ObjectiveTo investigate the molecular pathogenesis of pulmonary fibrosis induced by bleomycin in a murine model,and provide novel insights for clinical diagnosis and treatment. MethodsFrom Gene Expression Omnibus,we downloaded microarray data extracted from experiments of bleomycin induced pulmonary fibrosis in wild-type mice. With BRB-Array Tools,differentially expressed genes at different time points during disease development were screened,selected and analyzed by DAVID software. ResultsBRB array analysis identified 45101 differentially expressed genes. After induction by bleomycin on 7th day,1164 genes and 735 genes were significantly up-regulated and down-regulated (P<0.05,fold change>2),respectively. On 14th day,731 genes and 390 genes were significantly up-regulated and down-regulated (P<0.05,fold change>2),respectively. DAVID analysis revealed that the up-regulated genes were significantly enriched in cell cycle,p53 signaling and chemokine signaling pathway,damaging reaction and collagen metabolism gene sets. While the down-regulated genes were enriched in the drug metabolism pathway gene set. ConclusionsBioinformatics methodologies are able to efficiently analyze microarray data and extract its underlying information,provide novel insights for major molecular events and shift of cell signaling pathway during pulmonary fibrosis progression,and furthermore,finding molecular markers for early diagnosis and therapeutic targets.
ObjectiveTo comprehensively collect quality assessment tools of systematic review/meta-analysis (SR/MA) of randomized controlled trials (RCTs), and compare the differences of numbers and contents of items, in order to provide references for optimizing and using these quality assessment tools. MethodsWe searched PubMed and EMbase databases up to December 31th, 2013 for quality assessment tools of SR/MA of RCTs. EndNote X3 software was used for screening literature and Excel 2010 software was used for data extraction. A descriptive analysis was performed. ResultsA total of 61 studies including 32 quality assessment tools were included. Among them, 30 tools were for methodological quality and 2 tools for reporting quality. These tools were developed by different medical universities or colleges, research institutes, national health institutes, and some famous epidemiologists and methodologists from 1984 to 2007. Among the 32 tools, 4 tools were scales, while 28 were checklists. The numbers of items of these tools ranged from 5 to 101, among them, 9 tools had more than 20 items. ConclusionThere are many quality assessment tools for SR/MA, but none of them is generally acknowledged. The quality, contents of items, and applicability of these tools are different, and some of them are too long to use. In practice and decision-making, most of the tools have the problems of low relevance and applicability. How to regularly use these tools to guide the research, practice and decision-making of SR/MA is still needed to be further researched.