Existence results for partial neutral functional differential equations with state-dependent delay

In this paper we study the existence of mild solutions for a class of first order abstract partial neutral differential equations with state-dependent delay. (C) 2008 Elsevier Ltd. All rights reserved.

Global solutions for abstract impulsive neutral differential equations

We study the existence of mild solutions for a class of impulsive neutral functional differential equation defined on the whole real axis. Some concrete applications to ordinary and partial neutral differential equations with impulses are considered. (C) 2010 Elsevier Ltd. All rights reserved.

Expectation Propagation with Factorizing Distributions: A Gaussian Approximation and Performance Results for Simple Models

We discuss the expectation propagation (EP) algorithm for approximate Bayesian inference using a factorizing posterior approximation. For neural network models, we use a central limit theorem argument to make EP tractable when the number of parameters is large. For two types of models, we show that EP can achieve optimal generalization performance when data are drawn from a simple distribution.

Molecular evidence of horizontal transmission of hepatitis C virus within couples

Hepatitis C virus (HCV) transmission has decreased with the adoption of universal blood donor screening and social policies to reduce the risk of infection in intravenous drug users, but remains a worldwide health problem. The objective of this study was to evaluate the phylogenetic relationships among sequences from different HCV genomic regions from sexual partners of infected patients. Nine couples with a stable relationship and without other risk factors for HCV infection and 42 control patients were selected, and the NS3 and NS5B regions were analysed. Phylogenetic analysis showed that viruses from five of the couples had a common origin, clustering in the same monophyletic group, with bootstrap values greater than 70. For the other couples, monophyletic groups were observed, but without bootstrap support. Thus, using two different viral genome regions, a common source of infection was observed in both members of five couples. These data strongly support HCV transmission within couples.

Molecular epidemiology and genetic diversity of hepatitis B virus genotype E in an isolated Afro-Colombian community

Hepatitis B virus (HBV) infection is a significant public health concern with 350 million chronic carriers worldwide. Eight HBV genotypes (A-H) have been described so far. Genotype E (HBV/E) is widely distributed in West Africa and has rarely been found in other continents, except for a few cases in individuals with an African background. In this study, we characterized HBV genotypes in Quibdo, Colombia, by partial S/P gene sequencing, and found, for the first time, HBV/E circulating in nine Afro-Colombian patients who had no recent contact with Africa. The presence of HBV/E in this community as a monophyletic group suggests that it was a result of a recent introduction by some Afro-descendent contact or, alternatively, that the virus came with slaves brought to Colombia. By using sequences with sampling dates, we estimated the substitution rate to be about 3.2x10(-4) substitutions per site per year, which resulted in a time to the most recent common ancestor (TMRCA) of 29 years. In parallel, we also estimated the TMRCA for HBV/E by using two previously estimated substitution rates (7.7x10(-4) and 1.5x10(-5) substitutions per site per year). The TMRCA was around 35 years under the higher rate and 1500 years under the slower rate. In sum, this work reports for the first time the presence of an exclusively African HBV genotype circulating in South America. We also discuss the time of the entry of this virus into America based on different substitution rates estimated for HBV.

Hepatitis B virus and hepatitis delta virus genotypes in outbreaks of fulminant hepatitis (Labrea black fever) in the western Brazilian Amazon region

The genotypes of hepatitis B (HBV) and delta (HDV) viruses circulating among fulminant hepatitis cases from the western Amazon Basin of Brazil were characterized in this study. HBV and HDV isolates were obtained from liver samples from 14 patients who developed fulminant hepatitis and died during 1978-1989. HBV DNA and HDV RNA were detected in all samples. Phylogenetic analyses of HDV sequences showed that they all clustered with previously characterized sequences of HDV genotype 3 (HDV-3). HBV genotypes F, A and D were found in 50.0, 28.6 and 21.4% of cases, respectively. These results confirm the predominance of HDV-3 in South America and its association with the severe form of hepatitis, and the finding of the co-infection of HDV-3 with different genotypes of HBV suggests that the association between HDV-3 and HBV-F is not necessarily causally related to a more severe clinical course of infection.

Model for Differential Nursing Diagnosis of Alterations in Urinary Elimination Based on Fuzzy Logic

Nursing diagnoses associated with alterations of urinary elimination require different interventions, Nurses, who are not specialists, require support to diagnose and manage patients with disturbances of urine elimination. The aim of this study was to present a model based on fuzzy logic for differential diagnosis of alterations in urinary elimination, considering nursing diagnosis approved by the North American Nursing Diagnosis Association, 2001-2002. Fuzzy relations and the maximum-minimum composition approach were used to develop the system. The model performance was evaluated with 195 cases from the database of a previous study, resulting in 79.0% of total concordance and 19.5% of partial concordance, when compared with the panel of experts. Total discordance was observed in only three cases (1.5%). The agreement between model and experts was excellent (kappa = 0.98, P < .0001) or substantial (kappa = 0.69, P < .0001) when considering the overestimative accordance (accordance was considered when at least one diagnosis was equal) and the underestimative discordance (discordance was considered when at least one diagnosis was different), respectively. The model herein presented showed good performance and a simple theoretical structure, therefore demanding few computational resources.

A Bayesian approach to fuzzy hypotheses testing for the estimation of optimal age for vaccination against measles

Fuzzy Bayesian tests were performed to evaluate whether the mother`s seroprevalence and children`s seroconversion to measles vaccine could be considered as ""high"" or ""low"". The results of the tests were aggregated into a fuzzy rule-based model structure, which would allow an expert to influence the model results. The linguistic model was developed considering four input variables. As the model output, we obtain the recommended age-specific vaccine coverage. The inputs of the fuzzy rules are fuzzy sets and the outputs are constant functions, performing the simplest Takagi-Sugeno-Kang model. This fuzzy approach is compared to a classical one, where the classical Bayes test was performed. Although the fuzzy and classical performances were similar, the fuzzy approach was more detailed and revealed important differences. In addition to taking into account subjective information in the form of fuzzy hypotheses it can be intuitively grasped by the decision maker. Finally, we show that the Bayesian test of fuzzy hypotheses is an interesting approach from the theoretical point of view, in the sense that it combines two complementary areas of investigation, normally seen as competitive. (C) 2007 IMACS. Published by Elsevier B.V. All rights reserved.

Exploring the knowledge contained in neuroimages: Statistical discriminant analysis and automatic segmentation of the most significant changes

Objective: The aim of this article is to propose an integrated framework for extracting and describing patterns of disorders from medical images using a combination of linear discriminant analysis and active contour models. Methods: A multivariate statistical methodology was first used to identify the most discriminating hyperplane separating two groups of images (from healthy controls and patients with schizophrenia) contained in the input data. After this, the present work makes explicit the differences found by the multivariate statistical method by subtracting the discriminant models of controls and patients, weighted by the pooled variance between the two groups. A variational level-set technique was used to segment clusters of these differences. We obtain a label of each anatomical change using the Talairach atlas. Results: In this work all the data was analysed simultaneously rather than assuming a priori regions of interest. As a consequence of this, by using active contour models, we were able to obtain regions of interest that were emergent from the data. The results were evaluated using, as gold standard, well-known facts about the neuroanatomical changes related to schizophrenia. Most of the items in the gold standard was covered in our result set. Conclusions: We argue that such investigation provides a suitable framework for characterising the high complexity of magnetic resonance images in schizophrenia as the results obtained indicate a high sensitivity rate with respect to the gold standard. (C) 2010 Elsevier B.V. All rights reserved.

A decision support system to facilitate management of patients with acute gastrointestinal bleeding

Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.

DC-SIGN (CD209) gene promoter polymorphisms in a Brazilian population and their association with human T-cell lymphotropic virus type 1 infection

This study evaluated four polymorphisms located in the DC-SIGN (CD209) gene promoter region (positions -336, -332 -201 and -139) in DNA samples from four Brazilian ethnic groups (Caucasians, Afro-Brazilian, Asians and Amerindians) to establish the population distribution of these single-nucleotide polymorphisms (SNPs) and correlated DC-SIGN polymorphisms and infection in samples from human T-cell lymphotropic virus type 1 (HTLV-1)-infected individuals. To identify CD209 SNPs, 452 bp of the CD209 promoter region were sequenced and the genotype and allelic frequencies were evaluated. This is the first study to show genetic polymorphism in the CD209 gene in distinct Brazilian ethnic groups with the distribution of allelic and genotypic frequency. The results showed that -336A and -139A SNPs were quite common in Asians and that the -201T allele was not observed in Caucasians, Asians or Amerindians. No significant differences were observed between individuals with HTLV-1 disease and asymptomatic patients. However, the -336A variant was more frequent in HTLV-1 -infected patients [HTLV-1-associated myelopathy/tropical spastic paraparesis (HAM/TSP), 80%; healthy asymptomatic HTLV-1 carriers, 90 %] than in the control group (70 %) [P=0.0197, odds ratio (OR)=2.511, 95 % confidence interval (CI)=1.218-5.179). In addition, the -139A allele was found to be associated with protection against HTLV-1 infection (P=0.0037, OR=0.3758, 95% CI=0.1954-0.7229) when the HTLV-1 -infected patients as a whole were compared with the healthy-control group. These observations suggest that the -139A allele may be associated with HTLV-1 infection, although no significant association was observed among asymptomatic and HAM/TSP patients. In conclusion, the variation observed in SNPs -336 and -139 indicates that this lectin may be of crucial importance in the susceptibility/transmission of HTLV-1 infections.

An association rule-based method to support medical image diagnosis with efficiency

In this paper, we propose a method based on association rule-mining to enhance the diagnosis of medical images (mammograms). It combines low-level features automatically extracted from images and high-level knowledge from specialists to search for patterns. Our method analyzes medical images and automatically generates suggestions of diagnoses employing mining of association rules. The suggestions of diagnosis are used to accelerate the image analysis performed by specialists as well as to provide them an alternative to work on. The proposed method uses two new algorithms, PreSAGe and HiCARe. The PreSAGe algorithm combines, in a single step, feature selection and discretization, and reduces the mining complexity. Experiments performed on PreSAGe show that this algorithm is highly suitable to perform feature selection and discretization in medical images. HiCARe is a new associative classifier. The HiCARe algorithm has an important property that makes it unique: it assigns multiple keywords per image to suggest a diagnosis with high values of accuracy. Our method was applied to real datasets, and the results show high sensitivity (up to 95%) and accuracy (up to 92%), allowing us to claim that the use of association rules is a powerful means to assist in the diagnosing task.

Decay chain differential equations: Solution through matrix algebra

A matricial method to solve the decay chain differential equations system is presented. The quantity of each nuclide in the chain at a time t may be evaluated by analytical expressions obtained in a simple way using recurrence relations. This method may be applied to problems of radioactive buildup and decay and can be easily implemented computationally. (C) 2009 Elsevier B.V. All rights reserved.