168 research outputs found

    Computational Analysis of HIV-1 Resistance Based on Gene Expression Profiles and the Virus-Host Interaction Network

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    A very small proportion of people remain negative for HIV infection after repeated HIV-1 viral exposure, which is called HIV-1 resistance. Understanding the mechanism of HIV-1 resistance is important for the development of HIV-1 vaccines and Acquired Immune Deficiency Syndrome (AIDS) therapies. In this study, we analyzed the gene expression profiles of CD4+ T cells from HIV-1-resistant individuals and HIV-susceptible individuals. One hundred eighty-five discriminative HIV-1 resistance genes were identified using the Minimum Redundancy-Maximum Relevance (mRMR) and Incremental Feature Selection (IFS) methods. The virus protein target enrichment analysis of the 185 HIV-1 resistance genes suggested that the HIV-1 protein nef might play an important role in HIV-1 infection. Moreover, we identified 29 infection information exchanger genes from the 185 HIV-1 resistance genes based on a virus-host interaction network analysis. The infection information exchanger genes are located on the shortest paths between virus-targeted proteins and are important for the coordination of virus infection. These proteins may be useful targets for AIDS prevention or therapy, as intervention in these pathways could disrupt communication with virus-targeted proteins and HIV-1 infection

    Regulation of hTERT by BCR-ABL at multiple levels in K562 cells

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    <p>Abstract</p> <p>Background</p> <p>The cytogenetic characteristic of Chronic Myeloid Leukemia (CML) is the formation of the Philadelphia chromosome gene product, BCR-ABL. Given that BCR-ABL is the specific target of Gleevec in CML treatment, we investigated the regulation of the catalytic component of telomerase, hTERT, by BCR-ABL at multiple levels in K562 cells.</p> <p>Methods</p> <p>Molecular techniques such as over expression, knockdown, real-time PCR, immunoprecipitation, western blotting, reporter assay, confocal microscopy, telomerase assays and microarray were used to suggest that hTERT expression and activity is modulated by BCR-ABL at multiple levels.</p> <p>Results</p> <p>Our results suggest that BCR-ABL plays an important role in regulating hTERT in K562 (BCR-ABL positive human leukemia) cells. When Gleevec inhibited the tyrosine kinase activity of BCR-ABL, phosphorylation of hTERT was downregulated, therefore suggesting a positive correlation between BCR-ABL and hTERT. Gleevec treatment inhibited <it>hTERT </it>at mRNA level and significantly reduced telomerase activity (TA) in K562 cells, but not in HL60 or Jurkat cells (BCR-ABL negative cells). We also demonstrated that the transcription factor STAT5a plays a critical role in <it>hTERT </it>gene regulation in K562 cells. Knockdown of STAT5a, but not STAT5b, resulted in a marked downregulation of <it>hTERT </it>mRNA level, TA and hTERT protein level in K562 cells. Furthermore, translocation of hTERT from nucleoli to nucleoplasm was observed in K562 cells induced by Gleevec.</p> <p>Conclusions</p> <p>Our data reveal that BCR-ABL can regulate TA at multiple levels, including transcription, post-translational level, and proper localization. Thus, suppression of cell growth and induction of apoptosis by Gleevec treatment may be partially due to TA inhibition. Additionally, we have identified STAT5a as critical mediator of the <it>hTERT </it>gene expression in BCR-ABL positive CML cells, suggesting that targeting STAT5a may be a promising therapeutic strategy for BCR-ABL positive CML patients.</p

    Foreign aid, instability and governance in Africa

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    This study contributes to the attendant literature by bundling governance dynamics and focusing on foreign aid instability instead of foreign aid. We assess the role of foreign aid instability on governance dynamics in fifty three African countries for the period 1996-2010. An autoregressive endogeneity-robust Generalized Method of Moments is employed. Instabilities are measured in terms of variance of the errors and standard deviations. Three main aid indicators are used, namely: total aid, aid from multilateral donors and bilateral aid. Principal Component Analysis is used to bundle governance indicators, namely: political governance (voice & accountability and political stability/no violence), economic governance (regulation quality and government effectiveness), institutional governance (rule of law and corruption-control) and general governance (political, economic and institutional governance). Our findings show that foreign aid instability increases governance standards, especially political and general governance. Policy implications are discussed
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