Network Spotlight

Team Training & Development hosted its first Career Workshop recently, and project managers were instrumental in communicating the event to their teams. Teams Cragg, Jakobsson, and Wichmann represented the greatest number of trainees in attendance, so their project managers, Cláudia Mendes, PhD, Laura Castilla-Vallmanya, PhD, and Johnson Agniswamy, PhD, respectively, did an outstanding job connecting their trainees to the new Resource Team and its events!

Collaborative Research Network (CRN) Teams Kordower, Liddle, and Rio each created open-access protocols that were among the top 100 most viewed protocols on protocols.io during the month of August. These protocols include Mouse Perfusions (Team Kordower), Y-Maze Protocol (Team Liddle), and Culture and Transfection of HEK293T Cells (Team Rio).

Members of the Assessment of Motor and Non-Motor PD Symptoms Working Group, Roberta Marongiu, PhD (CRN Team Kaplitt), Thomas Wichmann, MD (CRN Team Wichmann), Alexandra Nelson, MD, PhD (CRN Team Edwards), Per Svennigsson, MD, PhD (CRN Team Kaplitt), Eileen Ruth Torres, PhD (CRN Team Kaplitt), and Jacquelyn Haytayan, BSc (CRN Team Kaplitt), developed guidelines and considerations for the most commonly used rodent behavioral assays of Parkinson’s disease. They also added a collection of suggested protocols for these assays to the ASAP workspace on protocols.io. ASAP applauds the working group’s contribution to reproducibility and standardization of rodent behavior assays in Parkinson’s. 

Members of the Clinical and Immune Working Group, Xiqun Chen, MD, PhD (CRN Team Chen), Anthony Schapira, PhD (CRN Team Schapira), Weiyi Peng, PhD (CRN Team Chen), and Sara Lucas Del Pozo, MD (CRN Team Schapira), developed standardized templates for reporting on metadata associated with participants of a clinical trial and studies that utilize PBMCs. Metadata is important for ensuring data is understandable and reusable to anyone now or in the future. ASAP applauds the working group’s contribution to the standardization and reuse of clinical datasets.