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2 result(s) for "Roberto, In^es Conceição"
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Hydrolysate detoxification with activated charcoal for xylitol production by Candida guilliermondii
A detoxification method using activated charcoal with concentrated rice straw hemicellulosic hydrolysate improved the conversion of xylose to xylitol by the yeast Candida guilliermondii by 22%. This was achieved when the hydrolysate:charcoal ratio was 40 g g^sup -1^, resulting in removal of 27% of phenolic compounds. Under this condition, the xylitol yield factor (0.72 g g^sup -1^) and volumetric productivity (0.61 g l^sup -1^ h^sup -1^) were close to those attained in a semi-defined medium simulating hydrolysate sugars.[PUBLICATION ABSTRACT]
Interdependence between confirmed and discarded cases of dengue, chikungunya and Zika viruses in Brazil: A multivariate time-series analysis
The co-circulation of different arboviruses in the same time and space poses a significant threat to public health given their rapid geographic dispersion and serious health, social, and economic impact. Therefore, it is crucial to have high quality of case registration to estimate the real impact of each arboviruses in the population. In this work, a Vector Autoregressive (VAR) model was developed to investigate the interrelationships between discarded and confirmed cases of dengue, chikungunya, and Zika in Brazil. We used data from the Brazilian National Notifiable Diseases Information System (SINAN) from 2010 to 2017. There were three peaks in the series of dengue notification in this period occurring in 2013, 2015 and in 2016. The series of reported cases of both Zika and chikungunya reached their peak in late 2015 and early 2016. The VAR model shows that the Zika series have a significant impact on the dengue series and vice versa, suggesting that several discarded and confirmed cases of dengue could actually have been cases of Zika. The model also suggests that the series of confirmed and discarded chikungunya cases are almost independent of the cases of Zika, however, affecting the series of dengue. In conclusion, co-circulation of arboviruses with similar symptoms could have lead to misdiagnosed diseases in the surveillance system. We argue that the routinely use of mathematical and statistical models in association with traditional symptom-surveillance could help to decrease such errors and to provide early indication of possible future outbreaks. These findings address the challenges regarding notification biases and shed new light on how to handle reported cases based only in clinical-epidemiological criteria when multiples arboviruses co circulate in the same population. Footnotes * Figures have been changed and supplementary files updated