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Molecular signatures of obstructive sleep apnea in adults : A review and perspective
(2009-04-01) Arnardottir, Erna S.; Mackiewicz, Miroslaw; Gislason, Thorarinn; Teff, Karen L.; Pack, Allan I.; Department of Engineering
The consequences of obstructive sleep apnea (OSA) are largely mediated by chronic intermittent hypoxia and sleep fragmentation. The primary molecular domains affected are sympathetic activity, oxidative stress and infammation. Other affected domains include adipokines, adhesion molecules and molecules that respond to endoplasmic reticulum stress. Changes in molecular domains affected by OSA, assessed in blood and/or urine, can provide a molecular signature for OSA that could potentially be used diagnostically and to predict who is likely to develop different OSA-related comorbidities. High-throughput discovery strategies such as microarrays, assessing changes in gene expression in circulating blood cells, have the potential to fnd new candidates and pathways thereby expanding the molecular signatures for OSA. More research is needed to fully understand the pathophysiological signifcance of these molecular signatures and their relationship with OSA comorbidities. Many OSA subjects are obese, and obesity is an independent risk factor for many comorbidities associated with OSA. Moreover, obesity affects the same molecular pathways as OSA. Thus, a challenge to establishing a molecular signature for OSA is to separate the effects of OSA from obesity. We propose that the optimal strategy is to evaluate the temporal changes in relevant molecular pathways during sleep and, in particular, the alterations from before to after sleep when assessed in blood and/or urine. Such changes will be at least partly a consequence of chronic intermittent hypoxia and sleep fragmentation that occurs during sleep.
Verk
Bayesian testing of many hypotheses × many genes : A study of sleep apnea
(2009-03) Jensen, Shane T.; Erkan, Ibrahim; Arnardottir, Erna S.; Small, Dylan S.; Department of Engineering
Substantial statistical research has recently been devoted to the analysis of large-scale microarray experiments which provide a measure of the simultaneous expression of thousands of genes in a particular condition. A typical goal is the comparison of gene expression between two conditions (e.g., diseased vs. nondiseased) to detect genes which show differential expression. Classical hypothesis testing procedures have been applied to this problem and more recent work has employed sophisticated models that allow for the sharing of information across genes. However, many recent gene expression studies have an experimental design with several conditions that requires an even more involved hypothesis testing approach. In this paper, we use a hierarchical Bayesian model to address the situation where there are many hypotheses that must be simultaneously tested for each gene. In addition to having many hypotheses within each gene, our analysis also addresses the more typical multiple comparison issue of testing many genes simultaneously. We illustrate our approach with an application to a study of genes involved in obstructive sleep apnea in humans.
Verk
Kæfisvefn veldur hjarta- og æðasjúkdómum - segir doktorsnemi í líffræöi
(2009) Arnardóttir, Erna Sif; Verkfræðideild
Verk
Distributed and high-performance multimedia : Introduction
(2007) Kosh, Harald; Amsaleg, Laurent; Pauwels, Eric; Jónsson, Björn Þór; Department of Computer Science
Verk
Performance and overhead of semantic cache management
(2006) Jónsson, Björn Þór; Arinbjarnar, María; Þórsson, Bjarnsteinn; Franklin, Michael J.; Srivastava, Divesh; Department of Computer Science
The emergence of query-based online data services and e-commerce applications has prompted much recent research on data caching. This article studies semantic caching, a caching architecture for such applications, that caches the results of selection queries. The primary contribution of this article is to revisit the performance and overhead of semantic caching using a modern database server and modern hardware. Initially, the performance study focuses on simple workloads and demonstrates several benefits of semantic caching, including low overhead, insensitivity to the physical layout of the database, reduced network traffic, and the ability to answer some queries without contacting the server. With moderately complex workloads, careful coding of remainder queries is required to maintain efficient query processing at the server. Using very complex workloads, we demonstrate that semantic caching works well in a range of applications, especially in network-constrained environments.

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