1000 resultados para COMPLEX MICELLES


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Recent studies have demonstrated that IGF-I associates with VN through IGF-binding proteins (IGFBP) which in turn modulate IGF-stimulated biological functions such as cell proliferation, attachment and migration. Since IGFs play important roles in transformation and progression of breast tumours, we aimed to describe the effects of IGF-I:IGFBP:VN complexes on breast cell function and to dissect mechanisms underlying these responses. In this study we demonstrate that substrate-bound IGF-I:IGFBP:VN complexes are potent stimulators of MCF-7 breast cell survival, which is mediated by a transient activation of ERK/MAPK and sustained activation of PI3-K/AKT pathways. Furthermore, use of pharmacological inhibitors of the MAPK and PI3-K pathways confirms that both pathways are involved in IGF-I:IGFBP:VN complex-mediated increased cell survival. Microarray analysis of cells stimulated to migrate in response to IGF-I:IGFBP:VN complexes identified differential expression of genes with previously reported roles in migration, invasion and survival (Ephrin-B2, Sharp-2, Tissue-factor, Stratifin, PAI-1, IRS-1). These changes were not detected when the IGF-I analogue (\[L24]\[A31]-IGF-I), which fails to bind to the IGF-I receptor, was substituted; confirming the IGF-I-dependent differential expression of genes associated with enhanced cell migration. Taken together, these studies have established that IGF-I:IGFBP:VN complexes enhance breast cell migration and survival, processes central to facilitating metastasis. This study highlights the interdependence of ECM and growth factor interactions in biological functions critical for metastasis and identifies potential novel therapeutic targets directed at preventing breast cancer progression.

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hSSB1 is a recently discovered single-stranded DNA binding protein that is essential for efficient repair of DNA double-strand breaks (DSBs) by the homologous recombination pathway. hSSB1 is required for the efficient recruitment of the MRN complex to sites of DSBs and for the efficient initiation of ATM dependent signalling. Here we explore the interplay between hSSB1 and MRN. We demonstrate that hSSB1 binds directly to NBS1, a component of the MRN complex, in a DNA damage independent manner. Consistent with the direct interaction, we observe that hSSB1 greatly stimulates the endo-nuclease activity of the MRN complex, a process that requires the C-terminal tail of hSSB1. Interestingly, analysis of two point mutations in NBS1, associated with Nijmegen breakage syndrome, revealed weaker binding to hSSB1, suggesting a possible disease mechanism.

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hSSB1 is a newly discovered single-stranded DNA (ssDNA)-binding protein that is essential for efficient DNA double-strand break signalling through ATM. However, the mechanism by which hSSB1 functions to allow efficient signalling is unknown. Here, we show that hSSB1 is recruited rapidly to sites of double-strand DNA breaks (DSBs) in all interphase cells (G1, S and G2) independently of, CtIP, MDC1 and the MRN complex (Rad50, Mre11, NBS1). However expansion of hSSB1 from the DSB site requires the function of MRN. Strikingly, silencing of hSSB1 prevents foci formation as well as recruitment of MRN to sites of DSBs and leads to a subsequent defect in resection of DSBs as evident by defective RPA and ssDNA generation. Our data suggests that hSSB1 functions upstream of MRN to promote its recruitment at DSBs and is required for efficient resection of DSBs. These findings, together with previous work establish essential roles of hSSB1 in controlling ATM activation and activity, and subsequent DSB resection and homologous recombination (HR).

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This research investigated the role of mother-centred issues that influence breastfeeding behaviours. The need for social marketing research for breastfeeding is indicated by the fact that despite evidence of the health benefits to both the infant and mother of longer breastfeeding duration, rates in developed countries have failed to increase in recent decades. Breastfeeding is a complex behaviour that for many women involves barriers that influence their commitment to continue breastfeeding. Structural equation modelling was used on a sample of 405 respondents to an online survey. The analysis revealed that personal social support had a significant impact on breastfeeding self-efficacy, which in turn had a significant impact on breastfeeding behaviour. The findings and implications for both social marketing theory and practice are discussed.

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The thermal behavior and decomposition of kaolinite-potassium acetate intercalation complex was investigated through a combination of thermogravimetric analysis and infrared emission spectroscopy. Three main changes were observed at 48, 280, 323 and 460 °C which were attributed to (a) the loss of adsorbed water (b) loss of the water coordinated to acetate ion in the layer of kaolinite (c) loss of potassium acetate in the complex and (d) water through dehydroxylation. It is proposed that the KAc intercalation complex is stability except heating at above 300 °C. The infrared emission spectra clearly show the decomposition and dehydroxylation of the kaolinite intercalation complex when the temperature is raised. The dehydration of the intercalation complex is followed by the loss of intensity of the stretching vibration bands at region 3600-3200 cm-1. Dehydroxylation is followed by the decrease in intensity in the bands between 3695 and 3620 cm-1. Dehydration is completed by 400 °C and partial dehydroxylation by 650 °C. The inner hydroxyl group remained until around 700 °C.

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Mid-infrared (MIR) and near-infrared (NIR) spectroscopy have been used to study the molecular structure of halloysite and potassium acetate intercalated halloysite and to determine the structural changes of halloysite through intercalation. The MIR spectra show all fundamental vibrations including the hydroxyl units, basic aluminosilicate framework and water molecules in the structure of halloysite and its intercalation complex. Comparison between halloysite and halloysite-potassium acetate intercalation complex shows almost all bands observed for halloysite are also observed for halloysite-potassium acetate intercalation complex apart from bands observed in the 1700-1300 cm-1 region, but with differences in band intensity. However, NIR, based on MIR spectra, provide sufficient evidence to analyze the structural changes of halloysite through intercalation. There are obvious differences between halloysite and halloysite-potassium acetate intercalation complex in the all spectral ranges. Therefore, the reproducibility of measurement and richness of qualitative information should be simultaneously considered for proper selection of a spectroscopic method for molecular structural analysis.

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This paper describes and evaluates the novel utility of network methods for understanding human interpersonal interactions within social neurobiological systems such as sports teams. We show how collective system networks are supported by the sum of interpersonal interactions that emerge from the activity of system agents (such as players in a sports team). To test this idea we trialled the methodology in analyses of intra-team collective behaviours in the team sport of water polo. We observed that the number of interactions between team members resulted in varied intra-team coordination patterns of play, differentiating between successful and unsuccessful performance outcomes. Future research on small-world networks methodologies needs to formalize measures of node connections in analyses of collective behaviours in sports teams, to verify whether a high frequency of interactions is needed between players in order to achieve competitive performance outcomes.

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Genetic research of complex diseases is a challenging, but exciting, area of research. The early development of the research was limited, however, until the completion of the Human Genome and HapMap projects, along with the reduction in the cost of genotyping, which paves the way for understanding the genetic composition of complex diseases. In this thesis, we focus on the statistical methods for two aspects of genetic research: phenotype definition for diseases with complex etiology and methods for identifying potentially associated Single Nucleotide Polymorphisms (SNPs) and SNP-SNP interactions. With regard to phenotype definition for diseases with complex etiology, we firstly investigated the effects of different statistical phenotyping approaches on the subsequent analysis. In light of the findings, and the difficulties in validating the estimated phenotype, we proposed two different methods for reconciling phenotypes of different models using Bayesian model averaging as a coherent mechanism for accounting for model uncertainty. In the second part of the thesis, the focus is turned to the methods for identifying associated SNPs and SNP interactions. We review the use of Bayesian logistic regression with variable selection for SNP identification and extended the model for detecting the interaction effects for population based case-control studies. In this part of study, we also develop a machine learning algorithm to cope with the large scale data analysis, namely modified Logic Regression with Genetic Program (MLR-GEP), which is then compared with the Bayesian model, Random Forests and other variants of logic regression.