EzArray: A web-based highly automated Affymetrix expression array data management and analysis system

<p>Abstract</p> <p>Background</p> <p>Though microarray experiments are very popular in life science research, managing and analyzing microarray data are still challenging tasks for many biologists. Most microarray programs require users to have sophisticated knowledge of mathematics, statistics and computer skills for usage. With accumulating microarray data deposited in public databases, easy-to-use programs to re-analyze previously published microarray data are in high demand.</p> <p>Results</p> <p>EzArray is a web-based Affymetrix expression array data management and analysis system for researchers who need to organize microarray data efficiently and get data analyzed instantly. EzArray organizes microarray data into projects that can be analyzed online with predefined or custom procedures. EzArray performs data preprocessing and detection of differentially expressed genes with statistical methods. All analysis procedures are optimized and highly automated so that even novice users with limited pre-knowledge of microarray data analysis can complete initial analysis quickly. Since all input files, analysis parameters, and executed scripts can be downloaded, EzArray provides maximum reproducibility for each analysis. In addition, EzArray integrates with Gene Expression Omnibus (GEO) and allows instantaneous re-analysis of published array data.</p> <p>Conclusion</p> <p>EzArray is a novel Affymetrix expression array data analysis and sharing system. EzArray provides easy-to-use tools for re-analyzing published microarray data and will help both novice and experienced users perform initial analysis of their microarray data from the location of data storage. We believe EzArray will be a useful system for facilities with microarray services and laboratories with multiple members involved in microarray data analysis. EzArray is freely available from <url>http://www.ezarray.com/</url>.</p

EzArray: A web-based highly automated Affymetrix expression array data management and analysis system-0

O analyze previously published data. The sample information is automatically populated in the project based on the subset information stored in GEO GDS records. (B) Selecting samples to start new Express Analysis. While in most cases, default analysis methods and parameters can be used directly due to our built-in logics, experienced users have options to select methods and enter specific analysis parameters. Once the analysis is started, a pop-up window will appear showing currently running jobs. On the pop-up window, users can stop running jobs, remove failed jobs, or review finished jobs. In addition, users do not have to wait for results; instead, they can bookmark the page and come back later to review the results. (C) Example execution results from a run of Express Analysis with data shown in (B). The resulting files, including executed scripts and execution logs, are classified, listed, hyper-linked, and compressed in one file for easy downloading.<p><b>Copyright information:</b></p><p>Taken from "EzArray: A web-based highly automated Affymetrix expression array data management and analysis system"</p><p>http://www.biomedcentral.com/1471-2105/9/46</p><p>BMC Bioinformatics 2008;9():46-46.</p><p>Published online 24 Jan 2008</p><p>PMCID:PMC2265266.</p><p></p

2-Deoxy-D-glucose ameliorates inflammation and fibrosis in a silicosis mouse model by inhibiting hypoxia-inducible factor-1α in alveolar macrophages

Inhaling silica causes the occupational illness silicosis, which mostly results in the gradual fibrosis of lung tissue. Previous research has demonstrated that hypoxia-inducible factor-1α (HIF-1α) and glycolysis-related genes are up-regulated in silicosis. The role of 2-deoxy-D-glucose (2-DG) as an inhibitor of glycolysis in silicosis mouse models and its molecular mechanisms remain unclear. Therefore, we used 2-DG to observe its effect on pulmonary inflammation and fibrosis in a silicosis mouse model. Furthermore, in vitro cell experiments were conducted to explore the specific mechanisms of HIF-1α. Our study found that 2-DG down-regulated HIF-1α levels in alveolar macrophages induced by silica exposure and reduced the interleukin-1β (IL-1β) level in pulmonary inflammation. Additionally, 2-DG reduced silica-induced pulmonary fibrosis. From these findings, we hypothesize that 2-DG reduced glucose transporter 1 (GLUT1) expression by inhibiting glycolysis, which inhibits the expression of HIF-1α and ultimately reduces transcription of the inflammatory cytokine, IL-1β, thus alleviating lung damage. Therefore, we elucidated the important regulatory role of HIF-1α in an experimental silicosis model and the potential defense mechanisms of 2-DG. These results provide a possible effective strategy for 2-DG in the treatment of silicosis

Quitting cigarettes completely or switching to smokeless tobacco: do US data replicate the Swedish results?

BACKGROUND: Swedish male smokers are more likely than female smokers to switch to smokeless tobacco(snus) and males' smoking cessation rate is higher than that of females. These results have fuelled international debate over promoting smokeless tobacco for harm reduction. This study examines whether similar results emerge in the United States, one of few other western countries where smokeless tobacco has long been widely available. METHODS: US DATA SOURCE: national sample in Tobacco Use Supplement to Current Population Survey, 2002, with 1-year follow-up in 2003. Analyses included adult self-respondents in this longitudinal sample (n = 15,056). Population-weighted rates of quitting smoking and switching to smokeless tobacco were computed for the 1-year period. RESULTS: Among US men, few current smokers switched to smokeless tobacco (0.3% in 12 months). Few formersmokers turned to smokeless tobacco (1.7%). Switching between cigarettes and smokeless tobacco, infrequent among current tobacco users (&lt;4%), was more often from smokeless to smoking. Men quit smokeless tobacco at three times the rate of quitting cigarettes (38.8% vs 11.6%, p&lt;0.001). Overall, US men have no advantage over women in quitting smoking (11.7% vs 12.4%, p = 0.65), even though men are far likelier to use smokeless tobacco. CONCLUSION: The Swedish results are not replicated in the United States. Both male and female US smokersappear to have higher quit rates for smoking than have their Swedish counterparts, despite greater use of smokelesstobacco in Sweden. Promoting smokeless tobacco for harm reduction in countries with ongoing tobacco control programmes may not result in any positive population effect on smoking cessation