Association study between the rs165599 catechol-O-methyltransferase genetic polymorphism and schizophrenia in a Brazilian sample

Schizophrenia is a severe psychiatric disorder with frequent recurrent psychotic relapses and progressive functional impairment. It results from a poorly understood gene-environment interaction. The gene encoding catechol-O-methyltransferase (COMT) is a likely candidate for schizophrenia. Its rs165599 (A/G) polymorphism has been shown to be associated with alteration of COMT gene expression. Therefore, the present study aimed to investigate a possible association between schizophrenia and this polymorphism. The distribution of the alleles and genotypes of this polymorphism was investigated in a Brazilian sample of 245 patients and 834 controls. The genotypic frequencies were in Hardy-Weinberg equilibrium and no statistically significant differences were found between cases and controls when analyzed according to gender or schizophrenia subtypes. There was also no difference in homozygosis between cases and controls. Thus, in the sample studied, there was no evidence of any association between schizophrenia and rs165599 (A/G) polymorphism in the non-coding region 3' of the COMT gene.

Production and carbon allocation in monocultures and mixed-species plantations of Eucalyptus grandis and Acacia mangium in Brazil

Introducing nitrogen-fixing tree species in fast-growing eucalypt plantations has the potential to improve soil nitrogen availability compared with eucalypt monocultures. Whether or not the changes in soil nutrient status and stand structure will lead to mixtures that out-yield monocultures depends on the balance between positive interactions and the negative effects of interspecific competition, and on their effect on carbon (C) uptake and partitioning. We used a C budget approach to quantify growth, C uptake and C partitioning in monocultures of Eucalyptus grandis (W. Hill ex Maiden) and Acacia mangium (Willd.) (treatments E100 and A100, respectively), and in a mixture at the same stocking density with the two species at a proportion of 1 : 1 (treatment MS). Allometric relationships established over the whole rotation, and measurements of soil CO2 efflux and aboveground litterfall for ages 4-6 years after planting were used to estimate aboveground net primary production (ANPP), total belowground carbon flux (TBCF) and gross primary production (GPP). We tested the hypotheses that (i) species differences for wood production between E. grandis and A. mangium monocultures were partly explained by different C partitioning strategies, and (ii) the observed lower wood production in the mixture compared with eucalypt monoculture was mostly explained by a lower partitioning aboveground. At the end of the rotation, total aboveground biomass was lowest in A100 (10.5 kg DM m(-2)), intermediate in MS (12.2 kg DM m(-2)) and highest in E100 (13.9 kg DM m(-2)). The results did not support our first hypothesis of contrasting C partitioning strategies between E. grandis and A. mangium monocultures: the 21% lower growth (delta B-w) in A100 compared with E100 was almost entirely explained by a 23% lower GPP, with little or no species difference in ratios such as TBCF/GPP, ANPP/TBCF, delta B-w/ANPP and delta B-w/GPP. In contrast, the 28% lower delta B-w in MS than in E100 was explained both by a 15% lower GPP and by a 15% lower fraction of GPP allocated to wood growth, thus partially supporting our second hypothesis: mixing the two species led to shifts in C allocations from above- to belowground, and from growth to litter production, for both species.

Evaluation of physiologic complexity in time series using generalized sample entropy and surrogate data analysis

Complexity in time series is an intriguing feature of living dynamical systems, with potential use for identification of system state. Although various methods have been proposed for measuring physiologic complexity, uncorrelated time series are often assigned high values of complexity, errouneously classifying them as a complex physiological signals. Here, we propose and discuss a method for complex system analysis based on generalized statistical formalism and surrogate time series. Sample entropy (SampEn) was rewritten inspired in Tsallis generalized entropy, as function of q parameter (qSampEn). qSDiff curves were calculated, which consist of differences between original and surrogate series qSampEn. We evaluated qSDiff for 125 real heart rate variability (HRV) dynamics, divided into groups of 70 healthy, 44 congestive heart failure (CHF), and 11 atrial fibrillation (AF) subjects, and for simulated series of stochastic and chaotic process. The evaluations showed that, for nonperiodic signals, qSDiff curves have a maximum point (qSDiff(max)) for q not equal 1. Values of q where the maximum point occurs and where qSDiff is zero were also evaluated. Only qSDiff(max) values were capable of distinguish HRV groups (p-values 5.10 x 10(-3); 1.11 x 10(-7), and 5.50 x 10(-7) for healthy vs. CHF, healthy vs. AF, and CHF vs. AF, respectively), consistently with the concept of physiologic complexity, and suggests a potential use for chaotic system analysis. (C) 2012 American Institute of Physics. [http://dx.doi.org/10.1063/1.4758815]

Validation of the Brazilian Portuguese version of the Beck Depression Inventory-II in a community sample

Background: The Beck Depression Inventory (BDI) is used worldwide for detecting depressive symptoms. This questionnaire has been revised (1996) to match the DSM-IV criteria for a major depressive episode. We assessed the reliability and the validity of the Brazilian Portuguese version of the BDI-II for non-clinical adults. Methods: The questionnaire was applied to 60 college students on two occasions. Afterwards, 182 community-dwelling adults completed the BDI-II, the Self-Report Questionnaire, and the K10 Scale. Trained psychiatrists performed face-to-face interviews with the respondents using the Structured Clinical Interview (SCID-I), the Montgomery-angstrom sberg Depression Scale, and the Hamilton Anxiety Scale. Descriptive analysis, signal detection analysis (Receiver Operating Characteristics), correlation analysis, and discriminant function analysis were performed to investigate the psychometric properties of the BDI-II. Results: The intraclass correlation coefficient of the BDI-II was 0.89, and the Cronbach's alpha coefficient of internal consistency was 0.93. Taking the SCID as the gold standard, the cut-off point of 10/11 was the best threshold for detecting depression, yielding a sensitivity of 70% and a specificity of 87%. The concurrent validity (a correlation of 0.63-0.93 with scales applied simultaneously) and the predictive ability of the severity level (over 65% correct classification) were acceptable. Conclusion: The BDI-II is reliable and valid for measuring depressive symptomatology among Portuguese-speaking Brazilian non-clinical populations.