Compostos fenólicos em frutos de bananeira.

Os compostos fenólicos são encontrados em muitas frutas e a quantificação desses metabólicos revela informações importantes a respeito da qualidade dos alimentos e dos potenciais benefícios à saúde (atividade antioxidante e atitumoral, e.g. - TALCOTT et al., 2003). A banana é amplamente consumida por todas as classes sociais e seu consumo é elevado, alcançando 162 Kg/pessoa/ano em algumas regiões da África (FAO, 2012)

Espectroscopia de infravermelho médio e quimiometria aplicadas a discriminação de acessos de bananeira.

O Brasil é o quinto produtor mundial de banana, tendo produzido aproximadamente 6,9 milhões de toneladas em 2010, em uma área aproximada de 487 mil hectares (FAO, 2012). Entretanto, há poucos cultivares para exploração comercial com potencial agronômico, tolerantes às pragas e doenças e que apresentem frutos com boas características pós-colheita e organolépticas. Uma das estratégias à solução desse problema é a seleção de novos genótipos, por meio do melhoramento genético, visando o aumento do valor nutricional e funcional (biofortificação), associado às boas características agronômicas

A machine learning and chemometrics assisted interpretation of spectroscopic data: a NMR-based metabolomics platform for the assessment of Brazilian propolis

In this work, a metabolomics dataset from 1H nuclear magnetic resonance spectroscopy of Brazilian propolis was analyzed using machine learning algorithms, including feature selection and classification methods. Partial least square-discriminant analysis (PLS-DA), random forest (RF), and wrapper methods combining decision trees and rules with evolutionary algorithms (EA) showed to be complementary approaches, allowing to obtain relevant information as to the importance of a given set of features, mostly related to the structural fingerprint of aliphatic and aromatic compounds typically found in propolis, e.g., fatty acids and phenolic compounds. The feature selection and decision tree-based algorithms used appear to be suitable tools for building classification models for the Brazilian propolis metabolomics regarding its geographic origin, with consistency, high accuracy, and avoiding redundant information as to the metabolic signature of relevant compounds.The work is partially funded by ERDF -European Regional Development Fund through the COMPETE Programme (operational programme for competitiveness) and by National Funds through the FCT (Portuguese Foundation for Science and Technology) within projects ref. COMPETE FCOMP-01-0124-FEDER-015079 and PEstOE/ EEI/UI0752/2011. RC's work is funded by a PhD grant from the Portuguese FCT ( ref. SFRH/BD/66201/2009)

Decoding the neural substrates of reward-related decision making with functional MRI

Although previous studies have implicated a diverse set of brain regions in reward-related decision making, it is not yet known which of these regions contain information that directly reflects a decision. Here, we measured brain activity using functional MRI in a group of subjects while they performed a simple reward-based decision-making task: probabilistic reversal-learning. We recorded brain activity from nine distinct regions of interest previously implicated in decision making and separated out local spatially distributed signals in each region from global differences in signal. Using a multivariate analysis approach, we determined the extent to which global and local signals could be used to decode subjects' subsequent behavioral choice, based on their brain activity on the preceding trial. We found that subjects' decisions could be decoded to a high level of accuracy on the basis of both local and global signals even before they were required to make a choice, and even before they knew which physical action would be required. Furthermore, the combined signals from three specific brain areas (anterior cingulate cortex, medial prefrontal cortex, and ventral striatum) were found to provide all of the information sufficient to decode subjects' decisions out of all of the regions we studied. These findings implicate a specific network of regions in encoding information relevant to subsequent behavioral choice

New anti-perovskite-type Superconductor ZnNyNi3

We have synthesized a new superconductor ZnNyNi3 with Tc ~3 K. The crystal structure has the same anti-perovskite-type such as MgCNi3 and CdCNi3. As far as we know, this is the third superconducting material in Ni-based anti-perovskite series. For this material, superconducting parameters, lower-critical field Hc1(0), upper-critical field Hc2(0), coherence length x(0), penetration depth l(0), and Gintzburg -Landau parameter k(0) have been experimentally determined.Comment: 13 pages, 3 figures, 1 tabl

Metabolic profiling and classification of propolis samples from Southern Brazil: an NMR-based platform coupled with machine learning

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching 90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.Financial support for this investigation by National Council for Scientific and Technological Development (CNPq), Coordination for the Improvement of Higher Education Personnel (CAPES), Brazilian Biosciences National Laboratory (LNBioCNPEM/MCTI), Foundation for Support of Scientific and Technological Research in the State of Santa Catarina (FAPESC), and Portuguese Foundation for Science and Technology (FCT) is acknowledged. The research fellowship granted by CNPq to the first author is also acknowledged. The work was partially funded by a CNPq and FCT agreement through the PropMine grant

The Affective Impact of Financial Skewness on Neural Activity and Choice

Few finance theories consider the influence of “skewness” (or large and asymmetric but unlikely outcomes) on financial choice. We investigated the impact of skewed gambles on subjects' neural activity, self-reported affective responses, and subsequent preferences using functional magnetic resonance imaging (FMRI). Neurally, skewed gambles elicited more anterior insula activation than symmetric gambles equated for expected value and variance, and positively skewed gambles also specifically elicited more nucleus accumbens (NAcc) activation than negatively skewed gambles. Affectively, positively skewed gambles elicited more positive arousal and negatively skewed gambles elicited more negative arousal than symmetric gambles equated for expected value and variance. Subjects also preferred positively skewed gambles more, but negatively skewed gambles less than symmetric gambles of equal expected value. Individual differences in both NAcc activity and positive arousal predicted preferences for positively skewed gambles. These findings support an anticipatory affect account in which statistical properties of gambles—including skewness—can influence neural activity, affective responses, and ultimately, choice

Genetic Determinants of Financial Risk Taking

Individuals vary in their willingness to take financial risks. Here we show that variants of two genes that regulate dopamine and serotonin neurotransmission and have been previously linked to emotional behavior, anxiety and addiction (5-HTTLPR and DRD4) are significant determinants of risk taking in investment decisions. We find that the 5-HTTLPR s/s allele carriers take 28% less risk than those carrying the s/l or l/l alleles of the gene. DRD4 7-repeat allele carriers take 25% more risk than individuals without the 7-repeat allele. These findings contribute to the emerging literature on the genetic determinants of economic behavior

Ideal Spin Filters: Theoretical Study of Electron Transmission Through Ordered and Disordered Interfaces Between Ferromagnetic Metals and Semiconductors

It is predicted that certain atomically ordered interfaces between some ferromagnetic metals (F) and semiconductors (S) should act as ideal spin filters that transmit electrons only from the majority spin bands or only from the minority spin bands of the F to the S at the Fermi energy, even for F with both majority and minority bands at the Fermi level. Criteria for determining which combinations of F, S and interface should be ideal spin filters are formulated. The criteria depend only on the bulk band structures of the S and F and on the translational symmetries of the S, F and interface. Several examples of systems that meet these criteria to a high degree of precision are identified. Disordered interfaces between F and S are also studied and it is found that intermixing between the S and F can result in interfaces with spin anti-filtering properties, the transmitted electrons being much less spin polarized than those in the ferromagnetic metal at the Fermi energy. A patent application based on this work has been commenced by Simon Fraser University.Comment: RevTeX, 12 pages, 5 figure

Under pressure: Response urgency modulates striatal and insula activity during decision-making under risk

When deciding whether to bet in situations that involve potential monetary loss or gain (mixed gambles), a subjective sense of pressure can influence the evaluation of the expected utility associated with each choice option. Here, we explored how gambling decisions, their psychophysiological and neural counterparts are modulated by an induced sense of urgency to respond. Urgency influenced decision times and evoked heart rate responses, interacting with the expected value of each gamble. Using functional MRI, we observed that this interaction was associated with changes in the activity of the striatum, a critical region for both reward and choice selection, and within the insula, a region implicated as the substrate of affective feelings arising from interoceptive signals which influence motivational behavior. Our findings bridge current psychophysiological and neurobiological models of value representation and action-programming, identifying the striatum and insular cortex as the key substrates of decision-making under risk and urgency