Ghrelin Increases Beta-Catenin Level through Protein Kinase A Activation and Regulates OPG Expression in Rat Primary Osteoblasts.

Ghrelin, by binding growth hormone secretagogue receptor (GHS-R), promotes osteoblast proliferation but the signaling mechanism of GHS-R on these cells remains unclear. Since canonical Wnt/β-catenin pathway is critically associated with bone homeostasis, we investigated its involvement in mediating ghrelin effects in osteoblasts and in osteoblast-osteoclast cross talk. Ghrelin (10(-10)M) significantly increased β-catenin levels in rat osteoblasts (rOB). This stimulatory action on β-catenin involves a specific interaction with GHS-R1a, as it is prevented by the selective GHS-R1a antagonist, D-Lys(3)-GHRP-6 (10(-7)M). The effect of ghrelin on β-catenin involves the phosphorylation and inactivation of GSK-3β via protein kinase A (PKA). Inhibition of PKA activity reduces the facilitatory action of ghrelin on β-catenin stabilization. Ghrelin treatment of rOB significantly increases the expression of osteoprotegerin (OPG), which plays an important role in the regulation of osteoclastogenesis, and this effect is blocked by D-Lys(3)-GHRP-6. Furthermore, ghrelin reduced RANKL/OPG ratio thus contrasting osteoclastogenesis. Accordingly, conditioned media from rOB treated with ghrelin decreased the number of multinucleated TRAcP+ cells as compared with the conditioned media from untreated-control rOB. Our data suggest new roles for ghrelin in modulating bone homeostasis via a specific interaction with GHSR-1a in osteoblasts with subsequent enhancement of both β-catenin levels and OPG expression

Analysis of RWM with a 3D Model of Conducting Structures

Abstract In this paper we present some preliminary results of a coupling between the MHD stability code MARS-F and the three-dimensional eddy currents code CARIDDI, aimed at the analysis of Resistive Wall Modes with 3D conducting structures

Glucagon-like peptide-1 receptor and sarcoglycan delta genetic variants can affect cardiovascular risk in chronic kidney disease patients under hemodialysis

Background Chronic kidney disease (CKD) patients under hemodialysis show a higher risk of cardiovascular (CV) mortality and morbidity than the general population. This study aims to identify genetic markers that could explain the increased CV risk in hemodialysis. Methods A total of 245 CKD patients under hemodialysis were recruited and followed up for 5\u2009years to record CV events. Genetic analysis was performed using single-nucleotide polymorphisms (SNPs) genotyping by Infinium Expanded Multi-Ethnic Genotyping Array (Illumina, San Diego, CA, USA) comparing patients with and without a history of CV events [161 cardiovascular diseases (CVDs) and 84 no CVDs]. The fixation index (Fst) measure was used to identify the most differentiated SNPs, and gene ontology analysis [Protein Analysis THrough Evolutionary Relationships (PANTHER) and Ingenuity Pathway Analysis (IPA)] was applied to define the biological/pathological roles of the associated SNPs. Partitioning tree analysis interrogated the genotype\u2013phenotype relationship between discovered genetic variants and CV phenotypes. Cox regression analysis measured the effect of these SNPs on new CV events during the follow-up (FU). Results Fst analysis identified 3218 SNPs that were significantly different between CVD and no CVD. Gene ontology analysis identified two of these SNPs as involved in cardiovascular disease pathways (Ingenuity Pathway) and heart development (Panther) and belonging to 2 different genes: Glucagon-like peptide-1 receptor (GLP1R) and Sarcoglycan delta (SGCD). The phenotype\u2013genotype analysis found a higher percentage of CVD patients carrying the GLP1R rs10305445 allele A (P\u2009=\u20090.03) and lower percentages of CVD patients carrying the SGCD rs145292439 allele A (P\u2009=\u20090.038). Moreover, SGCD rs145292439 was associated with higher levels of high-density lipoprotein (P\u2009=\u20090.015). Cox analysis confirmed the increased frequency of CV events during the 5-year FU in patients carrying GLP1R rs1035445 allele A but it did not show any significant association with SGCD rs145292439. Conclusions This study identified GLP1R rs10305445 and SCGD rs145292439 as potential genetic markers that may explain the higher risk of CVD in hemodialysis patients