Arrhythmogenic cardiomyopathy of the right ventricle. Predictive value of QT interval dispersion to assess arrhythmogenic risk and sudden death

OBJECTIVE: To determine in arrhythmogenic right ventricular cardiomyopathy the value of QT interval dispersion for identifying the induction of sustained ventricular tachycardia in the electrophysiological study or the risk of sudden cardiac death. METHODS: We assessed QT interval dispersion in the 12-lead electrocardiogram of 26 patients with arrhythmogenic right ventricular cardiomyopathy. We analyzed its association with sustained ventricular tachycardia and sudden cardiac death, and in 16 controls similar in age and sex. RESULTS: (mean ± SD). QT interval dispersion: patients = 53.8±14.1ms; control group = 35.0±10.6ms, p=0.001. Patients with induction of ventricular tachycardia: 52.5±13.8ms; without induction of ventricular tachycardia: 57.5±12.8ms, p=0.420. In a mean follow-up period of 41±11 months, five sudden cardiac deaths occurred. QT interval dispersion in this group was 62.0±17.8, and in the others it was 51.9±12.8ms, p=0.852. Using a cutoff > or = 60ms to define an increase in the degree of the QT interval dispersion, we were able to identify patients at risk of sudden cardiac death with a sensitivity of 60%, a specificity of 57%, and positive and negative predictive values of 25% and 85%, respectively. CONCLUSION: Patients with arrhythmogenic right ventricular cardiomyopathy have a significant increase in the degree of QT interval dispersion when compared with the healthy population. However it, did not identify patients with induction of ventricular tachycardia in the electrophysiological study, showing a very low predictive value for defining the risk of sudden cardiac death in the population studied.

Reduction of QTc interval dispersion. Potential mechanism of cardiac protection of pyridostigmine bromide

OBJECTIVE: Parasympathetic dysfunction is an independent risk factor in individuals with coronary artery disease, and cholinergic stimulation is a potential therapeutical option. We determined the effects of pyridostigmine bromide, a reversible anticholinesterase agent, on electrocardiographic variables of healthy individuals. METHODS: We carried out a cross-sectional, double blind, randomized, placebo-controlled study. We obtained electrocardiographic tracings in 12 simultaneous leads of 10 healthy young individuals at rest before and after oral administration of 45 mg of pyridostigmine or placebo. RESULTS: Pyridostigmine increased RR intervals (before: 886±27 ms vs after: 1054±37 ms) and decreased QTc dispersion (before: 72±9ms vs after: 45±3ms), without changing other electrocardiographic variables (PR segment, QT interval, QTc, and QT dispersion). CONCLUSION: Bradycardia and the reduction in QTc dispersion induced by pyridostigmine may effectively represent a protective mechanism if these results can be reproduced in individuals with cardiovascular diseases.

Patrones dinámicos de abundancia y dispersión de una plaga en un paisaje heterogéneo. Dynamic patterns of abundance and dispersion of a pest in a heterogeneous landscape.

El desarrollo de conocimiento empírico sobre cómo la heterogeneidad espacial de un paisaje afecta los patrones de movimiento de una especie animal es considerado una prioridad para el manejo y la conservación de las especies y sus hábitats. En el caso de los insectos plaga, estos estudios resultan importantes ya que aportan las bases teóricas y empíricas fundamentales para su manejo. La persistencia de éstas especies en un paisaje modificado depende de la interrelación entre procesos ecológicos y la estructura del paisaje, tales como la interacción entre especies, la disponibilidad de parches hábitat y la influencia de las prácticas de manejo. El análisis de éstos procesos en un agroecosistema permite simplificar los modelos de heterogeneidad espacial, debido a que los lotes de cultivo son internamente homogéneos y los disturbios antropogénicos generalmente ocurren a la escala de parche, permitiendo determinar las respuestas de los insectos a dicha escala. La alfalfa (Medicago sativa) es un recurso fundamental para la producción agropecuaria y en Argentina, es el recurso forrajero más importante, constituyendo la base de la producción ganadera del país. Actualmente se cultivan alrededor de 5 millones de hectáreas, de las cuales un millón se siembran en la provincia de Córdoba. Además, cumple un rol importante en la sustentabilidad de los sistemas de producción por su función de recuperación de la fertilidad y estabilidad edáfica. La isoca de la alfalfa (Colias lesbia) es la plaga principal del cultivo, produciendo en promedio la pérdida de un corte por año. La hipótesis principal de nuestro trabajo es que los patrones de abundancia y movilidad de la isoca de la alfalfa son afectados por la estructura del paisaje y las prácticas de manejo. Los objetivos específicos del proyecto son: (a) Establecer el efecto de la estructura del paisaje y y el manejo del cultivo en la abundancia de los distintos estadios de Colias lesbia. (b) Determinar los patrones de dispersión de Colias lesbia en relación a la heterogeneidad espacial del paisaje (c) Generar un modelo predictivo de la abundancia de Colias lesbia según la estructura espacial del paisaje, el clima y el manejo del cultivo. (d) Desarrollar un conjunto de recomendaciones de manejo a escala regional para el control de la isoca de la alfalfa. Para ello se elegirán lotes de alfalfa en la región este de la provincia de Córdoba, en el departamento de San Justo, donde se realizará un relevamiento inicial del área de estudio y se dialogará con los productores. Paralelamente, se realizará una clasificación supervisada del área de estudio a partir de escenas de imágenes Landsat TM. En los parches seleccionados, durante 3 años y durante los meses de verano, se muestrearán quincenalmente los distintos estadios de Colias lesbia. Se realizarán análisis de correlación y regresión entre las variables independientes (métricas de la configuración y dinámica del paisaje) y las variables dependientes, (abundancia media de los diferentes estadios de las poblaciones). Asimismo, se realizarán experimentos de marcado-liberación-recaptura para determinar cómo el movimiento de la especie depende de la estructura del paisaje. Para modelar el movimiento inherente de la especie se combinará la información obtenida en el campo con un modelo de difusión utilizando métodos bayesianos. Se espera obtener modelos que permitan comprender los mecanismos que generan los patrones observados. Con esta información se propondrán lineamientos generales y específicos para un manejo de la isoca de la alfalfa a escala regional. En tal sentido, se espera aportar información para restringir la dispersión de la plaga, y reducir los costos y perjuicios del control químico que podrían evitarse con la aplicación de prácticas de manejo integrado y de "manejo de área" que minimicen el impacto de la plaga como también contribuir al conocimiento general de la ecología de insectos.

Molecular phylogenies, chromosomes and dispersion in Brazilian akodontines (Rodentia, Sigmodontinae)

A new molecular phylogeny for akodontine rodents from Brazil was proposed. The phylogenetic tree was enriched with the area of occurrence and with information on the karyotype of the samples. Based on this enriched tree, and with a described methodology, hypotheses were proposed on the karyotype and area of occurrence of the ancestors of each Clade. Thus it was possible to discuss hypotheses on chromosome evolution of the group, and on dispersion events from the "area of original differentiation" of akodontines in the Andes. Chromosome evolution started with high diploid numbers (2n=52) and showed a tendency to reduction (until 2n=14 in more recent clades). Independent side-branches of the tree showed 2n reduction and in one case the 2n increased. At least four dispersion events from the Andes down to South-eastern Brazil were proposed. The results should suggest the direction of new studies on comparative karyology.

Trade disclosure and price dispersion

This paper determines the effects of post-trade opaqueness on market performance. We find that the degree of market transparency has important effects on market equilibria. In particular, we show that dealers operating in a transparent structure set regret-free prices at each period making zero expected profits in each of the two trading rounds, whereas in the opaque market dealers invest in acquiring information at the beginning of the trading day. Moreover, we obtain that if there is no trading activity in the first period, then market makers only change their quotes in the opaque market. Additionally, we show that trade disclosure increases the informational efficiency of transaction prices and reduces volatility. Finally, concerning welfare of market participants, we obtain ambiguous results. Keywords: Market microstructure, Post-trade transparency, Price experimentation, Price dispersion.

Co-movements between US and UK stock prices: the roles of macroeconomic information and time-series varying conditional correlations

This paper provides evidence on the sources of co-movement in monthly US and UK stock price movements by investigating the role of macroeconomic and financial variables in a bivariate system with time-varying conditional correlations. Crosscountry communality in response is uncovered, with changes in the US Federal Funds rate, UK bond yields and oil prices having similar negative effects in both markets. Other variables also play a role, especially for the UK market. These effects do not, however, explain the marked increase in cross-market correlations observed from around 2000, which we attribute to time variation in the correlations of shocks to these markets. A regime-switching smooth transition model captures this time variation well and shows the correlations increase dramatically around 1999-2000. JEL classifications: C32, C51, G15 Keywords: international stock returns, DCC-GARCH model, smooth transition conditional correlation GARCH model, model evaluation.

Genetical exchanges between one Biomphalaria glabrata (Gastropoda: Planorbidae) and a varying number of partners

When one pigmented Biomphalaria glabrata is mated with 1 to 20 albino snails, the percentage of albino parent producing pigmented offspring decreases while the percentage of parent laying albino offspring increases. If the number of snaisl/group increases, the mean duration of the use of allosperm decreases.

Epidemiologia de la leishmaniasis tegumentaria en merida, Venezuela. I. Diversidade y dispersion de especies flebotominas en tres pisos altitudinales y su possible rôle en la transmission de enfermedad

Como parte de un estudio epidemiológico sobre leishmaniasis en el Estado Mérida, Venezuela, se presenta la diversidad y dispersión de las especies flebotominas identificadas en 15 localidades ubicadas en 3 pisos altitudinales entre los 175 y los 1.960 m.s.n.m. De 7.126 espécimes capturados (5.132 hombres y 1.994 femenino) se registran 24 especies de Lutzomyia, reconociéndose 10 de las llmadas antropofílicas. Se detalla la distribución de las especies en cada piso altitudinal y en el domicilio humano, el peridomicilio y el ambiente silvestre. Se discute el posible papel que juegan las diferentes especies en la transmisión de la leishmaniasis tegumentaria en cada piso altitudinal en particular y en la región andino-venezolana, en general.

Bayesian Inference in the Time Varying Cointegration Model

There are both theoretical and empirical reasons for believing that the parameters of macroeconomic models may vary over time. However, work with time-varying parameter models has largely involved Vector autoregressions (VARs), ignoring cointegration. This is despite the fact that cointegration plays an important role in informing macroeconomists on a range of issues. In this paper we develop time varying parameter models which permit cointegration. Time-varying parameter VARs (TVP-VARs) typically use state space representations to model the evolution of parameters. In this paper, we show that it is not sensible to use straightforward extensions of TVP-VARs when allowing for cointegration. Instead we develop a specification which allows for the cointegrating space to evolve over time in a manner comparable to the random walk variation used with TVP-VARs. The properties of our approach are investigated before developing a method of posterior simulation. We use our methods in an empirical investigation involving a permanent/transitory variance decomposition for inflation.

Large Time-Varying Parameter VARs

In this paper we develop methods for estimation and forecasting in large timevarying parameter vector autoregressive models (TVP-VARs). To overcome computational constraints with likelihood-based estimation of large systems, we rely on Kalman filter estimation with forgetting factors. We also draw on ideas from the dynamic model averaging literature and extend the TVP-VAR so that its dimension can change over time. A final extension lies in the development of a new method for estimating, in a time-varying manner, the parameter(s) of the shrinkage priors commonly-used with large VARs. These extensions are operationalized through the use of forgetting factor methods and are, thus, computationally simple. An empirical application involving forecasting inflation, real output, and interest rates demonstrates the feasibility and usefulness of our approach.

Model Switching and Model Averaging in Time- Varying Parameter Regression Models

This paper investigates the usefulness of switching Gaussian state space models as a tool for implementing dynamic model selecting (DMS) or averaging (DMA) in time-varying parameter regression models. DMS methods allow for model switching, where a different model can be chosen at each point in time. Thus, they allow for the explanatory variables in the time-varying parameter regression model to change over time. DMA will carry out model averaging in a time-varying manner. We compare our exact approach to DMA/DMS to a popular existing procedure which relies on the use of forgetting factor approximations. In an application, we use DMS to select different predictors in an in ation forecasting application. We also compare different ways of implementing DMA/DMS and investigate whether they lead to similar results.

On the time-varying relationship between EMU sovereign spreads and their determinants

We use a dynamic multipath general-to-specific algorithm to capture structural instability in the link between euro area sovereign bond yield spreads against Germany and their underlying determinants over the period January 1999 – August 2011. We offer new evidence suggesting a significant heterogeneity across countries, both in terms of the risk factors determining spreads over time as well as in terms of the magnitude of their impact on spreads. Our findings suggest that the relationship between euro area sovereign risk and the underlying fundamentals is strongly timevarying, turning from inactive to active since the onset of the global financial crisis and further intensifying during the sovereign debt crisis. As a general rule, the set of financial and macro spreads’ determinants in the euro area is rather unstable but generally becomes richer and stronger in significance as the crisis evolves.

Time Varying Dimension Models

Time varying parameter (TVP) models have enjoyed an increasing popularity in empirical macroeconomics. However, TVP models are parameter-rich and risk over-fitting unless the dimension of the model is small. Motivated by this worry, this paper proposes several Time Varying dimension (TVD) models where the dimension of the model can change over time, allowing for the model to automatically choose a more parsimonious TVP representation, or to switch between different parsimonious representations. Our TVD models all fall in the category of dynamic mixture models. We discuss the properties of these models and present methods for Bayesian inference. An application involving US inflation forecasting illustrates and compares the different TVD models. We find our TVD approaches exhibit better forecasting performance than several standard benchmarks and shrink towards parsimonious specifications.

Hierarchical Shrinkage in Time-Varying Parameter Models

In this paper, we forecast EU-area inflation with many predictors using time-varying parameter models. The facts that time-varying parameter models are parameter-rich and the time span of our data is relatively short motivate a desire for shrinkage. In constant coefficient regression models, the Bayesian Lasso is gaining increasing popularity as an effective tool for achieving such shrinkage. In this paper, we develop econometric methods for using the Bayesian Lasso with time-varying parameter models. Our approach allows for the coefficient on each predictor to be: i) time varying, ii) constant over time or iii) shrunk to zero. The econometric methodology decides automatically which category each coefficient belongs in. Our empirical results indicate the benefits of such an approach.

Permeability estimates from poro-elastic dispersion analyses of sonic logs

Modern sonic logging tools designed for shallow environmental and engineering applications allow for P-wave phase velocity measurements over a wide frequency band. Methodological considerations indicate that, for saturated unconsolidated sediments in the silt to sand range and source frequencies ranging from approximately 1 to 30 kHz, the observable poro-elastic P-wave velocity dispersion is sufficiently pronounced to allow for reliable first-order estimations of the underlying permeability structure. These predictions have been tested on and verified for a surficial alluvial aquifer. Our results indicate that, even without any further calibration, the thus obtained permeability estimates as well as their variabilities within the pertinent lithological units are remarkably close to those expected based on the corresponding granulometric characteristics.