/signal transducer and activator of transcription 3 (IL-6/STAT3) signaling destructs cartilage and bone in RA patients. Chrysoeriol is a flavone found in medicinal herbs such as Chrysanthemi Indici Flos (the dried capitulum of Chrysanthemum indicum L.). These herbs are commonly used in treating RA. Chrysoeriol has been shown to exert anti-inflammatory effects and inhibit STAT3 signaling in our previous studies. This study aimed to determine whether chrysoeriol inhibits hyperproliferation of RA-FLS, and whether inhibiting STAT3 signaling is one of the underlying mechanisms. METHODS: IL-6/soluble IL-6 receptor (IL-6/sIL-6R)-stimulated RA-FLS were used to evaluate the effects of chrysoeriol. CCK-8 assay and crystal violet staining were used to examine cell proliferation. Annexin V-FITC/PI double staining was used to detect cell apoptosis. Western blotting was employed to determine protein levels. RESULTS: Chrysoeriol suppressed hyperproliferation of, and evoked apoptosis in, IL-6/sIL-6R-stimulated RA-FLS. The apoptotic effect of chrysoeriol was verified by its ability to cleave caspase-3 and caspase-9. Mechanistic studies revealed that chrysoeriol inhibited activation/phosphorylation of Janus kinase 2 (JAK2, Tyr1007/1008) and STAT3 (Tyr705); decreased STAT3 nuclear level and down-regulated protein levels of Bcl-2 and Mcl-1 that are transcriptionally regulated by STAT3. Over-activation of STAT3 significantly diminished anti-proliferative effects of chrysoeriol in IL-6/sIL-6R-stimulated RA-FLS. CONCLUSIONS: We for the first time demonstrated that chrysoeriol suppresses hyperproliferation of RA-FLS, and suppression of JAK2/STAT3 signaling contributes to the underlying mechanisms. This study provides pharmacological and chemical justifications for the traditional use of chrysoeriol-containing herbs in treating RA, and provides a pharmacological basis for developing chrysoeriol into a novel anti-RA agent.

Detection and classification of organophosphate nerve agent simulants using support vector machines with multiarray sensors.

The need for rapid and accurate detection systems is expanding and the utilization of cross-reactive sensor arrays to detect chemical warfare agents in conjunction with novel computational techniques may prove to be a potential solution to this challenge. We have investigated the detection, prediction, and classification of various organophosphate (OP) nerve agent simulants using sensor arrays with a novel learning scheme known as support vector machines (SVMs). The OPs tested include parathion, malathion, dichlorvos, trichlorfon, paraoxon, and diazinon. A new data reduction software program was written in MATLAB V. 6.1 to extract steady-state and kinetic data from the sensor arrays. The program also creates training sets by mixing and randomly sorting any combination of data categories into both positive and negative cases. The resulting signals were fed into SVM software for "pairwise" and "one" vs all classification. Experimental results for this new paradigm show a significant increase in classification accuracy when compared to artificial neural networks (ANNs). Three kernels, the S2000, the polynomial, and the Gaussian radial basis function (RBF), were tested and compared to the ANN. The following measures of performance were considered in the pairwise classification: receiver operating curve (ROC) Az indices, specificities, and positive predictive values (PPVs). The ROC Az) values, specifities, and PPVs increases ranged from 5% to 25%, 108% to 204%, and 13% to 54%, respectively, in all OP pairs studied when compared to the ANN baseline. Dichlorvos, trichlorfon, and paraoxon were perfectly predicted. Positive prediction for malathion was 95%.