6 resultados para Multicultural and Diversity

em CORA - Cork Open Research Archive - University College Cork - Ireland


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In this study, marine sponges collected in Irish waters were analysed for their associated microbiota. Of the approximately 240 bacterial isolates obtained from two sponges several showed antimicrobial activity; among them members of genera which have rarely been shown to produce antimicrobial compounds. Differences observed from the sponge-derived groups of isolates in terms of bioactivity suggests that S. carnosus isolates may be a better source of antibacterial compounds, while Leucosolenia sp. isolates appear to be a better source of antifungal compounds. More than 60% of fungal isolates obtained from 12 sponge samples proved to be bioactive. One of the isolates, which was closely related to Fusarium oxysporum and showed activity against bacteria and fungi, was investigated for its secondary metabolite genes. At least 5 different NRPS genes, with a sequence similarity as low as 50 % to known genes, were identified highlighting the likelihood that this isolate may be capable of producing novel secondary metabolites. A Micromonospora sp. was isolated from a Haliclona simulans sample collected in Irish waters. The isolate inhibited the growth of Gram positive bacterial test strains in three different antimicrobial assays. Employing preparative layer chromatography the compound responsible for the bioactivity could be isolated. According to LC-MS andNMR data the bioactive compound could indeed be novel. Finally, two deep water sponges were shown to host a remarkably different bacterial and archaeal diversity by application of 454 Pyrosequencing. The L. diversichela –proteobacterial community was dominated by a single ƴ-proteobacterial bacterium whereas the S. normani sample hosted a largely sponge specific microbial community, even more diverse than has been previously reported for shallow water sponges. Organisms potentially involved in nitrification, sulphate reduction and secondary metabolite production were found to be spatially distributed in the sponge. Furthermore, a deep sea specific population was implied.

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Advances in culture independent technologies over the last decade have highlighted the pivotal role which the gut microbiota plays in maintaining human health. Conversely, perturbations to the composition or actions of the ‘normal/functioning’ microbiota have been frequently associated with the pathogenesis of several disease states. Therefore the selective modulation of enteric microbial communities represents a viable target for the development of novel treatments for such diseases. Notably, while bovine whey proteins and exercise have been shown to positively influence several physiological processes, such as energy balance, their effect on the composition or functionality of the gut microbiota remains largely unknown. In this thesis, a variety of ex vivo, murine and human models are used in conjunction with high-throughput DNA sequencing-based analysis to provide valuable and novel insights into the impact of both whey proteins and exercise on enteric microbial communities. Overall the results presented in this thesis highlight that the consumption both whey protein isolate (WPI), and individual component proteins of whey such as bovine serum albumin (BSA) and lactoferrin, reduce high fat diet associated body weight gain and are associated with beneficial alterations within the murine gut microbiota. Although the impact of exercise on enteric microbial communities remains less clear, it may be that longer term investigations are required for the true effect of exercise on the gut microbiota to be fully elucidated.

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The human gut is host to a diversity of microorganisms including the single-celled microbial eukaryote Blastocystis. Although Blastocystis has a global distribution, there is dearth of information relating to its prevalence and diversity in many human populations. The mode of Blastocystis transmission to humans is also insufficiently characterised, however, it is speculated to vary between different populations. Here we investigated the incidence and genetic diversity of Blastocystis in a US population and also the possibility of Blastocystis human-human transmission between healthy individuals using family units (N = 50) living in Boulder, Colorado as our sample-set. Ten of the 139 (~ 7%) individuals in our dataset were positive for Blastocystis, nine of whom were adults and one individual belonging to the children/adolescents group. All positive cases were present in different family units. A number of different Blastocystis subtypes (species) were detected with no evidence of mixed infections. The prevalence of Blastocystis in this subset of the US population is comparatively low relative to other industrialised populations investigated to date; however, subtype diversity was largely consistent with that previously reported in studies of European populations. The distribution of Blastocystis within family units indicates that human-human transmission is unlikely to have occurred within families that participated in this study. It is not unexpected that given the world-wide variation in human living conditions and lifestyles between different populations, both the prevalence of Blastocystis and its mode of transmission to humans may vary considerably.

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The analysis of energy detector systems is a well studied topic in the literature: numerous models have been derived describing the behaviour of single and multiple antenna architectures operating in a variety of radio environments. However, in many cases of interest, these models are not in a closed form and so their evaluation requires the use of numerical methods. In general, these are computationally expensive, which can cause difficulties in certain scenarios, such as in the optimisation of device parameters on low cost hardware. The problem becomes acute in situations where the signal to noise ratio is small and reliable detection is to be ensured or where the number of samples of the received signal is large. Furthermore, due to the analytic complexity of the models, further insight into the behaviour of various system parameters of interest is not readily apparent. In this thesis, an approximation based approach is taken towards the analysis of such systems. By focusing on the situations where exact analyses become complicated, and making a small number of astute simplifications to the underlying mathematical models, it is possible to derive novel, accurate and compact descriptions of system behaviour. Approximations are derived for the analysis of energy detectors with single and multiple antennae operating on additive white Gaussian noise (AWGN) and independent and identically distributed Rayleigh, Nakagami-m and Rice channels; in the multiple antenna case, approximations are derived for systems with maximal ratio combiner (MRC), equal gain combiner (EGC) and square law combiner (SLC) diversity. In each case, error bounds are derived describing the maximum error resulting from the use of the approximations. In addition, it is demonstrated that the derived approximations require fewer computations of simple functions than any of the exact models available in the literature. Consequently, the regions of applicability of the approximations directly complement the regions of applicability of the available exact models. Further novel approximations for other system parameters of interest, such as sample complexity, minimum detectable signal to noise ratio and diversity gain, are also derived. In the course of the analysis, a novel theorem describing the convergence of the chi square, noncentral chi square and gamma distributions towards the normal distribution is derived. The theorem describes a tight upper bound on the error resulting from the application of the central limit theorem to random variables of the aforementioned distributions and gives a much better description of the resulting error than existing Berry-Esseen type bounds. A second novel theorem, providing an upper bound on the maximum error resulting from the use of the central limit theorem to approximate the noncentral chi square distribution where the noncentrality parameter is a multiple of the number of degrees of freedom, is also derived.

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Pre-treatment HCV quasispecies complexity and diversity may predict response to interferon based anti-viral therapy. The objective of this study was to retrospectively (1) examine temporal changes in quasispecies prior to the start of therapy and (2) investigate extensively quasispecies evolution in a group of 10 chronically infected patients with genotype 3a, treated with pegylated alpha 2a-Interferon and ribavirin. The degree of sequence heterogeneity within the hypervariable region 1 was assessed by analyzing 20-30 individual clones in serial serum samples. Genetic parameters, including amino acid Shannon entropy, Hamming distance and genetic distance were calculated for each sample. Treatment outcome was divided into (1) sustained virological responders (SVR) and (2) treatment failure (TF).Our results indicate, (1) quasispecies complexity and diversity are lower in the SVR group, (2) quasispecies vary temporally and (3) genetic heterogeneity at baseline can be used to predict treatment outcome. We discuss the results from the perspective of replicative homeostasis. We discuss the results from the perspective of replicative homeostasis.

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As a prominent form of land use across much of upland Europe, extensive livestock grazing may hold the key to the sustainable management of these landscapes. Recent agricultural policy reform, however, has resulted in a decline in upland sheep numbers, prompting concern for the biodiversity value of these areas. This study quantifies the effects of varying levels of grazing management on plant, ground beetle and breeding bird diversity and assemblage in the uplands and lowlands of hill sheep farms in County Kerry, Ireland. Farms represent a continuum of light to heavy grazing, measured using a series of field indicators across several habitats, such as the internationally important blanket bog, home to the ground beetle, Carabus clatratus. Linear mixed effects modelling and non-metric multidimensional scaling are employed to disentangle the most influential management and environmental factors. Grazing state may be determined by the presence of Molinia caerulea or Nardus stricta, and variables such as % traditional ewes, % vegetation litter and % scrub prove valuable indicators of diversity. Measures of ecosystem functioning, e.g. plant biomass (nutrient cycling) and % vegetation cover (erosion rates) are influenced by plant diversity, which is influenced by grazing management. Levels of the ecosystem service, soil organic carbon, vary with ground beetle abundance and diversity, potentially influencing carbon sequestration and thereby climate change. The majority of species from all three taxa are found in the lowlands, with the exception of birds such as meadow pipit and skylark. The scale of measurement should be determined by the size and mobility of the species in question. The challenge is to manage these high nature value landscapes using agri-environment schemes which enhance biodiversity by maintaining structural heterogeneity across a range of scales, altitudes and habitats whilst integrating the decisions of people living and working in these marginal areas.