Your browser doesn't support javascript.
loading
Show: 20 | 50 | 100
Results 1 - 1 de 1
Filter
Add filters








Language
Year range
1.
Biol. Res ; 49: 1-9, 2016. ilus, graf, tab
Article in English | LILACS | ID: biblio-950852

ABSTRACT

BACKGROUND: Acute respiratory distress syndrome (ARDS) is a potentially devastating form of acute inflammatory lung injury as well as a major cause of acute respiratory failure. Although researchers have made significant progresses in elucidating the pathophysiology of this complex syndrome over the years, the absence of a universal detail disease mechanism up until now has led to a series of practical problems for a definitive treatment. This study aimed to predict some genes or pathways associated with sepsis-related ARDS based on a public microarray dataset and to further explore the molecular mechanism of ARDS. RESULTS: A total of 122 up-regulated DEGs and 91 down-regulated differentially expressed genes (DEGs) were obtained. The up- and down-regulated DEGs were mainly involved in functions like mitotic cell cycle and pathway like cell cycle. Protein-protein interaction network of ARDS analysis revealed 20 hub genes including cyclin B1 (CCNB1), cyclin B2 (CCNB2) and topoisomerase II alpha (TOP2A). A total of seven transcription factors including forkhead box protein M1 (FOXM1) and 30 target genes were revealed in the transcription factor-target gene regulation network. Furthermore, co-cited genes including CCNB2-CCNB1 were revealed in literature mining for the relations ARDS related genes. CONCLUSIONS: Pathways like mitotic cell cycle were closed related with the development of ARDS. Genes including CCNB1, CCNB2 and TOP2A, as well as transcription factors like FOXM1 might be used as the novel gene therapy targets for sepsis related ARDS


Subject(s)
Humans , Respiration Disorders/genetics , Sepsis/complications , Sepsis/genetics , Genetic Association Studies , Transcriptome , Transcription Factors , Down-Regulation , Cell Cycle/genetics , Up-Regulation , Gene Targeting , Gene Expression Profiling , Databases, Genetic , Protein Interaction Maps
SELECTION OF CITATIONS
SEARCH DETAIL