The impact of highly active antiretroviral therapy on the survival of vertically HIV-infected children and adolescents in Belo Horizonte, Brazil

The use of highly active antiretroviral therapy (HAART) for human immunodeficiency virus (HIV)-infected patients has reduced the number of acquired immune deficiency syndrome-related deaths worldwide. This study assessed the impact of HAART on the survival and death rates of vertically HIV-infected children and adolescents in Belo Horizonte, Brazil. Data were obtained from a historic cohort of vertically HIV-infected children and adolescents aged zero-19 years old who were admitted from March 1989-December 2004 and were followed until June 2006. Patients who used HAART were included if they were treated for at least 12 weeks. Of 359 patients, 320 patients met the inclusion criteria. The overall mortality rate was 9.7% [31/320; 95% confidence interval (CI): 6.0-13%]. The median survival for the non-HAART and HAART groups was 31.5 and 55.9 months, respectively (log rank = 22.11, p < 0.0001). In the multivariate analysis, the statistically significant variables were HAART and the weight-for-age Z score < -2, with HAART constituting a protective factor [relative risk (RR): 0.13; CI 95%: 0.05-0.33] and malnutrition constituting a risk factor (RR: 3.44; CI 95%: 1.60-7.40) for death. The incidence of death was 5.1/100 person-years in the non-HAART group and 0.8/100 person-years in the HAART group (p < 0.0001).

Incidence of active mycobacterial infections in Brazilian patients with chronic inflammatory arthritis and negative evaluation for latent tuberculosis infection at baseline - A longitudinal analysis after using TNFa blockers

Several studies point to the increased risk of reactivation of latent tuberculosis infection (LTBI) in patients with chronic inflammatory arthritis (CIAs) after using tumour necrosis factor (TNF)a blockers. To study the incidence of active mycobacterial infections (aMI) in patients starting TNFa blockers, 262 patients were included in this study: 109 with rheumatoid arthritis (RA), 93 with ankylosing spondylitis (AS), 44 with juvenile idiopathic arthritis (JIA) and 16 with psoriatic arthritis (PsA). All patients had indication for anti-TNFa therapy. Epidemiologic and clinical data were evaluated and a simple X-ray and tuberculin skin test (TST) were performed. The control group included 215 healthy individuals. The follow-up was 48 months to identify cases of aMI. TST positivity was higher in patients with AS (37.6%) than in RA (12.8%), PsA (18.8%) and JIA (6.8%) (p < 0.001). In the control group, TST positivity was 32.7%. Nine (3.43%) patients were diagnosed with aMI. The overall incidence rate of aMI was 86.93/100,000 person-years [95% confidence interval (CI) 23.6-217.9] for patients and 35.79/100,000 person-years (95% CI 12.4-69.6) for control group (p < 0.001). All patients who developed aMI had no evidence of LTBI at the baseline evaluation. Patients with CIA starting TNFa blockers and no evidence of LTBI at baseline, particularly with nonreactive TST, may have higher risk of aMI.

Networks in Argentine agriculture: a multiple-case study approach

Argentina is among the four largest producers of soybeans, sunflower, corn, and wheat, among other agricultural products. Institutional and policy changes during the 1990s fostered the development of Argentine agriculture and the introduction of innovative process and product technologies (no-till, agrochemicals, GMO, GPS) and new investments in modern, large-scale sunflower and soybean processing plants. In addition to technological changes, a "quiet revolution" occurred in the way agricultural production was carried out and organized: from self-production or ownership agriculture to a contract-based agriculture. The objective of this paper is to explore and describe the emergence of networks in the Argentine crop production sector. The paper presents and describes four cases that currently represent about 50% of total grain and oilseed production in Argentina: "informal hybrid form", "agricultural trust fund", "investor-oriented corporate structure", and "network of networks". In all cases, hybrid forms involve a group of actors linked by common objectives, mainly to gain scale, share resources, and improve the profitability of the business. Informal contracts seem to be the most common way of organizing the agriculture process, but using short-term contracts and sequential interfirm collaboration. Networks of networks involve long-term relationships and social development, and reciprocal interfirm collaboration. Agricultural trust fund and investor-oriented corporate structures have combined interfirm collaboration and medium-term relationships. These organizational forms are highly flexible and show a great capacity to adapt to challenges; they are competitive because they enjoy aligned incentives, flexibility, and adaptability.

Adolescent support networks in a health care context: the interface between health, family and education

AbstractOBJECTIVEAnalyze adolescents' perceptions about support networks and their health needs.METHODAnalytical and interpretive study using focus groups conducted in municipal state schools in Fortaleza, in the State of Ceará during the first semester of 2012. The sample comprised 36 male and female adolescents aged between 13 and 16 years attending the ninth grade of the second phase of elementary school.RESULTSThematic analysis revealed that the health care support network and interaction between health professionals, education professionals and family members was insufficient, constituting a lack of an integrated network to enable and provide support for health promotion.CONCLUSIONCoordination between education, health and family services has the potential to act as a support network to help meet adolescents' healthcare needs and demands.

Comparison between artificial neural networks and maximum likelihood classification in digital soil mapping

Soil surveys are the main source of spatial information on soils and have a range of different applications, mainly in agriculture. The continuity of this activity has however been severely compromised, mainly due to a lack of governmental funding. The purpose of this study was to evaluate the feasibility of two different classifiers (artificial neural networks and a maximum likelihood algorithm) in the prediction of soil classes in the northwest of the state of Rio de Janeiro. Terrain attributes such as elevation, slope, aspect, plan curvature and compound topographic index (CTI) and indices of clay minerals, iron oxide and Normalized Difference Vegetation Index (NDVI), derived from Landsat 7 ETM+ sensor imagery, were used as discriminating variables. The two classifiers were trained and validated for each soil class using 300 and 150 samples respectively, representing the characteristics of these classes in terms of the discriminating variables. According to the statistical tests, the accuracy of the classifier based on artificial neural networks (ANNs) was greater than of the classic Maximum Likelihood Classifier (MLC). Comparing the results with 126 points of reference showed that the resulting ANN map (73.81 %) was superior to the MLC map (57.94 %). The main errors when using the two classifiers were caused by: a) the geological heterogeneity of the area coupled with problems related to the geological map; b) the depth of lithic contact and/or rock exposure, and c) problems with the environmental correlation model used due to the polygenetic nature of the soils. This study confirms that the use of terrain attributes together with remote sensing data by an ANN approach can be a tool to facilitate soil mapping in Brazil, primarily due to the availability of low-cost remote sensing data and the ease by which terrain attributes can be obtained.