People with chronic schizophrenia die on average 10-15 years sooner than the general population, mostly due to physical comorbidity. While sociodemographic, chronic lifestyle and iatrogenic factors are important contributors to this comorbidity, a growing body of research is beginning to suggest that early signs of cardiometabolic dysfunction may be present from the onset of psychosis in some young adults, and may even be detectable before the onset of psychosis. Given that primary prevention is the best means to prevent the onset of more chronic and severe cardiometabolic phenotypes such as CVD, there is clear need to be able to identify young adults with psychosis who are most at risk of future adverse cardiometabolic outcomes, such that the most intensive interventions can be directed in an informed way to attenuate the risk or even prevent those adverse outcomes from occurring.In this talk, Ben will first outline some recent advances in our understanding of the association between cardiometabolic and schizophrenia spectrum disorders. He will then introduce the field of cardiometabolic risk prediction, and highlight how existing tools developed for older general population adults are unlikely to be suitable for young people with psychosis. Finally, he will discuss the current state of play and the future of the Psychosis Metabolic Risk Calculator (PsyMetRiC), a novel clinically useful cardiometabolic risk prediction algorithm tailored for young people with psychosis, which has been developed and externally validated using data from three psychosis early intervention services in the UK.

The last two decades have seen a rise in online projects such as Wikipedia or OpenStreetMap in which people collaborate to create a common product. Contributors in such projects often work together sequentially. Essentially, the first contributor generates an entry (e.g., a Wikipedia article) independently which is then adjusted in the following by other contributors by adding or correcting information. We refer to this way of working together as sequential collaboration. This process has not yet been studied in the context of judgment and decision making even though research has demonstrated that Wikipedia and OpenStreetMap yield very accurate information. In this talk, I give first insights into the structure of sequential collaboration, how adjusting each other’s judgments can yield more accurate final estimates, which boundary conditions need to be met, and which underlying mechanisms may be responsible for successful collaboration. A preprint is available at https://psyarxiv.com/w4xdk/

Membrane interfaces formed at junctions between cells are often associated with characteristic patterns of membrane protein organization, such as in epithelial tissues and between cells of the immune system. While this organization can be influenced by receptor clustering, lipid domain formation, and cytoskeletal dynamics, this talk will describe how cell surface molecular height can directly contribute to the spatial arrangement of membrane proteins and downstream signaling. Using a new optical method for characterizing molecular height, together with experiments using giant vesicles in vitro systems and live immune cells, we are investigating how cell surface molecular heights can be key contributors to cell-cell communication.