Evidence of a higher prevalence of HPV infection in HTLV-1-infected women: a cross-sectional study

INTRODUCTION:HTLV-1 infection increases susceptibility to other infections. Few studies have addressed the co-infection between HPV and HTLV-1 and the immune response involved in this interaction. The aim of this study was to determine the prevalence of cervical HPV infection in HTLV-1-infected women and to establish the risk factors involved in this co-infection. METHODS: A cross-sectional study was carried out in Salvador, Brazil, between September 2005 and December 2008, involving 50 HTLV-1-infected women from the HTLV Reference Center and 40 uninfected patients from gynecological clinic, both at the Bahiana School of Medicine. HPV infection was assessed using hybrid capture. HTLV-1 proviral load was quantified using real-time polymerase chain reaction (PCR). RESULTS: The mean age of HTLV-1-infected women (38 ± 10 years) was similar to that of the control group (36 ± 13 years). The prevalence of HPV infection was 44% in the HTLV-1-infected group and 22.5% in uninfected women (p = 0.03). HTLV-1-infected women had lower mean age at onset of sexual life (17 ± 3 years versus 19 ± 3 years; p = 0.03) and greater number of lifetime partners compared with the control group (4 ± 3 versus 2 ± 1; p < 0.01). In the group of HTLV-1-infected patients, there was neither difference in HTLV-1 proviral load between HPV-infected women and the uninfected. CONCLUSIONS: The prevalence of HPV infection was higher in HTLV-1-infected women. Further studies should be performed to evaluate the progression of this co-infection.

O Sinclinal de ferro de Torre de Moncorvo: um recurso mineral como catalisador de um Tempolntermitente

Dissertação de mestrado integrado em Arquitectura

On the length of bank-firm relationships: an empirical application to a major French bank

NIPE - WP 01/ 2016

Assessment of Galectin-3 Polymorphism in Subjects with Chronic Chagas Disease

AbstractBackground:Galectin-3, a β-galactoside binding lectin, has been described as a mediator of cardiac fibrosis in experimental studies and as a risk factor associated with cardiovascular events in subjects with heart failure. Previous studies have evaluated the genetic susceptibility to Chagas disease in humans, including the polymorphisms of cytokine genes, demonstrating correlations between the genetic polymorphism and cardiomyopathy development in the chronic phase. However, the relationship between the galectin-3 single nucleotide polymorphism (SNP) and phenotypic variations in Chagas disease has not been evaluated.Objective:The present study aimed to determine whether genetic polymorphisms of galectin-3 may predispose to the development of cardiac forms of Chagas disease.Methods:Fifty-five subjects with Chagas disease were enrolled in this observational study. Real-time polymerase chain reaction (PCR) was used for genotyping the variants rs4644 and rs4652 of the galectin-3 gene.Results:For the SNP rs4644, the relative risk for the cardiac form was not associated with the genotypes AA (OR = 0.79, p = 0.759), AC (OR = 4.38, p = 0.058), or CC (OR = 0.39, p = 0.127). Similarly, for the SNP rs4652, no association was found between the genotypes AA (OR = 0.64, p = 0.571), AC (OR = 2.85, p = 0.105), or CC (OR = 0.49, p = 0.227) and the cardiac form of the disease.Conclusion:Our results showed no association between the different genotypes for both SNPs of the galectin-3 gene and the cardiac form of Chagas disease. (Arq Bras Cardiol. 2015; [online].ahead print, PP.0-0)

Are one factor logarithmic volatility models useful to fit the features of financial data? An application to microsoft data.

This paper provides empirical evidence that continuous time models with one factor of volatility, in some conditions, are able to fit the main characteristics of financial data. It also reports the importance of the feedback factor in capturing the strong volatility clustering of data, caused by a possible change in the pattern of volatility in the last part of the sample. We use the Efficient Method of Moments (EMM) by Gallant and Tauchen (1996) to estimate logarithmic models with one and two stochastic volatility factors (with and without feedback) and to select among them.

Mediation incomplete information bargaining with filtered communication

We analyze a continuous-time bilateral double auction in the presence of two-sided incomplete information and a smallest money unit. A distinguishing feature of our model is that intermediate concessions are not observable by the adversary: they are only communicated to a passive auctioneer. An alternative interpretation is that of mediated bargaining. We show that an equilibrium using only the extreme agreements always exists and display the necessary and sufficient condition for the existence of (perfect Bayesian) equilibra which yield intermediate agreements. For the symmetric case with uniform type distribution we numerically calculate the equilibria. We find that the equilibrium which does not use compromise agreements is the least efficient, however, the rest of the equilibria yield the lower social welfare the higher number of compromise agreements are used.

Coupling and monotonicity of queueing processes

The main purpose of this work is to give a survey of main monotonicity properties of queueing processes based on the coupling method. The literature on this topic is quite extensive, and we do not consider all aspects of this topic. Our more concrete goal is to select the most interesting basic monotonicity results and give simple and elegant proofs. Also we give a few new (or revised) proofs of a few important monotonicity properties for the queue-size and workload processes both in single-server and multi- server systems. The paper is organized as follows. In Section 1, the basic notions and results on coupling method are given. Section 2 contains known coupling results for renewal processes with focus on construction of synchronized renewal instants for a superposition of independent renewal processes. In Section 3, we present basic monotonicity results for the queue-size and workload processes. We consider both discrete-and continuous-time queueing systems with single and multi servers. Less known results on monotonicity of queueing processes with dependent service times and interarrival times are also presented. Section 4 is devoted to monotonicity of general Jackson-type queueing networks with Markovian routing. This section is based on the notable paper [17]. Finally, Section 5 contains elements of stability analysis of regenerative queues and networks, where coupling and monotonicity results play a crucial role to establish minimal suficient stability conditions. Besides, we present some new monotonicity results for tandem networks.

Technology shocks and aggregate fluctuations in an estimated hybrid RBC model

This paper contributes to the on-going empirical debate regarding the role of the RBC model and in particular of technology shocks in explaining aggregate fluctuations. To this end we estimate the model’s posterior density using Markov-Chain Monte-Carlo (MCMC) methods. Within this framework we extend Ireland’s (2001, 2004) hybrid estimation approach to allow for a vector autoregressive moving average (VARMA) process to describe the movements and co-movements of the model’s errors not explained by the basic RBC model. The results of marginal likelihood ratio tests reveal that the more general model of the errors significantly improves the model’s fit relative to the VAR and AR alternatives. Moreover, despite setting the RBC model a more difficult task under the VARMA specification, our analysis, based on forecast error and spectral decompositions, suggests that the RBC model is still capable of explaining a significant fraction of the observed variation in macroeconomic aggregates in the post-war U.S. economy.

Stochastic Search Variable Selection in Vector Error Correction Models with an Application to a Model of the UK Macroeconomy

This paper develops methods for Stochastic Search Variable Selection (currently popular with regression and Vector Autoregressive models) for Vector Error Correction models where there are many possible restrictions on the cointegration space. We show how this allows the researcher to begin with a single unrestricted model and either do model selection or model averaging in an automatic and computationally efficient manner. We apply our methods to a large UK macroeconomic model.

Global Warming And Extreme Events: Rethinking The Timing And Intensity Of Environmental Policy

The possibility of low-probability extreme events has reignited the debate over the optimal intensity and timing of climate policy. In this paper we therefore contribute to the literature by assessing the implications of low-probability extreme events on environmental policy in a continuous-time real options model with “tail risk”. In a nutshell, our results indicate the importance of tail risk and call for foresighted pre-emptive climate policies.

Bayesian Model Averaging in the Instrumental Variable Regression Model

This paper considers the instrumental variable regression model when there is uncertainty about the set of instruments, exogeneity restrictions, the validity of identifying restrictions and the set of exogenous regressors. This uncertainty can result in a huge number of models. To avoid statistical problems associated with standard model selection procedures, we develop a reversible jump Markov chain Monte Carlo algorithm that allows us to do Bayesian model averaging. The algorithm is very exible and can be easily adapted to analyze any of the di¤erent priors that have been proposed in the Bayesian instrumental variables literature. We show how to calculate the probability of any relevant restriction (e.g. the posterior probability that over-identifying restrictions hold) and discuss diagnostic checking using the posterior distribution of discrepancy vectors. We illustrate our methods in a returns-to-schooling application.

Dark Clouds or Silver Linings? Knightian Uncertainty and Climate Change

This paper examines the impact of Knightian uncertainty upon optimal climate policy through the prism of a continuous-time real option modelling framework. We analytically determine optimal intertemporal climate policies under ambiguous assessments of climate damages. Additionally, numerical simulations are provided to illustrate the properties of the model. The results indicate that increasing Knightian uncertainty accelerates climate policy, i.e. policy makers become more reluctant to postpone the timing of climate policies into the future.

Evidence against a direct role of klotho in insulin resistance.

The klotho gene may be involved in the aging process. Klotho is a coactivator of FGF23, a regulator of phosphate and vitamin D metabolism. It has also been reported to be downregulated in insulin resistance syndromes and paradoxically to directly inhibit IGF-1 and insulin signaling. Our aim was to study klotho's regulation and effects on insulin and IGF-1 signaling to unravel this paradox. We studied klotho tissue distribution and expression by quantitative real-time polymerase chain reaction and Western blotting in obese Zucker rats and high-fat fed Wistar rats, two models of insulin resistance. Klotho was expressed in kidneys but at much lower levels (<1.5%) in liver, muscle, brain, and adipose tissue. There were no significant differences between insulin resistant and control animals. We next produced human recombinant soluble klotho protein (KLEC) and studied its effects on insulin and IGF-1 signaling in cultured cells. In HEK293 cells, FGF23 signaling (judged by FRS2-alpha and ERK1/2 phosphorylation) was activated by conditioned media from KLEC-producing cells (CM-KLEC); however, IGF-1 signaling was unaffected. CM-KLEC did not inhibit IGF-1 and insulin signaling in L6 and Hep G2 cells, as judged by Akt and ERK1/2 phosphorylation. We conclude that decreased klotho expression is not a general feature of rodent models of insulin resistance. Further, the soluble klotho protein does not inhibit IGF-1 and/or insulin signaling in HEK293, L6, and HepG2 cells, arguing against a direct role of klotho in insulin signaling. However, the hypothesis that klotho indirectly regulates insulin sensitivity via FGF23 activation remains to be investigated.

Global Warming and Fat Tailed-uncertainty: Rethinking the Timing and Intensity of Climate Policy

The possibility of low-probability extreme natural events has reignited the debate over the optimal intensity and timing of climate policy. In this paper, we contribute to the literature by assessing the implications of low-probability extreme events on environmental policy in a continuous-time real options model with “tail risk”. In a nutshell, our results indicate the importance of tail risk and call for foresighted pre-emptive climate policies.

Impact of genetic polymorphisms in cytomegalovirus glycoprotein B on outcomes in solid-organ transplant recipients with cytomegalovirus disease.

BACKGROUND:It is unknown whether specific viral polymorphisms affect in vivo therapeutic response in patients with cytomegalovirus (CMV) disease. Polymorphisms in the CMV glycoprotein B (gB) gene allow discrimination of 4 distinct genotypes (gB1-gB4). We assessed the influence of gB genotypes on the clinical and virologic outcome of CMV disease. METHODS:Solid-organ transplant recipients enrolled in a multicenter trial of CMV disease treatment (VICTOR study) were included in this study. CMV gB genotyping was performed using quantitative real-time polymerase chain reaction at day 0 (start of antiviral therapy). RESULTS:Among 239 patients with CMV disease, the prevalence of gB strain types was 26% for gB1, 10% for gB2, 10% for gB3, and 5% for gB4, whereas mixed infections were present in 49%. Donor-seropositive/recipient-seropositive patients were more likely to have mixed gB infection than donor-seropositive/recipient-seronegative patients (40% vs. 12%; P = .001). Median baseline viral loads were higher and time to viral eradication was longer ( P = .006 and P = .026 , respectively) for mixed infection versus infection with a single genotype. In a multivariate model, mixed gB infection was a significant predictor of failure to eradicate virus by day 21 (mixed vs single genotype; odds ratio, 2.66; 95% confidence interval, 1.31-5.38; P = .007 ) after controlling for baseline viral load, CMV serostatus at baseline, ganciclovir resistance, and antiviral treatment. No effect of gB genotype was seen on virologic or clinical CMV recurrence. CONCLUSIONS:No specific gB genotype appears to confer a specific CMV virulence advantage. However, mixed gB genotype infections are associated with higher viral loads and delayed viral clearance.