A generative model for inorganic materials design.

The design of functional materials with desired properties is essential in driving technological advances in areas such as energy storage, catalysis and carbon capture. Generative models accelerate materials design by directly generating new materials given desired property constraints, but current methods have a low success rate in proposing stable crystals or can satisfy only a limited set of property constraints. Here we present MatterGen, a model that generates stable, diverse inorganic materials across the periodic table and can further be fine-tuned to steer the generation towards a broad range of property constraints.

A real-world data analysis of electronic health records to investigate the associations of predominant negative symptoms with healthcare resource utilisation, costs and treatment patterns among patients with schizophrenia.

Objectives: Negative symptoms in schizophrenia are associated with significant illness burden. We sought to investigate clinical outcomes for patients with schizophrenia who present with predominant negative symptoms (PNS) vs without PNS.

Design: Retrospective analysis of electronic health record (EHR) data.

Formin Binding Protein 1 (FNBP1) regulates non-canonical Wnt signaling and vertebrate gastrulation.

The Formin protein Daam1 is required for Wnt-induced cytoskeletal changes during gastrulation, though how it accomplishes this remains unresolved. Here we report the characterization of Formin Binding Protein 1 (FNBP1) as a binding partner of Daam1. The interaction of Daam1 with FNBP1 and its domains required for this interaction were delineated.

Insomnia Polygenic Component on Attention Deficit-Hyperactivity Disorder: Exploring this Association Using Genomic Data from Brazilian Families.

 Insomnia is highly prevalent among individuals with Attention-Deficit/Hyperactivity Disorder (ADHD). However, the biological mechanisms shared between both conditions is still elusive. We aimed to investigate whether insomnia's genomic component is able to predict ADHD in childhood and adolescence.

Real-world predictors of relapse in patients with schizophrenia and schizoaffective disorder in a large health system.

Schizophrenia is often characterized by recurring relapses, which are associated with a substantial clinical and economic burden. Early identification of individuals at the highest risk for relapse in real-world treatment settings could help improve outcomes and reduce healthcare costs. Prior work has identified a few consistent predictors of relapse in schizophrenia, however, studies to date have been limited to insurance claims data or small patient populations.