Novel affinity pairs "tag-receptor" for the purification of fusion proteins

Fundação para a Ciência e Tecnologia - SFRH/BD/48804/2008 and the project PTDC/BI/65383/2006 assigned to Prof. Cecíla Roque and also to Associate Laboratory REQUIMTE (Pest-C/EQB/LA0006/2011)

Analysis of the detection coefficient for the association between leprosy and pregnancy in the integration region of Carajas, State of Para, Brazil

Introduction The association between leprosy and pregnancy is currently poorly understood and has been linked to serious clinical consequences. Methods A retrospective study between 2007 and 2009 was performed in the integration region of Carajás, Brazil on a population of pregnant lepers, with non-lepers of ages 12-49 years serving as the reference population. Results Twenty-nine pregnant lepers were studied during the study period. The detection rates (DRs) for the studied association were 4.7 in 2007, 9.4 in 2008, and 4.3 in 2009. Conclusions The Carajás region presented a medium pattern of endemicity during most of the study period, with a high DR found in 2008.

Leprosy and pregnancy: detection coefficient and proposal for a new index

Introduction Our study presents a method to generate a novel detection coefficient for the association between leprosy and pregnancy (DCLP). Methods The DCLP was calculated for women from the State of Pará (2007-2009), Brazil. Data were ordered, divided into five equal parts (corresponding to the P20, P40, P60, and P80 percentiles), and classified as low, medium, high, very high, or hyperendemic. Results Using the new index, we established the DCLP parameters for low (<0.36), medium (0.36-0.69), high (0.70-1.09), very high (1.10-1.50), and hyperendemic (>1.50). Conclusions The new DCLP is more appropriate than the overall detection coefficient (DC), which does not take into account the particularities of the interaction between a disease and a specific physiological state.

Geographic weighted regression: applicability to epidemiological studies of leprosy

Abstract: INTRODUCTION: Geographic information systems (GIS) enable public health data to be analyzed in terms of geographical variability and the relationship between risk factors and diseases. This study discusses the application of the geographic weighted regression (GWR) model to health data to improve the understanding of spatially varying social and clinical factors that potentially impact leprosy prevalence. METHODS: This ecological study used data from leprosy case records from 1998-2006, aggregated by neighborhood in the Duque de Caxias municipality in the State of Rio de Janeiro, Brazil. In the GWR model, the associations between the log of the leprosy detection rate and social and clinical factors were analyzed. RESULTS: Maps of the estimated coefficients by neighborhood confirmed the heterogeneous spatial relationships between the leprosy detection rates and the predictors. The proportion of households with piped water was associated with higher detection rates, mainly in the northeast of the municipality. Indeterminate forms were strongly associated with higher detections rates in the south, where access to health services was more established. CONCLUSIONS: GWR proved a useful tool for epidemiological analysis of leprosy in a local area, such as Duque de Caxias. Epidemiological analysis using the maps of the GWR model offered the advantage of visualizing the problem in sub-regions and identifying any spatial dependence in the local study area.

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

The effects of solvent composition on the affinity of a peptide towards hair keratin: experimental and molecular dynamics data

The study of the interaction between hair filaments and formulations or peptides is of utmost importance in fields like cosmetic research. Keratin intermediate filaments structure is not fully described, limiting the molecular dynamics (MD) studies in this field although its high potential to improve the area. We developed a computational model of a truncated protofibril, simulated its behavior in alcoholic based formulations and with one peptide. The simulations showed a strong interaction between the benzyl alcohol molecules of the formulations and the model, leading to the disorganization of the keratin chains, which regress with the removal of the alcohol molecules. This behavior can explain the increase of peptide uptake in hair shafts evidenced in fluorescence microscopy pictures. The model developed is valid to computationally reproduce the interaction between hair and alcoholic formulations and provide a robust base for new MD studies about hair properties. It is shown that the MD simulations can improve hair cosmetic research, improving the uptake of a compound of interest.

Heart Weight and Heart Weight/Body Weight Coefficient in Malnourished Adults

OBJECTIVE: To compare the heart weight and the heart weight/body weight coefficient of adults with and without chronic malnutrition. METHODS: In an initial case series of 210 autopsies performed in adults, we recorded body and heart weights and calculated the heart weight/body weight coefficients (HW/BW x 100). The exclusion criteria were as follows: positive serology for Chagas' disease, edema, obesity, heart diseases, hepatopathies, nephropathies, and systemic arterial hypertension. Malnutrition was characterized as a body mass index <18.5kg/m². Differences with p<0.05 were considered significant. RESULTS: Individuals in the malnourished (n=15) and control (n=21) groups were statistically different, respectively, in regard to body mass index (15.9±1.7 versus 21.3±2.5kg/m²), heart weight (267.3±59.8 versus 329.1±50.4g), and the HW/BW coefficient (0.64±0.12 versus 0.57±0.09%). A positive and significant correlation was observed between heart weight and body mass index (r=0.52), and between heart weight and body weight (r=0.65). CONCLUSION: Malnourished individuals have lighter hearts and a greater HW/BW coefficient than non-malnourished individuals do. These findings indicate a possible preservation of the myocardium in relation to the intensity of weight loss associated with the probable relative increase in cardiac connective tissue and heart blood vessels.

Optimal designs for the prediction in hierarchical random coefficient regression models

Magdeburg, Univ., Fak. für Mathematik, Diss., 2015

Lp-solutions to BSDEs with super-linear growth coefficient. Application to degenerate semilinear PDEs.

We consider multidimensional backward stochastic differential equations (BSDEs). We prove the existence and uniqueness of solutions when the coefficient grow super-linearly, and moreover, can be neither locally Lipschitz in the variable y nor in the variable z. This is done with super-linear growth coefficient and a p-integrable terminal condition (p & 1). As application, we establish the existence and uniqueness of solutions to degenerate semilinear PDEs with superlinear growth generator and an Lp-terminal data, p & 1. Our result cover, for instance, the case of PDEs with logarithmic nonlinearities.

Weighted approval voting

To allow society to treat unequal alternatives distinctly we propose a natural extension of Approval Voting by relaxing the assumption of neutrality. According to this extension, every alternative receives ex-ante a non-negative and finite weight. These weights may differ across alternatives. Given the voting decisions of every individual (individuals are allowed to vote for, or approve of, as many alternatives as they wish to), society elects all alternatives for which the product of total number of votes times exogenous weight is maximal. Our main result is an axiomatic characterization of this voting procedure.

Weighted Hardy spaces for the unit disc: approximation properties

In this paper we study basic properties of the weighted Hardy space for the unit disc with the weight function satisfying Muckenhoupt's (Aq) condition, and study related approximation problems (expansion, moment and interpolation) with respect to two incomplete systems of holomorphic functions in this space.

Chagas' disease: selective affinity and cytotoxicity of Trypanosoma cruzi-immune lymphocytes to parasympathetic ganglion cells

The megaesophagus and megacolon endemic in South America are related , to Chagas' disease. These mega conditions are found in patients with chronic Chagas's infection, when the parasite is not demonstrable in the lesions. These are characterized by depopulation of parasympathetic ganglion cells, dilation and hypertrophy of the viscera. In the experiments described here we deminstrate a selective affinity and adherence of Trypanosoma cruzi-immune lymphocytes to myenteric, parasympathetic ganglion cells, leading to neuronolysis. None of these features are observed when non-immune lymphocytes from control rabbits are used, or when the immune lymphocytes are allowed to react with CNS neurons. This demonstration is an indication of the high degree of specificity of the destruction of parasympathetic neurons in Chagas' disease. We postulate that the T. cruzi-immune lymphocyte rejection of parasympathetic neurons, but not of CNS neurons, might be related to recognition of a cross-reacting antigenic determinant secreted only by the target neurons. In favor of this interpretation is the observation of lymphocytic infiltrates and parasympathetic ganglion cell destruction in chronic Chagas' infection in the absence of encephalitis.

Risk prediction of prevalent diabetes in a Swiss population using a weighted genetic score--the CoLaus Study.

AIMS/HYPOTHESIS: Several susceptibility genes for type 2 diabetes have been discovered recently. Individually, these genes increase the disease risk only minimally. The goals of the present study were to determine, at the population level, the risk of diabetes in individuals who carry risk alleles within several susceptibility genes for the disease and the added value of this genetic information over the clinical predictors. METHODS: We constructed an additive genetic score using the most replicated single-nucleotide polymorphisms (SNPs) within 15 type 2 diabetes-susceptibility genes, weighting each SNP with its reported effect. We tested this score in the extensively phenotyped population-based cross-sectional CoLaus Study in Lausanne, Switzerland (n = 5,360), involving 356 diabetic individuals. RESULTS: The clinical predictors of prevalent diabetes were age, BMI, family history of diabetes, WHR, and triacylglycerol/HDL-cholesterol ratio. After adjustment for these variables, the risk of diabetes was 2.7 (95% CI 1.8-4.0, p = 0.000006) for individuals with a genetic score within the top quintile, compared with the bottom quintile. Adding the genetic score to the clinical covariates improved the area under the receiver operating characteristic curve slightly (from 0.86 to 0.87), yet significantly (p = 0.002). BMI was similar in these two extreme quintiles. CONCLUSIONS/INTERPRETATION: In this population, a simple weighted 15 SNP-based genetic score provides additional information over clinical predictors of prevalent diabetes. At this stage, however, the clinical benefit of this genetic information is limited.