Anomalous centrality evolution of two-particle angular correlations from Au-Au collisions at root s(NN)=62 and 200 GeV

We present two-dimensional (2D) two-particle angular correlations measured with the STAR detector on relative pseudorapidity eta and azimuth phi for charged particles from Au-Au collisions at root s(NN) = 62 and 200 GeV with transverse momentum p(t) >= 0.15 GeV/c, vertical bar eta vertical bar <= 1, and 2 pi in azimuth. Observed correlations include a same-side (relative azimuth <pi/2) 2D peak, a closely related away-side azimuth dipole, and an azimuth quadrupole conventionally associated with elliptic flow. The same-side 2D peak and away-side dipole are explained by semihard parton scattering and fragmentation (minijets) in proton-proton and peripheral nucleus-nucleus collisions. Those structures follow N-N binary-collision scaling in Au-Au collisions until midcentrality, where a transition to a qualitatively different centrality trend occurs within one 10% centrality bin. Above the transition point the number of same-side and away-side correlated pairs increases rapidly relative to binary-collision scaling, the eta width of the same-side 2D peak also increases rapidly (eta elongation), and the phi width actually decreases significantly. Those centrality trends are in marked contrast with conventional expectations for jet quenching in a dense medium. The observed centrality trends are compared to perturbative QCD predictions computed in HIJING, which serve as a theoretical baseline, and to the expected trends for semihard parton scattering and fragmentation in a thermalized opaque medium predicted by theoretical calculations and phenomenological models. We are unable to reconcile a semihard parton scattering and fragmentation origin for the observed correlation structure and centrality trends with heavy-ion collision scenarios that invoke rapid parton thermalization. If the collision system turns out to be effectively opaque to few-GeV partons the present observations would be inconsistent with the minijet picture discussed here. DOI: 10.1103/PhysRevC.86.064902

Stoichiometry, structure, and transport in the quasi-one-dimensional metal Li0.9Mo6O17

A correlation between lattice parameters, oxygen composition, and the thermoelectric and Hall coefficients is presented for single-crystal Li0.9Mo6O17, a quasi-one-dimensional (Q1D) metallic compound. The possibility that this compound is a compensated metal is discussed in light of a substantial variability observed in the literature for these transport coefficients.

Cardiovascular risk among health professionals working in pre-hospital care services

The objective of this study was to assess the cardiovascular risk factors among health professionals, particularly hypertension, and stratify them according to the Framingham Risk Score (FRS). The participants were 154 professionals working in pre-hospital care in Sao Paulo, Brazil, and on the Br-116 highway. Values were considered significant for p<0.05. The prevalence of hypertension was 33%, 20.1% were smokers, 47% consumed alcoholic beverages, 64% were sedentary, 66% were obese/overweight and 70% had an altered abdominal circumference. In terms of laboratory values: glucose >= 110mg/dL11%, total cholesterol >= 200mg/dL-36%, LDL-c >= 130mg/dL-33%, HDL-c<60mg/dL89%, triglycerides >= 150mg/dL-30% and C reactive protein >= 0.5mg/dL-16%. The FRS was average in 10.3% and high in 1.3%. In logistic regression analysis, it was verified that hypertension was associated with: HDL-c (odds ratio: 0.257,) and FRS (odds ratio: 23.159). There was strong correlation between hypertension and FRS. Data are noteworthy, as this is a relatively young sample of health professionals.

Structure-semantics interplay in complex networks and its effects on the predictability of similarity in texts

The classification of texts has become a major endeavor with so much electronic material available, for it is an essential task in several applications, including search engines and information retrieval. There are different ways to define similarity for grouping similar texts into clusters, as the concept of similarity may depend on the purpose of the task. For instance, in topic extraction similar texts mean those within the same semantic field, whereas in author recognition stylistic features should be considered. In this study, we introduce ways to classify texts employing concepts of complex networks, which may be able to capture syntactic, semantic and even pragmatic features. The interplay between various metrics of the complex networks is analyzed with three applications, namely identification of machine translation (MT) systems, evaluation of quality of machine translated texts and authorship recognition. We shall show that topological features of the networks representing texts can enhance the ability to identify MT systems in particular cases. For evaluating the quality of MT texts, on the other hand, high correlation was obtained with methods capable of capturing the semantics. This was expected because the golden standards used are themselves based on word co-occurrence. Notwithstanding, the Katz similarity, which involves semantic and structure in the comparison of texts, achieved the highest correlation with the NIST measurement, indicating that in some cases the combination of both approaches can improve the ability to quantify quality in MT. In authorship recognition, again the topological features were relevant in some contexts, though for the books and authors analyzed good results were obtained with semantic features as well. Because hybrid approaches encompassing semantic and topological features have not been extensively used, we believe that the methodology proposed here may be useful to enhance text classification considerably, as it combines well-established strategies. (c) 2012 Elsevier B.V. All rights reserved.

Correlation of soil microbial community responses to contamination with crude oil with and without chromium and copper

Soil microcosms contaminated with crude oil with or without chromium and copper were monitored over a period of 90 days for microbial respiration, biomass, and for dehydrogenase, lipase, acid phosphatase, and arylsulfatase activities. In addition, the community structure was followed by enumerating the total heterotrophic and oil-degrading viable bacteria and by performing a denaturing gradient gel electrophoresis (DGGE) of the PCR amplified 16S rDNA. A significant difference was observed for biochemical activities and microbial community structures between the microcosms comprised of uncontaminated soil, soil contaminated with crude oil and soil contaminated with crude oil and heavy metals. The easily measured soil enzyme activities correlated well with microbial population levels, community structures and rates of respiration (CO2 production). The estimation of microbial responses to soil contamination provides a more thorough understanding of the microbial community function in contaminated soil, in situations where technical and financial resources are limited and may be useful in addressing bioremediation treatability and effectiveness. (C) 2012 Published by Elsevier Ltd.

The structure and resilience of financial market networks

Financial markets can be viewed as a highly complex evolving system that is very sensitive to economic instabilities. The complex organization of the market can be represented in a suitable fashion in terms of complex networks, which can be constructed from stock prices such that each pair of stocks is connected by a weighted edge that encodes the distance between them. In this work, we propose an approach to analyze the topological and dynamic evolution of financial networks based on the stock correlation matrices. An entropy-related measurement is adopted to quantify the robustness of the evolving financial market organization. It is verified that the network topological organization suffers strong variation during financial instabilities and the networks in such periods become less robust. A statistical robust regression model is proposed to quantity the relationship between the network structure and resilience. The obtained coefficients of such model indicate that the average shortest path length is the measurement most related to network resilience coefficient. This result indicates that a collective behavior is observed between stocks during financial crisis. More specifically, stocks tend to synchronize their price evolution, leading to a high correlation between pair of stock prices, which contributes to the increase in distance between them and, consequently, decrease the network resilience. (C) 2012 American Institute of Physics. [doi:10.1063/1.3683467]

STRUCTURE AND DYNAMICS: THE TRANSITION FROM NONEQUILIBRIUM TO EQUILIBRIUM IN INTEGRATE-AND-FIRE DYNAMICS

The transient and equilibrium properties of dynamics unfolding in complex systems can depend critically on specific topological features of the underlying interconnections. In this work, we investigate such a relationship with respect to the integrate-and-fire dynamics emanating from a source node and an extended network model that allows control of the small-world feature as well as the length of the long-range connections. A systematic approach to investigate the local and global correlations between structural and dynamical features of the networks was adopted that involved extensive simulations (one and a half million cases) so as to obtain two-dimensional correlation maps. Smooth, but diverse surfaces of correlation values were obtained in all cases. Regarding the global cases, it has been verified that the onset avalanche time (but not its intensity) can be accurately predicted from the structural features within specific regions of the map (i.e. networks with specific structural properties). The analysis at local level revealed that the dynamical features before the avalanches can also be accurately predicted from structural features. This is not possible for the dynamical features after the avalanches take place. This is so because the overall topology of the network predominates over the local topology around the source at the stationary state.

Ligand- and Structure-Based Drug Design Strategies and PPAR delta/alpha Selectivity

Peroxisome-proliferator-activated receptors are a class of nuclear receptors with three subtypes: a, ? and d. Their main function is regulating gene transcription related to lipid and carbohydrate metabolism. Currently, there are no peroxisome-proliferator-activated receptors d drugs being marketed. In this work, we studied a data set of 70 compounds with a and d activity. Three partial least square models were created, and molecular docking studies were performed to understand the main reasons for peroxisome-proliferator-activated receptors d selectivity. The obtained results showed that some molecular descriptors (log P, hydration energy, steric and polar properties) are related to the main interactions that can direct ligands to a particular peroxisome-proliferator-activated receptors subtype.

Structure- and Ligand-Based Structure-Activity Relationships for a Series of Inhibitors of Aldolase

Aldolase has emerged as a promising molecular target for the treatment of human African trypanosomiasis. Over the last years, due to the increasing number of patients infected with Trypanosoma brucei, there is an urgent need for new drugs to treat this neglected disease. In the present study, two-dimensional fragment-based quantitative-structure activity relationship (QSAR) models were generated for a series of inhibitors of aldolase. Through the application of leave-one-out and leave-many-out cross-validation procedures, significant correlation coefficients were obtained (r(2) = 0.98 and q(2) = 0.77) as an indication of the statistical internal and external consistency of the models. The best model was employed to predict pK(i) values for a series of test set compounds, and the predicted values were in good agreement with the experimental results, showing the power of the model for untested compounds. Moreover, structure-based molecular modeling studies were performed to investigate the binding mode of the inhibitors in the active site of the parasitic target enzyme. The structural and QSAR results provided useful molecular information for the design of new aldolase inhibitors within this structural class.

Structural XANES characterization of Ca0.99Sm0.01TiO3 perovskite and correlation with photoluminescence emission

In this work, CaTiO3:Sm (CT:Sm) were prepared by a soft chemical processing at different annealing temperatures starting with a disordered structure and reaching an ordered one, with the propose to understand the relationship between structural order-disorder and photoluminescence emission. The samples were characterized by titanium K-edge, Titanium L-II and L-III-edge XANES, electron paramagnetic resonance (EPR) and photoluminescence (PL) measurements. XANES results clearly point the presence of local distortion in [TiO6] octahedral clusters until the crystallization was completed. The interactions of the network clusters that form the CT:Sm structures provides favorable structural and electronic conditions for the appearance of PL phenomena. (C) 2012 Published by Elsevier B.V.

Musicians' working memory for tones, words, and pseudowords

Studies investigating factors that influence tone recognition generally use recognition tests, whereas the majority of the studies on verbal material use self-generated responses in the form of serial recall tests. In the present study we intended to investigate whether tonal and verbal materials share the same cognitive mechanisms, by presenting an experimental instrument that evaluates short-term and working memories for tones, using self-generated sung responses that may be compared to verbal tests. This paradigm was designed according to the same structure of the forward and backward digit span tests, but using digits, pseudowords, and tones as stimuli. The profile of amateur singers and professional singers in these tests was compared in forward and backward digit, pseudoword, tone, and contour spans. In addition, an absolute pitch experimental group was included, in order to observe the possible use of verbal labels in tone memorization tasks. In general, we observed that musical schooling has a slight positive influence on the recall of tones, as opposed to verbal material, which is not influenced by musical schooling. Furthermore, the ability to reproduce melodic contours (up and down patterns) is generally higher than the ability to reproduce exact tone sequences. However, backward spans were lower than forward spans for all stimuli (digits, pseudowords, tones, contour). Curiously, backward spans were disproportionately lower for tones than for verbal material-that is, the requirement to recall sequences in backward rather than forward order seems to differentially affect tonal stimuli. This difference does not vary according to musical expertise.

Mutation Spectrum in the Large GTPase Dynamin 2, and Genotype-Phenotype Correlation in Autosomal Dominant Centronuclear Myopathy

Centronuclear myopathy (CNM) is a genetically heterogeneous disorder associated with general skeletal muscle weakness, type I fiber predominance and atrophy, and abnormally centralized nuclei. Autosomal dominant CNM is due to mutations in the large GTPase dynamin 2 (DNM2), a mechanochemical enzyme regulating cytoskeleton and membrane trafficking in cells. To date, 40 families with CNM-related DNM2 mutations have been described, and here we report 60 additional families encompassing a broad genotypic and phenotypic spectrum. In total, 18 different mutations are reported in 100 families and our cohort harbors nine known and four new mutations, including the first splice-site mutation. Genotype-phenotype correlation hypotheses are drawn from the published and new data, and allow an efficient screening strategy for molecular diagnosis. In addition to CNM, dissimilar DNM2 mutations are associated with Charcot-Marie-Tooth (CMT) peripheral neuropathy (CMTD1B and CMT2M), suggesting a tissue-specific impact of the mutations. In this study, we discuss the possible clinical overlap of CNM and CMT, and the biological significance of the respective mutations based on the known functions of dynamin 2 and its protein structure. Defects in membrane trafficking due to DNM2 mutations potentially represent a common pathological mechanism in CNM and CMT. Hum Mutat 33: 949-959, 2012. (C) 2012 Wiley Periodicals, Inc.

Structure-based drug design studies on a series of aldolase inhibitors

Human African trypanosomiasis, also known as sleeping sickness, is a major cause of death in Africa, and for which there are no safe and effective treatments available. The enzyme aldolase from Trypanosoma brucei is an attractive, validated target for drug development. A series of alkyl‑glycolamido and alkyl-monoglycolate derivatives was studied employing a combination of drug design approaches. Three-dimensional quantitative structure-activity relationships (3D QSAR) models were generated using the comparative molecular field analysis (CoMFA). Significant results were obtained for the best QSAR model (r2 = 0.95, non-cross-validated correlation coefficient, and q2 = 0.80, cross-validated correlation coefficient), indicating its predictive ability for untested compounds. The model was then used to predict values of the dependent variables (pKi) of an external test set,the predicted values were in good agreement with the experimental results. The integration of 3D QSAR, molecular docking and molecular dynamics simulations provided further insight into the structural basis for selective inhibition of the target enzyme.