No abstract

Vaccinia virus (VV) is a cytocidal virus that causes major changes in host cell

No abstract

No abstract

No abstract

The huge quantities of data available in the CVS repositories of large, long-lived libre (free, open source) software projects, and the many interrelationships among those data offer opportunities for extracting large amounts of valuable information about their structure, evolution and internal processes. Unfortunately, the sheer volume of that information renders it almost unusable without applying methodologies which highlight the relevant information for a given aspect of the project. In this paper, we propose the use of a well known set of methodologies (social network analysis) for characterizing libre software projects, their evolution over time and their internal structure. In addition, we show how we have applied such methodologies to real cases, and extract some preliminary conclusions from that experience.

The ability of dendrimer 2G-[Si{O(CH(2))(2)N(Me)(2) (+)(CH(2))(2)NMe(3) (+)(I(-))(2)}](8) (NN16) to transfect a wide range of cell types, as well as the possible biomedical application in direct or indirect inhibition of HIV replication, was investigated. Cells implicated in HIV infection such as primary peripheral blood mononuclear cells (PBMC) and immortalized suspension cells (lymphocytes), primary macrophages and dendritic cells, and immortalized adherent cells (astrocytes and trophoblasts) were analyzed. Dendrimer toxicity was evaluated by mitochondrial activity, cell membrane rupture, release of lactate dehydrogenase, erythrocyte hemolysis, and the effect on global gene expression profiles using whole-genome human microarrays. Cellular uptake of genetic material was determined using flow cytometry and confocal microscopy. Transfection efficiency and gene knockdown was investigated using dendrimer-delivered antisense oligonucleotides and small interfering RNA (siRNA). Very little cytotoxicity was detected in a variety of cells relevant to HIV infection and erythrocytes after NN16 dendrimer treatment. Imaging of cellular uptake showed high transfection efficiency of genetic material in all cells tested. Interestingly, NN16 further enhanced the reduction of HIV protein 24 antigen release by antisense oligonucleotides due to improved transfection efficiency. Finally, the dendrimer complexed with siRNA exhibited therapeutic potential by specifically inhibiting cyclooxygenase-2 gene expression in HIV-infected nervous system cells. NN16 dendrimers demonstrated the ability to transfect genetic material into a vast array of cells relevant to HIV pathology, combining high efficacy with low toxicity. These results suggest that NN16 dendrimers have the potential to be used as a versatile non-viral vector for gene therapy against HIV infection.

Adverse reactions to capecitabine-based chemotherapy limit full administration of cytotoxic agents. Likewise, genetic variations associated with capecitabine-related adverse reactions are associated with controversial results and a low predictive value. Thus, more evidence on the role of these variations is needed. We evaluated the association between nine polymorphisms in MTHFR, CDA, TYMS, ABCB1, and ENOSF1 and adverse reactions, dose reductions, treatment delays, and overall toxicity in 239 colorectal cancer patients treated with capecitabine-based regimens. The ABCB1*1 haplotype was associated with a high risk of delay in administration or reduction in the dose of capecitabine, diarrhea, and overall toxicity. CDA rs2072671 A was associated with a high risk of overall toxicity. TYMS rs45445694 was associated with a high risk of delay in administration or reduction in the dose of capecitabine, HFS >1 and HFS >2. Finally, ENOSF1 rs2612091 was associated with HFS >1, but was a poorer predictor than TYMS rs45445694. A score based on ABCB1-CDA polymorphisms efficiently predicts patients at high risk of severe overall toxicity (PPV, 54%; sensitivity, 43%) in colorectal cancer patients treated with regimens containing capecitabine. Polymorphisms in ABCB1, CDA, ENOSF1,and TYMS could help to predict specific and overall severe adverse reactions to capecitabine.