146 research outputs found

    Cognitive flexibility and performance in children and adolescents with threshold and sub-threshold bipolar disorder

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    Greater understanding of cognitive function in children and adolescents with bipolar disorder (BD) is of critical importance to improve our ability to design targeted treatments to help with real-world impairment, including academic performance. We sought to evaluate cognitive performance among children with either BD type I, II, or β€œnot otherwise specified” (NOS) participating in multi-site Course and Outcome of Bipolar Youth study compared to typically developing controls (TDC) without psycho-pathology. In particular, we sought to test the hypothesis that BD-I and BD-II youths with full threshold episodes of mania or hypomania would have cognitive deficits, including in reversal learning, vs. those BD-NOS participants with sub-threshold episodes and TDCs. N = 175 participants (BD-I = 81, BD-II = 11, BD-NOS = 28, TDC = 55) completed Cambridge Neuropsychological Automated Testing Battery (CANTAB) tasks. A priori analyses of the simple reversal stage of the CANTAB intra-/extra-dimensional shift task showed that aggregated BD-I/II participants required significantly more trials to complete the task than either BD-NOS participants with sub-syndromal manic/hypomanic symptoms or than TDCs. BD participants across sub-types had impairments in sustained attention and information processing for emotionally valenced words. Our results align with prior findings showing that BD-I/II youths with distinct episodes have specific alterations in reversal learning. More broadly, our study suggests that further work is necessary to see the interaction between neurocognitive performance and longitudinal illness course. Additional work is required to identify the neural underpinnings of these differences as targets for potential novel treatments, such as cognitive remediation

    Inferring stabilizing mutations from protein phylogenies : application to influenza hemagglutinin

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    One selection pressure shaping sequence evolution is the requirement that a protein fold with sufficient stability to perform its biological functions. We present a conceptual framework that explains how this requirement causes the probability that a particular amino acid mutation is fixed during evolution to depend on its effect on protein stability. We mathematically formalize this framework to develop a Bayesian approach for inferring the stability effects of individual mutations from homologous protein sequences of known phylogeny. This approach is able to predict published experimentally measured mutational stability effects (ΔΔG values) with an accuracy that exceeds both a state-of-the-art physicochemical modeling program and the sequence-based consensus approach. As a further test, we use our phylogenetic inference approach to predict stabilizing mutations to influenza hemagglutinin. We introduce these mutations into a temperature-sensitive influenza virus with a defect in its hemagglutinin gene and experimentally demonstrate that some of the mutations allow the virus to grow at higher temperatures. Our work therefore describes a powerful new approach for predicting stabilizing mutations that can be successfully applied even to large, complex proteins such as hemagglutinin. This approach also makes a mathematical link between phylogenetics and experimentally measurable protein properties, potentially paving the way for more accurate analyses of molecular evolution
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