Comparison of conventional serology and PCR methods for the routine diagnosis of Trypanosoma cruzi infection

Introduction Trypanosoma cruzi, a flagellated protozoan, is the etiologic agent of Chagas disease, and it is estimated that approximately 5 million people in Brazil are infected with this parasite. This work aimed to compare the current diagnostic methods for Chagas disease, including conventional serological (IFAT and ELISA) and molecular techniques (PCR), to introduce PCR as an auxiliary technique. Methods A total of 106 chagasic patients were evaluated: 88 from endemic areas of Parana, 6 from São Paulo, 3 from Minas Gerais, 3 from Rio Grande do Sul, 1 from Bahia and 5 from the Santa Catarina T. cruzi outbreak. The samples were analyzed by conventional serological methods (IFAT, ELISA), hemoculture and PCR to confirm Chagas disease. Results When IFAT was used to determine antibody levels, the sensitivity was 81.7% for patients with the cardiac form of the disease and 100% for the other clinical forms. In contrast, ELISA showed 84% sensitivity and 100% specificity. The use of serological and molecular techniques and their implications for the diagnosis of Chagas disease in non-endemics area are discussed. Conclusions PCR constitutes an excellent support methodology for the laboratory diagnosis of Chagas disease due to its high sensitivity and specificity.

Evaluation of two sweeping methods for estimating the number of immature Aedes aegypti (Diptera: Culicidae) in large containers

Introduction Here, we evaluated sweeping methods used to estimate the number of immature Aedes aegypti in large containers. Methods III/IV instars and pupae at a 9:1 ratio were placed in three types of containers with, each one with three different water levels. Two sweeping methods were tested: water-surface sweeping and five-sweep netting. The data were analyzed using linear regression. Results The five-sweep netting technique was more suitable for drums and water-tanks, while the water-surface sweeping method provided the best results for swimming pools. Conclusions Both sweeping methods are useful tools in epidemiological surveillance programs for the control of Aedes aegypti.

The performance of four molecular methods for the laboratory diagnosis of congenital toxoplasmosis in amniotic fluid samples

Introduction Toxoplasmosis may be life-threatening in fetuses and in immune-deficient patients. Conventional laboratory diagnosis of toxoplasmosis is based on the presence of IgM and IgG anti-Toxoplasma gondii antibodies; however, molecular techniques have emerged as alternative tools due to their increased sensitivity. The aim of this study was to compare the performance of 4 PCR-based methods for the laboratory diagnosis of toxoplasmosis. One hundred pregnant women who seroconverted during pregnancy were included in the study. The definition of cases was based on a 12-month follow-up of the infants. Methods Amniotic fluid samples were submitted to DNA extraction and amplification by the following 4 Toxoplasma techniques performed with parasite B1 gene primers: conventional PCR, nested-PCR, multiplex-nested-PCR, and real-time PCR. Seven parameters were analyzed, sensitivity (Se), specificity (Sp), positive predictive value (PPV), negative predictive value (NPV), positive likelihood ratio (PLR), negative likelihood ratio (NLR) and efficiency (Ef). Results Fifty-nine of the 100 infants had toxoplasmosis; 42 (71.2%) had IgM antibodies at birth but were asymptomatic, and the remaining 17 cases had non-detectable IgM antibodies but high IgG antibody titers that were associated with retinochoroiditis in 8 (13.5%) cases, abnormal cranial ultrasound in 5 (8.5%) cases, and signs/symptoms suggestive of infection in 4 (6.8%) cases. The conventional PCR assay detected 50 cases (9 false-negatives), nested-PCR detected 58 cases (1 false-negative and 4 false-positives), multiplex-nested-PCR detected 57 cases (2 false-negatives), and real-time-PCR detected 58 cases (1 false-negative). Conclusions The real-time PCR assay was the best-performing technique based on the parameters of Se (98.3%), Sp (100%), PPV (100%), NPV (97.6%), PLR (∞), NLR (0.017), and Ef (99%).

Depressive symptoms and harmful alcohol use in hepatitis C patients: prevalence and correlates

Introduction It is important to understand the characteristics and vulnerabilities of people who have hepatitis C because this disease is currently an important public health problem. The objective of this study was to estimate the prevalence of depressive symptoms and harmful alcohol use in patients with hepatitis C and to study the association between these outcomes and demographic, psychosocial and clinical variables. Methods This cross-sectional, descriptive and analytical study involved 82 hepatitis C patients who were being treated with pegylated interferon and ribavirin at a public university hospital. The primary assessments used in the study were the Alcohol Use Disorders Identification Test and the Beck Depression Inventory. Bivariate analyses were followed by logistic regression. Results The prevalence of depressive symptoms was 30.5% (n=25), and that of harmful alcohol use was 34.2% (n=28). Logistic regression analysis showed that individuals who were dissatisfied with their social support (OR=4.41; CI=1.00-19.33) and were unemployed (OR=6.31; CI=1.44-27.70) were at a higher risk for depressive symptoms, whereas harmful alcohol use was associated with the male sex (OR=6.78; CI=1.38-33.19) and the use of illicit substances (OR=7.42; CI=1.12-49.00). Conclusions High prevalence rates of depressive symptoms and harmful alcohol use were verified, indicating vulnerabilities that must be properly monitored and treated to reduce emotional suffering in this population.

Da sobrevivência física à sobrevivência mental : aspectos do funcionamento psíquico em ex-combatentes da guerra colonial portuguesa

Tese de Doutoramento apresentada ao ISPA - Instituto Universitário

Leishmania, Babesia and Ehrlichia in urban pet dogs: co-infection or cross-reaction in serological methods?

INTRODUCTION: The present study was designed to assess the occurrence of co-infection or cross-reaction in the serological techniques used for detecting the anti-Leishmania spp., -Babesia canis vogeli and -Ehrlichia canis antibodies in urban dogs from an area endemic to these parasites. METHODS: The serum samples from dogs were tested for the Babesia canis vogeli strain Belo Horizonte antigen and Ehrlichia canis strain São Paulo by immunofluorescence antibody test (IFAT) and by anti-Leishmania immunoglobulin G (IgG) antibody detection to assess Leishmania infection. We used the following four commercial kits for canine visceral leishmaniasis: ELISA, IFAT, Dual Path Platform (DPP) (Bio Manguinhos(r)/FIOCRUZ/MS) and a rK39 RDT (Kalazar Detect Canine Rapid Test; Inbios). RESULTS : Of 96 serum samples submitted to serological assays, 4 (4.2%) were positive for Leishmania as determined by ELISA; 12 (12.5%), by IFAT; 14 (14.6%) by rK39 RDT; and 20 (20.8%), by DPP. Antibodies against Ehrlichia and Babesia were detected in 23/96 (23.9%) and 30/96 (31.2%) samples, respectively. No significant association was identified between the results of tests for detecting Babesia or Ehrlichia and those for detecting Leishmania (p-value>0.05). CONCLUSIONS: In the present study, we demonstrated co-infection with Ehrlichia or Babesia and Leishmania in dogs from Minas Gerais (Brazil); we also found that the serological tests that were used did not cross-react.

PRELIMINARY RESULTS OF A LARGE-SCALE TREE INVENTORY OF UPLAND RAIN FOREST IN THE CENTRAL AMAZON

A large-scale inventory of trees > 10cm DBH was conducted in the upland "terra firme" rain forest of the Distrito Agropecuário da SUFRAMA (Manaus Free Zone Authority Agricultural District) approximately 65Km north of the city of Manaus (AM), Srasil. Thegeneral appearance and structure of the forest is described together with local topography and soil texture. Thepreliminary results of the Inventory provide a minimum estimate of 698 tree species in 53 families in the 40Km radius sampled, including 17 undescribed species. Themost numerically abundant families, Lecythidaceae, Leguminosae, 5apotaceae and Burseraceae as also among the most species rich families. One aspect of this diverse assemblage is the proliferation of species within certain genera, Including 26 genera In 17 families with 6 or more species or morphospecies. Most species have very low abundances of less than 1 tree per hectare. While more abundant species do exist at densities ranging up to a mean of 12 trees per ha, many have clumped distributions leading to great variation in local species abundance. The degree of similarity between hectare samples based int the Coefficient of Community similarity Index varies widely over different sample hectares for five ecologically different families. Soil texture apparently plays a significant role In determining species composition in the different one hectare plots examined while results for other variable were less consistent. Greater differences in similarity indices are found for comparisons with a one hectare sample within the same formation approximately 40Km to the south. It is concluded that homogeneity of tree community composition within this single large and diverse yet continuous upland forest formation can not be assumed.

Mapping the Pasture Steppe in Bayankhongor, Mongolia: comparison of classification methods, using Landsat-8 and geophysical data

Grasslands in semi-arid regions, like Mongolian steppes, are facing desertification and degradation processes, due to climate change. Mongolia’s main economic activity consists on an extensive livestock production and, therefore, it is a concerning matter for the decision makers. Remote sensing and Geographic Information Systems provide the tools for advanced ecosystem management and have been widely used for monitoring and management of pasture resources. This study investigates which is the higher thematic detail that is possible to achieve through remote sensing, to map the steppe vegetation, using medium resolution earth observation imagery in three districts (soums) of Mongolia: Dzag, Buutsagaan and Khureemaral. After considering different thematic levels of detail for classifying the steppe vegetation, the existent pasture types within the steppe were chosen to be mapped. In order to investigate which combination of data sets yields the best results and which classification algorithm is more suitable for incorporating these data sets, a comparison between different classification methods were tested for the study area. Sixteen classifications were performed using different combinations of estimators, Landsat-8 (spectral bands and Landsat-8 NDVI-derived) and geophysical data (elevation, mean annual precipitation and mean annual temperature) using two classification algorithms, maximum likelihood and decision tree. Results showed that the best performing model was the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), using the decision tree. For maximum likelihood, the model that incorporated Landsat-8 bands with mean annual precipitation (Model 5) and the one that incorporated Landsat-8 bands with mean annual precipitation and mean annual temperature (Model 13), achieved the higher accuracies for this algorithm. The decision tree models consistently outperformed the maximum likelihood ones.

Development of benchmarks for operating costs and resources consumption to be used in healthcare building sustainability assessment methods

Since the last decade of the twentieth century, the healthcare industry is paying attention to the environmental impact of their buildings and therefore new regulations, policy goals and Buildings Sustainability Assessment (HBSA) methods are being developed and implemented. At the present, healthcare is one of the most regulated industries and it is also one of the largest consumers of energy per net floor area. To assess the sustainability of healthcare buildings it is necessary to establish a set of benchmarks related with their life-cycle performance. They are both essential to rate the sustainability of a project and to support designers and other stakeholders in the process of designing and operating a sustainable building, by allowing the comparison to be made between a project and the conventional and best market practices. This research is focused on the methodology to set the benchmarks for resources consumption, waste production, operation costs and potential environmental impacts related to the operational phase of healthcare buildings. It aims at contributing to the reduction of the subjectivity found in the definition of the benchmarks used in Building Sustainability Assessment (BSA) methods, and it is applied in the Portuguese context. These benchmarks will be used in the development of a Portuguese HBSA method.

Using stated preference methods to assess environmental impacts of forest biomass power plants in Portugal

As a renewable energy source, the use of forest biomass for electricity generation is advantageous in comparison with fossil fuels, however the activity of forest biomass power plants causes adverse impacts, affecting particularly neighbouring communities. The main objective of this study is to estimate the effects of the activity of forest biomass power plants on the welfare of two groups of stakeholders, namely local residents and the general population and we apply two stated preference methods: contingent valuation and discrete choice experiments, respectively. The former method was applied to estimate the minimum compensation residents of neighbouring communities of two forest biomass power plants in Portugal would be willing to accept. The latter method was applied among the general population to estimate their willingness to pay to avoid specific environmental impacts. The results show that the presence of the selected facilities affects individuals’ well-being. On the other hand, in the discrete choice experiments conducted among the general population all impacts considered were significant determinants of respondents’ welfare levels. The results of this study stress the importance of performing an equity analysis of the welfare effects on different groups of stakeholders from the installation of forest biomass power plants, as their effects on welfare are location and impact specific. Policy makers should take into account the views of all stakeholders either directly or indirectly involved when deciding crucial issues regarding the sitting of new forest biomass power plants, in order to achieve an efficient and equitable outcome.

Decision methods applied to solve a safety problem on a waste treatment facility

To solve a health and safety problem on a waste treatment facility, different multicriteria decision methods were used, including the PROV Exponential decision method. Four alternatives and ten attributes were considered. We found a congruent solution, validated by the different methods. The AHP and the PROV Exponential decision method led us to the same options ordering, but the last method reinforced one of the options as being the best performing one, and detached the least performing option. Also, the ELECTRE I method results led to the same ordering which allowed to point the best solution with reasonable confidence. This paper demonstrates the potential of using multicriteria decision methods to support decision making on complex problems such as risk control and accidents prevention.

Qualitative risk assessment during polymer mortar test specimens preparation - methods comparison

Polymer binder modification with inorganic nanomaterials (NM) could be a potential and efficient solution to control matrix flammability of polymer concrete (PC) materials without sacrificing other important properties. Occupational exposures can occur all along the life cycle of a NM and “nanoproducts” from research through scale-up, product development, manufacturing, and end of life. The main objective of the present study is to analyse and compare different qualitative risk assessment methods during the production of polymer mortars (PM) with NM. The laboratory scale production process was divided in 3 main phases (pre-production, production and post-production), which allow testing the assessment methods in different situations. The risk assessment involved in the manufacturing process of PM was made by using the qualitative analyses based on: French Agency for Food, Environmental and Occupational Health & Safety method (ANSES); Control Banding Nanotool (CB Nanotool); Ecole Polytechnique Fédérale de Lausanne method (EPFL); Guidance working safely with nanomaterials and nanoproducts (GWSNN); Istituto Superiore per la Prevenzione e la Sicurezza del Lavoro, Italy method (ISPESL); Precautionary Matrix for Synthetic Nanomaterials (PMSN); and Stoffenmanager Nano. It was verified that the different methods applied also produce different final results. In phases 1 and 3 the risk assessment tends to be classified as medium-high risk, while for phase 2 the more common result is medium level. It is necessary to improve the use of qualitative methods by defining narrow criteria for the methods selection for each assessed situation, bearing in mind that the uncertainties are also a relevant factor when dealing with the risk related to nanotechnologies field.

Automated network resilience optimization using computational intelligence methods

This paper presents an automated optimization framework able to provide network administrators with resilient routing configurations for link-state protocols, such as OSPF or IS-IS. In order to deal with the formulated NP-hard optimization problems, the devised framework is underpinned by the use of computational in- telligence optimization engines, such as Multi-objective Evolutionary Algorithms (MOEAs). With the objective of demonstrating the framework capabilities, two il- lustrative Traffic Engineering methods are described, allowing to attain routing con- figurations robust to changes in the traffic demands and maintaining the network stable even in the presence of link failure events. The presented illustrative results clearly corroborate the usefulness of the proposed automated framework along with the devised optimization methods.

Comparison of different numerical methods for the solution of the time-fractional reaction-diffusion equation with variable diffusion coefficient

In this work we perform a comparison of two different numerical schemes for the solution of the time-fractional diffusion equation with variable diffusion coefficient and a nonlinear source term. The two methods are the implicit numerical scheme presented in [M.L. Morgado, M. Rebelo, Numerical approximation of distributed order reaction- diffusion equations, Journal of Computational and Applied Mathematics 275 (2015) 216-227] that is adapted to our type of equation, and a colocation method where Chebyshev polynomials are used to reduce the fractional differential equation to a system of ordinary differential equations