| Literature DB >> 24548661 |
David M Maslove1, Hector R Wong2.
Abstract
Sepsis is a complex inflammatory response to infection. Microarray-based gene expression studies of sepsis have illuminated the complex pathogen recognition and inflammatory signaling pathways that characterize sepsis. More recently, gene expression profiling has been used to identify diagnostic and prognostic gene signatures, as well as novel therapeutic targets. Studies in pediatric cohorts suggest that transcriptionally distinct subclasses might account for some of the heterogeneity seen in sepsis. Time series analyses have pointed to rapid and dynamic shifts in transcription patterns associated with various phases of sepsis. These findings highlight current challenges in sepsis knowledge translation, including the need to adapt complex and time-consuming whole-genome methods for use in the intensive care unit environment, where rapid diagnosis and treatment are essential.Entities:
Keywords: bioinformatics; gene expression; genomics; microarrays; sepsis; septic shock
Mesh:
Year: 2014 PMID: 24548661 PMCID: PMC3976710 DOI: 10.1016/j.molmed.2014.01.006
Source DB: PubMed Journal: Trends Mol Med ISSN: 1471-4914 Impact factor: 11.951