14 research outputs found

    An Analysis of the Impact of Guangxi Agricultural Finance, Loan and Insurance on the Trade between Guangxi and CAFTA

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    Financial support, agriculture loan and insurance are the main funding modes for the development of agriculture. This study firstly uses software eviews6.0 to make an analysis of the current state of the Trade between Guangxi and CAFTA, and then makes a study of the data of the funds and the trading volume of Guangxi-ASEAN, and comes to the conclusion that the funds involved has an effect on the trade volume. Generally, government fiscal support curbs the trade while the agricultural loan and the agricultural insurance promote it; however, the case in Guangxi seems the opposite. The trade volume is promoted by government financial support while curbed by loan and insurance

    Comparative proteomic and bioinformatic analysis of the effects of a high-grain diet on the hepatic metabolism in lactating dairy goats.

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    To gain insight on the impart of high-grain diets on liver metabolism in ruminants, we employed a comparative proteomic approach to investigate the proteome-wide effects of diet in lactating dairy goats by conducting a proteomic analysis of the liver extracts of 10 lactating goats fed either a control diet or a high-grain diet. More than 500 protein spots were detected per condition by two-dimensional electrophoresis (2-DE). In total, 52 differentially expressed spots (≥2.0-fold changed) were excised and analyzed using MALDI TOF/TOF. Fifty-one protein spots were successfully identified. Of these, 29 proteins were upregulated, while 22 were downregulated in the high-grain fed vs. control animals. Differential expressions of proteins including alpha enolase, elongation factor 2, calreticulin, cytochrome b5, apolipoprotein A-I, catalase, was verified by mRNA analysis and/or Western blotting. Database searches combined with Gene Ontology (GO) analysis and KEGG pathway analysis revealed that the high-grain diet resulted in altered expression of proteins related to amino acids metabolism. These results suggest new candidate proteins that may contribute to a better understanding of the signaling pathways and mechanisms that mediate liver adaptation to high-grain diet

    GRB7 plays a promoting role in the progression of gastric cancer

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    Abstract Background Gastric cancer is a clinically common tumor, showing an upward trend of both incidence and mortality. GRB7 has been identified as a vital regulator in tumor progression. This study aims to uncover the biological function of GRB7 in gastric cancer process. Methods immunohistochemical (IHC) staining using a tissue microarray (TMA), quantitative reverse transcription PCR (qRT-PCR) and Western blotting were performed to detect the expression of genes. Furthermore, gastric cancer cell lines AGS and MGC-803 were transfected with short hairpin RNAs against GRB7. The biological function of GRB7 in gastric cancer cells were examined by CCK-8, flow cytometry, wound healing and Transwell assays. Then, in vivo tumor formation assay was conducted to explore the effects of GRB7 on tumor growth. Finally, expression levels of proteins related to cell functions were determined by Western blotting. Coimmunoprecipitation (CoIP) assay was performed to assess the protein-protein interaction. Results GRB7 was up-regulated in gastric cancer tissues and cell lines, and its expression was inversely proportional to survival of gastric cancer patients. Moreover, GRB7 knockdown inhibited proliferative, migratory abilities, as well as promoted cell apoptosis in gastric cancer cells. Further study suggested that GRB7 silencing could suppress gastric cancer tumor growth in vivo. Furthermore, our study uncovered an important interaction between GRB7 and MyD88. Silencing MyD88 was observed to alleviate the malignant phenotypes promoted by GRB7 in gastric cancer cells. Conclusions Together, this study provided evidence that GRB7 may be an effective molecular targets for the treatment of gastric cancer

    The primer sequences used for quantitative qRT-PCR of the differentially expressed genes related to diet type.

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    <p>The primer sequences used for quantitative qRT-PCR of the differentially expressed genes related to diet type.</p

    Western blot analysis of calreticulin (CALR; A) and apolipoprotein A-I (ApoA-I; B) in liver tissue samples from high-grain diet and control groups.

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    <p>Protein extracts of liver tissue samples were prepared and subjected to immunodetection with the indicated antibodies. Intensities of CALR and ApoA-I bands were normalized to the corresponding β-actin control. Values are presented as means ± SD; n = 5. * <i>P</i><0.05.</p

    Gene ontology (GO) analysis of differentially expressed proteins.

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    <p>GO annotations are presented by category: A) biological process B) cellular components C) molecular function.</p

    KEGG pathway analysis of differentially expressed proteins.

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    <p>Pathway enrichment analysis was performed using the DAVID web application.</p

    Representative 2-DE images of proteins extracted from dairy goat liver.

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    <p>A) Control group; B) High-grain diet group. Equal amounts of protein (850 µg) were loaded and separated on 17-cm IPG strips (pH 3–10), followed by electrophoresis on 12.5% SDS-PAGE gels for second dimension electrophoresis. The gels were stained with CCB G250. Experiments were performed in triplicate.</p

    2-DE patterns of proteins extracted from dairy goat liver.

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    <p>A. Control group; B. High-grain diet group. Fifty-two differentially expressed proteins showing significant spot intensity changes are marked in A and B. The proteins to which these 52 differentially expressed protein spots correspond are listed in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080698#pone-0080698-t002" target="_blank">Table 2</a>.</p

    Identification of differentially expressed liver proteins.

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    a<p>Numbering corresponds to the 2-DE gel in <a href="http://www.plosone.org/article/info:doi/10.1371/journal.pone.0080698#pone-0080698-g001" target="_blank">Fig.1</a>.</p>b<p>The total number of identified peptide.</p>c<p>Increased(>) or decreased(<) compared with the control group.</p
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