Cognitive functioning and efficacy of cognitive intervention in Multiple Sclerosis

Tese de Doutoramento em Psicologia Clínica / Psicologia

The isolation of Aspergillus spp from harvested maize in three Portuguese regions

In Portugal, maize is the cereal that involves more agriculture explorations. Aspergillus spp., among other species, are usually associated with this cereal, during drying and storage, making this commodity susceptible to mycotoxins (such as aflatoxins, ochratoxins, and cyclopiazonic acid). The aim of this study was to evaluate the mycotoxigenic potential of isolated Aspergillus strains from these maize samples and correlate it with the sampling place, the weather conditions, and local practices during drying and storage. The samples were collected between November 2008 and April 2009 in maize association of producers facilities in Coimbra, Santarém and Portalegre. The isolated strains were divided in three distinct groups, Aspergillus section Flavi, Aspergillus section Nigri and others Aspergillus. The preliminary results show that there are differences between the incidence of these groups in the three sampling places, especially in Coimbra, probably due to a lower mean temperatures and higher humidity levels. These data will be presented and discussed.

New integrative computational approaches unveil the Saccharomyces cerevisiae pheno-metabolomic fermentative profile and allow strain selection for winemaking

During must fermentation by Saccharomyces cerevisiae strains thousands of volatile aroma compounds are formed. The objective of the present work was to adapt computational approaches to analyze pheno-metabolomic diversity of a S. cerevisiae strain collection with different origins. Phenotypic and genetic characterization together with individual must fermentations were performed, and metabolites relevant to aromatic profiles were determined. Experimental results were projected onto a common coordinates system, revealing 17 statistical-relevant multi-dimensional modules, combining sets of most-correlated features of noteworthy biological importance. The present method allowed, as a breakthrough, to combine genetic, phenotypic and metabolomic data, which has not been possible so far due to difficulties in comparing different types of data. Therefore, the proposed computational approach revealed as successful to shed light into the holistic characterization of S. cerevisiae pheno-metabolome in must fermentative conditions. This will allow the identification of combined relevant features with application in selection of good winemaking strains.