No abstract

The NF-kB pathway is key to epithelial immune defense and has been implicated in secretion of antimicrobial peptides, release of cytokines/chemokines to mobilize immune effector cells, and activation of adaptive immunity. The expression of many inflammatory genes following infection involves the remodeling of the chromatin structure. We reported here that histone deacetylases (HDACs) and NF-kB signaling coordinate expression of CX3CL1 in epithelial cells following Cryptosporidium parvum infection. Upregulation of CX3CL1 was detected in cultured human biliary epithelial cells following infection. Expression of miR-424 and miR-503 was downregulated, and was involved in the induction of CX3CL1 in infected cells. C. parvum infection suppressed transcription of the mir-424-503 gene in a NF-kB- and HDAC-dependent manner. Increased promoter recruitment of NF-kB p50 and HDACs, and decreased promoter H3 acetylation associated with the mir-424-503 gene were observed in infected cells. Upregulation of CX3CL1 in biliary epithelial cells and increased infiltration of CX3CR1+ cells were detected during C. parvum infection in vivo. Induction of CX3CL1 and downregulation of miR-424 and miR-503 were also detected in epithelial cells in response to LPS stimulation. The above results indicate that HDACs and NF-kB signaling coordinate epithelial expression of CX3CL1 to promote mucosal antimicrobial defense through suppression of the mir-424-503 gene.

No abstract

Despite considerable evidence that vagal neural efferent pathways between brainstem and pancreatic islets may alter the secretion of insulin, afferent pathways which might affect this system have received little attention. In the present work we have examined the effects on plasma insulin concentration of several treatments designed to alter the neural activity of the hepatic vagus nerve, a major afferent pathway between the liver and the medulla. The hepatic vagus nerve was acutely sectioned or stimulated electrically in separate experiments in rats. In a third experiment, glucose or 3-O-methylglucose was given ip to stimulate or inhibit, respectively, the hypothetical hepatic glucoreceptors. The effects of these treatments were assessed by measuring arterial or portal plasma insulin concentrations. Anesthesia and its possible secondary inhibitory effects on insulin secretion were avoided by a spinal sectioning of the rats in the cervical region, before experimentation. Acute section of the hepatic vagus nerve between the liver and the main anterior vagal trunk caused an increase in both arterial and portal plasma insulin concentrations. Stimulation of the central end of the nerve suppressed the concentration of the hormone in both the arterial and portal plasma relative to sham-stimulated controls. Section of the celiac vagal branches to the pancreas abolished these changes. Intraperitoneal glucose enhanced arterial insulin more in sham-vagotomized than in hepatic-vagotomized rats. After 3-O-methylglucose was given ip, the response was the opposite: insulin rose more in the arterial plasma of the hepatic-vagotomized animals than in those sham vagotomized. These results suggest that the hepatic vagus nerve plays a role in the regulation of insulin secretion. They are consistent with the hypothesis that afferent fibers in this nerve exert a tonic inhibition on the brainstem centers of an efferent vagal pancreatic neuroendocrine system.

Most real networks are too large or they are not available for real time analysis. Therefore, in practice, decisions are made based on partial information about the ground truth network. It is of great interest to have metrics to determine if an inferred network (the partial information network) is similar to the ground truth. In this paper we develop a test for similarity between the inferred and the true network. Our research utilizes a network visualization tool, which systematically discovers a network, producing a sequence of snapshots of the network. We introduce and test our metric on the consecutive snapshots of a network, and against the ground truth.To test the scalability of our metric we use a random matrix theory approach while discovering Erdös-Rényi graphs. This scaling analysis allows us to make predictions about the performance of the discovery process.