Effects of long-acting testosterone undecanoate on bone mineral density in middle-aged men with late-onset hypogonadism and metabolic syndrome: results from a 36 months controlled study

We evaluated the effects of long-term testosterone replacement therapy (TRT) on the bone mineral density (BMD) in obese patients with metabolic syndrome (MS) and late-onset hypogonadism (LOH). Sixty men (mean age 57 ± 10) with low serum testosterone (T < 320 ng/dL) and MS regardless the presence of osteoporosis were enrolled. Forty men received intramuscular T-undecanoate (TU) four times/year for 36 months and 20 age-matched hypogonadal men with MS in whom T treatment was contraindicated were used as controls. Hormonal, biochemical markers, vertebral and femoral BMD by dual-energy x-ray absorptiometry were measured. At baseline, overall patients had mild osteopenia (lumbar BMD= 0.891 ± 0.097 g/cm(2); femoral BMD= 0.847 ± 0.117 g/cm(2)). TU induced a significant improvement of bone mass after 36 months (lumbar BMD=1.053 ± 0.145 g/cm(2); p < 0.002; femoral BMD=0.989 ± 0.109; p < 0.003 g/cm(2)) with a 5%/year increase and a significant reduction in hs-CRP without changes in body mass index. A direct relationship between serum T and BMD increments at the lumbar (r(2)?= 0.66, p < 0.0001) and femoral (r(2)?=0.52, p < 0.0001) sites was demonstrated. Study adherence was 50% without serious side effects. Long-term TRT in middle-aged men with LOH and MS determines a significant increase in both vertebral and femoral BMD related to increased serum T levels, probably independently from estradiol modifications.     

Bayesian inference for a flexible class of bivariate beta distributions

Several bivariate beta distributions have been proposed in the literature. In particular, Olkin and Liu [A bivariate beta distribution. Statist Probab Lett. 2003;62(4):407–412] proposed a 3 parameter bivariate beta model which Arnold and Ng [Flexible bivariate beta distributions. J Multivariate Anal. 2011;102(8):1194–1202] extend to 5 and 8 parameter models. The 3 parameter model allows for only positive correlation, while the latter models can accommodate both positive and negative correlation. However, these come at the expense of a density that is mathematically intractable. The focus of this research is on Bayesian estimation for the 5 and 8 parameter models. Since the likelihood does not exist in closed form, we apply approximate Bayesian computation, a likelihood free approach. Simulation studies have been carried out for the 5 and 8 parameter cases under various priors and tolerance levels. We apply the 5 parameter model to a real data set by allowing the model to serve as a prior to correlated proportions of a bivariate beta binomial model. Results and comparisons are then discussed.     

The Frisch Elasticity in the Mercosur Countries: A Pseudo‐Panel Approach

In estimating the Frisch elasticity – i.e., the elasticity of substitution between worked hours and real wages, holding constant the marginal utility of wealth – for the Mercosur countries, this article finds a strong heterogeneity. It argues that severe liquidity constraints are the main reason for the negative estimates and that the heterogeneity is the outcome of differences in many relevant economic dimensions – ranging from sectorial specialisation to welfare‐state provisions and labour‐market specificities. The diversity of Frisch elasticities calls for the development of a cross‐country (rather than a within‐country) policy approach, since they crucially affect the dynamics of the business cycle, the synchronisation of which is a step prior to the design of macro‐convergence policies in the Mercosur context.     

“Governance and corruption: is history repeating itself?” Fostering a debate and inviting contributions from a multidisciplinary perspective

Corruption is a critical phenomenon, both domestically and internationally. Corruption is a concept difficult to circumscribe referring to a large variety of levels, expressions and profiles. Due to its characteristics corruption has to be approached assuming a multi-perspective view. We believe that corruption ha to be studies assuming that this is multi-perspective and multi-disciplinary. We support the idea that governance perspective has to be considered central and innovative. The multi-disciplinary perspective wasn't completely explored in order to comprehend how the corruption phenomenon works and which consequences it is able to determine. Our study aims to stimulate the debate on the link between governance and the phenomenon of corruption as an illness affecting our capitalistic societies in many respects.     

Markov random field-based image subsampling method

The use of Bayesian models for the reconstruction of images degraded by both some blurring function H and the presence of noise has become popular in recent years. Making an analogy between classical degradation processes and resampling, we propose a Bayesian model for generating finer resolution images. The approach involves defining resampling, or aggregation, as a linear operator applied to an original picture to produce derived lower resolution data which represent our available experimental infor-mation. Within this framework, the operation of making inference on the orginal data can be viewed as an inverse linear transformation problem. This problem, formalized through Bayes' theorem, can be solved by the classical maximum a posteriori estimation procedure. Image local characteristics are assumed to follow a Gaussian Markov random field. Under some mild assumptions, simple, iterative and local operations are involved, making parallel 'relaxation' processing feasible. experimental results are shown on some images, for which good subsampling estimates are obtained.     

On elliptical multilevel models

Multilevel models have been widely applied to analyze data sets which present some hierarchical structure. In this paper we propose a generalization of the normal multilevel models, named elliptical multilevel models. This proposal suggests the use of distributions in the elliptical class, thus involving all symmetric continuous distributions, including the normal distribution as a particular case. Elliptical distributions may have lighter or heavier tails than the normal ones. In the case of normal error models with the presence of outlying observations, heavy-tailed error models may be applied to accommodate such observations. In particular, we discuss some aspects of the elliptical multilevel models, such as maximum likelihood estimation and residual analysis to assess features related to the fitting and the model assumptions. Finally, two motivating examples analyzed under normal multilevel models are reanalyzed under Student-t and power exponential multilevel models. Comparisons with the normal multilevel model are performed by using residual analysis.     

Marginal Nested Interactions for Contingency Tables

We introduce a new definition of generalized marginal interactions, called marginal nested interactions, which includes baseline, local, continuation and reverse continuation logits and odds ratios as special cases. The significant aspect of this definition is the inclusion of new types of logits and odds ratios that can handle non-ordinal, ordinal and partially ordered categorical variables in a flexible and appropriate way. It is proved also that the marginal nested interactions define a saturated model of a multi-way contingency table.