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Seven new compounds, including three new flavans [tupichinol A-C (1-3)], three new spirostanol sapogenins [tupichigenin D-F (4-6)], and one new pregnane genin [tupipregnenolone (7)], together with 18 known compounds, were isolated from the underground parts of Tupistra chinensis. The structures of the new compounds were elucidated by spectroscopic analysis and chemical evidence. The structures and relative stereochemistry of 1 and 9 were further confirmed by single-crystal X-ray crystallographic analysis. Compounds Delta(25(27))-pentrogenin, 10, and ranmogenin A showed 100%, 96%, and 80% inhibition, respectively, against human gastric tumor (NUGC) cells at a concentration of 50 microM. Delta(25(27))-pentrogenin showed 100% inhibition against human nasopharyngeal carcinoma (HONE-1) cells at a concentration of 50 microM.

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Different geographical origins and species of Paris obtained from southwestern China were discriminated by near infrared (NIR) spectroscopy and high performance liquid chromatography (HPLC) combined with multivariate analysis. The NIR parameter settings were scanning (64 times), resolution (4 cm−1), scanning range (10000 cm−1∼4000 cm−1) and parallel collection (3 times). NIR spectrum was optimized by TQ 8.6 software, and the ranges 7455∼6852 cm−1 and 5973∼4007 cm−1 were selected according to the spectrum standard deviation. The contents of polyphyllin I, polyphyllin II, polyphyllin VI, and polyphyllin VII and total steroid saponins were detected by HPLC. The contents of chemical components data matrix and spectrum data matrix were integrated and analyzed by partial least squares discriminant analysis (PLS-DA). From the PLS-DA model of NIR spectrum, Paris samples were separated into three groups according to the different geographical origins. The R2X and Q2Y described accumulative contribution rates were 99.50% and 94.03% of the total variance, respectively. The PLS-DA model according to 12 species of Paris described 99.62% of the variation in X and predicted 95.23% in Y. The results of the contents of chemical components described differences among collections quantitatively. A multivariate statistical model of PLS-DA showed geographical origins of Paris had a much greater influence on Paris compared with species. NIR and HPLC combined with multivariate analysis could discriminate different geographical origins and different species. The quality of Paris showed regional dependence.

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