Augmented Mixed Models For Clustered Proportion Data.

Often in biomedical research, we deal with continuous (clustered) proportion responses ranging between zero and one quantifying the disease status of the cluster units. Interestingly, the study population might also consist of relatively disease-free as well as highly diseased subjects, contributing to proportion values in the interval [0, 1]. Regression on a variety of parametric densities with support lying in (0, 1), such as beta regression, can assess important covariate effects. However, they are deemed inappropriate due to the presence of zeros and/or ones. To evade this, we introduce a class of general proportion density, and further augment the probabilities of zero and one to this general proportion density, controlling for the clustering. Our approach is Bayesian and presents a computationally convenient framework amenable to available freeware. Bayesian case-deletion influence diagnostics based on q-divergence measures are automatic from the Markov chain Monte Carlo output. The methodology is illustrated using both simulation studies and application to a real dataset from a clinical periodontology study.

Structural Connectivity Of The Default Mode Network And Cognition In Alzheimer׳s Disease.

Disconnectivity between the Default Mode Network (DMN) nodes can cause clinical symptoms and cognitive deficits in Alzheimer׳s disease (AD). We aimed to examine the structural connectivity between DMN nodes, to verify the extent in which white matter disconnection affects cognitive performance. MRI data of 76 subjects (25 mild AD, 21 amnestic Mild Cognitive Impairment subjects and 30 controls) were acquired on a 3.0T scanner. ExploreDTI software (fractional Anisotropy threshold=0.25 and the angular threshold=60°) calculated axial, radial, and mean diffusivities, fractional anisotropy and streamline count. AD patients showed lower fractional anisotropy (P=0.01) and streamline count (P=0.029), and higher radial diffusivity (P=0.014) than controls in the cingulum. After correction for white matter atrophy, only fractional anisotropy and radial diffusivity remained significantly lower in AD compared to controls (P=0.003 and P=0.05). In the parahippocampal bundle, AD patients had lower mean and radial diffusivities (P=0.048 and P=0.013) compared to controls, from which only radial diffusivity survived for white matter adjustment (P=0.05). Regression models revealed that cognitive performance is also accounted for by white matter microstructural values. Structural connectivity within the DMN is important to the execution of high-complexity tasks, probably due to its relevant role in the integration of the network.

Reduced Plasma Angiotensin Ii Levels Are Reversed By Hydroxyurea Treatment In Mice With Sickle Cell Disease.

Sickle cell disease (SCD) pathogenesis leads to recurrent vaso-occlusive and hemolytic processes, causing numerous clinical complications including renal damage. As vasoconstrictive mechanisms may be enhanced in SCD, due to endothelial dysfunction and vasoactive protein production, we aimed to determine whether the expression of proteins of the renin-angiotensin system (RAS) may be altered in an animal model of SCD. Plasma angiotensin II (Ang II) was measured in C57BL/6 (WT) mice and mice with SCD by ELISA, while quantitative PCR was used to compare the expressions of the genes encoding the angiotensin-II-receptors 1 and 2 (AT1R and AT2R) and the angiotensin-converting enzymes (ACE1 and ACE2) in the kidneys, hearts, livers and brains of mice. The effects of hydroxyurea (HU; 50-75mg/kg/day, 4weeks) treatment on these parameters were also determined. Plasma Ang II was significantly diminished in SCD mice, compared with WT mice, in association with decreased AT1R and ACE1 expressions in SCD mice kidneys. Treatment of SCD mice with HU reduced leukocyte and platelet counts and increased plasma Ang II to levels similar to those of WT mice. HU also increased AT1R and ACE2 gene expression in the kidney and heart. Results indicate an imbalanced RAS in an SCD mouse model; HU therapy may be able to restore some RAS parameters in these mice. Further investigations regarding Ang II production and the RAS in human SCD may be warranted, as such changes may reflect or contribute to renal damage and alterations in blood pressure.

Censored Linear Regression Models For Irregularly Observed Longitudinal Data Using The Multivariate-t Distribution.

In acquired immunodeficiency syndrome (AIDS) studies it is quite common to observe viral load measurements collected irregularly over time. Moreover, these measurements can be subjected to some upper and/or lower detection limits depending on the quantification assays. A complication arises when these continuous repeated measures have a heavy-tailed behavior. For such data structures, we propose a robust structure for a censored linear model based on the multivariate Student's t-distribution. To compensate for the autocorrelation existing among irregularly observed measures, a damped exponential correlation structure is employed. An efficient expectation maximization type algorithm is developed for computing the maximum likelihood estimates, obtaining as a by-product the standard errors of the fixed effects and the log-likelihood function. The proposed algorithm uses closed-form expressions at the E-step that rely on formulas for the mean and variance of a truncated multivariate Student's t-distribution. The methodology is illustrated through an application to an Human Immunodeficiency Virus-AIDS (HIV-AIDS) study and several simulation studies.