2,856 research outputs found

    Functional characterization and structure-guided mutational analysis of the transsulfuration enzyme cystathionine γ-lyase from toxoplasma gondii

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    Sulfur-containing amino acids play essential roles in many organisms. The protozoan parasite Toxoplasma gondii includes the genes for cystathionine β-synthase and cystathionine γ-lyase (TgCGL), as well as for cysteine synthase, which are crucial enzymes of the transsulfuration and de novo pathways for cysteine biosynthesis, respectively. These enzymes are specifically expressed in the oocyst stage of T. gondii. However, their functionality has not been investigated. Herein, we expressed and characterized the putative CGL from T. gondii. Recombinant TgCGL almost exclusively catalyses the α,γ-hydrolysis of L-cystathionine to form L-cysteine and displays marginal reactivity toward L-cysteine. Structure-guided homology modelling revealed two striking amino acid differences between the human and parasite CGL active-sites (Glu59 and Ser340 in human to Ser77 and Asn360 in toxoplasma). Mutation of Asn360 to Ser demonstrated the importance of this residue in modulating the specificity for the catalysis of α,β-versus α,γ-elimination of L-cystathionine. Replacement of Ser77 by Glu completely abolished activity towards L-cystathionine. Our results suggest that CGL is an important functional enzyme in T. gondii, likely implying that the reverse transsulfuration pathway is operative in the parasite; we also probed the roles of active-site architecture and substrate binding conformations as determinants of reaction specificity in transsulfuration enzymes

    Serum eosinophil cationic protein (S-ECP) in a population with low prevalence of atopy

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    AbstractThe study is a part of the European Community Respiratory Health Survey. A random sample (n=351) of 20–44-year olds and persons of the same age with asthma-like symptoms or current asthma medication according to a postal questionnaire (n=95) were studied. Interview was taken, methacholine challenge was done and ECP, total and specific IgE were measured from serum. The median S-ECP value was 8.0 μg/l in the random sample. The geometric mean of S-ECP was higher in subjects with, than without atopy (10.2. vs 8.9 μg/l, P<0.01) and in subjects with bronchial hyperresponsiveness (BHR) than in subjects without BHR (9.9 vs 8.0 μg/l,P <0.01). The levels correlated weakly to forced expiratory volume in one second (FEV1) (r=0.13, P<0.01) and were not independently correlated with respiratory symptoms, asthma or FEV1 after adjusting for BHR, IgE, sensitisation and smoking. Our results indicate that the level of eosinophil activation is low in a population with a low prevalence of atopy, even when BHR is common

    Cluster approximations for infection dynamics on random networks

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    In this paper, we consider a simple stochastic epidemic model on large regular random graphs and the stochastic process that corresponds to this dynamics in the standard pair approximation. Using the fact that the nodes of a pair are unlikely to share neighbors, we derive the master equation for this process and obtain from the system size expansion the power spectrum of the fluctuations in the quasi-stationary state. We show that whenever the pair approximation deterministic equations give an accurate description of the behavior of the system in the thermodynamic limit, the power spectrum of the fluctuations measured in long simulations is well approximated by the analytical power spectrum. If this assumption breaks down, then the cluster approximation must be carried out beyond the level of pairs. We construct an uncorrelated triplet approximation that captures the behavior of the system in a region of parameter space where the pair approximation fails to give a good quantitative or even qualitative agreement. For these parameter values, the power spectrum of the fluctuations in finite systems can be computed analytically from the master equation of the corresponding stochastic process.Comment: the notation has been changed; Ref. [26] and a new paragraph in Section IV have been adde

    Probabilistic Analysis of Facility Location on Random Shortest Path Metrics

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    The facility location problem is an NP-hard optimization problem. Therefore, approximation algorithms are often used to solve large instances. Such algorithms often perform much better than worst-case analysis suggests. Therefore, probabilistic analysis is a widely used tool to analyze such algorithms. Most research on probabilistic analysis of NP-hard optimization problems involving metric spaces, such as the facility location problem, has been focused on Euclidean instances, and also instances with independent (random) edge lengths, which are non-metric, have been researched. We would like to extend this knowledge to other, more general, metrics. We investigate the facility location problem using random shortest path metrics. We analyze some probabilistic properties for a simple greedy heuristic which gives a solution to the facility location problem: opening the κ\kappa cheapest facilities (with κ\kappa only depending on the facility opening costs). If the facility opening costs are such that κ\kappa is not too large, then we show that this heuristic is asymptotically optimal. On the other hand, for large values of κ\kappa, the analysis becomes more difficult, and we provide a closed-form expression as upper bound for the expected approximation ratio. In the special case where all facility opening costs are equal this closed-form expression reduces to O(ln(n)4)O(\sqrt[4]{\ln(n)}) or O(1)O(1) or even 1+o(1)1+o(1) if the opening costs are sufficiently small.Comment: A preliminary version accepted to CiE 201

    Critical behaviour of combinatorial search algorithms, and the unitary-propagation universality class

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    The probability P(alpha, N) that search algorithms for random Satisfiability problems successfully find a solution is studied as a function of the ratio alpha of constraints per variable and the number N of variables. P is shown to be finite if alpha lies below an algorithm--dependent threshold alpha\_A, and exponentially small in N above. The critical behaviour is universal for all algorithms based on the widely-used unitary propagation rule: P[ (1 + epsilon) alpha\_A, N] ~ exp[-N^(1/6) Phi(epsilon N^(1/3)) ]. Exponents are related to the critical behaviour of random graphs, and the scaling function Phi is exactly calculated through a mapping onto a diffusion-and-death problem.Comment: 7 pages; 3 figure

    Dynamic scaling regimes of collective decision making

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    We investigate a social system of agents faced with a binary choice. We assume there is a correct, or beneficial, outcome of this choice. Furthermore, we assume agents are influenced by others in making their decision, and that the agents can obtain information that may guide them towards making a correct decision. The dynamic model we propose is of nonequilibrium type, converging to a final decision. We run it on random graphs and scale-free networks. On random graphs, we find two distinct regions in terms of the "finalizing time" -- the time until all agents have finalized their decisions. On scale-free networks on the other hand, there does not seem to be any such distinct scaling regions

    Percolation with Multiple Giant Clusters

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    We study the evolution of percolation with freezing. Specifically, we consider cluster formation via two competing processes: irreversible aggregation and freezing. We find that when the freezing rate exceeds a certain threshold, the percolation transition is suppressed. Below this threshold, the system undergoes a series of percolation transitions with multiple giant clusters ("gels") formed. Giant clusters are not self-averaging as their total number and their sizes fluctuate from realization to realization. The size distribution F_k, of frozen clusters of size k, has a universal tail, F_k ~ k^{-3}. We propose freezing as a practical mechanism for controlling the gel size.Comment: 4 pages, 3 figure

    Magnetic properties of the low-dimensional spin-1/2 magnet \alpha-Cu_2As_2O_7

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    In this work we study the interplay between the crystal structure and magnetism of the pyroarsenate \alpha-Cu_2As_2O_7 by means of magnetization, heat capacity, electron spin resonance and nuclear magnetic resonance measurements as well as density functional theory (DFT) calculations and quantum Monte Carlo (QMC) simulations. The data reveal that the magnetic Cu-O chains in the crystal structure represent a realization of a quasi-one dimensional (1D) coupled alternating spin-1/2 Heisenberg chain model with relevant pathways through non-magnetic AsO_4 tetrahedra. Owing to residual 3D interactions antiferromagnetic long range ordering at T_N\simeq10K takes place. Application of external magnetic field B along the magnetically easy axis induces the transition to a spin-flop phase at B_{SF}~1.7T (2K). The experimental data suggest that substantial quantum spin fluctuations take place at low magnetic fields in the ordered state. DFT calculations confirm the quasi-one-dimensional nature of the spin lattice, with the leading coupling J_1 within the structural dimers. QMC fits to the magnetic susceptibility evaluate J_1=164K, the weaker intrachain coupling J'_1/J_1 = 0.55, and the effective interchain coupling J_{ic1}/J_1 = 0.20.Comment: Accepted for publication in Physical Review

    Almost all trees are almost graceful

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    The Graceful Tree Conjecture of Rosa from 1967 asserts that the vertices of each tree T of order n can be injectively labeled by using the numbers {1,2,…,n} in such a way that the absolute differences induced on the edges are pairwise distinct. We prove the following relaxation of the conjecture for each γ>0 and for all n>n 0(γ). Suppose that (i) the maximum degree of T is bounded by (Formula presented.)), and (ii) the vertex labels are chosen from the set {1,2,…,⌈(1+γ)n⌉}. Then there is an injective labeling of V(T) such that the absolute differences on the edges are pairwise distinct. In particular, asymptotically almost all trees on n vertices admit such a labeling. The proof proceeds by showing that a certain very natural randomized algorithm produces a desired labeling with high probability
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