Fracionamento de diferentes classes de compostos químicos por cromatografia líquida em coluna.

Resumo

Characterization of anti-crotalic antibodies

AbstractCrotalus durissus terrificus, C. d. collilineatus, C. d. cascavella and C. d. marajoensis are responsible minor but severe snake bites in Brazil. The venoms of these snakes share the presence of crotoxin, a neurotoxin comprising of two associated components, crotapotin and phospholipase A2 (PLA2). Treatment of the victims with specific antiserum is the unique effective therapeutic measure. The ability of anti-Crotalus antisera produced by the routine using crude venom to immunize horses or purified crotoxin and PLA2 as individual immunogens was compared. Antisera obtained from horses immunized with C. durissus terrificus crude venom were able to recognize and neutralize not only the toxins presents in C. durissus terrificus, but also the ones present in the venoms from C. d. collilineatus, C. d. cascavella and C. d. marajoensis. Antisera from horses immunized with individual crotoxin or PLA2, although in lesser titers, were also able of recognizing the toxins in all four Crotalus species and neutralize the lethality of the C. d. terrificus venom

Learning to Generate Ambiguous Sequences

In this paper, we experiment with methods for obtaining binary sequences with a random probability mass function and with low autocorrelation and use it to generate ambiguous outcomes. Outputs from a neural network are mixed and shuffled, resulting in binary sequences whose probability mass function is non-convergent, constantly moving and changing. Empirical comparison with algorithms that generate ambiguity shows that the sequences generated by the proposed method have a significantly lower serial dependence. Therefore, the method is useful in scenarios where observes can see and record the outcome of each draw sequentially, by hindering the ability to make useful statistical inferences

Linear Predictability vs. Bull and Bear Market Models in Strategic Asset Allocation Decisions: Evidence from UK Data

Most papers in the portfolio choice literature have examined linear predictability frameworks based on the idea that simple but flexible Vector Autoregressive (VAR) models can be expanded to produce portfolio allocations that hedge against the bull and bear dynamics typical of financial markets through careful selection of predictor variables that capture business cycles and market sentiment. Yet, a distinct literature exists that shows that nonlinear econometric frameworks, such as Markov switching, are also natural tools to compute optimal portfolios arising from the existence of good and bad market states. This paper examines whether and how simple VARs can produce portfolio rules similar to those obtained under a simple Markov switching, by studying the effects of expanding both the order of the VAR and the number/selection of predictor variables included. In a typical stock-bond strategic asset allocation problem for U.K. data, we compute the out-of-sample certainty equivalent returns for a wide range of VARs and compare these measures of performance with those of nonlinear models. We conclude that most VARs cannot produce portfolio rules, hedging demands, or (net of transaction costs) out-of-sample performances that approximate those obtained from equally simple nonlinear frameworks

ITS-rDNA phylogeny of Colletotrichum spp. causal agent of apple glomerella leaf spot.

Several diseases have affected apple production, among them there is Glomerella leaf spot (GLS) caused by Colletotrichum spp. The first report of this disease in apple was in plants nearby citrus orchards in São Paulo State, Brazil. The origin of this disease is still not clear, and studies based on the molecular phylogeny could relate the organisms evolutionarily and characterize possible mechanisms of divergent evolution. The amplification of 5.8S-ITS (Internal Transcribed Spacer) of rDNA of 51 pathogenic Colletotrichum spp. isolates from apples, pineapple guava and citrus produced one fragment of approximately 600 bases pairs (bp) for all the isolates analyzed. The amplified fragments were cleaved with restriction enzymes, and fragments from 90 to 500bp were obtained. The sequencing of this region allowed the generation of a phylogenetic tree, regardless of their hosts, and 5 isolated groups were obtained. From the "in silico" comparison, it was possible to verify a variation from 93 to 100% of similarity between the sequences studied and the Genbank data base. The causal agent of GLS is nearly related (clustered) to isolates of pineapple guava and to the citrus isolates used as control

Different spatial distribution of inflammatory cells in the tumor microenvironment of ABC and GBC subgroups of diffuse large B cell lymphoma

Diffuse Large B-Cell Lymphoma (DLBCL) presents a high clinical and biological heterogeneity, and the tumor microenvironment chracteristics are important in its progression. The aim of this study was to evaluate tumor T, B cells, macrophages and mast cells distribution in GBC and ABC DLBCL subgroups through a set of morphometric parameters allowing to provide a quantitative evaluation of the morphological features of the spatial patterns generated by these inflammatory cells. Histological ABC and GCB samples were immunostained for CD4, CD8, CD68, CD 163, and tryptase in order to determine both percentage and position of positive cells in the tissue characterizing their spatial distribution. The results evidenced that cell patterns generated by CD4-, CD8-, CD68-, CD163- and tryptase-positive cell profiles exhibited a significantly higher uniformity index in ABC than in GCB subgroup. The positive-cell distributions appeared clustered in tissues from GCB, while in tissues from ABC such a feature was lower or absent. The combinations of spatial statistics-derived parameters can lead to better predictions of tumor cell infiltration than any classical morphometric method providing a more accurate description of the functional status of the tumor, useful for patient prognosis

Regime Shifts in Mean-Variance Efficient Frontiers: Some International Evidence

Regime switching models have been assuming a central role in financial applications because of their well-known ability to capture the presence of rich non-linear patterns in the joint distribution of asset returns. This paper examines how the presence of regimes in means, variances, and correlations of asset returns translates into explicit dynamics of the Markowitz mean-variance frontier. In particular, the paper shows both theoretically and through an application to international equity portfolio diversification that substantial differences exist between bull and bear regime-specific frontiers, both in statistical and in economic terms. Using Morgan Stanley Capital International (MSCI) investable indices for five countries/macro-regions, it is possible to characterize the mean-variance frontiers and optimal portfolio strategies in bull periods, in bear periods, and in periods where high uncertainty exists on the nature of the current regime. A recursive back-testing exercise shows that between 1998 and 2010, adopting a switching mean-variance strategy may have yielded considerable risk-adjusted payoffs, which are the largest in correspondence to the 2007-2009 financial crisis

Interindividual variation and consistency of migratory behavior in the Eurasian woodcock

Diverse spatio-temporal aspects of avian migration rely on relatively rigid endogenous programs. However, flexibility in migratory behavior may allow effective coping with unpredictable variation in ecological conditions that can occur during migration. We aimed at characterizing inter- and intraindividual variation of migratory behavior in a forest-dwelling wader species, the Eurasian woodcock Scolopax rusticola, focusing on spatio-temporal consistency across repeated migration episodes. By satellite-tracking birds from their wintering sites along the Italian peninsula to their breeding areas, we disclosed a remarkable variability in migration distances, with some birds flying more than 6,000 km to Central Asian breeding grounds (up to 101\ub0E). Prebreeding migration was faster and of shorter duration than postbreeding migration. Birds moving over longer distances migrated faster during prebreeding migration, and those breeding at northernmost latitudes left their wintering areas earlier. Moreover, birds making longer migrations departed earlier from their breeding sites. Breeding site fidelity was very high, whereas fidelity to wintering areas increased with age. Migration routes were significantly consistent, both among repeated migration episodes and between pre- and postbreeding migration. Prebreeding migration departure date was not significantly repeatable, whereas arrival date to the breeding areas was highly repeatable. Hence, interindividual variation in migratory behavior of woodcocks was mostly explained by the location of the breeding areas, and spatial consistency was relatively large through the entire annual cycle. Flexibility in prebreeding migration departure date may suggest that environmental effects have a larger influence on temporal than on spatial aspects of migratory behavior