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OBJECTIVEThis study investigated the relationship between circulating soluble receptor for advanced glycation end products (sRAGE) and parameters of bone health in patients with Charcot neuroarthropathy (CNA).RESEARCH DESIGN AND METHODSEighty men (aged 55.3 ± 9.0 years), including 30 healthy control subjects, 30 type 2 diabetic patients without Charcot, and 20 type 2 diabetic patients with stage 2 (nonacute) CNA, underwent evaluations of peripheral and autonomic neuropathy, nerve conduction, markers of bone turnover, bone mineral density, and bone stiffness of the calcaneus.RESULTSCNA patients had worse peripheral and autonomic neuropathy and a lower bone stiffness index than diabetic or control individuals (77.1, 103.3, and 105.1, respectively; P < 0.05), but no difference in bone mineral density (P > 0.05). CNA subjects also had lower sRAGE levels than control (162 vs. 1,140 pg/mL; P < 0.01) and diabetic (162 vs. 522 pg/mL; P < 0.05) subjects, and higher circulating osteocalcin levels.CONCLUSIONSCNA patients had significantly lower circulating sRAGE, with an accompanying increase in serum markers of bone turnover, and reduced bone stiffness in the calcaneus not accompanied by reductions in bone mineral density. These data suggest a failure of RAGE defense mechanisms against oxidative stress in diabetes. Future studies should determine if medications that increase sRAGE activity could be useful in mitigating progression to CNA.

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One of the great challenges of modern science is to faithfully model, and understand, matter at a wide range of scales. Starting with atoms, the vastness of the space of possible configurations poses a formidable challenge to any simulation of complex atomic and molecular systems. We introduce a computational method to reduce the complexity of atomic configuration space by systematically recognising hierarchical levels of atomic structure, and identifying the individual components. Given a list of atomic coordinates, a network is generated based on the distances between the atoms. Using the technique of modularity optimisation, the network is decomposed into modules. This procedure can be performed at different resolution levels, leading to a decomposition of the system at different scales, from which hierarchical structure can be identified. By considering the amount of information required to represent a given modular decomposition we can furthermore find the most succinct descriptions of a given atomic ensemble. Our straightforward, automatic and general approach is applied to complex crystal structures. We show that modular decomposition of these structures considerably simplifies configuration space, which in turn can be used in discovery of novel crystal structures, and opens up a pathway towards accelerated molecular dynamics of complex atomic ensembles. The power of this approach is demonstrated by the identification of a possible allotrope of boron containing 56 atoms in the primitive unit cell, which we uncover using an accelerated structure search, based on a modular decomposition of a known dense phase of boron, γ-B 28 .

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