A structural basis for IκB kinase 2 activation via oligomerization-dependent trans auto-phosphorylation.

Activation of the IκB kinase (IKK) is central to NF-κB signaling. However, the precise activation mechanism by which catalytic IKK subunits gain the ability to induce NF-κB transcriptional activity is not well understood. Here we report a 4 Å x-ray crystal structure of human IKK2 (hIKK2) in its catalytically active conformation. The hIKK2 domain architecture closely resembles that of Xenopus IKK2 (xIKK2). However, whereas inactivated xIKK2 displays a closed dimeric structure, hIKK2 dimers adopt open conformations that permit higher order oligomerization within the crystal. Reversible oligomerization of hIKK2 dimers is observed in solution. Mutagenesis confirms that two of the surfaces that mediate oligomerization within the crystal are also critical for the process of hIKK2 activation in cells. We propose that IKK2 dimers transiently associate with one another through these interaction surfaces to promote trans auto-phosphorylation as part of their mechanism of activation. This structure-based model supports recently published structural data that implicate strand exchange as part of a mechanism for IKK2 activation via trans auto-phosphorylation. Moreover, oligomerization through the interfaces identified in this study and subsequent trans auto-phosphorylation account for the rapid amplification of IKK2 phosphorylation observed even in the absence of any upstream kinase

Advanced Stochastic Optimization Modeling of the Water-energy-food Nexus for Robust Energy and Agricultural Development: Coal Mining Industry in Shanxi province, China

In this presentation, we discuss a modeling framework able to carry out an integrated systems analysis of interdependent energy-food-water-environmental systems while accounting for the competition to those systems posed by restricted natural resources under inherent uncertainties and systemic risks. The case study focuses on developments of coal industry in water-scarce regions of China. Coal is the main energy source in China responsible for country’s energy security. However, coal-based industries consume large quantities of water, which exacerbates the problem of water scarcity. The model accounts for water consumption by various coal mining, processing, and conversion technologies, as well as water and land requirements by different crops and management systems. Uncertain water supply and demand require robust solutions that would ensure demand-production balances and other (environmental, social) constraints in all scenarios. The model derives robust interdependent strategic and adaptive decisions using the “public-private partnership” principle. Strategic long-term decisions comprise the choice of coal-related technologies, land allocation, crop portfolio, and management technologies, while adaptive decisions concern trade and water management. Systemic risks and energy-food-water security considerations are characterized by quantile-based indicators arising due to systemic interdependencies among the systems and decisions of various stakeholders and potential adversaries. Robust solutions provide insights into how to develop and coordinate, in a sustainable way, the complex linkages and trade-offs, at spatial and temporal scales, between energy, agriculture, and water sectors, as well as how to manage potential systemic risks inherent to them. The model explores new coherent energy-food-water-environmental policies accounting for local-global interdependencies induced by national-international trade, as well as self-sufficient local solutions

Image-Domain Material Decomposition for Dual-energy CT using Unsupervised Learning with Data-fidelity Loss

Background: Dual-energy CT (DECT) and material decomposition play vital roles in quantitative medical imaging. However, the decomposition process may suffer from significant noise amplification, leading to severely degraded image signal-to-noise ratios (SNRs). While existing iterative algorithms perform noise suppression using different image priors, these heuristic image priors cannot accurately represent the features of the target image manifold. Although deep learning-based decomposition methods have been reported, these methods are in the supervised-learning framework requiring paired data for training, which is not readily available in clinical settings. Purpose: This work aims to develop an unsupervised-learning framework with data-measurement consistency for image-domain material decomposition in DECT

Historical context modifies plant diversity–community productivity relationships in alpine grassland

While most studies yield positive relationships between biodiversity (B) and ecosystem functioning (EF), awareness is growing that BEF relationships can vary with ecological context. The awareness has led to increased efforts to understand how contemporary environmental context modifies BEF relationships, but the role of historical context, and the mechanisms by which it may influence biodiversity effects, remains poorly understood. We examined how historical context alters plant diversity–community productivity relationships via plant species interactions in alpine grassland. We also tested how historical context modifies interactions between plants and arbuscular mycorrhizal (AM) fungi, which can potentially mediate the above processes. We studied biodiversity effects on plant community productivity at two grassland sites with different histories related to grazing intensity—heavy versus light livestock grazing—but similar current management. We assembled experimental communities of identical species composition with plants from each of the two sites in disturbed soil from a contemporary heavily grazed grassland, ranging in species richness from one to two, three and six species. Moreover, we carried out a mycorrhizal hyphae-exclusion experiment to test how plant interactions with AM fungi influence plant responses to historical context. We detected a significantly positive diversity–productivity relationship that was driven by complementarity effects in communities composed of plants from the site without heavy-grazing history, but no such relationship in plant communities composed of plants from the site with heavy-grazing history. Plants from the site with heavy-grazing history had increased competitive ability and increased yields in low-diversity communities but disrupted complementarity effects in high-diversity communities. Moreover, plants of one species from the site with heavy-grazing history benefitted more from AM fungal communities than did plants from the site without such history. Synthesis. Using the same experimental design and species, communities assembled by plants from two sites with different historical contexts showed different plant diversity–community productivity relationships. Our results suggest that historical context can alter plant diversity–community productivity relationships via plant species interactions and potentially plant–soil interactions. Therefore, considering historical contexts of ecological communities is of importance for advancing our understanding of long-term impacts of anthropogenic disturbance on ecosystem functioning

Endothelin-1 receptor blockade prevents renal injury in experimental hypercholesterolemia

Endothelin-1 receptor blockade prevents renal injury in experimental hypercholesterolemia.BackgroundThe potent vasoconstrictor endothelin-1 is involved in regulation of renal function, and is up-regulated in hypercholesterolemia (HC), a risk factor for renal disease that increases oxidative stress and impairs renal hemodynamic responses. However, the involvement of endothelin (ET) in this disease process is yet unknown.MethodsRegional renal hemodynamics and function in vivo were quantified in pigs at baseline and during infusion of acetylcholine using electron beam computed tomography after a 12-week normal diet (N = 6), HC diet (N = 6), and HC diet orally supplemented (4mg/kg/day) with the selective ET receptor-A (ET-A) blocker ABT-627 (HC+ET-A, N = 6). Plasma levels of 8-epi-PGF2-α-isoprostanes, markers of oxidative stress, were measured using enzyme immunoassay, and renal tissue was studied ex vivo using Western blotting, electrophoretic mobility shift assay, and immunohistochemistry.ResultsTotal and low-density lipoprotein (LDL) cholesterol were similarly increased, but isoprostanes were decreased in HC+ET-A compared to HC alone. Basal renal perfusion was similar among the groups, while glomerular filtration rate (GFR) increased in HC+ET-A compared to HC. Stimulated perfusion and GFR were blunted in HC, but normalized in HC+ET-A. Moreover, ET blockade increased expression of endothelial nitric oxide synthase, and decreased endothelial expression of the oxidized-LDL receptor LOX-1, as well as tubular immunoreactivity of inducible nitric oxide synthase, nitrotyrosine, nuclear factor-κB, transforming growth factor-β, and tubulointerstitial and perivascular trichrome staining.ConclusionET-A blockade improves renal hemodynamic and function in HC, and decreases oxidative stress, and renal vascular and tubulointerstitial inflammation and fibrosis. These findings support a role for the endogenous ET system in renal injury in HC and atherosclerosis

Lattice instabilities of cubic NiTi from first principles

The phonon dispersion relation of NiTi in the simple cubic B2 structure is computed using first-principles density-functional perturbation theory with pseudopotentials and a plane-wave basis set. Lattice instabilities are observed to occur across nearly the entire Brillouin zone, excluding three interpenetrating tubes of stability along the (001) directions and small spheres of stability centered at R. The strongest instability is that of the doubly degenerate M5' mode. The atomic displacements of one of the eigenvectors of this mode generate a good approximation to the observed B19' ground-state structure.Comment: 11 pages, 3 figure

Integration of range images in a multi-view stereo system

A novel method for integrating multiple range images in a multi-view stereo imaging system is presented here. Due to self-occlusion an individual range image provides only a partial model of an object surface. Therefore multiple range images from differing viewpoints must be captured and merged to extend the surface area that can be captured. In our approach range images are decomposed into subset patches and then evaluated in a "confidence competition". Redundant patches are removed whilst winning patches are merged to complete a single plausible mesh that represents the acquired object surface