Cerebral microbleeds and cognitive decline in a hemodialysis patient: Case report and review of literature

Cerebral microbleeds (CMBs) are small hemosiderin deposits indicative of prior cerebral microscopic hemorrhage and previously thought to be clinically silent. Recent population‐based cross‐sectional studies and prospective longitudinal cohort studies have revealed association between CMB and cognitive dysfunction. In the general population, CMBs are associated with age, hypertension, and cerebral amyloid angiopathy. In the chronic kidney disease (CKD) population, diminished estimated glomerular filtration rate has been found to be an independent risk factor for CMB, raising the possibility that a uremic milieu may predispose to microbleeds. In the end‐stage renal disease (ESRD) population on hemodialysis, the incidence of microbleeds is significantly higher compared with a control group without history of CKD or stroke. We present an ESRD patient on chronic hemodialysis with a history of gradual cognitive decline and progressive CMBs. Through this case and literature review, we illustrate the need to develop detection and prediction models to treat this frequent development in ESRD patients.     

Application of boundary element method to 3-D problems of coupled thermoelasticity

This paper deals with a new boundary element method for analysis of the quasistatic problems in coupled thermoelasticity. Through some mathematical manipulation of the Navier equation in elasticity, the heat conduction equation is transformed into a simpler form, similar to the uncoupled-type equation with the modified thermal conductivity which shows the coupling effects. This procedure enables us to treat the coupled thermoelastic problems as an uncoupled one, A few examples are computed by the proposed BEM, and the results obtained are compared with the analytical ones available in the literature, whereby the accuracy and versatility of the proposed method are demonstrated.     

Direct adaptive fuzzy control with membership function tuning

In this paper, a direct self‐structured adaptive fuzzy control is introduced for the class of nonlinear systems with unknown dynamic models. Control is accomplished by an adaptive fuzzy system with a fixed number of rules and adaptive membership functions. The reference signal and state errors are used to tune the membership functions and update them instantaneously. The Lyapunov synthesis method is also used to guarantee the stability of the closed loop system. The proposed control scheme is applied to an inverted pendulum and a magnetic levitation system, and its effectiveness is shown via simulation. Copyright © 2011 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society     

Roles of Sexual Objectification Experiences and Internalization of Standards of Beauty in Eating Disorder Symptomatology: A Test and Extension of Objectification Theory.

This study extends the literature on eating disorder symptomatology by testing, based on extant literature on objectification theory (B. L. Fredrickson & T. Roberts, 1997) and the role of sociocultural standards of beauty (e.g., L. J. Heinberg, J. K. Thompson, & S. Stormer, 1995), a model that examines (a) links of reported sexual objectification experiences to eating disorder-related variables and (b) the mediating roles of body surveillance, body shame, and internalization of sociocultural standards of beauty. Consistent with hypotheses, with a sample of 221 young women, support was found for a model in which (a) internalization of sociocultural standards of beauty mediated the links of sexual objectification experiences to body surveillance, body shame, and eating disorder symptoms, (b) body surveillance was an additional mediator of the link of reported sexual objectification experiences to body shame, and (c) body shame mediated the links of internalization and body surveillance to disordered eating. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Identification of Candidate mRNA Isoforms for Prostate Cancer-Risk SNPs Utilizing Iso-eQTL and sQTL Methods

Single nucleotide polymorphisms (SNPs) impacting the alternative splicing (AS) process (sQTLs) or isoform expression (iso-eQTL) are implicated as important cancer regulatory elements. To find the sQTL and iso-eQTL, we retrieved prostate cancer (PrCa) tissue RNA-seq and genotype data originating from 385 PrCa European patients from The Cancer Genome Atlas. We conducted RNA-seq analysis with isoform-based and splice event-based approaches. The MatrixEQTL was used to identify PrCa-associated sQTLs and iso-eQTLs. The overlap between sQTL and iso-eQTL with GWAS loci and those that are differentially expressed between cancer and normal tissue were identified. The cis-acting associations (FDR < 0.05) for PrCa-risk SNPs identified 42, 123, and 90 PrCa-associated cassette exons, intron retention, and mRNA isoforms belonging to 25, 95, and 83 genes, respectively; while assessment of trans-acting association (FDR < 0.05) yielded 59, 65, and 196 PrCa-associated cassette exons, intron retention and mRNA isoforms belonging to 35, 55, and 181 genes, respectively. The results suggest that functional PrCa-associated SNPs can play a role in PrCa genesis by making an important contribution to the dysregulation of AS and, consequently, impacting the expression of the mRNA isoforms.     

Prediction of heavy oil viscosity using a radial basis function neural network

Heavy oil and extra heavy oil resources comprise about 75% of petroleum resources. The most important characteristic of heavy oils is their viscosity. Consequently, to extract and prepare these kinds of crude oil for use, great emphasis should be put on viscosity. The present study highlights the application of intelligent model named radial basis function (RBF) network optimized by genetic algorithm for estimation of diluted heavy oil viscosity in presence on kerosene. The input parameters of model were temperature and mass fraction of kerosene. The output of model was viscosity of heavy oil. Genetic algorithm was utilized to optimize the tuning parameters of RBF model. The outcomes of this study showed that the proposed model is accurate in estimation of target data.