Regression models for grouped survival data: Estimation and sensitivity analysis

In this study, regression models are evaluated for grouped survival data when the effect of censoring time is considered in the model and the regression structure is modeled through four link functions. The methodology for grouped survival data is based on life tables, and the times are grouped in k intervals so that ties are eliminated. Thus, the data modeling is performed by considering the discrete models of lifetime regression. The model parameters are estimated by using the maximum likelihood and jackknife methods. To detect influential observations in the proposed models, diagnostic measures based on case deletion, which are denominated global influence, and influence measures based on small perturbations in the data or in the model, referred to as local influence, are used. In addition to those measures, the local influence and the total influential estimate are also employed. Various simulation studies are performed and compared to the performance of the four link functions of the regression models for grouped survival data for different parameter settings, sample sizes and numbers of intervals. Finally, a data set is analyzed by using the proposed regression models. (C) 2010 Elsevier B.V. All rights reserved.

Double generalized linear model for tissue culture proportion data: a Bayesian perspective

Joint generalized linear models and double generalized linear models (DGLMs) were designed to model outcomes for which the variability can be explained using factors and/or covariates. When such factors operate, the usual normal regression models, which inherently exhibit constant variance, will under-represent variation in the data and hence may lead to erroneous inferences. For count and proportion data, such noise factors can generate a so-called overdispersion effect, and the use of binomial and Poisson models underestimates the variability and, consequently, incorrectly indicate significant effects. In this manuscript, we propose a DGLM from a Bayesian perspective, focusing on the case of proportion data, where the overdispersion can be modeled using a random effect that depends on some noise factors. The posterior joint density function was sampled using Monte Carlo Markov Chain algorithms, allowing inferences over the model parameters. An application to a data set on apple tissue culture is presented, for which it is shown that the Bayesian approach is quite feasible, even when limited prior information is available, thereby generating valuable insight for the researcher about its experimental results.

Evaluation of FAO Penman-Monteith and alternative methods for estimating reference evapotranspiration with missing data in Southern Ontario, Canada

Grass reference evapotranspiration (ETo) is an important agrometeorological parameter for climatological and hydrological studies, as well as for irrigation planning and management. There are several methods to estimate ETo, but their performance in different environments is diverse, since all of them have some empirical background. The FAO Penman-Monteith (FAD PM) method has been considered as a universal standard to estimate ETo for more than a decade. This method considers many parameters related to the evapotranspiration process: net radiation (Rn), air temperature (7), vapor pressure deficit (Delta e), and wind speed (U); and has presented very good results when compared to data from lysimeters Populated with short grass or alfalfa. In some conditions, the use of the FAO PM method is restricted by the lack of input variables. In these cases, when data are missing, the option is to calculate ETo by the FAD PM method using estimated input variables, as recommended by FAD Irrigation and Drainage Paper 56. Based on that, the objective of this study was to evaluate the performance of the FAO PM method to estimate ETo when Rn, Delta e, and U data are missing, in Southern Ontario, Canada. Other alternative methods were also tested for the region: Priestley-Taylor, Hargreaves, and Thornthwaite. Data from 12 locations across Southern Ontario, Canada, were used to compare ETo estimated by the FAD PM method with a complete data set and with missing data. The alternative ETo equations were also tested and calibrated for each location. When relative humidity (RH) and U data were missing, the FAD PM method was still a very good option for estimating ETo for Southern Ontario, with RMSE smaller than 0.53 mm day(-1). For these cases, U data were replaced by the normal values for the region and Delta e was estimated from temperature data. The Priestley-Taylor method was also a good option for estimating ETo when U and Delta e data were missing, mainly when calibrated locally (RMSE = 0.40 mm day(-1)). When Rn was missing, the FAD PM method was not good enough for estimating ETo, with RMSE increasing to 0.79 mm day(-1). When only T data were available, adjusted Hargreaves and modified Thornthwaite methods were better options to estimate ETo than the FAO) PM method, since RMSEs from these methods, respectively 0.79 and 0.83 mm day(-1), were significantly smaller than that obtained by FAO PM (RMSE = 1.12 mm day(-1). (C) 2009 Elsevier B.V. All rights reserved.

Cattle Grazing Distribution and Efficacy of Strategic Mineral Mix Placement in Tropical Brazilian Pastures

A study was conducted in Brazil to identify factors affecting grazing distribution of yearling Nelore cross heifers and to evaluate the efficacy of placement of a salt-mineral mix away from water to improve uniformity of grazing. Two pastures (25 ha and 42 ha) were evaluated for four 15-d sessions. Mineral mix was placed 590 m to 780 m from water during two sessions and at water for two sessions. Stubble heights were measured at the beginning and end of each session in 1-ha subunits of each pasture. Cattle locations were recorded oil clay 13 and 14 of each session by horseback observers. Heifers avoided areas with a preponderance of forbs and taller grass (P < 0.001). For the first 15 days of the study cattle avoided subunits farther from water. Thereafter, horizontal distance from water had no affect on grazing use (P > 0.10). Stubble height reduction was more uniform (P < 0.05) when the mineral mix was Lit water compared to away from water. In contrast, heifers spent less time farther from water when Mineral mix was placed at water (P = 0.02) based Oil Visual observations. Strategic placement of a salt-mineral mix away from water does not appear to be a reliable tool to improve cattle grazing distribution in humid tropical pastures from 25 ha to 45 ha in size.

Genetic population data of 12 STR loci of the PowerPlex (R) Y system in the state of Sao Paulo population (Southeast of Brazil)

Allele frequency distributions and population data for 12 Y-chromosomal short tandem repeats (STRs) included in the PowerPlex (R) Y Systems (Promega) were obtained for a sample of 200 healthy unrelated males living in S (a) over tildeo Paulo State (Southeast of Brazil). A total of 192 haplotypes were identified, of which 184 were unique and 8 were found in 2 individuals. The average gene diversity of the 12 Y-STR was 0.6746 and the haplotype diversity was 0.9996. Pairwise analysis confirmed that our population is more similar with the Italy, North Portugal and Spain, being more distant of the Japan. (c) 2007 Elsevier Ireland Ltd. All rights reserved.

Brazilian Network of Food Data Systems and LATINFOODS Regional Technical Compilation Committee: Food composition activities (2006-2009)

The Brazilian Network of Food Data Systems (BRASILFOODS) has been keeping the Brazilian Food Composition Database-USP (TBCA-USP) (http://www.fcf.usp.br/tabela) since 1998. Besides the constant compilation, analysis and update work in the database, the network tries to innovate through the introduction of food information that may contribute to decrease the risk for non-transmissible chronic diseases, such as the profile of carbohydrates and flavonoids in foods. In 2008, data on carbohydrates, individually analyzed, of 112 foods, and 41 data related to the glycemic response produced by foods widely consumed in the country were included in the TBCA-USP. Data (773) about the different flavonoid subclasses of 197 Brazilian foods were compiled and the quality of each data was evaluated according to the USDAs data quality evaluation system. In 2007, BRASILFOODS/USP and INFOODS/FAO organized the 7th International Food Data Conference ""Food Composition and Biodiversity"". This conference was a unique opportunity for interaction between renowned researchers and participants from several countries and it allowed the discussion of aspects that may improve the food composition area. During the period, the LATINFOODS Regional Technical Compilation Committee and BRASILFOODS disseminated to Latin America the Form and Manual for Data Compilation, version 2009, ministered a Food Composition Data Compilation course and developed many activities related to data production and compilation. (C) 2010 Elsevier Inc. All rights reserved.

Inflation targeting in emerging economies: What do the data say?

In a recent thought-provoking paper, Ball and Sheridan [Ball, L., Sheridan, N., 2005. Does inflation targeting matter? In: Bernanke, B.S., Woodford, M. (Eds.), The Inflation-Targeting Debate, University of Chicago Press] show that the available evidence for a group of developed economies does not lend credence to the belief that adopting an inflation targeting regime (IT) was instrumental in bringing inflation and inflation volatility down. Here, we extend Ball and Sheridan`s analysis for a subset of 36 emerging market economies and find that, for them, the story is quite different. Compared to non-targeters, developing countries adopting the IT regime not only experienced greater drops in inflation, but also in growth volatility, thus corroborating the view that the regime`s ""constrained flexibility"" to deal with adverse shocks delivered concrete welfare gains. (c) 2006 Elsevier B.V. All rights reserved.

Unraveling the Na,K-ATPase alpha(4) Subunit Assembling Induced by Large Amounts of C(12)E(8) by Means of Small-Angle X-ray Scattering

In the current work, we studied the effect of the nonionic detergent dodecyloctaethyleneglycol, C(12)E(8), on the structure and oligomeric form of the Na,K-ATPase membrane enzyme (sodium-potassium pump) in aqueous suspension, by means of small-angle X-ray scattering (SAXS). Samples composed of 2 mg/mL of Na,K-ATPase, extracted from rabbit kidney medulla, in the presence of a small amount of C(12)E(8) (0.005 mg/mL) and in larger concentrations ranging from 2.7 to 27 mg/mL did not present catalytic activity. Under this condition, an oligomerization of the alpha subunits is expected. SAXS data were analyzed by means of a global fitting procedure supposing that the scattering is due to two independent contributions: one coming from the enzyme and the other one from C(12)E(8) micelles. In the small detergent content (0.005 mg/mL), the SAXS results evidenced that Na,K-ATPase is associated into aggregates larger than (alpha beta)(2) form. When 2.7 mg/mL of C(12)E(8) is added, the data analysis revealed the presence of alpha(4) aggregates in the solution and some free micelles. Increasing the detergent amount up to 27 mg/mL does not disturb the alpha(4) aggregate: just more micelles of the same size and shape are proportionally formed in solution. We believe that our results shed light on a better understanding of how nonionic detergents induce subunit dissociation and reassembling to minimize the exposure of hydrophobic residues to the aqueous solvent.

Usefulness of Proteinuria as a Prognostic Marker of Mortality and Cardiovascular Events Among Patients Undergoing Percutaneous Coronary Intervention (Data from the Evaluation of Oral Xemilofiban in Controlling Thrombotic Events [EXCITE] Trial)

Proteinuria was associated with cardiovascular events and mortality in community-based cohorts. The association of proteinuria with mortality and cardiovascular events in patients undergoing percutaneous coronary intervention (PCI) was unknown. The association of urinary dipstick proteinuria with mortality and cardiovascular events (composite of death, myocardial infarction, or nonhemorrhagic stroke) in 5,835 subjects of the EXCITE trial was evaluated. Dipstick urinalysis was performed before PCI, and proteinuria was defined as trace or greater. Subjects were followed up for 210 days/7 months after enrollment for the occurrence of events. Multivariate Cox regression analysis evaluated the independent association of proteinuria with each outcome. Mean age was 59 years, 21% were women, 18% had diabetes mellitus, and mean estimated glomerular filtration rate was 90 ml/min/1.73 m(2). Proteinuria was present in 750 patients (13%). During follow-up, 22 subjects (2.9%) with proteinuria and 54 subjects (1.1%) without proteinuria died (adjusted hazard ratio 2.83, 95% confidence interval [CI] 1.65 to 4.84, p <0.001). The severity of proteinuria attenuated the strength of the association with mortality after PCI (low-grade proteinuria, hazard ratio 2.67, 95% CI 1.50 to 4.75; high-grade proteinuria, hazard ratio 3.76, 95% CI 1.24 to 11.37). No significant association was present for cardiovascular events during the relatively short follow-up, but high-grade proteinuria tended toward increased risk of cardiovascular events (hazard ratio 1.45, 95% CI 0.81 to 2.61). In conclusion, proteinuria was strongly and independently associated with mortality in patients undergoing PCI. These data suggest that such a relatively simple and clinically easy to use tool as urinary dipstick may be useful to identify and treat patients at high risk of mortality at the time of PCI. (C) 2008 Elsevier Inc. All rights reserved. (Am J Cardiol 2008;102:1151-1155)

Macromolecular assembly of polycystin-2 intracytosolic C-terminal domain

Mutations in PKD2 are responsible for approximately 15% of the autosomal dominant polycystic kidney disease cases. This gene encodes polycystin-2, a calcium-permeable cation channel whose C-terminal intracytosolic tail (PC2t) plays an important role in its interaction with a number of different proteins. In the present study, we have comprehensively evaluated the macromolecular assembly of PC2t homooligomer using a series of biophysical and biochemical analyses. Our studies, based on a new delimitation of PC2t, have revealed that it is capable of assembling as a homotetramer independently of any other portion of the molecule. Our data support this tetrameric arrangement in the presence and absence of calcium. Molecular dynamics simulations performed with a modified all-atoms structure-based model supported the PC2t tetrameric assembly, as well as how different populations are disposed in solution. The simulations demonstrated, indeed, that the best-scored structures are the ones compatible with a fourfold oligomeric state. These findings clarify the structural properties of PC2t domain and strongly support a homotetramer assembly of PC2.

Wavelet correlation between subjects: A time-scale data driven analysis for brain mapping using fMRI

Functional magnetic resonance imaging (fMRI) based on BOLD signal has been used to indirectly measure the local neural activity induced by cognitive tasks or stimulation. Most fMRI data analysis is carried out using the general linear model (GLM), a statistical approach which predicts the changes in the observed BOLD response based on an expected hemodynamic response function (HRF). In cases when the task is cognitively complex or in cases of diseases, variations in shape and/or delay may reduce the reliability of results. A novel exploratory method using fMRI data, which attempts to discriminate between neurophysiological signals induced by the stimulation protocol from artifacts or other confounding factors, is introduced in this paper. This new method is based on the fusion between correlation analysis and the discrete wavelet transform, to identify similarities in the time course of the BOLD signal in a group of volunteers. We illustrate the usefulness of this approach by analyzing fMRI data from normal subjects presented with standardized human face pictures expressing different degrees of sadness. The results show that the proposed wavelet correlation analysis has greater statistical power than conventional GLM or time domain intersubject correlation analysis. (C) 2010 Elsevier B.V. All rights reserved.

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.

The impact of functional connectivity changes on support vector machines mapping of fMRI data

Functional magnetic resonance imaging (fMRI) is currently one of the most widely used methods for studying human brain function in vivo. Although many different approaches to fMRI analysis are available, the most widely used methods employ so called ""mass-univariate"" modeling of responses in a voxel-by-voxel fashion to construct activation maps. However, it is well known that many brain processes involve networks of interacting regions and for this reason multivariate analyses might seem to be attractive alternatives to univariate approaches. The current paper focuses on one multivariate application of statistical learning theory: the statistical discrimination maps (SDM) based on support vector machine, and seeks to establish some possible interpretations when the results differ from univariate `approaches. In fact, when there are changes not only on the activation level of two conditions but also on functional connectivity, SDM seems more informative. We addressed this question using both simulations and applications to real data. We have shown that the combined use of univariate approaches and SDM yields significant new insights into brain activations not available using univariate methods alone. In the application to a visual working memory fMRI data, we demonstrated that the interaction among brain regions play a role in SDM`s power to detect discriminative voxels. (C) 2008 Elsevier B.V. All rights reserved.

FibroTest is an independent predictor of virologic response in chronic hepatitis C patients retreated with pegylated interferon alfa-2b and ribavirin in the EPIC(3) program

Background & Aims: EPIC-3 is a prospective, international study that has demonstrated the efficacy of PEG-IFN alfa-2b plus weight-based ribavirin in patients with chronic hepatitis C and significant fibrosis who previously failed any interferon-alfa/ribavirin therapy. The aim of the present study was to assess FibroTest (FT), a validated non-invasive marker of fibrosis in treatment-naive patients, as a possible alternative to biopsy as the baseline predictor of subsequent early virologic (EVR) and sustained virologic response (SVR) in previously treated patients. Methods: Of 2312 patients enrolled, 1459 had an available baseline FT, biopsy, and complete data. Uni- (UV) and multi-variable (MV) analyses were performed using FT and biopsy. Results: Baseline characteristics were similar as in the overall population; METAVIR stage: 28% F2, 29% F3, and 43% F4, previous relapsers 29%, previous PEG-IFN regimen 41%, high baseline viral load (BVL) 64%. 506 patients (35%) had undetectable HCV-RNA at TW12 (TW12neg), with 58% achieving SVR. The accuracy of FT was similar to that in naive patients: AUROC curve for the diagnosis of F4 vs F2 = 0.80 (p<0.00001). Five baseline factors were associated (p<0.001) with SVR in UV and MV analyses (odds ratio: UV/MV): fibrosis stage estimated using FT (4.5/5.9) or biopsy (1.5/1.6), genotype 2/3 (4.5/5.1), BVL (1.5/1.3), prior relapse (1.6/1.6), previous treatment with non-PEG-IFN (2.6/2.0). These same factors were associated (p <= 0.001) with EVR. Among patients TW12neg, two independent factors remained highly predictive of SVR by MV analysis (p <= 0.001): genotype 2/3 (odds ratio = 2.9), fibrosis estimated with FT (4.3) or by biopsy (1.5). Conclusions: FibroTest at baseline is a possible non-invasive alternative to biopsy for the prediction of EVR at 12 weeks and SVR, in patients with previous failures and advanced fibrosis, retreated with PEG-IFN alfa-2b and ribavirin. (C) 2010 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Molecular evidence of horizontal transmission of hepatitis C virus within couples

Hepatitis C virus (HCV) transmission has decreased with the adoption of universal blood donor screening and social policies to reduce the risk of infection in intravenous drug users, but remains a worldwide health problem. The objective of this study was to evaluate the phylogenetic relationships among sequences from different HCV genomic regions from sexual partners of infected patients. Nine couples with a stable relationship and without other risk factors for HCV infection and 42 control patients were selected, and the NS3 and NS5B regions were analysed. Phylogenetic analysis showed that viruses from five of the couples had a common origin, clustering in the same monophyletic group, with bootstrap values greater than 70. For the other couples, monophyletic groups were observed, but without bootstrap support. Thus, using two different viral genome regions, a common source of infection was observed in both members of five couples. These data strongly support HCV transmission within couples.