2,374 research outputs found

    Neuronal Transcriptome from C9orf72 Repeat Expanded Human Tissue is Associated with Loss of C9orf72 Function

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    A hexanucleotide G4C2 repeat expansion in C9orf72 is the most common genetic cause of familial and sporadic cases of amyotrophic lateral sclerosis (ALS) and frontotemporal degeneration (FTD). The mutation is associated with a reduction of C9orf72 protein and accumulation of toxic RNA and dipeptide repeat aggregates. The accumulation of toxic RNA has been proposed to sequester RNA binding proteins thereby altering RNA processing, consistent with previous transcriptome studies that have shown that the C9orf72 repeat expansion is linked to abundant splicing alterations and transcriptome changes. Here, we used a subcellular fractionation method and FACS to enrich for neuronal nuclei from C9orf72 repeat expanded post-mortem human ALS/FTD brains, and to remove neuronal nuclei with TDP-43 pathology which are observed in nearly all symptomatic C9orf72 repeat expanded cases. We show that the C9orf72 expansion is associated with relatively mild gene expression changes. Dysregulated genes were enriched for vesicle transport pathways, which is consistent with the known functions of C9orf72 protein. Further analysis suggests that the C9orf72 transcriptome is not driven by toxic RNA but is rather shaped by the depletion of pathologic TDP-43 nuclei and the loss of C9orf72 expression. These findings argue against RNA binding protein sequestration in neurons as a major contributor to C9orf72 mediated toxicity

    Dynamics and Pattern Formation in Large Systems of Spatially-Coupled Oscillators with Finite Response Times

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    We consider systems of many spatially distributed phase oscillators that interact with their neighbors. Each oscillator is allowed to have a different natural frequency, as well as a different response time to the signals it receives from other oscillators in its neighborhood. Using the ansatz of Ott and Antonsen (Ref. \cite{OA1}) and adopting a strategy similar to that employed in the recent work of Laing (Ref. \cite{Laing2}), we reduce the microscopic dynamics of these systems to a macroscopic partial-differential-equation description. Using this macroscopic formulation, we numerically find that finite oscillator response time leads to interesting spatio-temporal dynamical behaviors including propagating fronts, spots, target patterns, chimerae, spiral waves, etc., and we study interactions and evolutionary behaviors of these spatio-temporal patterns

    Reinforcement learning in ophthalmology: potential applications and challenges to implementation

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    Reinforcement learning is a subtype of machine learning in which a virtual agent, functioning within a set of predefined rules, aims to maximise a specified outcome or reward. This agent can consider multiple variables and many parallel actions at once to optimise its reward, thereby solving complex, sequential problems. Clinical decision making requires physicians to optimise patient outcomes within a set practice framework and, thus, presents considerable opportunity for the implementation of reinforcement learning-driven solutions. We provide an overview of reinforcement learning, and focus on potential applications within ophthalmology. We also explore the challenges associated with development and implementation of reinforcement learning solutions and discuss possible approaches to address them
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