The economic determinants of the Brazilian nominal term structure of interest rates

The purpose of this study is to identify the effects of monetary policy and macroeconomic shocks on the dynamics of the Brazilian term structure of interest rates. We estimate a near-VAR model under the identification scheme proposed by Christiano et al. (1996, 1999). The results resemble those of the US economy: monetary policy shocks that flatten the term structure of interest rates. We find that monetary policy shocks in Brazil explain a significantly larger share of the dynamics of the term structure than in the USA. Finally, we analyse the importance of standard macroeconomic variables (e. g. GDP, inflation and measure of country risk) to the dynamics of the term structure in Brazil.

Revisiting the interest rate puzzle

This article makes a connection between Lucas` (1978) asset pricing model and the macroeconomic dynamics for some selected countries. Both the relative risk aversion and the impatience for postponing consumption by synthesizing the investor behaviour can help to understand some key macroeconomic issues across countries, such as the savings decision and the real interest rate. I find that the government consumption makes worse the so-called `equity premium-interest rate puzzle`. The first root of the quadratic function for explaining the real interest rate can produce this puzzle, but not the second root. Thus, Mehra and Prescott (1985) identified only one possible solution.

Analyses of Individual and Organizational Competences Associated with Knowledge Management Practice

The research analyzed critical aspects of the knowledge management process based on the analyses of knowledge, abilities and attitudes required to individual knowledge workers and to organizations responsible for the management process. In the present work a characterization of the knowledge management process was developed and information and knowledge wokers defined. Competence concept was discussed and specialists gave opinions about critical competences to knowledge management process. The opinions were organized and analyzed by the Delphi method. The results aggregate to the management context by discussing an extremely important resource to organizations - knowledge - and because they support its management process. The research identified wide critical aspects that are compatible with current organizational challenges, directing the process management to important themes as: the worker able to create, the organization able to convert individual knowledge into organizational knowledge, knowledge sharing while still tacit, the maximization organizational knowledge use, information and knowledge generation and preservation, among others important topics to be observed by knowledge workers and by administrators responsible for the knowledge management process.

A new clinical and molecular form of Unverricht-Lundborg disease localized by homozygosity mapping

Progressive myoclonus epilepsy (PME) has a number of causes, of which Unverricht-Lundborg disease (ULD) is the most common. ULD has previously been mapped to a locus on chromosome 21 (EPM1). Subsequently, mutations in the cystatin B gene have been found in most cases. In the present work we identified an inbred Arab family with a clinical pattern compatible with ULD, but mutations in the cystatin B gene were absent. We sought to characterize the clinical and molecular features of the disorder. The family was studied by multiple field trips to their town to clarify details of the complex consanguineous relationships and to personally examine the family. DNA was collected for subsequent molecular analyses from 21 individuals. A genome-wide screen was performed using 811 microsatellite markers. Homozygosity mapping was used to identify loci of interest. There were eight affected individuals. Clinical onset was at 7.3 +/- 1.5 years with myoclonic or tonic-clonic seizures. All had myoclonus that progressed in severity over time and seven had tonic-clonic seizures. Ataxia, in addition to myoclonus, occurred in all. Detailed cognitive assessment was not possible, but there was no significant progressive dementia. There was intrafamily variation in severity; three required wheelchairs in adult life; the others could walk unaided. MRI, muscle and skin biopsies on one individual were unremarkable. We mapped the family to a 15-megabase region at the pericentromeric region of chromosome 12 with a maximum lod score of 6.32. Although the phenotype of individual subjects was typical of ULD, the mean age of onset (7.3 years versus 11 years for ULD) was younger. The locus on chromosome 12 does not contain genes for any other form of PME, nor does it have genes known to be related to cystatin B. This represents a new form of PME and we have designated the locus as EPM1B.

Individual differences in motivated social cognition: The case of self-serving information processing

Three experiments examined the hypothesis that people show consistency in motivated social cognitive processing across self-serving domains. Consistent with this hypothesis, Experiment 1 revealed that people who rated a task at which they succeeded as more important than a task at which they failed also cheated on a series of math problems, but only when they could rationalize their cheating as unintentional. Experiment 2 replicated this finding and demonstrated that a self-report measure of self-deception did not predict this rationalized cheating. Experiment 3 replicated Experiments 1 and 2 and ruled out several alternative explanations. These experiments suggest that people who show motivated processing in ego-protective domains also show motivated processing in extrinsic domains. These experiments also introduce a new measurement procedure for differentiating between intentional versus rationalized cheating.

Analyzing the connectivity between regions of interest: An approach based on cluster Granger causality for NRI data analysis

The identification, modeling, and analysis of interactions between nodes of neural systems in the human brain have become the aim of interest of many studies in neuroscience. The complex neural network structure and its correlations with brain functions have played a role in all areas of neuroscience, including the comprehension of cognitive and emotional processing. Indeed, understanding how information is stored, retrieved, processed, and transmitted is one of the ultimate challenges in brain research. In this context, in functional neuroimaging, connectivity analysis is a major tool for the exploration and characterization of the information flow between specialized brain regions. In most functional magnetic resonance imaging (fMRI) studies, connectivity analysis is carried out by first selecting regions of interest (ROI) and then calculating an average BOLD time series (across the voxels in each cluster). Some studies have shown that the average may not be a good choice and have suggested, as an alternative, the use of principal component analysis (PCA) to extract the principal eigen-time series from the ROI(s). In this paper, we introduce a novel approach called cluster Granger analysis (CGA) to study connectivity between ROIs. The main aim of this method was to employ multiple eigen-time series in each ROI to avoid temporal information loss during identification of Granger causality. Such information loss is inherent in averaging (e.g., to yield a single ""representative"" time series per ROI). This, in turn, may lead to a lack of power in detecting connections. The proposed approach is based on multivariate statistical analysis and integrates PCA and partial canonical correlation in a framework of Granger causality for clusters (sets) of time series. We also describe an algorithm for statistical significance testing based on bootstrapping. By using Monte Carlo simulations, we show that the proposed approach outperforms conventional Granger causality analysis (i.e., using representative time series extracted by signal averaging or first principal components estimation from ROIs). The usefulness of the CGA approach in real fMRI data is illustrated in an experiment using human faces expressing emotions. With this data set, the proposed approach suggested the presence of significantly more connections between the ROIs than were detected using a single representative time series in each ROI. (c) 2010 Elsevier Inc. All rights reserved.

Hyperplane navigation: A method to set individual scores in fMRI group datasets

Recent studies have demonstrated that spatial patterns of fMRI BOLD activity distribution over the brain may be used to classify different groups or mental states. These studies are based on the application of advanced pattern recognition approaches and multivariate statistical classifiers. Most published articles in this field are focused on improving the accuracy rates and many approaches have been proposed to accomplish this task. Nevertheless, a point inherent to most machine learning methods (and still relatively unexplored in neuroimaging) is how the discriminative information can be used to characterize groups and their differences. In this work, we introduce the Maximum Uncertainty Linear Discrimination Analysis (MLDA) and show how it can be applied to infer groups` patterns by discriminant hyperplane navigation. In addition, we show that it naturally defines a behavioral score, i.e., an index quantifying the distance between the states of a subject from predefined groups. We validate and illustrate this approach using a motor block design fMRI experiment data with 35 subjects. (C) 2008 Elsevier Inc. All rights reserved.

Individual risk prediction of nodal and distant metastasis for patients with typical bronchial carcinoid tumors

Objective: Bronchial typical carcinoid tumors are tow-grade malignancies. However, metastases are diagnosed in some patients. Predicting the individual risk of these metastases to determine patients eligible for a radical lymphadenectomy and patients to be followed-up because of distant metastasis risk is relevant. Our objective was to screen for predictive criteria of bronchial typical carcinoid tumor aggressiveness based on a logistic regression model using clinical, pathological and biomolecular data. Methods: A multicenter retrospective cohort study, including 330 consecutive patients operated on for bronchial typical carcinoid tumors and followed-up during a period more than 10 years in two university hospitals was performed. Selected data to predict the individual risk for both nodal and distant metastasis were: age, gender, TNM staging, tumor diameter and location (central/peripheral), tumor immunostaining index of p53 and Ki67, Bcl2 and the extracellular density of neoformed microvessels and of collagen/elastic extracellular fibers. Results: Nodal and distant metastasis incidence was 11% and 5%, respectively. Univariate analysis identified all the studied biomarkers as related to nodal metastasis. Multivariate analysis identified a predictive variable for nodal metastasis: neo angiogenesis, quantified by the neoformed pathological microvessels density. Distant metastasis was related to mate gender. Discussion: Predictive models based on clinical and biomolecular data could be used to predict individual risk for metastasis. Patients under a high individual risk for lymph node metastasis should be considered as candidates to mediastinal lymphadenectomy. Those under a high risk of distant metastasis should be followed-up as having an aggressive disease. Conclusion: Individual risk prediction of bronchial typical carcinoid tumor metastasis for patients operated on can be calculated in function of biomolecular data. Prediction models can detect high-risk patients and help surgeons to identify patients requiring radical lymphadenectomy and help oncologists to identify those as having an aggressive disease requiring prolonged follow-up. (C) 2008 European Association for Cardio-Thoracic Surgery. Published by Elsevier B.V. All rights reserved.

Individual vulnerability to escalated aggressive behavior by a low dose of alcohol: decreased serotonin receptor mRNA in the prefrontal cortex of male mice

Low to moderate doses of alcohol consumption induce heightened aggressive behavior in some, but not all individuals. Individual vulnerability for this nonadaptive behavior may be determined by an interaction of genetic and environmental factors with the sensitivity of alcohol`s effects on brain and behavior. We used a previously established protocol for alcohol oral self-administration and characterized alcohol-heightened aggressive (AHA) mice as compared with alcohol non-heightened (ANA) counterparts. A week later, we quantified mRNA steady state levels of several candidate genes in the serotonin [5-hydroxytryptamine (5-HT)] system in different brain areas. We report a regionally selective and significant reduction of all 5-HT receptor subtype transcripts, except for 5-HT(3), in the prefrontal cortex of AHA mice. Comparable gene expression profile was previously observed in aggressive mice induced by social isolation or by an anabolic androgenic steroid. Additional change in the 5-HT(1B) receptor transcripts was seen in the amygdala and hypothalamus of AHA mice. In both these areas, 5-HT(1B) mRNA was elevated when compared with ANA mice. In the hypothalamus, AHA mice also showed increased transcripts for 5-HT(2A) receptor. In the midbrain, 5-HT synthetic enzyme, 5-HT transporter and 5-HT receptors mRNA levels were similar between groups. Our results emphasize a role for postsynaptic over presynaptic 5-HT receptors in mice which showed escalated aggression after the consumption of a moderate dose of alcohol. This gene expression profile of 5-HT neurotransmission components in the brain of mice may suggest a vulnerability trait for alcohol-heightened aggression.

An MRI-based approach for the measurement of the dorsolateral prefrontal cortex in humans

The dorsolateral prefrontal cortex (DLPFC) has been implicated in the pathophysiology of mental disorders. Previous region-of-interest MRI studies that attempted to delineate this region adopted various landmarks and measurement techniques, with inconsistent results. We developed a new region-of-interest measurement method to obtain morphometric data of this region from structural MRI scans, taking into account knowledge from cytoarchitectonic postmortem studies and the large inter-individual variability of this region. MRI scans of 10 subjects were obtained, and DLPFC tracing was performed in the coronal plane by two independent raters using the semi-automated software Brains2. The intra-class correlation coefficients between two independent raters were 0.94 for the left DLPFC and 0.93 for the right DLPFC. The mean +/- S.D. DLPFC volumes were 9.23 +/- 2.35 ml for the left hemisphere and 8.20 +/- 2.08 ml for the right hemisphere. Our proposed method has high inter-rater reliability and is easy to implement, permitting the standardized measurement of this region for clinical research applications. (C) 2009 Elsevier Ireland Ltd. All rights reserved.

Orbitofrontal cortex gray matter volumes in bipolar disorder patients: a region-of-interest MRI study

Objectives: Functional and postmortem studies suggest that the orbitofrontal cortex (OFC) is involved in the pathophysiology of bipolar disorder (BD). This anatomical magnetic resonance imaging (MRI) study examined whether BD patients have smaller OFC gray matter volumes compared to healthy comparison subjects (HC). Methods: Twenty-eight BD patients were compared to 28 age- and gender-matched HC. Subjects underwent a 1.5T MRI with 3D spoiled gradient recalled acquisition. Total OFC and medial and lateral subdivisions were manually traced by a blinded examiner. Images were segmented and gray matter volumes were calculated using an automated method. Results: Analysis of covariance, with intracranial volume as covariate, showed that BD patients and HC did not differ in gray matter volumes of total OFC or its subdivisions. However, total OFC gray matter volume was significantly smaller in depressed patients (n = 10) compared to euthymic patients (n = 18). Moreover, total OFC gray matter volumes were inversely correlated with depressive symptom intensity, as assessed by the Hamilton Depression Rating Scale. OFC gray matter volumes were not related to lithium treatment, age at disease onset, number of episodes, or family history of mood disorders. Conclusions: Our results suggest that abnormal OFC gray matter volumes are not a pervasive characteristic of BD, but may be associated with specific clinical features of the disorder.