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https://www.selleckchem.com/products/pirtobrutinib-loxo-305.html e used to infer other biologically relevant networks to formulate new biological hypotheses.BACKGROUND High-throughput omics technologies have enabled the comprehensive reconstructions of genome-scale metabolic networks for many organisms. However, only a subset of reactions is active in each cell which differs from tissue to tissue or from patient to patient. Reconstructing a subnetwork of the generic metabolic network from a provided set of context-specific active reactions is a demanding computational task. RESULTS We propose SWIFTCC and SWIFTCORE as effective methods for flux consistency checking and the context-specific reconstruction of genome-scale metabolic networks which consistently outperform the previous approaches. CONCLUSIONS We have derived an approximate greedy algorithm which efficiently scales to increasingly large metabolic networks. SWIFTCORE is freely available for non-commercial use in the GitHub repository at https//mtefagh.github.io/swiftcore/.BACKGROUND AND PURPOSE "Take Charge" is a novel, community-based self-directed rehabilitation intervention which helps a person with stroke take charge of their own recovery. In a previous randomized controlled trial, a single Take Charge session improved independence and health-related quality of life 12 months following stroke in Māori and Pacific New Zealanders. We tested the same intervention in three doses (zero, one, or two sessions) in a larger study and in a broader non-Māori and non-Pacific population with stroke. We aimed to confirm whether the Take Charge intervention improved quality of life at 12 months after stroke in a different population and whether two sessions were more effective than one. METHODS We randomized 400 people within 16 weeks of acute stroke who had been discharged to institution-free community living at seven centers in New Zealand to a single Take Charge session (TC1, n = 132), two Take Charge sessions six

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