Modeled structure of a G-protein-coupled receptor:The cholecystokinin-1 receptor

The Cholecystokinin-1 receptor (CCK1R) mediates actions of CCK in areas of the central nervous system and of the gut. It is a potential target to treat a number of diseases. As for all G-protein-coupled receptors, docking of ligands into modeled CCK1R binding site should greatly help to understand intrinsic mechanisms of activation. Here, we describe the procedure we used to progressively build a structural model for the CCK1R, to integrated, and on the basis of site-directed mutagenesis data on its binding site. Reliability of the CCK1R model was confirmed by interaction networks that involved conserved and functionally crucial motifs in G-protein-coupled receptors, such as Glu/Asp-Arg-Tyr and Asn-Pro-Xaa-Xaa-Tyr motifs. In addition, the 3-D structure of CCK1R-bound CCK resembled that determined by NMR in a lipid environment. The derived computational model was also used for revealing binding modes of several nonpeptide ligands and for rationalizing ligand structure-activity relationships known from experiments. Our findings indeed support that our "validated CCK1R model" could be used to study the intrinsic mechanism of CCK1R activation and design new ligands.

Organizational structure and the periphery of the gene regulatory network in B-cell lymphoma

Background:
The physical periphery of a biological cell is mainly described by signaling pathways which are triggered by transmembrane proteins and receptors that are sentinels to control the whole gene regulatory network of a cell. However, our current knowledge about the gene regulatory mechanisms that are governed by extracellular signals is severely limited.Results: The purpose of this paper is three fold. First, we infer a gene regulatory network from a large-scale B-cell lymphoma expression data set using the C3NET algorithm. Second, we provide a functional and structural analysis of the largest connected component of this network, revealing that this network component corresponds to the peripheral region of a cell. Third, we analyze the hierarchical organization of network components of the whole inferred B-cell gene regulatory network by introducing a new approach which exploits the variability within the data as well as the inferential characteristics of C3NET. As a result, we find a functional bisection of the network corresponding to different cellular components.

Conclusions:
Overall, our study allows to highlight the peripheral gene regulatory network of B-cells and shows that it is centered around hub transmembrane proteins located at the physical periphery of the cell. In addition, we identify a variety of novel pathological transmembrane proteins such as ion channel complexes and signaling receptors in B-cell lymphoma. © 2012 Simoes et al.; licensee BioMed Central Ltd.

Structure and interactions of ultracold Yb ions and Rb atoms

In order to study ultracold charge-transfer processes in hybrid atom-ion traps, we have mapped out the potential-energy curves and molecular parameters for several low-lying states of the Rb, Yb+ system. We employ both a multireference configuration interaction and a full configuration interaction (FCI) approach. Turning points, crossing points, potential minima, and spectroscopic molecular constants are obtained for the lowest five molecular states. Long-range parameters, including the dispersion coefficients, are estimated from our ab initio data. The separated-atom ionization potentials and atomic polarizability of the ytterbium atom (ad=128.4 atomic units) are in good agreement with experiment and previous calculations. We present some dynamical calculations for (adiabatic) scattering lengths for the two lowest (Yb, Rb+) channels that were carried out in our work. However, we find that the pseudopotential approximation is rather limited in validity and only applies to nK temperatures. The adiabatic scattering lengths for both the triplet and singlet channels indicate that both are large and negative in the FCI approximation.

Hierarchical Bayesian models in ecology: Reconstructing species interaction networks from non-homogeneous species abundance data

The relationships among organisms and their surroundings can be of immense complexity. To describe and understand an ecosystem as a tangled bank, multiple ways of interaction and their effects have to be considered, such as predation, competition, mutualism and facilitation. Understanding the resulting interaction networks is a challenge in changing environments, e.g. to predict knock-on effects of invasive species and to understand how climate change impacts biodiversity. The elucidation of complex ecological systems with their interactions will benefit enormously from the development of new machine learning tools that aim to infer the structure of interaction networks from field data. In the present study, we propose a novel Bayesian regression and multiple changepoint model (BRAM) for reconstructing species interaction networks from observed species distributions. The model has been devised to allow robust inference in the presence of spatial autocorrelation and distributional heterogeneity. We have evaluated the model on simulated data that combines a trophic niche model with a stochastic population model on a 2-dimensional lattice, and we have compared the performance of our model with L1-penalized sparse regression (LASSO) and non-linear Bayesian networks with the BDe scoring scheme. In addition, we have applied our method to plant ground coverage data from the western shore of the Outer Hebrides with the objective to infer the ecological interactions. (C) 2012 Elsevier B.V. All rights reserved.

Quantitative structure-toxicity relationships for chlorophenols to bioluminescent lux-marked bacteria using atom-based semi-empirical molecular-orbital descriptors

Literature data on the toxicity of chlorophenols for three luminescent bacteria (Vibrio fischeri, and the lux-marked Pseudomonas fluorescens 10586s pUCD607 and Burkholderia spp. RASC c2 (Tn4431)) have been analyzed in relation to a set of computed molecular physico-chemical properties. The quantitative structure-toxicity relationships of the compounds in each species showed marked differences when based upon semi-empirical molecular-orbital molecular and atom based properties. For mono-, di- and tri-chlorophenols multiple linear regression analysis of V. fischeri toxicity showed a good correlation with the solvent accessible surface area and the charge on the oxygen atom. This correlation successfully predicted the toxicity of the heavily chlorinated phenols, suggesting in V. fischeri only one overall mechanism is present for all chlorophenols. Good correlations were also found for RASC c2 with molecular properties, such as the surface area and the nucleophilic super-delocalizability of the oxygen. In contrast the best QSTR for P. fluorescens contained the 2nd order connectivity index and ELUMO suggesting a different, more reactive mechanism. Cross-species correlations were examined, and between V. fischeri and RASC c2 the inclusion of the minimum value of the nucleophilic susceptibility on the ring carbons produced good results. Poorer correlations were found with P. fluorescens highlighting the relative similarity of V. fischeri and RASC c2, in contrast to that of P. fluorescens.

Phylogeny versus body size as determinants of food web structure

Food webs are the complex networks of trophic interactions that stoke the metabolic fires of life. To understand what structures these interactions in natural communities, ecologists have developed simple models to capture their main architectural features. However, apparently realistic food webs can be generated by models invoking either predator-prey body-size hierarchies or evolutionary constraints as structuring mechanisms. As a result, this approach has not conclusively revealed which factors are the most important. Here we cut to the heart of this debate by directly comparing the influence of phylogeny and body size on food web architecture. Using data from 13 food webs compiled by direct observation, we confirm the importance of both factors. Nevertheless, phylogeny dominates in most networks. Moreover, path analysis reveals that the size-independent direct effect of phylogeny on trophic structure typically outweighs the indirect effect that could be captured by considering body size alone. Furthermore, the phylogenetic signal is asymmetric: closely related species overlap in their set of consumers far more than in their set of resources. This is at odds with several food web models, which take only the view-point of consumers when assigning interactions. The echo of evolutionary history clearly resonates through current food webs, with implications for our theoretical models and conservation priorities.

Use of data dependence graphs in the design of bit-level systolic arrays

The use of bit-level systolic array circuits as building blocks in the construction of larger word-level systolic systems is investigated. It is shown that the overall structure and detailed timing of such systems may be derived quite simply using the dependence graph and cut-set procedure developed by S. Y. Kung (1988). This provides an attractive and intuitive approach to the bit-level design of many VLSI signal processing components. The technique can be applied to ripple-through and partly pipelined circuits as well as fully systolic designs. It therefore provides a means of examining the relative tradeoff between levels of pipelining, chip area, power consumption, and throughput rate within a given VLSI design.

Design and test of a bit parallel 2nd order IIR filter structure

Test procedures for a pipelined bit-parallel IIR filter chip which maximally exploit its regularity are described. It is shown that small modifications to the basic architecture result in significant reductions in the number of test patterns required to test such chips. The methods used allow 100% fault coverage to be achieved using less than 1000 test vectors for a chip which has 12 bit data and coefficients.

Mapping patterns of multiple deprivation using self-organising maps: An application to EU-SILC data for Ireland

The development of conceptual frameworks for the analysis of social exclusion has somewhat out-stripped related methodological developments. This paper seeks to contribute to filling this gap through the application of self-organising maps (SOMs) to the analysis of a detailed set of material deprivation indicators relating to the Irish case. The SOM approach allows us to offer a differentiated and interpretable picture of the structure of multiple deprivation in contemporary Ireland. Employing this approach, we identify 16 clusters characterised by distinct profiles across 42 deprivation indicators. Exploratory analyses demonstrate that, controlling for equivalised household income, SOM cluster membership adds substantially to our ability to predict subjective economic stress. Moreover, in comparison with an analogous latent class approach, the SOM analysis offers considerable additional discriminatory power in relation to individuals' experience of their economic circumstances. The results suggest that the SOM approach could prove a valuable addition to a 'methodological platform' for analysing the shape and form of social exclusion. (c) 2009 Elsevier Inc. All rights reserved.

Structure of the methanol synthesis catalyst determined by in situ HERFD XAS and EXAFS

A Cu/ZnO/Al2O3 commercial catalyst for methanol synthesis from syngas was investigated under operational conditions. HERFD XAS and EXAFS data were recorded under different reaction gas mixtures, temperatures, and pressures. Activation of the catalyst precursor occurred via a Cu+ intermediate. The active catalyst predominantly consists of metallic Cu and ZnO. Methanol production only starts when all accessible Cu is reduced. The structure of the active catalyst did not change with temperature or pressure even though the methanol yield changed strongly. Formation of a carbon-containing layer on top of the catalyst surface was detected by TPD, which was correlated with a several-hour induction period in the methanol production after the catalyst reduction.

Crystal structure and magnetic properties of the new phase Mn3IrSi

A new phase in the ternary Ir-Mn-Si system has been synthesised. From powder neutron diffraction data the crystal structure was determined to be of the AlAu4 type and to be described in the cubic space group P2(1)3 with the unit cell a = 6.4973(3) Angstrom. Susceptibility measurements using a SQUID-magnetometer showed a transition typical of anti ferromagnetism, with T-N = 210 K. Low temperature antiferromagnetic order is confirmed by extra peaks in neutron diffractograms recorded at 10 and 80 K. (C) 2004 Elsevier B.V. All rights reserved.

Crystal and magnetic structure of Mn3IrSi

A new ternary Ir-Mn-Si phase with stoichiometry Mn₃IrSi has been synthesized and found to crystallize in the cubic AlAu₄-type structure, space group P2₁3 with Z=4, which is an ordered form of the beta-Mn structure. The unit cell dimension was determined by x-ray powder diffraction to a=6.4973(3) Angstrom. In addition to the crystal structure, we have determined the magnetic structure and properties using superconducting quantum interference device magnetometry and Rietveld refinements of neutron powder diffraction data. A complex noncollinear magnetic structure is found, with magnetic moments of 2.97(4)u(B) at 10 K only on the Mn atoms. The crystal structure consists of a triangular network built up by Mn atoms, on which the moments are rotated 120degrees around the triangle axes. The magnetic unit cell is the same as the crystallographic and carries no net magnetic moment. The Neel temperature was determined to be 210 K. A first-principles study, based on density functional theory in a general noncollinear formulation, reproduces the experimental results with good agreement. The observed magnetic structure is argued to be the result of frustration of antiferromagnetic couplings by the triangular geometry.

The Temporal Focus Scale:Factor structure and association with alcohol use in a sample of Northern Irish school children

The Temporal Focus Scale (TFS) is a 12-item self-report measure of cognitive engagement with the temporal domains of past, present and future. Developed in college student samples, a three-factor structure with adequate reliability and validity was documented in a series of independent studies. We tested the factor structure of the scale in a sample of Northern Irish adolescents and found that our data supported a three factor structure, although there were problems with item 10. Because time perspective measures have been found to relate differentially to various health behaviours, we tested the relations between scores on the TFS and self-reported alcohol use. Results showed that scores on the TFS were not consistent statistical predictors of drinking category in a logistic regression. Results are discussed in terms of scale development, future scale use and the assessment of health-compromising behaviours such as adolescent alcohol consumption. © 2012 The Foundation for Professionals in Services for Adolescents.

Direct, positive feedbacks produce instability in models of interrelationships among soil structure, plants and arbuscular mycorrhizal fungi

Current conceptual models of reciprocal interactions linking soil structure, plants and arbuscular mycorrhizal fungi emphasise positive feedbacks among the components of the system. However, dynamical systems with high dimensionality and several positive feedbacks (i.e. mutualism) are prone to instability. Further, organisms such as arbuscular mycorrhizal fungi (AMF) are obligate biotrophs of plants and are considered major biological agents in soil aggregate stabilization. With these considerations in mind, we developed dynamical models of soil ecosystems that reflect the main features of current conceptual models and empirical data, especially positive feedbacks and linear interactions among plants, AMF and the component of soil structure dependent on aggregates. We found that systems become increasingly unstable the more positive effects with Type I functional response (i.e., the growth rate of a mutualist is modified by the density of its partner through linear proportionality) are added to the model, to the point that increasing the realism of models by adding linear effects produces the most unstable systems. The present theoretical analysis thus offers a framework for modelling and suggests new directions for experimental studies on the interrelationship between soil structure, plants and AMF. Non-linearity in functional responses, spatial and temporal heterogeneity, and indirect effects can be invoked on a theoretical basis and experimentally tested in laboratory and field experiments in order to account for and buffer the local instability of the simplest of current scenarios. This first model presented here may generate interest in more explicitly representing the role of biota in soil physical structure, a phenomenon that is typically viewed in a more process- and management-focused context. (C) 2011 Elsevier Ltd. All rights reserved.

Are power laws that estimate fractal dimension a good descriptor of soil structure and its link to soil biological properties?

The study of interrelationships between soil structure and its functional properties is complicated by the fact that the quantitative description of soil structure is challenging. Soil scientists have tackled this challenge by taking advantage of approaches such as fractal geometry, which describes soil architectural complexity through a scaling exponent (D) relating mass and numbers of particles/aggregates to particle/aggregate size. Typically, soil biologists use empirical indices such as mean weight diameters (MWD) and percent of water stable aggregates (WSA), or the entire size distribution, and they have successfully related these indices to key soil features such as C and N dynamics and biological promoters of soil structure. Here, we focused on D, WSA and MWD and we tested whether: D estimated by the exponent of the power law of number-size distributions is a good and consistent correlate of MWD and WSA; D carries information that differs from MWD and WSA; the fraction of variation in D that is uncorrelated with MWD and WSA is related to soil chemical and biological properties that are thought to establish interdependence with soil structure (e.g., organic C, N, arbuscular mycorrhizal fungi). We analysed observational data from a broad scale field study and results from a greenhouse experiment where arbuscular mycorrhizal fungi (AMF) and collembola altered soil structure. We were able to develop empirical models that account for a highly significant and large portion of the correlation observed between WSA and MWD but we did not uncover the mechanisms that underlie this correlation. We conclude that most of the covariance between D and soil biotic (AMF, plant roots) and abiotic (C. N) properties can be accounted for by WSA and MWD. This result implies that the ecological effects of the fragmentation properties described by D and generally discussed under the framework of fractal models can be interpreted under the intuitive perspective of simpler indices and we suggest that the biotic components mostly impacted the largest size fractions, which dominate MWD, WSA and the scaling exponent ruling number-size distributions. (C) 2010 Elsevier Ltd. All rights reserved.