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Platycodin D (PD), a bioactive triterpenoid saponin isolated from Platycodi Radix (PR), possesses a vast range of biological activities. Although the pharmacological activities and pharmacokinetics of PD have been well demonstrated, information regarding the intestinal metabolisms of PD is very limited. In this study, human and rat fecal microflora were prepared and anaerobically incubated with PD at 37C for 48h, respectively. A highly sensitive and specific ultra performance liquid chromatography/quadrupole time-of-flight mass spectrometry (UPLC-Q-TOF/MS) was developed for the analysis of PD and related metabolites in the reaction samples. A Liquid-liquid extraction method was used for sample pretreatment and the chromatographic separation was performed on a 1.7 m particle size Syncronis C column using gradient elution system. Finally, a total of seven metabolites were detected and tentatively identified, such as the demethylation metabolite (M1), deoxidation metabolites (M3, M7) and hydrolysis at the C-28 oligosaccharide metabolites (M5, M6), which were first discovered in this experiment. The results indicate that hydrolysis, demethylation, dehydroxylation, and acetylation were the major metabolic pathways of PD in vitro. Additionally, four bacterial strains from human feces including Enterococcus sp.41, Bacillus sp.46, Escherichia sp.49 A and Escherichia sp.64 were detected and further identified with 16S rRNA gene sequencing due to their relatively strong metabolic capacity toward PD. The present study provides important information about the metabolism of PD, which will help elucidate the impact of intestinal bacteria on this active component. [ABSTRACT FROM AUTHOR]

Nucleobase and nucleoside compounds exist widely in various organisms. An often occurring problem in the discovery of new bioactive compounds from natural products is reisolation of known nucleobase and nucleoside compounds. To resolve this problem, a capillary electrophoresis-high resolution mass spectrometry (CE-HR-MS) method providing both rapid separation and accurate mass full-scan MS data was developed for the first time to screen and dereplicate known nucleobase and nucleoside compounds in crude extracts of natural products. Instrumental parameters were optimized to obtain optimum conditions for CE separation and electrospray ionization-time-of-flight mass spectrometry (ESI-TOF/MS) detection. The proposed method was verified to be precise, reproducible, and sensitive. Using this method, known nucleobase and nucleoside compounds in different marine medicinal organisms including Syngnathus acus Linnaeus; Hippocampus japonicus Kaup and Anthopleura lanthogrammica Berkly were successfully observed and identified. This work demonstrates that CE-HR-MS combined with an accurate mass database may be used as a powerful tool for dereplicating known nucleobase and nucleoside compounds in different types of natural products. Rapid dereplication of known nucleobase and nucleoside compounds allows researchers to focus on other leads with greater potential to yield new substances. [ABSTRACT FROM AUTHOR]

Two new flavone glycosides were isolated from the seeds of Impatiens balsamina L. and their structures were determined as quercetin-3-O-[α-l-rhamnose-(1 → 2)-β-d-glucopyranosyl]-5-O-β-d-glucopyranoside (1), and quercetin-3-O-[(6'''-O-caffeoyl)-α-l-rhamnose-(1 → 2)-β-d-glucopyranosyl]-5-O-β-d-glucopyranoside (2) on the basis of various spectral and chemical studies. [ABSTRACT FROM AUTHOR]

Background: Like microarray-based investigations, high-throughput proteomics techniques require machine learning algorithms to identify biomarkers that are informative for biological classification problems. Feature selection and classification algorithms need to be robust to noise and outliers in the data. Results: We developed a recursive support vector machine (R-SVM) algorithm to select important genes/biomarkers for the classification of noisy data. We compared its performance to a similar, state-of-the-art method (SVM recursive feature elimination or SVM-RFE), paying special attention to the ability of recovering the true informative genes/biomarkers and the robustness to outliers in the data. Simulation experiments show that a 5 %-~20 % improvement over SVM-RFE can be achieved regard to these properties. The SVM-based methods are also compared with a conventional univariate method and their respective strengths and weaknesses are discussed. RSVM was applied to two sets of SELDI-TOF-MS proteomics data, one from a human breast cancer study and the other from a study on rat liver cirrhosis. Important biomarkers found by the algorithm were validated by follow-up biological experiments. Conclusion: The proposed R-SVM method is suitable for analyzing noisy high-throughput proteomics and microarray data and it outperforms SVM-RFE in the robustness to noise and in the ability to recover informative features. The multivariate SVM-based method outperforms the univariate method in the classification performance, but univariate methods can reveal more of the differentially expressed features especially when there are correlations between the features. [ABSTRACT FROM AUTHOR]

Two new compounds, 5β-pregnane-2α,6α,20(S)-triol (1) and 8-hydroxyl-3-methoxyl-2(1H)-quinolone (2), were isolated fromScolopendra multidensNewport. Their structures were elucidated on the basis of spectroscopic methods including 1D and 2D NMR and HR-TOF-MS. [ABSTRACT FROM PUBLISHER]

The article discusses a study which aims to identify the flavonoid compounds found in the aerial parts of Mentha haplocalyx. The study were refluxed with 40% ethanol and diluted with hydrogen oxide. The study uses the mass and nuclear magnetic resonance (NMR) spectroscopy to identify the compounds. Result shows that isoleucanthogenin, apigenin, and tilianin are some of the compounds in the species.