An association between unrecognized gastroesophageal reflux disease and excessive daytime sleepiness in Taiwanese subjects suspected to have liver disease: a pilot study

<p>Abstract</p> <p>Background</p> <p>In traditional Chinese culture, liver disease is believed to underlie excessive daytime sleepiness (EDS). Consequently, Chinese patients with complaints of EDS and physicians who treat them suspect that a liver abnormality is present. If liver disease is ruled out, these patients are often discharged without treatment. Gastroesophageal reflux disease (GERD) is a common disorder also associated with EDS. This pilot study was undertaken to determine the prevalence of GERD among Taiwanese patients with complaints of EDS suspected to be related to liver disease but in whom no evidence for the latter was found.</p> <p>Methods</p> <p>From July 2009 to December 2009, 121 outpatients who presented to or were referred to the Department of Gastroenterology and Hepatology of the Chiayi Gung Memorial Hospital for evaluation of a complaint of EDS thought to be due to liver disease were examined. Demographic data were collected, and physical examinations and liver function tests were performed. Forty-eight patients had liver disease and were excluded. The Chinese Epworth Sleepiness Scale questionnaire (Chinese ESS) and the Chinese Gastroesophageal Reflux Disease Questionnaire (CGERDQ) were then administered to 73 included patients.</p> <p>Results</p> <p>More than half (56.2%) of the included patients were found to suffer from GERD. Patients with symptoms of GERD had higher mean CGERDQ scores than patients without symptoms of the disorder (18.88 ± 5.49 and 5.56 ± 3.57, respectively; <it>P </it>< 0.001). Patients with symptoms of GERD also had higher mean Chinese ESS scores than patients without symptoms (8.80 ± 5.49 and 3.13 ± 3.50, respectively; <it>P </it>< 0.001). Chinese ESS scores indicative of EDS were observed in 48.8% of patients with symptoms of GERD and in 3.1% of those without symptoms (<it>P </it>< 0.001). Differences between the two groups retained their significance after controlling for potential confounders.</p> <p>Conclusions</p> <p>A significant percentage of Taiwanese patients who complained of EDS and were admitted to our Hepatology/Gastroenterology Department due to a suspicion of liver disease actually had symptoms of GERD. Further studies are needed to ascertain whether treatment of GERD will effectively resolve EDS in these patients.</p

Development and Function of CD94-Deficient Natural Killer Cells

The CD94 transmembrane-anchored glycoprotein forms disulfide-bonded heterodimers with the NKG2A subunit to form an inhibitory receptor or with the NKG2C or NKG2E subunits to assemble a receptor complex with activating DAP12 signaling proteins. CD94 receptors expressed on human and mouse NK cells and T cells have been proposed to be important in NK cell tolerance to self, play an important role in NK cell development, and contribute to NK cell-mediated immunity to certain infections including human cytomegalovirus. We generated a gene-targeted CD94-deficient mouse to understand the role of CD94 receptors in NK cell biology. CD94-deficient NK cells develop normally and efficiently kill NK cell-susceptible targets. Lack of these CD94 receptors does not alter control of mouse cytomegalovirus, lymphocytic choriomeningitis virus, vaccinia virus, or Listeria monocytogenes. Thus, the expression of CD94 and its associated NKG2A, NKG2C, and NKG2E subunits is dispensable for NK cell development, education, and many NK cell functions

A Drosophila Model of ALS: Human ALS-Associated Mutation in VAP33A Suggests a Dominant Negative Mechanism

ALS8 is caused by a dominant mutation in an evolutionarily conserved protein, VAPB (vesicle-associated membrane protein (VAMP)-associated membrane protein B)/ALS8). We have established a fly model of ALS8 using the corresponding mutation in Drosophila VAPB (dVAP33A) and examined the effects of this mutation on VAP function using genetic and morphological analyses. By simultaneously assessing the effects of VAPwt and VAPP58S on synaptic morphology and structure, we demonstrate that the phenotypes produced by neuronal expression of VAPP58S resemble VAP loss of function mutants and are opposite those of VAP overexpression, suggesting that VAPP58S may function as a dominant negative. This is brought about by aggregation of VAPP58S and recruitment of wild type VAP into these aggregates. Importantly, we also demonstrate that the ALS8 mutation in dVAP33A interferes with BMP signaling pathways at the neuromuscular junction, identifying a new mechanism underlying pathogenesis of ALS8. Furthermore, we show that mutant dVAP33A can serve as a powerful tool to identify genetic modifiers of VAPB. This new fly model of ALS, with its robust pathological phenotypes, should for the first time allow the power of unbiased screens in Drosophila to be applied to study of motor neuron diseases

Systems Biology by the Rules: Hybrid Intelligent Systems for Pathway Modeling and Discovery

Background: Expert knowledge in journal articles is an important source of data for reconstructing biological pathways and creating new hypotheses. An important need for medical research is to integrate this data with high throughput sources to build useful models that span several scales. Researchers traditionally use mental models of pathways to integrate information and development new hypotheses. Unfortunately, the amount of information is often overwhelming and these are inadequate for predicting the dynamic response of complex pathways. Hierarchical computational models that allow exploration of semi-quantitative dynamics are useful systems biology tools for theoreticians, experimentalists and clinicians and may provide a means for cross-communication. Results: A novel approach for biological pathway modeling based on hybrid intelligent systems or soft computing technologies is presented here. Intelligent hybrid systems, which refers to several related computing methods such as fuzzy logic, neural nets, genetic algorithms, and statistical analysis, has become ubiquitous in engineering applications for complex control system modeling and design. Biological pathways may be considered to be complex control systems, which medicine tries to manipulate to achieve desired results. Thus, hybrid intelligent systems may provide a useful tool for modeling biological system dynamics and computational exploration of new drug targets. A new modeling approach based on these methods is presented in the context of hedgehog regulation of the cell cycle in granule cells. Code and input files can be found at the Bionet website: www.chip.ord/~wbosl/Software/Bionet. Conclusion: This paper presents the algorithmic methods needed for modeling complicated biochemical dynamics using rule-based models to represent expert knowledge in the context of cell cycle regulation and tumor growth. A notable feature of this modeling approach is that it allows biologists to build complex models from their knowledge base without the need to translate that knowledge into mathematical form. Dynamics on several levels, from molecular pathways to tissue growth, are seamlessly integrated. A number of common network motifs are examined and used to build a model of hedgehog regulation of the cell cycle in cerebellar neurons, which is believed to play a key role in the etiology of medulloblastoma, a devastating childhood brain cancer

The alpha-kinase family: an exceptional branch on the protein kinase tree

The alpha-kinase family represents a class of atypical protein kinases that display little sequence similarity to conventional protein kinases. Early studies on myosin heavy chain kinases in Dictyostelium discoideum revealed their unusual propensity to phosphorylate serine and threonine residues in the context of an alpha-helix. Although recent studies show that some members of this family can also phosphorylate residues in non-helical regions, the name alpha-kinase has remained. During evolution, the alpha-kinase domains combined with many different functional subdomains such as von Willebrand factor-like motifs (vWKa) and even cation channels (TRPM6 and TRPM7). As a result, these kinases are implicated in a large variety of cellular processes such as protein translation, Mg2+ homeostasis, intracellular transport, cell migration, adhesion, and proliferation. Here, we review the current state of knowledge on different members of this kinase family and discuss the potential use of alpha-kinases as drug targets in diseases such as cancer

Epidemiology of chronic kidney disease in children

In the past 30 years there have been major improvements in the care of children with chronic kidney disease (CKD). However, most of the available epidemiological data stem from end-stage renal disease (ESRD) registries and information on the earlier stages of pediatric CKD is still limited. The median reported incidence of renal replacement therapy (RRT) in children aged 0–19 years across the world in 2008 was 9 per million of the age-related population (4–18 years). The prevalence of RRT in 2008 ranged from 18 to 100 per million of the age-related population. Congenital disorders, including congenital anomalies of the kidney and urinary tract (CAKUT) and hereditary nephropathies, are responsible for about two thirds of all cases of CKD in developed countries, while acquired causes predominate in developing countries. Children with congenital disorders experience a slower progression of CKD than those with glomerulonephritis, resulting in a lower proportion of CAKUT in the ESRD population compared with less advanced stages of CKD. Most children with ESRD start on dialysis and then receive a transplant. While the survival rate of children with ERSD has improved, it remains about 30 times lower than that of healthy peers. Children now mainly die of cardiovascular causes and infection rather than from renal failure

Computational solutions for omics data

High-throughput experimental technologies are generating increasingly massive and complex genomic data sets. The sheer enormity and heterogeneity of these data threaten to make the arising problems computationally infeasible. Fortunately, powerful algorithmic techniques lead to software that can answer important biomedical questions in practice. In this Review, we sample the algorithmic landscape, focusing on state-of-the-art techniques, the understanding of which will aid the bench biologist in analysing omics data. We spotlight specific examples that have facilitated and enriched analyses of sequence, transcriptomic and network data sets.National Institutes of Health (U.S.) (Grant GM081871