Specific Binding of the Pathogenic Prion Isoform: Development and Characterization of a Humanized Single-Chain Variable Antibody Fragment

Murine monoclonal antibody V5B2 which specifically recognizes the pathogenic form of the prion protein represents a potentially valuable tool in diagnostics or therapy of prion diseases. As murine antibodies elicit immune response in human, only modified forms can be used for therapeutic applications. We humanized a single-chain V5B2 antibody using variable domain resurfacing approach guided by computer modelling. Design based on sequence alignments and computer modelling resulted in a humanized version bearing 13 mutations compared to initial murine scFv. The humanized scFv was expressed in a dedicated bacterial system and purified by metal-affinity chromatography. Unaltered binding affinity to the original antigen was demonstrated by ELISA and maintained binding specificity was proved by Western blotting and immunohistochemistry. Since monoclonal antibodies against prion protein can antagonize prion propagation, humanized scFv specific for the pathogenic form of the prion protein might become a potential therapeutic reagent

Mining Exceptional Social Behaviour

Essentially, our lives are made of social interactions. These can be recorded through personal gadgets as well as sensors adequately attached to people for research purposes. In particular, such sensors may record real time location of people. This location data can then be used to infer interactions, which may be translated into behavioural patterns. In this paper, we focus on the automatic discovery of exceptional social behaviour from spatio-temporal data. For that, we propose a method for Exceptional Behaviour Discovery (EBD). The proposed method combines Subgroup Discovery and Network Science techniques for finding social behaviour that deviates from the norm. In particular, it transforms movement and demographic data into attributed social interaction networks, and returns descriptive subgroups. We applied the proposed method on two real datasets containing location data from children playing in the school playground. Our results indicate that this is a valid approach which is able to obtain meaningful knowledge from the data.This work has been partially supported by the German Research Foundation (DFG) project “MODUS” (under grant AT 88/4-1). Furthermore, the research leading to these results has received funding (JG) from ESRC grant ES/N006577/1. This work was financed by the project Kids First, project number 68639