Multimodal Classification of Schizophrenia Patients with MEG and fMRI Data Using Static and Dynamic Connectivity Measures.

Mental disorders like schizophrenia are currently diagnosed by physicians/psychiatrists through clinical assessment and their evaluation of patient's self-reported experiences as the illness emerges. There is great interest in identifying biological markers of prognosis at the onset of illness, rather than relying on the evolution of symptoms across time. Functional network connectivity, which indicates a subject's overall level of "synchronicity" of activity between brain regions, demonstrates promise in providing individual subject predictive power.

Recognition of diverse RNAs by a single protein structural framework.

The coat proteins of different single-strand RNA phages utilize a common structural framework to recognize different RNA targets, making them suitable models for studies of RNA-protein recognition generally, especially for the class of proteins that bind RNA on a beta-sheet surface. Here we show that structurally distinct molecules are capable of satisfying the requirements for binding to Qbeta coat protein. Although the predicted secondary structures of the RNAs differ markedly, we contend that they are approximately equivalent structurally in their complexes with coat protein.