Sequencing of E2 and NS5A regions of HCV genotype 3a in Brazilian patients with chronic hepatitis

Hepatitis C virus (HCV) is a major cause of liver disease throughout the world. The NS5A and E2 proteins of HCV genotype 1 were reported to inhibit the double-stranded (ds) RNA-dependent protein kinase (PKR), which is involved in the cellular antiviral response induced by interferon (IFN). The response to IFN therapy is quite different between genotypes, with response rates among patients infected with types 2 and 3 that are two-three-fold higher than in patients infected with type 1. Interestingly, a significant percentage of HCV genotype 3-infected patients do not respond to treatment at all. The aim of this paper was to analyse the sequences of fragments of the E2 and NS5A regions from 33 outpatients infected with genotype 3a, including patients that have responded (SVR) or not responded (NR) to treatment. HCV RNA was extracted and amplified with specific primers for the NS5A and E2 regions and the PCR products were then sequenced. The sequences obtained covered amino acids (aa) 636-708 in E2 and in NS5A [including the IFN sensitivity determining region (ISDR), PKR-binding domain and extended V3 region)]. In the E2 and NS5A regions, we did observe aa changes among patients, but these changes were not statistically significant between the SVR and NR groups. In conclusion, our results suggest that the ISDR domain is not predictive of treatment success in patients infected with HCV genotype 3a.publishersversionpublishe

Modelo matemático para estimativa da temperatura média diária do ar no Estado de Goiás Mathematical model for estimating daily average air temperature in Goiás, Brazil

O objetivo deste trabalho foi desenvolver um modelo matemático de estimativa da temperatura média diária do ar no Estado de Goiás, que considera simultaneamente as variações espacial e temporal. O modelo foi desenvolvido por meio de uma combinação linear da altitude, latitude, longitude e da série trigonométrica de Fourier incompleta usando os três primeiros coeficientes harmônicos. Os parâmetros do modelo foram ajustados aos dados de 21 estações meteorológicas, por meio de regressão linear múltipla. O coeficiente de correlação resultante do ajuste do modelo foi de 0,91, e o índice de concordância de Willmott foi igual a 1. O modelo foi testado com os dados de três estações de altitudes diferentes: elevada (1.100 m), média (554 m) e baixa (431 m). O desempenho foi considerado mediano para altitudes baixas e elevadas, e muito bom para altitudes médias.<br>The objective of this work was to develop a mathematical model to predict the daily average of air temperature in Goiás, Brazil. The model was developed through a linear combination of altitude, latitude, longitude, and the incomplete trigonometric Fourier series using the first three harmonic coefficients. The parameters of the model were adjusted with data from 21 weather stations, using multiple linear regression. The resulting correlation coefficient of the model was 0.91, and the Willmott's index of agreement was close to 1. The model was tested with data from three additional weather stations at different altitudes: high (1,100 m), medium (554 m), and low (431 m). The performance of the model was reasonable for both high and low altitude stations, and very good for the medium altitude station