1000 resultados para NS5B REGION


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Background Genotyping of hepatitis C virus (HCV) has become an essential tool for prognosis and prediction of treatment duration. The aim of this study was to compare two HCV genotyping methods: reverse hybridization line probe assay (LiPA v.1) and partial sequencing of the NS5B region. Methods Plasma of 171 patients with chronic hepatitis C were screened using both a commercial method (LiPA HCV Versant, Siemens, Tarrytown, NY, USA) and different primers targeting the NS5B region for PCR amplification and sequencing analysis. Results Comparison of the HCV genotyping methods showed no difference in the classification at the genotype level. However, a total of 82/171 samples (47.9%) including misclassification, non-subtypable, discrepant and inconclusive results were not classified by LiPA at the subtype level but could be discriminated by NS5B sequencing. Of these samples, 34 samples of genotype 1a and 6 samples of genotype 1b were classified at the subtype level using sequencing of NS5B. Conclusions Sequence analysis of NS5B for genotyping HCV provides precise genotype and subtype identification and an accurate epidemiological representation of circulating viral strains.

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Hepatitis C virus (HCV) is a public health problem throughout the world and 3% of the world population is infected with this virus. It is estimated that 3-4 millions individuals are being infected every year. It has been estimated that around 1.5% of Brazilian population is anti-HCV positive and the Northeast region showed the highest prevalence in Brazil. The aim of this study was to characterize HCV genotypes circulating in Pernambuco State (PE), Brazil, located in the Northeast region of the country. This study included 85 anti-HCV positive patients followed up between 2004 and 2011. For genotyping, a 380bp fragment of HCV RNA in the NS5B region was amplified by nested PCR. Phylogenetic analysis was conducted using Bayesian Markov chain Monte Carlo simulation (MCMC) using BEAST v.1.5.3. From 85 samples, 63 (74.1%) positive to NS5B fragment were successfully sequenced. Subtype 1b was the most prevalent in this population (42-66.7%), followed by 3a (16-25.4%), 1a (4-6.3%) and 2b (1-1.6%). Twelve (63.1%) and seven (36.9%) patients with HCV and schistosomiasis were infected with subtypes 1b and 3a, respectively. Brazil is a large country with many different population backgrounds; a large variation in the frequencies of HCV genotypes is predictable throughout its territory. This study reports HCV genotypes from Pernambuco State where subtype 1b was found to be the most prevalent. Phylogenetic analysis suggests the presence of the different HCV strains circulating within this population. (C) 2012 Elsevier B.V. All rights reserved.

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Abstract Background Hepatitis C virus (HCV) is an important human pathogen affecting around 3% of the human population. In Brazil, it is estimated that there are approximately 2 to 3 million HCV chronic carriers. There are few reports of HCV prevalence in Rondônia State (RO), but it was estimated in 9.7% from 1999 to 2005. The aim of this study was to characterize HCV genotypes in 58 chronic HCV infected patients from Porto Velho, Rondônia (RO), Brazil. Methods A fragment of 380 bp of NS5B region was amplified by nested PCR for genotyping analysis. Viral sequences were characterized by phylogenetic analysis using reference sequences obtained from the GenBank (n = 173). Sequences were aligned using Muscle software and edited in the SE-AL software. Phylogenetic analyses were conducted using Bayesian Markov chain Monte Carlo simulation (MCMC) to obtain the MCC tree using BEAST v.1.5.3. Results From 58 anti-HCV positive samples, 22 were positive to the NS5B fragment and successfully sequenced. Genotype 1b was the most prevalent in this population (50%), followed by 1a (27.2%), 2b (13.6%) and 3a (9.0%). Conclusions This study is the first report of HCV genotypes from Rondônia State and subtype 1b was found to be the most prevalent. This subtype is mostly found among people who have a previous history of blood transfusion but more detailed studies with a larger number of patients are necessary to understand the HCV dynamics in the population of Rondônia State, Brazil.

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HuR is a ubiquitous, RNA binding protein that influences the stability and translation of several cellular mRNAs. Here, we report a novel role for HuR, as a regulator of proteins assembling at the 3' untranslated region (UTR) of viral RNA in the context of hepatitis C virus (HCV) infection. HuR relocalizes from the nucleus to the cytoplasm upon HCV infection, interacts with the viral polymerase (NS5B), and gets redistributed into compartments of viral RNA synthesis. Depletion in HuR levels leads to a significant reduction in viral RNA synthesis. We further demonstrate that the interaction of HuR with the 3' UTR of the viral RNA affects the interaction of two host proteins, La and polypyrimidine tract binding protein (PTB), at this site. HuR interacts with La and facilitates La binding to the 3' UTR, enhancing La-mediated circularization of the HCV genome and thus viral replication. In addition, it competes with PTB for association with the 3' UTR, which might stimulate viral replication. Results suggest that HuR influences the formation of a cellular/viral ribonucleoprotein complex, which is important for efficient initiation of viral RNA replication. Our study unravels a novel strategy of regulation of HCV replication through an interplay of host and viral proteins, orchestrated by HuR. IMPORTANCE Hepatitis C virus (HCV) is highly dependent on various host factors for efficient replication of the viral RNA. Here, we have shown how a host factor (HuR) migrates from the nucleus to the cytoplasm and gets recruited in the protein complex assembling at the 3' untranslated region (UTR) of HCV RNA. At the 3' UTR, it facilitates circularization of the viral genome through interaction with another host factor, La, which is critical for replication. Also, it competes with the host protein PTB, which is a negative regulator of viral replication. Results demonstrate a unique strategy of regulation of HCV replication by a host protein through alteration of its subcellular localization and interacting partners. The study has advanced our knowledge of the molecular mechanism of HCV replication and unraveled the complex interplay between the host factors and viral RNA that could be targeted for therapeutic interventions.

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In this study we examined the impact of weather variability and tides on the transmission of Barmah Forest virus (BFV) disease and developed a weather-based forecasting model for BFV disease in the Gladstone region, Australia. We used seasonal autoregressive integrated moving-average (SARIMA) models to determine the contribution of weather variables to BFV transmission after the time-series data of response and explanatory variables were made stationary through seasonal differencing. We obtained data on the monthly counts of BFV cases, weather variables (e.g., mean minimum and maximum temperature, total rainfall, and mean relative humidity), high and low tides, and the population size in the Gladstone region between January 1992 and December 2001 from the Queensland Department of Health, Australian Bureau of Meteorology, Queensland Department of Transport, and Australian Bureau of Statistics, respectively. The SARIMA model shows that the 5-month moving average of minimum temperature (β = 0.15, p-value < 0.001) was statistically significantly and positively associated with BFV disease, whereas high tide in the current month (β = −1.03, p-value = 0.04) was statistically significantly and inversely associated with it. However, no significant association was found for other variables. These results may be applied to forecast the occurrence of BFV disease and to use public health resources in BFV control and prevention.

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In the region of self-organized criticality (SOC) interdependency between multi-agent system components exists and slight changes in near-neighbor interactions can break the balance of equally poised options leading to transitions in system order. In this region, frequency of events of differing magnitudes exhibits a power law distribution. The aim of this paper was to investigate whether a power law distribution characterized attacker-defender interactions in team sports. For this purpose we observed attacker and defender in a dyadic sub-phase of rugby union near the try line. Videogrammetry was used to capture players’ motion over time as player locations were digitized. Power laws were calculated for the rate of change of players’ relative position. Data revealed that three emergent patterns from dyadic system interactions (i.e., try; unsuccessful tackle; effective tackle) displayed a power law distribution. Results suggested that pattern forming dynamics dyads in rugby union exhibited SOC. It was concluded that rugby union dyads evolve in SOC regions suggesting that players’ decisions and actions are governed by local interactions rules.

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1. Species' distribution modelling relies on adequate data sets to build reliable statistical models with high predictive ability. However, the money spent collecting empirical data might be better spent on management. A less expensive source of species' distribution information is expert opinion. This study evaluates expert knowledge and its source. In particular, we determine whether models built on expert knowledge apply over multiple regions or only within the region where the knowledge was derived. 2. The case study focuses on the distribution of the brush-tailed rock-wallaby Petrogale penicillata in eastern Australia. We brought together from two biogeographically different regions substantial and well-designed field data and knowledge from nine experts. We used a novel elicitation tool within a geographical information system to systematically collect expert opinions. The tool utilized an indirect approach to elicitation, asking experts simpler questions about observable rather than abstract quantities, with measures in place to identify uncertainty and offer feedback. Bayesian analysis was used to combine field data and expert knowledge in each region to determine: (i) how expert opinion affected models based on field data and (ii) how similar expert-informed models were within regions and across regions. 3. The elicitation tool effectively captured the experts' opinions and their uncertainties. Experts were comfortable with the map-based elicitation approach used, especially with graphical feedback. Experts tended to predict lower values of species occurrence compared with field data. 4. Across experts, consensus on effect sizes occurred for several habitat variables. Expert opinion generally influenced predictions from field data. However, south-east Queensland and north-east New South Wales experts had different opinions on the influence of elevation and geology, with these differences attributable to geological differences between these regions. 5. Synthesis and applications. When formulated as priors in Bayesian analysis, expert opinion is useful for modifying or strengthening patterns exhibited by empirical data sets that are limited in size or scope. Nevertheless, the ability of an expert to extrapolate beyond their region of knowledge may be poor. Hence there is significant merit in obtaining information from local experts when compiling species' distribution models across several regions.