Universal Cubic Eigenvalue Repulsion for Random Normal Matrices

Random matrix models consisting of normal matrices, defined by the sole constraint $[N^{\dag},N]=0$, will be explored. It is shown that cubic eigenvalue repulsion in the complex plane is universal with respect to the probability distribution of matrices. The density of eigenvalues, all correlation functions, and level spacing statistics are calculated. Normal matrix models offer more probability distributions amenable to analytical analysis than complex matrix models where only a model wth a Gaussian distribution are solvable. The statistics of numerically generated eigenvalues from gaussian distributed normal matrices are compared to the analytical results obtained and agreement is seen.Comment: 15 pages, 2 eps figures. to appar in Physical Review

Microsecond folding dynamics of the F13W G29A mutant of the B domain of staphylococcal protein A by laser-induced temperature jump

The small size (58 residues) and simple structure of the B domain of staphylococcal protein A (BdpA) have led to this domain being a paradigm for theoretical studies of folding. Experimental studies of the folding of BdpA have been limited by the rapidity of its folding kinetics. We report the folding kinetics of a fluorescent mutant of BdpA (G29A F13W), named F13W*, using nanosecond laser-induced temperature jump experiments. Automation of the apparatus has permitted large data sets to be acquired that provide excellent signal-to-noise ratio over a wide range of experimental conditions. By measuring the temperature and denaturant dependence of equilibrium and kinetic data for F13W*, we show that thermodynamic modeling of multidimensional equilibrium and kinetic surfaces is a robust method that allows reliable extrapolation of rate constants to regions of the folding landscape not directly accessible experimentally. The results reveal that F13W* is the fastest-folding protein of its size studied to date, with a maximum folding rate constant at 0 M guanidinium chloride and 45°C of 249,000 (s-1). Assuming the single-exponential kinetics represent barrier-limited folding, these data limit the value for the preexponential factor for folding of this protein to at least ≈2 x 10(6) s(-1)

Critical statistics for non-Hermitian matrices

We introduce a generalized ensemble of nonhermitian matrices interpolating between the Gaussian Unitary Ensemble, the Ginibre ensemble and the Poisson ensemble. The joint eigenvalue distribution of this model is obtained by means of an extension of the Itzykson-Zuber formula to general complex matrices. Its correlation functions are studied both in the case of weak nonhermiticity and in the case of strong nonhermiticity. In the weak nonhermiticity limit we show that the spectral correlations in the bulk of the spectrum display critical statistics: the asymptotic linear behavior of the number variance is already approached for energy differences of the order of the eigenvalue spacing. To lowest order, its slope does not depend on the degree of nonhermiticity. Close the edge, the spectral correlations are similar to the Hermitian case. In the strong nonhermiticity limit the crossover behavior from the Ginibre ensemble to the Poisson ensemble first appears close to the surface of the spectrum. Our model may be relevant for the description of the spectral correlations of an open disordered system close to an Anderson transition.Comment: 25 pages, 6 figure

An evolutionary strategy with machine learning for learning to rank in information retrieval

Learning to Rank (LTR) is one of the problems in Information Retrieval (IR) that nowadays attracts attention from researchers. The LTR problem refers to ranking the retrieved documents for users in search engines, question answering and product recommendation systems. There is a number of LTR approaches based on machine learning and computational intelligence techniques. Most existing LTR methods have limitations, like being too slow or not being very effective or requiring large computer memory to operate. This paper proposes a LTR method that combines a (1+1)-Evolutionary Strategy with machine learning. Three variants of the method are investigated: ES-Rank, IESR-Rank and IESVMRank. They differ on the mechanism to initialize the chromosome for the evolutionary process. ES-Rank simply sets all genes in the initial chromosome to the same value. IESRRank uses linear regression and IESVM-Rank uses support vector machine for the initialization process. Experimental results from comparing the proposed method to fourteen other approaches from the literature show that IESRRank achieves the overall best performance. Ten problem instances are used here, obtained from four datasets: MSLR-WEB10K, LETOR 3 and LETOR 4. Performance is measured at the top-10 query-document pairs retrieved, using five metrics: Mean Average Precision (MAP), Root Mean Square Error (RMSE), Precision (P@10), Reciprocal Rank (RR@10) and Normalized Discounted Cumulative Gain (NDCG@10). The contribution of this paper is an effective and efficient LTR method combining a listwise evolutionary technique with point-wise and pair-wise machine learning techniques

A spatial approach for the epidemiology of antibiotic use and resistance in community-based studies: the emergence of urban clusters of Escherichia coli quinolone resistance in Sao Paulo, Brasil

Copyright © Kiffer et al; licensee BioMed Central Ltd. 2011 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.Background Population antimicrobial use may influence resistance emergence. Resistance is an ecological phenomenon due to potential transmissibility. We investigated spatial and temporal patterns of ciprofloxacin (CIP) population consumption related to E. coli resistance emergence and dissemination in a major Brazilian city. A total of 4,372 urinary tract infection E. coli cases, with 723 CIP resistant, were identified in 2002 from two outpatient centres. Cases were address geocoded in a digital map. Raw CIP consumption data was transformed into usage density in DDDs by CIP selling points influence zones determination. A stochastic model coupled with a Geographical Information System was applied for relating resistance and usage density and for detecting city areas of high/low resistance risk. Results E. coli CIP resistant cluster emergence was detected and significantly related to usage density at a level of 5 to 9 CIP DDDs. There were clustered hot-spots and a significant global spatial variation in the residual resistance risk after allowing for usage density. Conclusions There were clustered hot-spots and a significant global spatial variation in the residual resistance risk after allowing for usage density. The usage density of 5-9 CIP DDDs per 1,000 inhabitants within the same influence zone was the resistance triggering level. This level led to E. coli resistance clustering, proving that individual resistance emergence and dissemination was affected by antimicrobial population consumption

The Impact of Hydrogen Bonding on Amide 1H Chemical Shift Anisotropy Studied by Cross-Correlated Relaxation and Liquid Crystal NMR Spectroscopy

Site-specific (1)H chemical shift anisotropy (CSA) tensors have been derived for the well-ordered backbone amide moieties in the B3 domain of protein G (GB3). Experimental input data include residual chemical shift anisotropy (RCSA), measured in six mutants that align differently relative to the static magnetic field when dissolved in a liquid crystalline Pf1 suspension, and cross-correlated relaxation rates between the (1)H(N) CSA tensor and either the (1)H-(15)N, the (1)H-(13)C', or the (1)H-(13)C(alpha) dipolar interactions. Analyses with the assumption that the (1)H(N) CSA tensor is symmetric with respect to the peptide plane (three-parameter fit) or without this premise (five-parameter fit) yield very similar results, confirming the robustness of the experimental input data, and that, to a good approximation, one of the principal components orients orthogonal to the peptide plane. (1)H(N) CSA tensors are found to deviate strongly from axial symmetry, with the most shielded tensor component roughly parallel to the N-H vector, and the least shielded component orthogonal to the peptide plane. DFT calculations on pairs of N-methyl acetamide and acetamide in H-bonded geometries taken from the GB3 X-ray structure correlate with experimental data and indicate that H-bonding effects dominate variations in the (1)H(N) CSA. Using experimentally derived (1)H(N) CSA tensors, the optimal relaxation interference effect needed for narrowest (1)H(N) TROSY line widths is found at similar to 1200 MHz

The Molecular Evolution of the p120-Catenin Subfamily and Its Functional Associations

p120-catenin (p120) is the prototypical member of a subclass of armadillo-related proteins that includes δ-catenin/NPRAP, ARVCF, p0071, and the more distantly related plakophilins 1–3. In vertebrates, p120 is essential in regulating surface expression and stability of all classical cadherins, and directly interacts with Kaiso, a BTB/ZF family transcription factor.To clarify functional relationships between these proteins and how they relate to the classical cadherins, we have examined the proteomes of 14 diverse vertebrate and metazoan species. The data reveal a single ancient δ-catenin-like p120 family member present in the earliest metazoans and conserved throughout metazoan evolution. This single p120 family protein is present in all protostomes, and in certain early-branching chordate lineages. Phylogenetic analyses suggest that gene duplication and functional diversification into “p120-like” and “δ-catenin-like” proteins occurred in the urochordate-vertebrate ancestor. Additional gene duplications during early vertebrate evolution gave rise to the seven vertebrate p120 family members. Kaiso family members (i.e., Kaiso, ZBTB38 and ZBTB4) are found only in vertebrates, their origin following that of the p120-like gene lineage and coinciding with the evolution of vertebrate-specific mechanisms of epigenetic gene regulation by CpG island methylation.The p120 protein family evolved from a common δ-catenin-like ancestor present in all metazoans. Through several rounds of gene duplication and diversification, however, p120 evolved in vertebrates into an essential, ubiquitously expressed protein, whereas loss of the more selectively expressed δ-catenin, p0071 and ARVCF are tolerated in most species. Together with phylogenetic studies of the vertebrate cadherins, our data suggest that the p120-like and δ-catenin-like genes co-evolved separately with non-neural (E- and P-cadherin) and neural (N- and R-cadherin) cadherin lineages, respectively. The expansion of p120 relative to δ-catenin during vertebrate evolution may reflect the pivotal and largely disproportionate role of the non-neural cadherins with respect to evolution of the wide range of somatic morphology present in vertebrates today

Fractional deuteration applied to biomolecular solid-state NMR spectroscopy

Solid-state Nuclear Magnetic Resonance can provide detailed insight into structural and dynamical aspects of complex biomolecules. With increasing molecular size, advanced approaches for spectral simplification and the detection of medium to long-range contacts become of critical relevance. We have analyzed the protonation pattern of a membrane-embedded ion channel that was obtained from bacterial expression using protonated precursors and D2O medium. We find an overall reduction of 50% in protein protonation. High levels of deuteration at Hα and Hβ positions reduce spectral congestion in (1H,13C,15N) correlation experiments and generate a transfer profile in longitudinal mixing schemes that can be tuned to specific resonance frequencies. At the same time, residual protons are predominantly found at amino-acid side-chain positions enhancing the prospects for obtaining side-chain resonance assignments and for detecting medium to long-range contacts. Fractional deuteration thus provides a powerful means to aid the structural analysis of complex biomolecules by solid-state NMR

Factors associated with youth gang membership in low and middle-income countries: a systematic review.

Youth gang membership is associated with delinquency, violent crime and trafficking – and gang members are themselves frequently the victims of these offences. Yet youth gangs can also provide a form of social capital, a sense of belonging and purpose to disenfranchised youth. This review identifies the factors associated with young people joining gangs, and the differences between gang-involved and non-gang-involved youth. Understanding these associations is essential to reduce the levels of gang membership and the incidence of related violence