Multivariate Approximations to Portfolio Return Distribution

This article proposes a three-step procedure to estimate portfolio return distributions under the multivariate Gram-Charlier (MGC) distribution. The method combines quasi maximum likelihood (QML) estimation for conditional means and variances and the method of moments (MM) estimation for the rest of the density parameters, including the correlation coefficients. The procedure involves consistent estimates even under density misspecification and solves the so-called ‘curse of dimensionality’ of multivariate modelling. Furthermore, the use of a MGC distribution represents a flexible and general approximation to the true distribution of portfolio returns and accounts for all its empirical regularities. An application of such procedure is performed for a portfolio composed of three European indices as an illustration. The MM estimation of the MGC (MGC-MM) is compared with the traditional maximum likelihood of both the MGC and multivariate Student’s t (benchmark) densities. A simulation on Value-at-Risk (VaR) performance for an equally weighted portfolio at 1% and 5% confidence indicates that the MGC-MM method provides reasonable approximations to the true empirical VaR. Therefore, the procedure seems to be a useful tool for risk managers and practitioners

Context-sensitive autoassociative memories as expert systems in medical diagnosis

BACKGROUND: The complexity of our contemporary medical practice has impelled the development of different decision-support aids based on artificial intelligence and neural networks. Distributed associative memories are neural network models that fit perfectly well to the vision of cognition emerging from current neurosciences. METHODS: We present the context-dependent autoassociative memory model. The sets of diseases and symptoms are mapped onto a pair of basis of orthogonal vectors. A matrix memory stores the associations between the signs and symptoms, and their corresponding diseases. A minimal numerical example is presented to show how to instruct the memory and how the system works. In order to provide a quick appreciation of the validity of the model and its potential clinical relevance we implemented an application with real data. A memory was trained with published data of neonates with suspected late-onset sepsis in a neonatal intensive care unit (NICU). A set of personal clinical observations was used as a test set to evaluate the capacity of the model to discriminate between septic and non-septic neonates on the basis of clinical and laboratory findings. RESULTS: We show here that matrix memory models with associations modulated by context can perform automatic medical diagnosis. The sequential availability of new information over time makes the system progress in a narrowing process that reduces the range of diagnostic possibilities. At each step the system provides a probabilistic map of the different possible diagnoses to that moment. The system can incorporate the clinical experience, building in that way a representative database of historical data that captures geo-demographical differences between patient populations. The trained model succeeds in diagnosing late-onset sepsis within the test set of infants in the NICU: sensitivity 100%; specificity 80%; percentage of true positives 91%; percentage of true negatives 100%; accuracy (true positives plus true negatives over the totality of patients) 93,3%; and Cohen's kappa index 0,84. CONCLUSION: Context-dependent associative memories can operate as medical expert systems. The model is presented in a simple and tutorial way to encourage straightforward implementations by medical groups. An application with real data, presented as a primary evaluation of the validity and potentiality of the model in medical diagnosis, shows that the model is a highly promising alternative in the development of accuracy diagnostic tools

Evidence for positive selection in the gene fruitless in Anastrepha fruit flies

<p>Abstract</p> <p>Background</p> <p>Many genes involved in the sex determining cascade have indicated signals of positive selection and rapid evolution across different species. Even though <it>fruitless </it>is an important gene involved mostly in several aspects of male courtship behavior, the few studies so far have explained its high rates of evolution by relaxed selective constraints. This would indicate that a large portion of this gene has evolved neutrally, contrary to what has been observed for other genes in the sex cascade.</p> <p>Results</p> <p>Here we test whether the <it>fruitless </it>gene has evolved neutrally or under positive selection in species of <it>Anastrepha </it>(Tephritidae: Diptera) using two different approaches, a long-term evolutionary analysis and a populational genetic data analysis. The first analysis was performed by using sequences of three species of <it>Anastrepha </it>and sequences from several species of <it>Drosophila </it>using the ratio of nonsynonymous to synonymous rates of evolution in PAML, which revealed that the <it>fru </it>region here studied has evolved by positive selection. Using Bayes Empirical Bayes we estimated that 16 sites located in the connecting region of the <it>fruitless </it>gene were evolving under positive selection. We also investigated for signs of this positive selection using populational data from 50 specimens from three species of <it>Anastrepha </it>from different localities in Brazil. The use of standard tests of selection and a new test that compares patterns of differential survival between synonymous and nonsynonymous in evolutionary time also provide evidence of positive selection across species and of a selective sweep for one of the species investigated.</p> <p>Conclusions</p> <p>Our data indicate that the high diversification of <it>fru </it>connecting region in <it>Anastrepha </it>flies is due at least in part to positive selection, not merely as a consequence of relaxed selective constraint. These conclusions are based not only on the comparison of distantly related taxa that show long-term divergence time, but also on recently diverged lineages and suggest that episodes of adaptive evolution in <it>fru </it>may be related to sexual selection and/or conflict related to its involvement in male courtship behavior.</p

Unraveling the effect of silent, intronic and missense mutations on VWF splicing: contribution of next generation sequencing in the study of mRNA

Large studies in von Willebrand disease patients, including Spanish and Portuguese registries, led to identification of >250 different mutations. It is a challenge to determine the pathogenic effect of potential splice site mutations on VWF mRNA. This study aimed to elucidate the true effects of 18 mutations on VWF mRNA processing, investigate the contribution of next-generation sequencing to in vivo mRNA study in von Willebrand disease, and compare the findings with in silico prediction. RNA extracted from patient platelets and leukocytes was amplified by RT-PCR and sequenced using Sanger and next generation sequencing techniques. Eight mutations affected VWF splicing: c.1533+1G>A, c.5664+2T>C and c.546G>A (p.=) prompted exon skipping; c.3223-7_3236dup and c.7082-2A>G resulted in activation of cryptic sites; c.3379+1G>A and c.7473G>A (p.=) demonstrated both molecular pathogenic mechanisms simultaneously; and the p.Cys370Tyr missense mutation generated two aberrant transcripts. Of note, the complete effect of 3 mutations was provided by next generation sequencing alone because of low expression of the aberrant transcripts. In the remaining 10 mutations, no effect was elucidated in the experiments. However, the differential findings obtained in platelets and leukocytes provided substantial evidence that 4 of these would have an effect on VWF levels. In this first report using next generation sequencing technology to unravel the effects of VWF mutations on splicing, the technique yielded valuable information. Our data bring to light the importance of studying the effect of synonymous and missense mutations on VWF splicing to improve the current knowledge of the molecular mechanisms behind von Willebrand disease.info:eu-repo/semantics/publishedVersio

Metabolic Networks of Sodalis glossinidius: A Systems Biology Approach to Reductive Evolution

Background: Genome reduction is a common evolutionary process affecting bacterial lineages that establish symbiotic or pathogenic associations with eukaryotic hosts. Such associations yield highly reduced genomes with greatly streamlined metabolic abilities shaped by the type of ecological association with the host. Sodalis glossinidius, the secondary endosymbiont of tsetse flies, represents one of the few complete genomes available of a bacterium at the initial stages of this process. In the present study, genome reduction is studied from a systems biology perspective through the reconstruction and functional analysis of genome-scale metabolic networks of S. glossinidius. Results: The functional profile of ancestral and extant metabolic networks sheds light on the evolutionary events underlying transition to a host-dependent lifestyle. Meanwhile, reductive evolution simulations on the extant metabolic network can predict possible future evolution of S. glossinidius in the context of genome reduction. Finally, knockout simulations in different metabolic systems reveal a gradual decrease in network robustness to different mutational events for bacterial endosymbionts at different stages of the symbiotic association. Conclusions: Stoichiometric analysis reveals few gene inactivation events whose effects on the functionality of S. glossinidius metabolic systems are drastic enough to account for the ecological transition from a free-living to hostdependent lifestyle. The decrease in network robustness across different metabolic systems may be associated with th