921 resultados para Forest genetic resources
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Background: Kallikrein 15 (KLK15)/Prostinogen is a plausible candidate for prostate cancer susceptibility. Elevated KLK15 expression has been reported in prostate cancer and it has been described as an unfavorable prognostic marker for the disease. Objectives: We performed a comprehensive analysis of association of variants in the KLK15 gene with prostate cancer risk and aggressiveness by genotyping tagSNPs, as well as putative functional SNPs identified by extensive bioinformatics analysis. Methods and Data Sources: Twelve out of 22 SNPs, selected on the basis of linkage disequilibrium pattern, were analyzed in an Australian sample of 1,011 histologically verified prostate cancer cases and 1,405 ethnically matched controls. Replication was sought from two existing genome wide association studies (GWAS): the Cancer Genetic Markers of Susceptibility (CGEMS) project and a UK GWAS study. Results: Two KLK15 SNPs, rs2659053 and rs3745522, showed evidence of association (p, 0.05) but were not present on the GWAS platforms. KLK15 SNP rs2659056 was found to be associated with prostate cancer aggressiveness and showed evidence of association in a replication cohort of 5,051 patients from the UK, Australia, and the CGEMS dataset of US samples. A highly significant association with Gleason score was observed when the data was combined from these three studies with an Odds Ratio (OR) of 0.85 (95% CI = 0.77-0.93; p = 2.7610 24). The rs2659056 SNP is predicted to alter binding of the RORalpha transcription factor, which has a role in the control of cell growth and differentiation and has been suggested to control the metastatic behavior of prostate cancer cells. Conclusions: Our findings suggest a role for KLK15 genetic variation in the etiology of prostate cancer among men of European ancestry, although further studies in very large sample sets are necessary to confirm effect sizes.
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Objective To identify the spatial and temporal clusters of Barmah Forest virus (BFV) disease in Queensland in Australia, using geographical information systems (GIS) and spatial scan statistic (SaTScan). Methods We obtained BFV disease cases, population and statistical local areas boundary data from Queensland Health and Australian Bureau of Statistics respectively during 1992-2008 for Queensland. A retrospective Poisson-based analysis using SaTScan software and method was conducted in order to identify both purely spatial and space-time BFV disease high-rate clusters. A spatial cluster size of a proportion of the population and a 200km circle radius and varying time windows from 1 month to 12 months were chosen (for the space-time analysis). Results The spatial scan statistic detected a most likely significant purely spatial cluster (including 23 SLAs) and a most likely significant space-time cluster (including 24 SLAs) in approximately the same location. Significant secondary clusters were also identified from both the analyses in several locations. Conclusions This study provides evidence of the existence of statistically significant BFV disease clusters in Queensland, Australia. The study also demonstrated the relevance and applicability of SaTScan in analysing on-going surveillance data to identify clusters to facilitate the development of effective BFV disease prevention and control strategies in Queensland, Australia.
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Barmah Forest Virus (BFV) disease is the most rapidly emerging mosquito-borne disease in Australia. BFV transmission depends on factors such as climate, virus, vector and the human population. However, the impact of climatic and social factors on BFV remains to be determined. This paper provided an overview of current research and discusses the future research directions on the BFV transmission. These research findings could be regarded as an impetus towards BFV prevention and control strategies.
Novel molecular markers of Chlamydia pecorum genetic diversity in the koala (Phascolarctos cinereus)
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Background Chlamydia pecorum is an obligate intracellular bacterium and the causative agent of reproductive and ocular disease in several animal hosts including koalas, sheep, cattle and goats. C. pecorum strains detected in koalas are genetically diverse, raising interesting questions about the origin and transmission of this species within koala hosts. While the ompA gene remains the most widely-used target in C. pecorum typing studies, it is generally recognised that surface protein encoding genes are not suited for phylogenetic analysis and it is becoming increasingly apparent that the ompA gene locus is not congruent with the phylogeny of the C. pecorum genome. Using the recently sequenced C. pecorum genome sequence (E58), we analysed 10 genes, including ompA, to evaluate the use of ompA as a molecular marker in the study of koala C. pecorum genetic diversity. Results Three genes (incA, ORF663, tarP) were found to contain sufficient nucleotide diversity and discriminatory power for detailed analysis and were used, with ompA, to genotype 24 C. pecorum PCR-positive koala samples from four populations. The most robust representation of the phylogeny of these samples was achieved through concatenation of all four gene sequences, enabling the recreation of a "true" phylogenetic signal. OmpA and incA were of limited value as fine-detailed genetic markers as they were unable to confer accurate phylogenetic distinctions between samples. On the other hand, the tarP and ORF663 genes were identified as useful "neutral" and "contingency" markers respectively, to represent the broad evolutionary history and intra-species genetic diversity of koala C. pecorum. Furthermore, the concatenation of ompA, incA and ORF663 sequences highlighted the monophyletic nature of koala C. pecorum infections by demonstrating a single evolutionary trajectory for koala hosts that is distinct from that seen in non-koala hosts. Conclusions While the continued use of ompA as a fine-detailed molecular marker for epidemiological analysis appears justified, the tarP and ORF663 genes also appear to be valuable markers of phylogenetic or biogeographic divisions at the C. pecorum intra-species level. This research has significant implications for future typing studies to understand the phylogeny, genetic diversity, and epidemiology of C. pecorum infections in the koala and other animal species.
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Background Barmah Forest virus (BFV) disease is a common and wide-spread mosquito-borne disease in Australia. This study investigated the spatio-temporal patterns of BFV disease in Queensland, Australia using geographical information system (GIS) tools and geostatistical analysis. Methods/Principal Findings We calculated the incidence rates and standardised incidence rates of BFV disease. Moran's I statistic was used to assess the spatial autocorrelation of BFV incidences. Spatial dynamics of BFV disease was examined using semi-variogram analysis. Interpolation techniques were applied to visualise and display the spatial distribution of BFV disease in statistical local areas (SLAs) throughout Queensland. Mapping of BFV disease by SLAs reveals the presence of substantial spatio-temporal variation over time. Statistically significant differences in BFV incidence rates were identified among age groups (χ2 = 7587, df = 7327,p<0.01). There was a significant positive spatial autocorrelation of BFV incidence for all four periods, with the Moran's I statistic ranging from 0.1506 to 0.2901 (p<0.01). Semi-variogram analysis and smoothed maps created from interpolation techniques indicate that the pattern of spatial autocorrelation was not homogeneous across the state. Conclusions/Significance This is the first study to examine spatial and temporal variation in the incidence rates of BFV disease across Queensland using GIS and geostatistics. The BFV transmission varied with age and gender, which may be due to exposure rates or behavioural risk factors. There are differences in the spatio-temporal patterns of BFV disease which may be related to local socio-ecological and environmental factors. These research findings may have implications in the BFV disease control and prevention programs in Queensland.
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We examined the structure and extent of genetic diversity in intrahost populations of Ross River virus (RRV) in samples from six human patients, focusing on the nonstructural (nsP3) and structural (E2) protein genes. Strikingly, although the samples were collected from contrasting ecological settings 3,000 kilometers apart in Australia, we observed multiple viral lineages in four of the six individuals, which is indicative of widespread mixed infections. In addition, a comparison with previously published RRV sequences revealed that these distinct lineages have been in circulation for at least 5 years, and we were able to document their long-term persistence over extensive geographical distances
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The study presents a multi-layer genetic algorithm (GA) approach using correlation-based methods to facilitate damage determination for through-truss bridge structures. To begin, the structure’s damage-suspicious elements are divided into several groups. In the first GA layer, the damage is initially optimised for all groups using correlation objective function. In the second layer, the groups are combined to larger groups and the optimisation starts over at the normalised point of the first layer result. Then the identification process repeats until reaching the final layer where one group includes all structural elements and only minor optimisations are required to fine tune the final result. Several damage scenarios on a complicated through-truss bridge example are nominated to address the proposed approach’s effectiveness. Structural modal strain energy has been employed as the variable vector in the correlation function for damage determination. Simulations and comparison with the traditional single-layer optimisation shows that the proposed approach is efficient and feasible for complicated truss bridge structures when the measurement noise is taken into account.
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Optimising the container transfer schedule at the multimodal terminals is known to be NP-hard, which implies that the best solution becomes computationally infeasible as problem sizes increase. Genetic Algorithm (GA) techniques are used to reduce container handling/transfer times and ships' time at the port by speeding up handling operations. The GA is chosen due to the relatively good results that have been reported even with the simplest GA implementations to obtain near-optimal solutions in reasonable time. Also discussed, is the application of the model to assess the consequences of increased scheduled throughput time as well as different strategies such as the alternative plant layouts, storage policies and number of yard machines. A real data set used for the solution and subsequent sensitivity analysis is applied to the alternative plant layouts, storage policies and number of yard machines.
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The presence of large number of single-phase distributed energy resources (DERs) can cause severe power quality problems in distribution networks. The DERs can be installed in random locations. This may cause the generation in a particular phase exceeds the load demand in that phase. Therefore the excess power in that phase will be fed back to the transmission network. To avoid this problem, the paper proposes the use of distribution static compensator (DSTATCOM) that needs to be connected at the first bus following a substation. When operated properly, the DSTATCOM can facilitate a set of balanced current flow from the substation, even when excess power is generated by DERs. The proposals are validated through extensive digital computer simulation studies using PSCAD and MATLAB.
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Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches to the virtual machine placement problem consider the energy consumption by physical machines in a data center only, but do not consider the energy consumption in communication network in the data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement in order to make the data center more energy-efficient. In this paper, we propose a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both the servers and the communication network in the data center. Experimental results show that the genetic algorithm performs well when tackling test problems of different kinds, and scales up well when the problem size increases.
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The native Australian fly Drosophila serrata belongs to the highly speciose montium subgroup of the melanogaster species group. It has recently emerged as an excellent model system with which to address a number of important questions, including the evolution of traits under sexual selection and traits involved in climatic adaptation along latitudinal gradients. Understanding the molecular genetic basis of such traits has been limited by a lack of genomic resources for this species. Here, we present the first expressed sequence tag (EST) collection for D. serrata that will enable the identification of genes underlying sexually-selected phenotypes and physiological responses to environmental change and may help resolve controversial phylogenetic relationships within the montium subgroup.