Mouse anti-Rat Kcnip1 monoclonal antibody, clone T66-93

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia. Previous genome-wide association studies had identified single-nucleotide polymorphisms in several genomic regions to be associated with AF. In human genome, copy number variations (CNVs) are known to contribute to disease susceptibility. Using a genome-wide multistage approach to identify AF susceptibility CNVs, we here show a common 4,470-bp diallelic CNV in the first intron of potassium interacting channel 1 gene (KCNIP1) is strongly associated with AF in Taiwanese populations (odds ratio = 2.27 for insertion allele; P = 6.23 x 10(-24)). KCNIP1 insertion is associated with higher KCNIP1 mRNA expression. KCNIP1-encoded protein potassium interacting channel 1 (KCHIP1) is physically associated with potassium Kv channels and modulates atrial transient outward current in cardiac myocytes. Overexpression of KCNIP1 results in inducible AF in zebrafish. In conclusions, a common CNV in KCNIP1 gene is a genetic predictor of AF risk possibly pointing to a functional pathway.

Background: The human body is colonized by a vast number of microbes. Microbiota can benefit many normal life processes, but can also cause many diseases by interfering the regular metabolism and immune system. Recent studies have demonstrated that the microbial community is closely associated with various types of cell carcinoma. The search for key factors, which also refer to cancer causing agents, can provide an important clue in understanding the regulatory mechanism of microbiota in uterine cervix cancer. Results: In this paper, we investigated microbiota composition and gene expression data for 58 squamous and adenosquamous cell carcinoma. A host-microbial covariance network was constructed based on the 16s rRNA and gene expression data of the samples, which consists of 259 abundant microbes and 738 differentially expressed genes (DEGs). To search for risk factors from host-microbial networks, the method of bi-partite betweenness centrality (BpBC) was used to measure the risk of a given node to a certain biological process in hosts. A web-based tool KF-finder was developed, which can efficiently query and visualize the knowledge of microbiota and differentially expressed genes (DEGs) in the network. Conclusions: Our results suggest that prevotellaceade, tissierellaceae and fusobacteriaceae are the most abundant microbes in cervical carcinoma, and the microbial community in cervical cancer is less diverse than that of any other boy sites in health. A set of key risk factors anaerococcus, hydrogenophilaceae, eubacterium, PSMB10, KCNIP1 and KRT13 have been identified, which are thought to be involved in the regulation of viral response, cell cycle and epithelial cell differentiation in cervical cancer. It can be concluded that permanent changes of microbiota composition could be a major force for chromosomal instability, which subsequently enables the effect of key risk factors in cancer. All our results described in this paper can be freely accessed from our website at http://www.nwpu-bioinformatics.com/KFfinder/.