[11C]CHDI-626, a PET Tracer Candidate for Imaging Mutant Huntingtin Aggregates with Reduced Binding to AD Pathological Proteins.

The expanded polyglutamine-containing mutant huntingtin (mHTT) protein is implicated in neuronal degeneration of medium spiny neurons in Huntington's disease (HD) for which multiple therapeutic approaches are currently being evaluated to eliminate or reduce mHTT. Development of effective and orthogonal biomarkers will ensure accurate assessment of the safety and efficacy of pharmacologic interventions. We have identified and optimized a class of ligands that bind to oligomerized/aggregated mHTT, which is a hallmark in the HD postmortem brain. These ligands are potentially useful imaging biomarkers for HD therapeutic development in both preclinical and clinical settings. We describe here the optimization of the benzo[4,5]imidazo[1,2-a]pyrimidine series that show selective binding to mHTT aggregates over Aß- and/or tau-aggregates associated with Alzheimer's disease pathology. Compound [11C]-2 was selected as a clinical candidate based on its high free fraction in the brain, specific binding in the HD mouse model, and rapid brain uptake/washout in nonhuman primate positron emission tomography imaging studies.

From EHRs to Linked Data: representing and mining encounter data for clinical expertise evaluation.

Translational science, today, involves multidisciplinary teams of scientists rather than single scientists. Teams facilitate biologically meaningful and clinically consequential breakthroughs. There are a myriad of sources of data about investigators, physicians, research resources, clinical encounters, and expertise to promote team interaction; however, much of this information is not connected and is left siloed. Large amounts of data have been published as Linked Data (LD), but there still remains a significant gap in the representation and connection of research resources and clinical expertise data. The CTSAconnect project addresses the problem of fragmentation and incompatible coding of information by creating a Semantic Framework that facilitates the production and consumption of LD about biomedical research resources, clinical activities, as well as investigator and physician expertise.

Direct2Experts: a pilot national network to demonstrate interoperability among research-networking platforms.

Research-networking tools use data-mining and social networking to enable expertise discovery, matchmaking and collaboration, which are important facets of team science and translational research. Several commercial and academic platforms have been built, and many institutions have deployed these products to help their investigators find local collaborators. Recent studies, though, have shown the growing importance of multiuniversity teams in science. Unfortunately, the lack of a standard data-exchange model and resistance of universities to share information about their faculty have presented barriers to forming an institutionally supported national network. This case report describes an initiative, which, in only 6 months, achieved interoperability among seven major research-networking products at 28 universities by taking an approach that focused on addressing institutional concerns and encouraging their participation. With this necessary groundwork in place, the second phase of this effort can begin, which will expand the network's functionality and focus on the end users.