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Creators/Authors contains: "Alexander, Brandon"

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  1. Securines and securamines are cytotoxic alkaloids that contain reactive alkene and heterocyclic residues embedded in skeletons comprising four to six oxidized rings. This structural complexity imparts a rich chemistry to the isolates but has impeded synthetic access to the structures in the nearly three decades since their isolation. We present a flexible route to eight isolates that exemplify the three skeletal classes of metabolites. The route proceeds by the modular assembly of the advanced azides38and49(13 steps, 6 to 10% yield), sequential oxidative photocyclizations, and late-stage functional group manipulations. With this approach, the targets were obtained in 17 to 19 steps, 12 to 13 purifications, and 0.5 to 3.5% overall yield. The structure of an advanced intermediate was elucidated by microcrystal electron diffraction (MicroED) analysis. The route will support structure-function and target identification studies of the securamines. 
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  2. null (Ed.)
    We study a simplified model of gene regulatory network evolution in which links (regulatory interactions) are added via various selection rules that are based on the structural and dynamical features of the network nodes (genes). Similar to well-studied models of ‘explosive’ percolation, in our approach, links are selectively added so as to delay the transition to large-scale damage propagation, i.e. to make the network robust to small perturbations of gene states. We find that when selection depends only on structure, evolved networks are resistant to widespread damage propagation, even without knowledge of individual gene propensities for becoming ‘damaged’. We also observe that networks evolved to avoid damage propagation tend towards disassortativity (i.e. directed links preferentially connect high degree ‘source’ genes to low degree ‘target’ genes and vice versa). We compare our simulations to reconstructed gene regulatory networks for several different species, with genes and links added over evolutionary time, and we find a similar bias towards disassortativity in the reconstructed networks. 
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