Assessing influence in survival data with a cure fraction and covariates

Diagnostic methods have been an important tool in regression analysis to detect anomalies, such as departures from error assumptions and the presence of outliers and influential observations with the fitted models. Assuming censored data, we considered a classical analysis and Bayesian analysis assuming no informative priors for the parameters of the model with a cure fraction. A Bayesian approach was considered by using Markov Chain Monte Carlo Methods with Metropolis-Hasting algorithms steps to obtain the posterior summaries of interest. Some influence methods, such as the local influence, total local influence of an individual, local influence on predictions and generalized leverage were derived, analyzed and discussed in survival data with a cure fraction and covariates. The relevance of the approach was illustrated with a real data set, where it is shown that, by removing the most influential observations, the decision about which model best fits the data is changed.

High-throughput SNP genotyping in the highly heterozygous genome of Eucalyptus: assay success, polymorphism and transferability across species

Background: High-throughput SNP genotyping has become an essential requirement for molecular breeding and population genomics studies in plant species. Large scale SNP developments have been reported for several mainstream crops. A growing interest now exists to expand the speed and resolution of genetic analysis to outbred species with highly heterozygous genomes. When nucleotide diversity is high, a refined diagnosis of the target SNP sequence context is needed to convert queried SNPs into high-quality genotypes using the Golden Gate Genotyping Technology (GGGT). This issue becomes exacerbated when attempting to transfer SNPs across species, a scarcely explored topic in plants, and likely to become significant for population genomics and inter specific breeding applications in less domesticated and less funded plant genera. Results: We have successfully developed the first set of 768 SNPs assayed by the GGGT for the highly heterozygous genome of Eucalyptus from a mixed Sanger/454 database with 1,164,695 ESTs and the preliminary 4.5X draft genome sequence for E. grandis. A systematic assessment of in silico SNP filtering requirements showed that stringent constraints on the SNP surrounding sequences have a significant impact on SNP genotyping performance and polymorphism. SNP assay success was high for the 288 SNPs selected with more rigorous in silico constraints; 93% of them provided high quality genotype calls and 71% of them were polymorphic in a diverse panel of 96 individuals of five different species. SNP reliability was high across nine Eucalyptus species belonging to three sections within subgenus Symphomyrtus and still satisfactory across species of two additional subgenera, although polymorphism declined as phylogenetic distance increased. Conclusions: This study indicates that the GGGT performs well both within and across species of Eucalyptus notwithstanding its nucleotide diversity >= 2%. The development of a much larger array of informative SNPs across multiple Eucalyptus species is feasible, although strongly dependent on having a representative and sufficiently deep collection of sequences from many individuals of each target species. A higher density SNP platform will be instrumental to undertake genome-wide phylogenetic and population genomics studies and to implement molecular breeding by Genomic Selection in Eucalyptus.

Screening of Food Grade Lipases to be Used in Esterification and Interesterification Reactions of Industrial Interest

Seven food grade commercially available lipases were immobilized by covalent binding on polysiloxane-polyvinyl alcohol (POS-PVA) hybrid composite and screened to mediate reactions of industrial interest. The synthesis of butyl butyrate and the interesterification of tripalmitin with triolein were chosen as model reactions. The highest esterification activity (240.63 mu M/g min) was achieved by Candida rugosa lipase, while the highest interesterification yield (31%, in 72 h) was achieved by lipase from Rhizopus oryzae, with the production of about 15 mM of the triglycerides C(50) and C(52). This lipase also showed a good performance in butyl butyrate synthesis, with an esterification activity of 171.14 mu M/g min. The results demonstrated the feasibility of using lipases from C. rugosa for esterification and R. oryzae lipase for both esterification and interesterification reactions.

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.

Ancestry informative markers in Amerindians from Brazilian Amazon

Ancestry informative markers (AIMs) are genetic loci with large frequency differences between the major ethnic groups and are very useful in admixture estimation. However, their frequencies are poorly known within South American indigenous populations, making it difficult to use them in admixture studies with Latin American populations, such as the trihybrid Brazilian population. To minimize this problem, the frequencies of the AIMs FY-null RB2300, LPL, AT3-1/1), Sb19.3, APO, and PV92 were determined via PCR and PCR-RFLP in four tribes from Brazilian Amazon (Tikuna, Kashinawa, Baniwa, and Kanamari), to evaluate their potential for discriminating indigenous populations from Europeans and Africans, as well as discriminating each tribe from the others. Although capable of differentiating tribes, as evidenced by the exact test of population differentiation, a neighbor-joining tree suggests that the AIMs are useless in obtaining reliable reconstructions of the biological relationships and evolutionary history that characterize the villages and tribes studied. The mean allele frequencies from these AIMs were very similar to those observed for North American natives. They discriminated Amerindians from Africans, but not from Europeans. On the other hand, the neighbor-joining dendrogram separated Africans and Europeans from Amerindians with a high statistical support (bootstrap = 0.989). The relatively low diversity (GST = 0.042) among North American natives and Amerindians from Brazilian Amazon agrees with the lack of intra-ethnic variation previously reported for these markers. Despite genetic drift effects, the mean allelic frequencies herein presented could be used as Amerindian parental frequencies in admixture estimates in urban Brazilian populations.

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.

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.

Assessing Individual Interethnic Admixture and Population Substructure Using a 48-Insertion-Deletion (INSEL) Ancestry-Informative Marker (AIM) Panel

Estimating the proportions of different ancestries in admixed populations is very important in population genetics studies, and it is particularly important for detecting population substructure effects in case-control association studies. In this work, a set of 48 ancestry, informative insertion, deletion polymorphisms (INDELs) were selected with the goal of efficiently measuring the proportions of three different ancestries (sub-Saharan African, European, and Native American) in mixed populations. All selected markers can be easily analyzed via multiplex PCR and detected with standard capillary electrophoresis. A total of 593 unrelated individuals representative of European, African, and Native American parental populations were typed, as were 380 individuals from three Brazilian populations with known admixture patterns. As expected, the interethnic admixture estimates show that individuals from southern Brazil present an almost exclusively European ancestry; Afro-descendant communities in the Amazon region, apart from the major African contribution, present some degree of admixture with Europeans and Native Americans; and a sample from Belem, in the northeastern Amazon, shows a significant contribution of the three ethnic groups, although with a greater European proportion. In summary, a panel of ancestry-informative INDELs was optimized and proven to be a variable tool for estimating individual and global ancestry proportions in admixed populations. The ability to accurately infer interethnic admixtures highlights the usefulness of this marker set for assessing population substructure in association studies, particularly those conducted in Brazilian and other Latin American populations sharing trihybrid ancestry patterns. Hum Mutat 31:184-190, 2010. (C) 2009 Wiley-Liss, Inc.

MODELLING OF HIGH-PRESSURE PHASE EQUILIBRIUM IN SYSTEMS OF INTEREST IN THE FOOD ENGINEERING FIELD USING THE PENG-ROBINSON EQUATION OF STATE WITH TWO DIFFERENT MIXING RULES

In this work, thermodynamic models for fitting the phase equilibrium of binary systems were applied, aiming to predict the high pressure phase equilibrium of multicomponent systems of interest in the food engineering field, comparing the results generated by the models with new experimental data and with those from the literature. Two mixing rules were used with the Peng-Robinson equation of state, one with the mixing rule of van der Waals and the other with the composition-dependent mixing rule of Mathias et al. The systems chosen are of fundamental importance in food industries, such as the binary systems CO(2)-limonene, CO(2)-citral and CO(2)-linalool, and the ternary systems CO(2)-Limonene-Citral and CO(2)-Limonene-Linalool, where high pressure phase equilibrium knowledge is important to extract and fractionate citrus fruit essential oils. For the CO(2)-limonene system, some experimental data were also measured in this work. The results showed the high capability of the model using the composition-dependent mixing rule to model the phase equilibrium behavior of these systems.

Prediction of the economic activity from the short and long-term interest rate differential: new evidences in Chile and the United States of America cases

The purpose of this work is to verify the stability of the relationship between real activity and interest rate spread. The test is based on Chen (1988) and Osorio and Galea (2006). The analysis is applied to Chile and the United States, from 1980 to 1999. In general, in both cases the relationship was statistically significant in early 80s, but a break point is found in both countries during that decades, suggesting that the relationship depends on the monetary rule follow by the Central Bank.

Comparative electrochemical study of 5832-9 stainless steel at different media of biological interest

The electrochemical behavior of ISO 5832-9 stainless steel at 37 degrees C in 0.9% NaCl, Ringer Lactate and minimum essential medium (MEM) has been studied, using linear voltammetry, and surface analysis by SEM and EDS. Mechanical and toxicity tests were made. ISO 5832-9 is passivated at corrosion potential (E) and it does not present pitting corrosion on the media studied from to 50 in V above the transpassivation potential (Ei). SEM and EDS analysis have shown that the sample previously immersed in MEM presents a diffirent behavior at 50 in V above El: the manganese oxide inclusions are absent in the surface. E. values and passivation current density values j(pass) changed according to the following. E(corr, RL) < E(corr,NaCl) < E(corr, MEM) and J (MEM) << j(RL) congruent to j(NaCl) The stainless steel was characterized as non toxic in the cytotoxicity assay

Immobilization of Catalysts of Biological Interest on Porous Oxidized Silicon Surfaces

The present paper deals with the immobilization of redox mediators and proteins onto protected porous silicon surfaces to obtain their direct electrochemical reactions and to retain their bioactivities. This paper shows that MP-11 and viologens are able to establish chemical bonds with 3-aminopropyltriethoxylsilane-modified porous silicon surface. The functionalization of the surfaces have been fully characterized by energy dispersive X-ray analysis (EDX) and X-ray photoelectron spectroscopy (XPS) to examine the immobilization of these mediators onto the solid surface. Amperometric and open circuit potential measurements have shown the direct electron transfer between glucose oxidase and the electrode in the presence of the viologen mediator covalently linked to the 3-aminopropyltriethoxylsilane (APTES)-modified porous silicon surfaces.

Predicting new molecular species of potential interest to atmospheric chemistry: The isomers HSI and HIS

Structural, vibrational, and energetic properties of new molecular species, HSI and HIS are investigated for the first time using a state-of-the-art theoretical approach. These molecules can be easily differentiated by their geometric parameters and vibrational spectra. HSI is much more stable, and a direct unimolecular isomerization is very unlikely. Kinetics estimates predict that only at low temperatures there is a possibility of isolating HIS. For HS-I, we estimate a bond dissociation energy of 46.25 kcal/mol, and a heat of formation at 298.15 K of 12.84 kcal/mol. For the H(2)S + I(2) -> HSI + HI reaction enthalpy, we found 8.40 kcal/ mol. (C) 2008 Elsevier B.V. All rights reserved.

Transcriptome analysis of Taenia solium cysticerci using Open Reading Frame ESTs (ORESTES)

Background: Human infection by the pork tapeworm Taenia solium affects more than 50 million people worldwide, particularly in underdeveloped and developing countries. Cysticercosis which arises from larval encystation can be life threatening and difficult to treat. Here, we investigate for the first time the transcriptome of the clinically relevant cysticerci larval form. Results: Using Expressed Sequence Tags (ESTs) produced by the ORESTES method, a total of 1,520 high quality ESTs were generated from 20 ORESTES cDNA mini-libraries and its analysis revealed fragments of genes with promising applications including 51 ESTs matching antigens previously described in other species, as well as 113 sequences representing proteins with potential extracellular localization, with obvious applications for immune-diagnosis or vaccine development. Conclusion: The set of sequences described here will contribute to deciphering the expression profile of this important parasite and will be informative for the genome assembly and annotation, as well as for studies of intra- and inter-specific sequence variability. Genes of interest for developing new diagnostic and therapeutic tools are described and discussed.