Rat Anti-Human TNFRSF17 monoclonal antibody, clone 446115

Gene expression profiling data can be used in toxicology to assess both the level and impact of toxicant exposure, aligned with a vision of 21st century toxicology. Here, we present a whole blood-derived gene signature that can distinguish current smokers from either nonsmokers or former smokers with high specificity and sensitivity. Such a signature that can be measured in a surrogate tissue (whole blood) may help in monitoring smoking exposure as well as discontinuation of exposure when the primarily impacted tissue (e.g., lung) is not readily accessible. The signature consisted of LRRN3, SASH1, PALLD, RGL1, TNFRSF17, CDKN1C, IGJ, RRM2, ID3, SERPING1, and FUCA1. Several members of this signature have been previously described in the context of smoking. The signature translated well across species and could distinguish mice that were exposed to cigarette smoke from ones exposed to air only or had been withdrawn from cigarette smoke exposure. Finally, the small signature of only 11 genes could be converted into a polymerase chain reaction-based assay that could serve as a marker to monitor compliance with a smoking abstinence protocol.

Periodontitis is a chrome inflammatory disease triggered by the host immune response. The aim of this study is to explote the disturbed pathways and genes in periodontitis. Transcriptome data of healthy and diseased gingival tissues and human pathway data were recruited from public available database. Then Gibbs sampling and Markov chain Monte Carlo (MCMC) algorithm were implemented to identify disturbed pathways and key genes. Disturbed pathways and key genes were identified under adjusted posterior value > 0.8. The researchers identified two disturbed pathways (cytokine-cytokine receptor interaction and hematopoietic cell lineage) and two key genes (TNFRSF17 and CXCL6). Gene expression analysis showed that all the disturbed pathways and key genes had increased expression levels in diseased gingival samples compared with healthy samples. The identified pathways and genes may play important role in periodontitis and could be consideied as potential biomarkers for early detection and therapy for periodontitis.