939 resultados para cell-penetrating peptides


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Microarrays have a wide range of applications in the biomedical field. From the beginning, arrays have mostly been utilized in cancer research, including classification of tumors into different subgroups and identification of clinical associations. In the microarray format, a collection of small features, such as different oligonucleotides, is attached to a solid support. The advantage of microarray technology is the ability to simultaneously measure changes in the levels of multiple biomolecules. Because many diseases, including cancer, are complex, involving an interplay between various genes and environmental factors, the detection of only a single marker molecule is usually insufficient for determining disease status. Thus, a technique that simultaneously collects information on multiple molecules allows better insights into a complex disease. Since microarrays can be custom-manufactured or obtained from a number of commercial providers, understanding data quality and comparability between different platforms is important to enable the use of the technology to areas beyond basic research. When standardized, integrated array data could ultimately help to offer a complete profile of the disease, illuminating mechanisms and genes behind disorders as well as facilitating disease diagnostics. In the first part of this work, we aimed to elucidate the comparability of gene expression measurements from different oligonucleotide and cDNA microarray platforms. We compared three different gene expression microarrays; one was a commercial oligonucleotide microarray and the others commercial and custom-made cDNA microarrays. The filtered gene expression data from the commercial platforms correlated better across experiments (r=0.78-0.86) than the expression data between the custom-made and either of the two commercial platforms (r=0.62-0.76). Although the results from different platforms correlated reasonably well, combining and comparing the measurements were not straightforward. The clone errors on the custom-made array and annotation and technical differences between the platforms introduced variability in the data. In conclusion, the different gene expression microarray platforms provided results sufficiently concordant for the research setting, but the variability represents a challenge for developing diagnostic applications for the microarrays. In the second part of the work, we performed an integrated high-resolution microarray analysis of gene copy number and expression in 38 laryngeal and oral tongue squamous cell carcinoma cell lines and primary tumors. Our aim was to pinpoint genes for which expression was impacted by changes in copy number. The data revealed that especially amplifications had a clear impact on gene expression. Across the genome, 14-32% of genes in the highly amplified regions (copy number ratio >2.5) had associated overexpression. The impact of decreased copy number on gene underexpression was less clear. Using statistical analysis across the samples, we systematically identified hundreds of genes for which an increased copy number was associated with increased expression. For example, our data implied that FADD and PPFIA1 were frequently overexpressed at the 11q13 amplicon in HNSCC. The 11q13 amplicon, including known oncogenes such as CCND1 and CTTN, is well-characterized in different type of cancers, but the roles of FADD and PPFIA1 remain obscure. Taken together, the integrated microarray analysis revealed a number of known as well as novel target genes in altered regions in HNSCC. The identified genes provide a basis for functional validation and may eventually lead to the identification of novel candidates for targeted therapy in HNSCC.

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A quantitative expression has been obtained for the equivalent resistance of an internal short in rechargeable cells under constant voltage charging.

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Proteolytic enzymes, such as matrix metalloproteinases (MMP), are associated to the progression of several cancers. They degrade extracellular components, which helps tumors to expand and cancer cells to escape from the primary site. Of all MMPs, gelatinases (MMP-2 and -9) and membrane type-1 matrix metalloproteinase (MT1-MMP, MMP-14), in particular, are often associated to more aggressive types of head and neck carcinomas as well as to a poorer outcome in patient survival. Although therapies during the last decades have advanced, the mortality of the disease is still rather high and adjuvant therapies are searched for continuously. MMP-9 and MT1-MMP are also involved in neo-angiogenesis, which is necessary for tumor expansion. For this reason, we have identified synthetic peptides-targeting gelatinases and MT1-MMP, and have also evaluated their anticancer effects in vitro and in vivo. Antigelatinolytic peptides effectively inhibited tongue-carcinoma cell invasion and reduced the growth of xenografted tumors. In tumor samples of mice that were treated with antigelatinolytic peptides, the micro-vessel density was significantly reduced. We also identified a novel MT1-MMP targeting peptide and demonstrated that it exerted anticancer effects against several malignant cell lines in vitro. The effects of MT1-MMP inhibition on tongue-squamous cell carcinomas were evaluated by using xenograft tumors, which it effectively inhibited. Tranexamic acid was also demonstrated to inhibit tongue-squamous cell carcinoma invasion, most probably due to its ability to prevent the plasmin-mediated activation of proMMP-9. Leukocyte β2 integrins are another interesting option when evaluating targets for the therapeutic intervention of inflammatory conditions or malignancies of hematopoietic origin, since β2 integrins are expressed mainly by leukocytes. We identified a novel technique for screening small-molecule libraries against β2 integrins, and by using this technique we identified a novel αMβ2 integrin-binding chemical (IMB-10). IMB-10 significantly enhances leukocyte adhesion and inhibits their motility. We also demonstrated that IMB-10 can be used to inhibit inflammation and lymphoma growth in vivo. Interestingly, IMB-10 also reduced leukocyte tumor infiltration and inhibited tumor invasion.

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Live recombinant Saccharomyces cerevisiae yeast expressing the envelope antigen of Japanese encephalitis virus (JEV) on the outer mannoprotein layer of the cell wall were examined for their ability to induce antigen-specific antibody responses in mice. When used as a modelantigen, parenteral immunization of mice with surface-expressing GFP yeast induced a strong anti-GFP antibody response in the absence of adjuvants. This antigen delivery approach was then used for a more stringent system, such as the envelope protein of JEV, which is a neurotropic virus requiring neutralizing antibodies for protection.Although 70% of cells were detected to express the total envelope protein on the surface by antibodies raised to the bacterially expressed protein, polyclonal anti-JEV antibodies failed to react with them. In marked contrast, yeast expressing the envelope fragments 238-398, 373-399 and 373-500 in front of a Gly-Ser linker were detected by anti-JEV antibodies as well as a monoclonal antibody but not by antibodies raised to the bacterially expressed protein. Immunization of mice with these surface-expressing recombinants resulted in a strong antibody response. However, the antibodies failed to neutralize the virus, although the fragments were selected based on neutralizing determinants.

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Analytical models of IEEE 802.11-based WLANs are invariably based on approximations, such as the well-known mean-field approximations proposed by Bianchi for saturated nodes. In this paper, we provide a new approach for modeling the situation when the nodes are not saturated. We study a State Dependent Attempt Rate (SDAR) approximation to model M queues (one queue per node) served by the CSMA/CA protocol as standardized in the IEEE 802.11 DCF. The approximation is that, when n of the M queues are non-empty, the attempt probability of the n non-empty nodes is given by the long-term attempt probability of n saturated nodes as provided by Bianchi's model. This yields a coupled queue system. When packets arrive to the M queues according to independent Poisson processes, we provide an exact model for the coupled queue system with SDAR service. The main contribution of this paper is to provide an analysis of the coupled queue process by studying a lower dimensional process and by introducing a certain conditional independence approximation. We show that the numerical results obtained from our finite buffer analysis are in excellent agreement with the corresponding results obtained from ns-2 simulations. We replace the CSMA/CA protocol as implemented in the ns-2 simulator with the SDAR service model to show that the SDAR approximation provides an accurate model for the CSMA/CA protocol. We also report the simulation speed-ups thus obtained by our model-based simulation.