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The Extraction Process Of Saccharum Alhagi And Antitumor Molecular Mechanism Research

Posted on:2017-01-09Degree:MasterType:Thesis
Country:ChinaCandidate:W WangFull Text:PDF
GTID:2284330485464729Subject:Integrative Medicine Clinical Medicine
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Objective: By using orthogonal test- Artificial Neural Network model for optimization of polysaccharide water extraction process from Saccharum Alhagi; and to explore the polysaccharide from Saccharum Alhagi with its compound Abnormal Savda Munziq on S180 tumor mice immune activity influence and in vitro on proliferation and apoptosis of human hepatocellular carcinoma BEL-7402 cells molecular mechanism.Methods:in the L9(3)4 orthogonal test design based on using a three layer Artificial Neural Networks and Genetic Algorithm model, establishment water extraction of polysaccharide from Saccharum Alhagi are the optimal process conditions. On the basis of, the use of CCK8 assay with different concentrations of polysaccharide from Saccharum Alhagi and its compound ASMq on human hepatocellular carcinoma cell line BEL-7402 cell proliferation inhibition; combined with annexin V FITC / PI double staining and flow cytometry technique detection of cell apoptosis and cell cycle; RT-qPCR and Western blot were measured before and after apoptosis related gene and protein expression changes.After by subcutaneous inoculated with S180 tumor cells and establish a model of tumor bearing mice, were used to detect the polysaccharide from Saccharum alhagi with its compound ASMq on mice with S180 solid tumor suppression rate of tumor and organ index;and on the content of serum TNF-α and IFN-γ were detected by ELISA method.Results: 1.Optimum process parameters of polysaccharide from Saccharum Alhagi: extraction temperature is 95℃, extraction time 2h, solid to liquid ratio of 1:6, alcohol precipitation concentration of 70%; under these conditions, the extraction 2 times, and three parallel test,obtained the average polysaccharide extraction rate of 8.77%, very close to the polysaccharide forecast rate of 8.75% and were significantly higher than those inorthogonal test results of 6.45%.2.Different concentrations of Saccharum Alhagi of polysaccharide compounded with the ASMq can significantly inhibited the proliferation of human hepatocellular carcinoma BEL-7402 cells and inhibition rates were concentration dependent manner(P < 0.01).3. polysaccharide from Saccharum Alhagi and its compound ASMq to cell cycle arrest in the G1 phase, and induced apoptosis of human hepatocellular carcinoma BEL-7402 cells.4.polysaccharide from Saccharum Alhagi and its compound ASMq induction and Bcl-2, EGFR mRNA and protein expression levels were downregulated, Bax mRNA and protein expression level increased with the blank control group, compared there was a statistically significant difference(P < 0.05).5.polysaccharide from Saccharum Alhagi and its compound ASMq can inhibit tumor growth and improve a tumor-burdened mice thymus index, spleen and liver index,compared with the control group was statistically significant. 6.polysaccharide from Saccharum Alhagi and its compound ASMq can improve a tumor-burdened mice serum TNF-α and IFN-γ, compared with the control group was statistically significant.Conclusion: Artificial Neural Networks- Algorithms model can comprehensively optimize polysaccharide from Saccharum Alhagi of water extraction process, is an effective measurement tools to predict polysaccharide content. And found in cells in vitro experiment, polysaccharide from Saccharum Alhagi and its compound ASMq can inhibit human liver cancer BEL- 7402 cells proliferation and induce cell apoptosis of liver cancer,the mechanism of apoptosis may be related to Bax expression level raised and EGFR, Bcl- 2 expression level down. At the same time, combined with polysaccharide from Saccharum Alhagi and its compound ASMq in animal studies to understand both can raise a tumor-burdened immune function in mice by promoting a tumor-burdened mice immune cells secreted TNF-α and IFN-γ.
Keywords/Search Tags:Saccharum Alhagi, polysaccharide, Artificial Neural Network, human hepatocellular carcinoma BEL-7402, Abnormal Savda Munziq
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