Leishmania replication protein A-1 binds in vivo single-stranded telomeric DNA

Replication protein A (RPA) is a highly conserved heterotrimeric single-stranded DNA-binding protein involved in different events of DNA metabolism. In yeast, subunits 1 (RPA-1) and 2 (RPA-2) work also as telomerase recruiters and, in humans, the complex unfolds G-quartet structures formed by the 3' G-rich telomeric strand. In most eukaryotes, RPA-1 and RPA-2 bind DNA using multiple OB fold domains. In trypanosomatids, including Leishmania, RPA-1 has a canonical OB fold and a truncated RFA-1 structural domain. In Leishmania amazonensis, RPA-1 alone can form a complex in vitro with the telomeric G-rich strand. In this work, we show that LaRPA-1 is a nuclear protein that associates in vivo with Leishmania telomeres. We mapped the boundaries of the OB fold DNA-binding domain using deletion mutants. Since Leishmania and other trypanosomatids lack homologues of known telomere end binding proteins, our results raise questions about the function of RPA-1 in parasite telomeres. (C) 2007 Elsevier B.V. All rights reserved.

A single nucleotide deletion at the C1 inhibitor gene as the cause of hereditary angioedema: insights from a Brazilian family

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Recanalization Rates after Acute Deep Vein Thrombosis: A Single-center Experience Using a Newly Proposed Vein Diameter Variation Index

Background: Duplex ultrasound scanning (DUS) is the method of choice for diagnosis of deep vein thrombosis (DVT). However, only a few studies have performed prospective serial DUS after an acute episode of DVT to assess its evolution. This study aimed to report our experience using DUS combined with a thrombosis score (TS) and a newly proposed vein diameter variation index (VDVI) to evaluate the rate of resolution of DVT by assessing and quantifying the early stages of vein recanalization in proximal vein segments within 6 months after an episode of acute lower extremity DVT.Methods: Twelve patients with first episode of acute lower extremity DVT confirmed by DUS as occurring in <= 10 days after the onset of venous thrombosis symptoms were followed up prospectively for 6 months. TS and VDVI were calculated at 1, 3, and 6 months to assess vein recanalization. Intra-thrombus arteriovenous fistula formation was also investigated and related to the recanalization process.Results: Seven (58%) women were included, with a total cohort median age of 53.5 +/- 19 years. The left lower extremity was affected in 7 (58%) patients. DVT was diagnosed in 55 proximal vein segments. All patients had proximal DVT, with involvement of the external iliac, femoral, and popliteal veins. After 6 months, there was a significant decrease in TS and increase in VDVI (P < 0.001) in all proximal vein segments assessed, indicating thrombus regression. The more distal the DVT was, the faster was the VDVI increase, with most popliteal veins being recanalized at 3 months (P < 0.001). Intra-thrombus arteriovenous fistula was identified in 50% of patients at 1 month while on anticoagulation.Conclusions: The combined use of two different DUS-based assessment tools, TS and the proposed VDVI, provided an effective method to prospectively assess vein recanalization rates after an episode of acute lower extremity DVT in this series of patients and may allow a correct evaluation of DVT and its resolution or progression.

Predicting breeding values for milk yield of Guzera (Bos indicus) cows using random regression models

Given the importance of Guzera breeding programs for milk production in the tropics, the objective of this study was to compare alternative random regression models for estimation of genetic parameters and prediction of breeding values. Test-day milk yields records (TDR) were collected monthly, in a maximum of 10 measurements. The database included 20,524 records of first lactation from 2816 Guzera cows. TDR data were analyzed by random regression models (RRM) considering additive genetic, permanent environmental and residual effects as random and the effects of contemporary group (CG), calving age as a covariate (linear and quadratic effects) and mean lactation curve as fixed. The genetic additive and permanent environmental effects were modeled by RRM using Wilmink, All and Schaeffer and cubic B-spline functions as well as Legendre polynomials. Residual variances were considered as heterogeneous classes, grouped differently according to the model used. Multi-trait analysis using finite-dimensional models (FDM) for testday milk records (TDR) and a single-trait model for 305-days milk yields (default) using the restricted maximum likelihood method were also carried out as further comparisons. Through the statistical criteria adopted, the best RRM was the one that used the cubic B-spline function with five random regression coefficients for the genetic additive and permanent environmental effects. However, the models using the Ali and Schaeffer function or Legendre polynomials with second and fifth order for, respectively, the additive genetic and permanent environmental effects can be adopted, as little variation was observed in the genetic parameter estimates compared to those estimated by models using the B-spline function. Therefore, due to the lower complexity in the (co)variance estimations, the model using Legendre polynomials represented the best option for the genetic evaluation of the Guzera lactation records. An increase of 3.6% in the accuracy of the estimated breeding values was verified when using RRM. The ranks of animals were very close whatever the RRM for the data set used to predict breeding values. Considering P305, results indicated only small to medium difference in the animals' ranking based on breeding values predicted by the conventional model or by RRM. Therefore, the sum of all the RRM-predicted breeding values along the lactation period (RRM305) can be used as a selection criterion for 305-day milk production. (c) 2014 Elsevier B.V. All rights reserved.

A note on model uncertainty in linear regression

We consider model selection uncertainty in linear regression. We study theoretically and by simulation the approach of Buckland and co-workers, who proposed estimating a parameter common to all models under study by taking a weighted average over the models, using weights obtained from information criteria or the bootstrap. This approach is compared with the usual approach in which the 'best' model is used, and with Bayesian model averaging. The weighted predictor behaves similarly to model averaging, with generally more realistic mean-squared errors than the usual model-selection-based estimator.

Precision of distances and ordering of microsatellite markers in consensus linkage maps of chromosomes 1, 3 and 4 from two reciprocal chicken populations using bootstrap sampling

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Comparison of multiple-input single-output single-user ultra-wideband systems with pre-distortion

This paper presents a performance analysis of a baseband multiple-input single-output ultra-wideband system over scenarios CM1 and CM3 of the IEEE 802.15.3a channel model, incorporating four different schemes of pre-distortion: time reversal, zero-forcing pre-equaliser, constrained least squares pre-equaliser, and minimum mean square error pre-equaliser. For the third case, a simple solution based on the steepest-descent (gradient) algorithm is adopted and compared with theoretical results. The channel estimations at the transmitter are assumed to be truncated and noisy. Results show that the constrained least squares algorithm has a good trade-off between intersymbol interference reduction and signal-to-noise ratio preservation, providing a performance comparable to the minimum mean square error method but with lower computational complexity. Copyright (C) 2011 John Wiley & Sons, Ltd.

Retrospective Clinical Study of 988 Dual Acid-Etched Implants Placed in Grafted and Native Bone for Single-Tooth Replacement

Purpose: To evaluate the influence of sex, implant characteristics, and bone grafting on the survival rate of dual acid-etched (DAE) implants. Materials and Methods: Patients treated with internal-hex DAE implants for single-tooth replacement in a military dental clinic between January 2005 and December 2010 were included in this study. Clinical data related to implant characteristics, implant location, presence of grafted bone, and implant failures were collected. The primary outcome was implant loss. The survival rate was analyzed using the Kaplan-Meier method. Cox regression modeling was used to determine which factors would predict implant failure. Results: DAE implants were evaluated in a total of 988 patients (80.3% men). Twenty-four (2.4%) implants failed, most were cylindric (54.2%) with regular platforms (70.8%) and were 10 mm long (58.3%). The failure rate was 2.4% for the anterior maxilla, 3.3% for the posterior maxilla, 1.6% for the anterior mandible, and 2.0% for posterior mandible. The cumulative survival rate was 97.6%. The failure rate was 8.8% in implants placed after sinus augmentation, 7.3% in bone block-grafted areas, and 1.6% in native bone. Based on multivariable analysis (Cox regression), sinus augmentation and bone block grafting had a statistically significant effect on implant failure; the hazard ratios were 5.5 and 4.6, respectively. Conclusion: The results revealed that DAE implants had high survival rates, and no influence of sex, location, shape, diameter, or length on failure rates could be observed. However, a significant association was observed between failure and presence of bone graft in the implant area. Int J Oral Maxillofac Implants 2012;27:1243-1248

Risk Factors and Survival Impact of Primary Graft Dysfunction After Lung Transplantation in a Single Institution

Background. Lung transplantation has become a standard procedure for some end-stage lung diseases, but primary graft dysfunction (PGD) is an inherent problem that impacts early and late outcomes. The aim of this study was to define the incidence, risk factors, and impact of mechanical ventilation time on mortality rates among a retrospective cohort of lung transplantations performed in a single institution. Methods. We performed a retrospective study of 118 lung transplantations performed between January 2003 and July 2010. The most severe form of PGD (grade III) as defined at 48 and 72 hours was examined for risk factors by multivariable logistic regression models using donor, recipient, and transplant variables. Results. The overall incidence of PGD at 48 hours was 19.8%, and 15.4% at 72 hours. According multivariate analysis, risk factors associated with PGD were donor smoking history for 48 hours (adjusted odds ratio [OR], 4.83; 95% confidence interval [CI], 1.236-18.896; P = .022) and older donors for 72 hours (adjusted OR, 1.046; 95% CI, 0.997-1.098; P = .022). The operative mortality was 52.9% among patients with PGD versus 20.3% at 48 hours (P = .012). At 72 hours, the mortality rate was 58.3% versus 21.2% (P = .013). The 90-days mortality was also higher among patients with PGD. The mechanical ventilation time was longer in patients with PGD III at 48 hours namely, a mean time of 72 versus 24 hours (P = .001). When PGD was defined at 72 hours, the mean ventilation time was even longer, namely 151 versus 24 hours (P < .001). The mean overall survival for patients who developed PGD at 48 hours was 490.9 versus 1665.5 days for subjects without PGD (P = .001). Considering PGD only at 72 hours, the mean survival was 177.7 days for the PGD group and 1628.9 days for the other patients (P < .001). Conclusion. PGD showed an important impacts on operative and 90-day mortality rates, mechanical ventilation time, and overall survival among lung transplant patients. PGD at 72 hours was a better predictor of lung transplant outcomes than at 48 hours. The use of donors with a smoking history or of advanced age were risk factors for the development of PGD.

The Truncated Inflated Beta Distribution

The study of proportions is a common topic in many fields of study. The standard beta distribution or the inflated beta distribution may be a reasonable choice to fit a proportion in most situations. However, they do not fit well variables that do not assume values in the open interval (0, c), 0 < c < 1. For these variables, the authors introduce the truncated inflated beta distribution (TBEINF). This proposed distribution is a mixture of the beta distribution bounded in the open interval (c, 1) and the trinomial distribution. The authors present the moments of the distribution, its scoring vector, and Fisher information matrix, and discuss estimation of its parameters. The properties of the suggested estimators are studied using Monte Carlo simulation. In addition, the authors present an application of the TBEINF distribution for unemployment insurance data.

Random regression analyses using B-spline functions to model growth of Nellore cattle

The objective of this study was to estimate (co)variance components using random regression on B-spline functions to weight records obtained from birth to adulthood. A total of 82 064 weight records of 8145 females obtained from the data bank of the Nellore Breeding Program (PMGRN/Nellore Brazil) which started in 1987, were used. The models included direct additive and maternal genetic effects and animal and maternal permanent environmental effects as random. Contemporary group and dam age at calving (linear and quadratic effect) were included as fixed effects, and orthogonal Legendre polynomials of age (cubic regression) were considered as random covariate. The random effects were modeled using B-spline functions considering linear, quadratic and cubic polynomials for each individual segment. Residual variances were grouped in five age classes. Direct additive genetic and animal permanent environmental effects were modeled using up to seven knots (six segments). A single segment with two knots at the end points of the curve was used for the estimation of maternal genetic and maternal permanent environmental effects. A total of 15 models were studied, with the number of parameters ranging from 17 to 81. The models that used B-splines were compared with multi-trait analyses with nine weight traits and to a random regression model that used orthogonal Legendre polynomials. A model fitting quadratic B-splines, with four knots or three segments for direct additive genetic effect and animal permanent environmental effect and two knots for maternal additive genetic effect and maternal permanent environmental effect, was the most appropriate and parsimonious model to describe the covariance structure of the data. Selection for higher weight, such as at young ages, should be performed taking into account an increase in mature cow weight. Particularly, this is important in most of Nellore beef cattle production systems, where the cow herd is maintained on range conditions. There is limited modification of the growth curve of Nellore cattle with respect to the aim of selecting them for rapid growth at young ages while maintaining constant adult weight.

Prognostic factors for survival in patients with colorectal liver metastases: experience of a single brazilian cancer center

CONTEXT: Liver metastases are a common event in the clinical outcome of patients with colorectal cancer and account for 2/3 of deaths from this disease. There is considerable controversy among the data in the literature regarding the results of surgical treatment and prognostic factors of survival, and no analysis have been done in a large cohort of patients in Brazil. OBJECTIVES: To characterize the results of surgical treatment of patients with colorectal liver metastases, and to establish prognostic factors of survival in a Brazilian population. METHOD: This was a retrospective study of patients undergoing liver resection for colorectal metastases in a tertiary cancer hospital from 1998 to 2009. We analyzed epidemiologic variables and the clinical characteristics of primary tumors, metastatic disease and its treatment, surgical procedures and follow-up, and survival results. Survival analyzes were done by the Kaplan-Meier method and the log-rank test was applied to determine the influence of variables on overall and disease-free survival. All variables associated with survival with P<0.20 in univariate analysis, were included in multivariate analysis using a Cox proportional hazard regression model. RESULTS: During the period analyzed, 209 procedures were performed on 170 patients. Postope-rative mortality in 90 days was 2.9% and 5-year overall survival was 64.9%. Its independent prognostic factors were the presence of extrahepatic disease at diagnosis of liver metastases, bilateral nodules and the occurrence of major complications after liver surgery. The estimated 5-year disease-free survival was 39.1% and its prognostic factors included R1 resection, extrahepatic disease, bilateral nodules, lymph node involvement in the primary tumor and primary tumors located in the rectum. CONCLUSION: Liver resection for colorectal metastases is safe and effective and the analysis of prognostic factors of survival in a large cohort of Brazilian patients showed similar results to those pointed in international series. The occurrence of major postoperative complications appears to be able to compromise overall survival and further investigation in needed in this topic.

Bootstrap confidence intervals for industrial recurrent event data

Industrial recurrent event data where an event of interest can be observed more than once in a single sample unit are presented in several areas, such as engineering, manufacturing and industrial reliability. Such type of data provide information about the number of events, time to their occurrence and also their costs. Nelson (1995) presents a methodology to obtain asymptotic confidence intervals for the cost and the number of cumulative recurrent events. Although this is a standard procedure, it can not perform well in some situations, in particular when the sample size available is small. In this context, computer-intensive methods such as bootstrap can be used to construct confidence intervals. In this paper, we propose a technique based on the bootstrap method to have interval estimates for the cost and the number of cumulative events. One of the advantages of the proposed methodology is the possibility for its application in several areas and its easy computational implementation. In addition, it can be a better alternative than asymptotic-based methods to calculate confidence intervals, according to some Monte Carlo simulations. An example from the engineering area illustrates the methodology.

Dose-dependent effect of a single GnRHa injection on the spawning of meagre ("Argyrosomus regius") broodstock reared in captivity

[EN]The present study aimed to determine the spawning efficacy, egg quality and quantity of captive breed meagre induced with a single gonadotrophin-releasing hormone agonist (GnRHa) injection of 0, 1, 5, 10, 15, 20, 25, 30, 40 or 50 μg kg–1 to determine a recommended optimum dose to induce spawning. The doses 10, 15 and 20 μg kg–1 gave eggs with the highest quality (measured as: percentage of viability, floating, fertilisation and hatch) and quantity (measured as: total number of eggs, number of viable eggs, number of floating eggs, number of hatched larvae and number of larvae that reabsorbed the yolk sac). All egg quantity parameters were described by Gaussian regression analysis with R2 = 0.89 or R2 = 0.88. The Gaussian regression analysis identified that the optimal dose used was 15 μg kg–1. The regression analysis highlighted that this comprehensive study examined doses that ranged from low doses insufficient to stimulate a high spawning response (significantly lower egg quantities, p < 0.05) compared to 15 μg kg–1 through to high doses that stimulated the spawning of significantly lower egg quantities and eggs with significantly lower quality (egg viability). In addition, the latency period (time from hormone application to spawning) decreased with increasing doses to give a regression (R2 = 0.93), which suggests that higher doses accelerated oocyte development that in turn reduced egg quality and quantity. The identification of an optimal dose for the spawning of meagre, which has high aquaculture potential, represents an important advance for the Mediterranean aquaculture industry.

Essays in Macroecometrics: methodological aspects and empirical applications

In the first chapter, I develop a panel no-cointegration test which extends Pesaran, Shin and Smith (2001)'s bounds test to the panel framework by considering the individual regressions in a Seemingly Unrelated Regression (SUR) system. This allows to take into account unobserved common factors that contemporaneously affect all the units of the panel and provides, at the same time, unit-specific test statistics. Moreover, the approach is particularly suited when the number of individuals of the panel is small relatively to the number of time series observations. I develop the algorithm to implement the test and I use Monte Carlo simulation to analyze the properties of the test. The small sample properties of the test are remarkable, compared to its single equation counterpart. I illustrate the use of the test through a test of Purchasing Power Parity in a panel of EU15 countries. In the second chapter of my PhD thesis, I verify the Expectation Hypothesis of the Term Structure in the repurchasing agreements (repo) market with a new testing approach. I consider an "inexact" formulation of the EHTS, which models a time-varying component in the risk premia and I treat the interest rates as a non-stationary cointegrated system. The effect of the heteroskedasticity is controlled by means of testing procedures (bootstrap and heteroskedasticity correction) which are robust to variance and covariance shifts over time. I fi#nd that the long-run implications of EHTS are verified. A rolling window analysis clarifies that the EHTS is only rejected in periods of turbulence of #financial markets. The third chapter introduces the Stata command "bootrank" which implements the bootstrap likelihood ratio rank test algorithm developed by Cavaliere et al. (2012). The command is illustrated through an empirical application on the term structure of interest rates in the US.