Posters

The characterization of autoimmune disease-specific biomarkers are of primary importance for the development of diagnostic tools and the comprehension of pathogenetic mechanisms leading to autoimmunity. To this aim a protein microarray was employed to analyze serum samples from patients with autoimmune hepatitis (e.g. AIH & PBC) and of healthy as controls. A panel of autoantigens able to discriminate among the groups of patients was identified for potential use as biomarkers.

Analytical identification of metabolites for a drug candidate is usually a time consuming and low-throughput task and is performed only at the later phases of drug development. Therefore the possibility to predict possible sites of human liver microsomal (HLM) metabolism using in silico techniques would be a very attractive feature for any medicinal chemist.

Of all the challenges facing medicinal chemists in general, one of the most significant must be transforming an active molecule into a viable drug. Lead optimization efforts are guided by a combination of factors, such as potency, ease of synthesis, patentability concerns, specific synthetic constrains of the interaction with the target, as well as the lead’s toxicity and ADME properties.

The miREC database integrates public data about miRNAs and their target genes involved in the development of EAC in human, collected from recent literature. In future versions the database will be complemented with information derived by analyzing our in-house data and new published data by other researchers. The miREC database is the first database that focuses on integrating all available information about genes and miRNAs involved in endometrial cancer.

A method is presented to visualize genome-wide information from epigenetic data. It is capable to integrate additional information. Applied to mouse data consisting of H3K4, H3K27, and H3K9 trimethylation for 3 different celltypes, the dynamic behavior and interplay was investigated.

Bactericidal efficacy of engineered sulfur nanoparticles

In this study the aim was to identify a miRNA expression signature that could be used to separate between normal and malignant prostate tissues. Nine miRNAs were found to be differentially expressed and they could be used to separate between the normal and malignant tissues. A cross-validation procedure confirmed the generality of this expression signature, showing an accuracy of 85%.

We present the results of initial work carried out within the OpenToxLink Virtual Organization, applying a Weight-of-Evidence (WoE) approach based on consensus across multiple sources of information for the prediction of adverse effects of a large set of potential antimalarial compounds. The work was carried out as part of the EU FP7 project SYNERGY, evaluating the support of decision dashboards and event-driven collaborative research of software developed within SYNERGY.

This poster introduces the recently enlarged DoCLab research group at Brunel University, London. This large multidisciplinary group brings together electronic, mechanical and computer engineers with molecular biologists, biochemists and clinical collaborators to develop fully integrated, multiplex Point-Of-Care-Tests (POCT) for the self- diagnosis of infectious diseases.