997 resultados para Cell Patterning


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In cancer, a subpopulation of malignant cells expresses markers of normal stem cells. These cells have the potential of initiating tumor growth and therefore also tumor recurrence. Thus, these cells are called cancer stem cells. A myriad of markers have been applied to identify these cells, but no single marker can be found exclusively in cancer stem cells. In many types of cancer, clinical recurrence and tumor progression are the main causes of mortality, despite intense oncological treatment. It has been proposed that the presence of cancer stem cells causes this resistance to therapy. The scope of this thesis is to investigate the role of stem cell markers and genes in the clinical setting. Especially, the aim was to elucidate the clinical significance of stem cell markers as novel prognostic and diagnostic tools in cancer. Tumor biopsy material from central nervous system tumors (oligodendroglioma, astrocytoma and glioblatoma), neural crest derived tumors (pheochromocytomas) and oral carcinoma was screened for stem cell markers. Initially, 15 stem cell markers were screened in a test series of gliomas. The markers applied for expanded tumor analyses (in 305 cases of glioma, 42 cases of pheochromocytoma, and 73 cases of oral carcinoma) were BMI-1, Snail, p16, mdm2, and c-Myc. Data on marker expression was compared with clinical and pathological parameters. In gliomas, BMI-1 expression was found in nearly all tumors analyzed, but the frequency of BMI-1 expressing cells was highly variable, ranging from 1 to 100%. In oligodendroglioma, BMI-1 expression was identified as a prognostic marker independent of tumor grade and clinical parameters. In pheochromocytoma, Snail expression was shown to distinguish between the metastatic and non-metastatic forms of the tumor. Snail expression was seen only in metastatic tumors, whereas non-metastatic tumors did not commonly express Snail. Finally, in oral carcinoma, BMI-1 expression was seen in roughly 80% of tumors, and Snail expression was high or very high in all cases. The lack of BMI-1 expression was associated with early relapse in oral carcinoma.

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BACKGROUND Hydrogel-based cell cultures are excellent tools for studying physiological events occurring in the growth and proliferation of cells, including cancer cells. Diffusion magnetic resonance is a physical technique that has been widely used for the characterisation of biological systems as well as hydrogels. In this work, we applied diffusion magnetic resonance imaging (MRI) to hydrogel-based cultures of human ovarian cancer cells. METHODS Diffusion-weighted spin-echo MRI measurements were used to obtain spatially-resolved maps of apparent diffusivities for hydrogel samples with different compositions, cell loads and drug (Taxol) treatment regimes. The samples were then characterised using their diffusivity histograms, mean diffusivities and the respective standard deviations, and pairwise Mann-Whitney tests. The elastic moduli of the samples were determined using mechanical compression testing. RESULTS The mean apparent diffusivity of the hydrogels was sensitive to the polymer content, cell load and Taxol treatment. For a given sample composition, the mean apparent diffusivity and the elastic modulus of the hydrogels exhibited a negative correlation. CONCLUSIONS Diffusivity of hydrogel-based cancer cell culture constructs is sensitive to both cell proliferation and Taxol treatment. This suggests that diffusion-weighted imaging is a promising technique for non-invasive monitoring of cancer cell proliferation in hydrogel-based, cellularly-sparse 3D cell cultures. The negative correlation between mean apparent diffusivity and elastic modulus suggests that the diffusion coefficient is indicative of the average density of the physical microenvironment within the hydrogel construct.

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Proximal tubule epithelial cells (PTEC) of the kidney line the proximal tubule downstream of the glomerulus and play a major role in the re-absorption of small molecular weight proteins that may pass through the glomerular filtration process. In the perturbed disease state PTEC also contribute to the inflammatory disease process via both positive and negative mechanisms via the production of inflammatory cytokines which chemo-attract leukocytes and the subsequent down-modulation of these cells to prevent uncontrolled inflammatory responses. It is well established that dendritic cells are responsible for the initiation and direction of adaptive immune responses. Both resident and infiltrating dendritic cells are localised within the tubulointerstitium of the renal cortex, in close apposition to PTEC, in inflammatory disease states. We previously demonstrated that inflammatory PTEC are able to modulate autologous human dendritic cell phenotype and functional responses. Here we extend these findings to characterise the mechanisms of this PTEC immune-modulation using primary human PTEC and autologous monocyte-derived dendritic cells (MoDC) as the model system. We demonstrate that PTEC express three inhibitory molecules: (i) cell surface PD-L1 that induces MoDC expression of PD-L1; (ii) intracellular IDO that maintains the expression of MoDC CD14, drives the expression of CD80, PD-L1 and IL-10 by MoDC and inhibits T cell stimulatory capacity; and (iii) soluble HLA-G (sHLA-G) that inhibits HLA-DR and induces IL-10 expression by MoDC. Collectively the results demonstrate that primary human PTEC are able to modulate autologous DC phenotype and function via multiple complex pathways. Further dissection of these pathways is essential to target therapeutic strategies in the treatment of inflammatory kidney disorders.

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Studies in both vertebrates and invertebrates have identified proteins of the Hedgehog (Hh) family of secreted signaling molecules as key organizers of tissue patterning. Initially discovered in Drosophila in 1992, Hh family members have been discovered in animals with body plans as diverse as those of mammals, insects and echinoderms. In humans three related Hh genes have been identified: Sonic, Indian and Desert hedgehog (Shh, Ihh and Dhh). Transduction of the Hh signal to the cytoplasm utilizes an unusual mechanism involving consecutive repressive interactions between Hh and its receptor components, Patched (Ptc) and Smoothened (Smo). Several cytoplasmic proteins involved in Hh signal transduction are known in Drosophila, but mammalian homologs are known only for the Cubitus interruptus (Ci) transcription factor (GLI(1-3)) and for the Ci/GLI-associated protein, Suppressor of Fused (Su(fu)). In this study I analyzed the mechanisms of how the Hh receptor Ptc regulates the signal transducer Smo, and how Smo relays the Shh signal from the cell surface to the cytoplasm ultimately leading to the activation of GLI transcription factors. In Drosophila, the kinesin-like protein Costal2 (Cos2) is required for suppression of Hh target gene expression in the absence of ligand, and loss of Cos2 causes embryonic lethality. Cos2 acts by bridging Smo to the Ci. Another protein, Su(Fu) exerts a weak suppressive influence on Ci activity and loss of Su(Fu) causes subtle changes in Drosophila wing pattern. This study revealed that domains in Smo that are critical for Cos2 binding in Drosophila are dispensable for mammalian Smo function. Furthermore, by analyzing the function of Su(Fu) and the closest mouse homologs of Cos2 by protein overexpression and RNA interference I found that inhibition of the Hh response pathway in the absence of ligand does not require Cos2 activity, but instead critically depends on the activity of Su(Fu). These results indicate that a major change in the mechanism of action of a conserved signaling pathway occurred during evolution, probably through phenotypic drift made possible by the existence in some species of two parallel pathways acting between the Hh receptor and the Ci/GLI transcription factors. In a second approach to unravel Hh signaling we cloned > 90% of all human full-length protein kinase cDNAs and constructed the corresponding kinase-activity deficient mutants. Using this kinome resource as a screening tool, two kinases, MAP3K10 and DYRK2 were found to regulate Shh signaling. DYRK2 directly phosphorylated and induced the proteasome dependent degradation of the key Hh-pathway regulated transcription factor, GLI2. MAP3K10, in turn, affected GLI2 indirectly by modulating the activity of DYRK2.

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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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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.

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The Baltic countries share public health problems typical of most Eastern European transition economies: morbidity and mortality from non-communicable diseases is higher than in Western European countries. This situation has many similarities compared to a neighbouring country, Finland during the late 1960s. There are reasons to expect that health disadvantage may be increasing among the less advantaged population groups in the Baltic countries. The evidence on social differences in health in the Baltic countries is, however, scattered to studies using different methodologies making comparisons difficult. This study aims to bridge the evidence gap by providing comparable standardized cross-sectional and time trend analyses to the social patterning of variation in health and two key health behaviours i.e. smoking and drinking in Estonia, Latvia, Lithuania and Finland in 1994-2004 representing Eastern European transition countries and a stable Western European country. The data consisted of similar cross-sectional postal surveys conducted in 1994, 1996, 1998, 2000, 2002 and 2004 on adult populations (aged 20 64 years) in Estonia (n=9049), Latvia (n=7685), Lithuania (n=11634) and Finland (n=18821) in connection with the Finbalt Health Monitor project. The main statistical method was logistic regression analysis. Perceived health was found to be worse among both men and women in the Baltic countries than in Finland. Poor health was associated with older age and lower education in all countries studied. Urbanization and marital status were not consistently related to health. The existing educational inequalities in health remained generally stable over time from 1994 to 2004. In the Baltic countries, however, improvement in perceived health was mainly found among the better educated men and women. Daily smoking was associated with young age, lower education and psychological distress in all countries. Among women smoking was also associated with urbanisation in all countries except Estonia. Among Lithuanian women, the educational gradient in smoking was weakest, and the overall prevalence of smoking increased over time. Drinking was generally associated with young age among men and women, and with education among women. Better educated women were more often frequent drinkers and less educated binge drinkers. The exception was that in Latvian men and women both frequent drinking and binge drinking were associated with low education. In conclusion, the Baltic countries are likely to resemble Western European countries rather than other transition societies. While health inequalities did not markedly change, substantial inequalities do remain, and there were indications of favourable developments mainly among the better educated. Pressures towards increasing health inequalities may therefore be visible in the future, which would be in accordance with the results on smoking and drinking in this study.