Imagine logging into your cryptocurrency exchange platform one morning only to find the website down, your funds gone, and no one to answer your questions. This nightmare has been a harsh reality for thousands of traders, with nearly 500 cryptocurrency exchanges having already failed. A new study from the University of Vaasa, Finland, sheds light on the risk factors in cryptocurrency exchanges and how to predict them. In his study, published in the valued Journal of International Financial Markets, Institutions & Money, Assistant Professor Niranjan Sapkota analyses data from 845 cryptocurrency exchanges. He identifies identifies several key indicators including transparency, centralisation, territorial access, fee structures, coin listings, referral schemes, etc., offering valuable insights into mitigating risks in this evolving market.

A new study, led by USC Mark and Mary Stevens Neuroimaging and Informatics Institute (Stevens INI), will explore structural alterations in the brains of people with bipolar disorder (BD), a chronic mental illness with one of the highest rates of attempted suicide — and for which no biological tools currently exist to guide diagnosis or treatment. The goal is to transform researchers’ understanding of the disease in the hopes of developing more effective treatments. Christopher R.K. Ching, PhD, assistant professor of research neurology at the Stevens INI, part of the Keck School of Medicine of USC, will lead a global network of psychiatric researchers in collaboration with Matthew Kempton, PhD, of King’s College London. The NIH-funded project supports efforts by the Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Consortium’s Bipolar Disorder Working Group (ENIGMA-BD), which Ching chairs. The team will use a large-scale analysis approach called voxel-based morphometry (VBM), which allows scientists to map subtle structural alterations across the entire brain. Unlike other neuroimaging methods that tend to average features across larger predefined brain regions, this technique enables precise, fine-resolution mapping of the emotion and reward processing centers affected in BD and other regions like the cerebellum often overlooked in prior studies.