Gender-based violence and socioeconomic inequalities: Does living in more deprived neighbourhoods increase women's risk of intimate partner violence?

This study investigates the influence of neighbourhood socioeconomic conditions on women's likelihood of experiencing intimate partner violence (IPV) in Sao Paulo, Brazil. Data from 940 women who were interviewed as part of the WHO multi-country study on women's health and domestic violence against women, and census data for Sao Paulo City, were analyzed using multilevel regression techniques. A neighbourhood socioeconomic-level scale was created, and proxies for the socioeconomic positions of the couple were included. Other individual level variables included factors related to partner's behaviour and women's experiences and attitudes. Women's risk of IPV did not vary across neighbourhoods in Sao Paulo nor was it influenced by her individual socioeconomic characteristics. However, women in the middle range of the socioeconomic scale were significantly more likely to report having experienced violence by a partner. Partner behaviours such as excessive alcohol use, controlling behaviour and multiple sexual partnerships were important predictors of IPV. A women's likelihood of IPV also increased if either her mother had experienced IPV or if she used alcohol excessively. These findings suggest that although the characteristics of people living in deprived neighbourhoods may influence the probability that a woman will experience IPV, higher-order contextual dynamics do not seem to affect this risk. While poverty reduction will improve the lives of individuals in many ways, strategies to reduce IPV should prioritize shifting norms that reinforce certain negative male behaviours. (C) 2012 Elsevier Ltd. All rights reserved.

Urea-Based Synthesis of Zinc Oxide Nanostructures at Low Temperature

The preparation of nanometer-sized structures of zinc oxide (ZnO) from zinc acetate and urea as raw materials was performed using conventional water bath heating and a microwave hydrothermal (MH) method in an aqueous solution. The oxide formation is controlled by decomposition of the added urea in the sealed autoclave. The influence of urea and the synthesis method on the final product formation are discussed. Broadband photoluminescence (PL) behavior in visible-range spectra was observed with a maximum peak centered in the green region which was attributed to different defects and the structural changes involved with ZnO crystals which were produced during the nucleation process.

High Prevalence of Dementia in a Community-Based Survey of Older People from Brazil: Association with Intellectual Activity Rather than Education

Although several surveys have been conducted around the world, few surveys have investigated the prevalence of dementia in Latin America. The aim of this study was to estimate dementia prevalence in a community sample in Ribeirao Preto, Brazil, and to evaluate its distribution across several socio-demographic and clinical characteristics and habits. The population was aged 60 years and older and a representative sample from three different social regions. The screening instruments used in the first phase were the Mini-Mental State Examination, the Fuld Object-Memory Evaluation, the Informant Questionnaire on Cognitive Decline in the Elderly, and the Bayer Activities of Daily Living Scale. In the second phase, the Cambridge Examination was employed to diagnose dementia according to the DSM-IV criteria. The estimate of dementia prevalence was adjusted for screening instrument performance, using the positive and negative predictive values. The data were weighted to compare frequencies, considering the sampling and the non-response effect, and subjected to multivariate analysis. In all, 1.145 elderly subjects were evaluated (mean age: 70.9 years), of whom 63.4% were female and 52.8% had up to 4 years of schooling (participation rates at the first and the second phases were 62.6 and 60%, respectively). The observed and estimated prevalences of dementia were 5.9% and 12.5%, respectively (n = 68). Alzheimer's disease was the main cause (60.3%). Dementia was associated with old age, low education, stroke, absence of arthritis, and not reading books. The estimated prevalence of dementia was higher than the prevalence previously found. Associated factors confirmed the importance of intellectual activities in prevention.

Nonculture-based identification of bacteria in milk by protein fingerprinting

Traditional methods for bacterial identification include Gram staining, culturing, and biochemical assays for phenotypic characterization of the causative organism. These methods can be time-consuming because they require in vitro cultivation of the microorganisms. Recently, however, it has become possible to obtain chemical profiles for lipids, peptides, and proteins that are present in an intact organism, particularly now that new developments have been made for the efficient ionization of biomolecules. MS has therefore become the state-of-the-art technology for microorganism identification in microbiological clinical diagnosis. Here, we introduce an innovative sample preparation method for nonculture-based identification of bacteria in milk. The technique detects characteristic profiles of intact proteins (mostly ribosomal) with the recently introduced MALDI SepsityperTM Kit followed by MALDI-MS. In combination with a dedicated bioinformatics software tool for databank matching, the method allows for almost real-time and reliable genus and species identification. We demonstrate the sensitivity of this protocol by experimentally contaminating pasteurized and homogenized whole milk samples with bacterial loads of 10(3)-10(8) colony-forming units (cfu) of laboratory strains of Escherichia coli, Enterococcus faecalis, and Staphylococcus aureus. For milk samples contaminated with a lower bacterial load (104 cfu mL-1), bacterial identification could be performed after initial incubation at 37 degrees C for 4 h. The sensitivity of the method may be influenced by the bacterial species and count, and therefore, it must be optimized for the specific application. The proposed use of protein markers for nonculture-based bacterial identification allows for high-throughput detection of pathogens present in milk samples. This method could therefore be useful in the veterinary practice and in the dairy industry, such as for the diagnosis of subclinical mastitis and for the sanitary monitoring of raw and processed milk products.

Exploration of the parameter space in an agent-based model of tuberculosis spread: emergence of drug resistance in developing vs developed countries

In this work we present an agent-based model for the spread of tuberculosis where the individuals can be infected with either drug-susceptible or drug-resistant strains and can also receive a treatment. The dynamics of the model and the role of each one of the parameters are explained. The whole set of parameters is explored to check their importance in the numerical simulation results. The model captures the beneficial impact of the adequate treatment on the prevalence of tuberculosis. Nevertheless, depending on the treatment parameters range, it also captures the emergence of drug resistance. Drug resistance emergence is particularly likely to occur for parameter values corresponding to less efficacious treatment, as usually found in developing countries.

Constraint-based analysis of gene interactions using restricted boolean networks and time-series data

Abstract Background A popular model for gene regulatory networks is the Boolean network model. In this paper, we propose an algorithm to perform an analysis of gene regulatory interactions using the Boolean network model and time-series data. Actually, the Boolean network is restricted in the sense that only a subset of all possible Boolean functions are considered. We explore some mathematical properties of the restricted Boolean networks in order to avoid the full search approach. The problem is modeled as a Constraint Satisfaction Problem (CSP) and CSP techniques are used to solve it. Results We applied the proposed algorithm in two data sets. First, we used an artificial dataset obtained from a model for the budding yeast cell cycle. The second data set is derived from experiments performed using HeLa cells. The results show that some interactions can be fully or, at least, partially determined under the Boolean model considered. Conclusions The algorithm proposed can be used as a first step for detection of gene/protein interactions. It is able to infer gene relationships from time-series data of gene expression, and this inference process can be aided by a priori knowledge available.

BDNF gene polymorphism, cognition and symptom severity in a Brazilian population-based sample of first-episode psychosis subjects

OBJECTIVE: To investigate the influence of brain-derived neurotrophic factor (BDNF) gene variations on cognitive performance and clinical symptomatology in first-episode psychosis (FEP). METHODS: We performed BDNF val66met variant genotyping, cognitive testing (verbal fluency and digit spans) and assessments of symptom severity (as assessed with the PANSS) in a population-based sample of FEP patients (77 with schizophreniform psychosis and 53 with affective psychoses) and 191 neighboring healthy controls. RESULTS: There was no difference in the proportion of Met allele carriers between FEP patients and controls, and no significant influence of BDNF genotype on cognitive test scores in either of the psychosis groups. A decreased severity of negative symptoms was found in FEP subjects that carried a Met allele, and this finding reached significance for the subgroup with affective psychoses (p < 0.01, ANOVA). CONCLUSIONS: These results suggest that, in FEP, the BDNF gene Val66Met polymorphism does not exert a pervasive influence on cognitive functioning but may modulate the severity of negative symptoms.

A holistic approach to model-based testing of Web service compositions

The behavior of composed Web services depends on the results of the invoked services; unexpected behavior of one of the invoked services can threat the correct execution of an entire composition. This paper proposes an event-based approach to black-box testing of Web service compositions based on event sequence graphs, which are extended by facilities to deal not only with service behavior under regular circumstances (i.e., where cooperating services are working as expected) but also with their behavior in undesirable situations (i.e., where cooperating services are not working as expected). Furthermore, the approach can be used independently of artifacts (e.g., Business Process Execution Language) or type of composition (orchestration/choreography). A large case study, based on a commercial Web application, demonstrates the feasibility of the approach and analyzes its characteristics. Test generation and execution are supported by dedicated tools. Especially, the use of an enterprise service bus for test execution is noteworthy and differs from other approaches. The results of the case study encourage to suggest that the new approach has the power to detect faults systematically, performing properly even with complex and large compositions. Copyright © 2012 John Wiley & Sons, Ltd.