Isolation and characterization of a bacteriocin produced by an isolated Bacillus subtilis LFB112 that exhibits antimicrobial activity against domestic animal pathogens

The emergence of multidrug-resistant pathogens and the restriction on the use antibiotics as growth promoters in feed have drawn attention to the search for possible alternatives. Much interest has been focused on bacteriocins because they exhibit inhibitory activity against pathogens. In this study, an antibacterial substance produced by an isolated Bacillus subtilis strain LFB112 from Chinese herbs, was identified as bacteriocin. It was effective against both Gram-positive and Gram-negative bacteriainvolved in domestic animal diseases, including Escherichia coli, Salmonella pullorum, Pseudomonas aeruginosa, Pasteurella multocida, Clostridium perfringens, Micrococcus luteus, Streptococcus bovisand Staphylococcus aureus. Two multidrug-resistant clinical isolates and a phytopathogenic yeast strain were also inhibited. The antimicrobial substance was secreted at the middle of the exponential phase, whose activity was sensitive to proteinase K and pronase E but resistant to the proteolytic action of papain, trypsin and pepsin. The antimicrobial activity was relatively heat resistant and also active over a wide range of pH 3 - 10. Sodium dodecyl sulfate-polyacrylamide gel electrophoresisanalysis revealed that the active peptide had an apparent molecular weight of about 6.3 kDa. It exhibited a bactericidal activity against S. aureus IVDC C56005. Such characteristics indicate that this bacteriocin may be a potential candidate for alternative agents to control important pathogens in domestic animal diseases

Copper(II) Can Kinetically Trap Arctic and Italian Amyloid‑β40 as Toxic Oligomers, Mimicking Cu(II) Binding to Wild-Type Amyloid‑β42: Implications for Familial Alzheimer’s Disease

The self-association of amyloid-β (Aβ) peptide into neurotoxic oligomers is believed to be central to Alzheimer’s disease (AD). Copper is known to impact Aβ assembly, while disrupted copper homeostasis impacts phenotype in Alzheimer’s models. Here we show the presence of substoichiometric Cu(II) has very different impacts on the assembly of Aβ40 and Aβ42 isoforms. Globally fitting microscopic rate constants for fibril assembly indicates copper will accelerate fibril formation of Aβ40 by increasing primary nucleation, while seeding experiments confirm that elongation and secondary nucleation rates are unaffected by Cu(II). In marked contrast, Cu(II) traps Aβ42 as prefibrillar oligomers and curvilinear protofibrils. Remarkably, the Cu(II) addition to preformed Aβ42 fibrils causes the disassembly of fibrils back to protofibrils and oligomers. The very different behaviors of the two Aβ isoforms are centered around differences in their fibril structures, as highlighted by studies of C-terminally amidated Aβ42. Arctic and Italian familiar mutations also support a key role for fibril structure in the interplay of Cu(II) with Aβ40/42 isoforms. The Cu(II) dependent switch in behavior between nonpathogenic Aβ40 wild-type and Aβ40 Arctic or Italian mutants suggests heightened neurotoxicity may be linked to the impact of physiological Cu(II), which traps these familial mutants as oligomers and curvilinear protofibrils, which cause membrane permeability and Ca(II) cellular influx

Electrical current-driven pinhole formation and insulator-metal transition in tunnel junctions

Current Induced Resistance Switching (CIS) was recently observed in thin tunnel junctions (TJs) with ferromagnetic (FM) electrodes and attributed to electromigration of metallic atoms in nanoconstrictions in the insulating barrier. The CIS effect is here studied in TJs with two thin (20 \AA) non-magnetic (NM) Ta electrodes inserted above and below the insulating barrier. We observe resistance (R) switching for positive applied electrical current (flowing from the bottom to the top lead), characterized by a continuous resistance decrease and associated with current-driven displacement of metallic ions from the bottom electrode into the barrier (thin barrier state). For negative currents, displaced ions return into their initial positions in the electrode and the electrical resistance gradually increases (thick barrier state). We measured the temperature (T) dependence of the electrical resistance of both thin- and thick-barrier states ($R_b$ and R$_B$ respectively). Experiments showed a weaker R(T) variation when the tunnel junction is in the $R_b$ state, associated with a smaller tunnel contribution. By applying large enough electrical currents we induced large irreversible R-decreases in the studied TJs, associated with barrier degradation. We then monitored the evolution of the R(T) dependence for different stages of barrier degradation. In particular, we observed a smooth transition from tunnel- to metallic-dominated transport. The initial degradation-stages are related to irreversible barrier thickness decreases (without the formation of pinholes). Only for later barrier degradation stages do we have the appearance of metallic paths between the two electrodes that, however, do not lead to metallic dominated transport for small enough pinhole radius.Comment: 10 pages, 3 figure

Dependence of quantum correlations of twin beams on pump finesse of optical parametric oscillator

The dependence of quantum correlation of twin beams on the pump finesse of an optical parametric oscillator is studied with a semi-classical analysis. It is found that the phase-sum correlation of the output signal and idler beams from an optical parametric oscillator operating above threshold depends on the finesse of the pump field when the spurious pump phase noise generated inside the optical cavity and the excess noise of the input pump field are involved in the Langevin equations. The theoretical calculations can explain the previously experimental results, quantitatively.Comment: 27 pages, 8 figure

Experimental Comparisons of Derivative Free Optimization Algorithms

In this paper, the performances of the quasi-Newton BFGS algorithm, the NEWUOA derivative free optimizer, the Covariance Matrix Adaptation Evolution Strategy (CMA-ES), the Differential Evolution (DE) algorithm and Particle Swarm Optimizers (PSO) are compared experimentally on benchmark functions reflecting important challenges encountered in real-world optimization problems. Dependence of the performances in the conditioning of the problem and rotational invariance of the algorithms are in particular investigated.Comment: 8th International Symposium on Experimental Algorithms, Dortmund : Germany (2009

Ground State Energy of the One-Component Charged Bose Gas

The model considered here is the `jellium' model in which there is a uniform, fixed background with charge density $-e\rho$ in a large volume $V$ and in which $N=\rho V$ particles of electric charge $+e$ and mass $m$ move --- the whole system being neutral. In 1961 Foldy used Bogolubov's 1947 method to investigate the ground state energy of this system for bosonic particles in the large $\rho$ limit. He found that the energy per particle is $-0.402 r_s^{-3/4} {me^4}/{\hbar^2}$ in this limit, where $r_s=(3/4\pi \rho)^{1/3}e^2m/\hbar^2$. Here we prove that this formula is correct, thereby validating, for the first time, at least one aspect of Bogolubov's pairing theory of the Bose gasComment: 38 pages latex. Typos corrected.Lemma 6.2 change

Opinion formation in multiplex networks with general initial distributions

We study opinion dynamics over multiplex networks where agents interact with bounded confidence. Namely, two neighbouring individuals exchange opinions and compromise if their opinions do not differ by more than a given threshold. In literature, agents are generally assumed to have a homogeneous confidence bound. Here, we study analytically and numerically opinion evolution over structured networks characterised by multiple layers with respective confidence thresholds and general initial opinion distributions. Through rigorous probability analysis, we show analytically the critical thresholds at which a phase transition takes place in the long-term consensus behaviour, over multiplex networks with some regularity conditions. Our results reveal the quantitative relation between the critical threshold and initial distribution. Further, our numerical simulations illustrate the consensus behaviour of the agents in network topologies including lattices and, small-world and scale-free networks, as well as for structure-dependent convergence parameters accommodating node heterogeneity. We find that the critical thresholds for consensus tend to agree with the predicted upper bounds in Theorems 4 and 5 in this paper. Finally, our results indicate that multiplexity hinders consensus formation when the initial opinion configuration is within a bounded range and, provide insight into information diffusion and social dynamics in multiplex systems modeled by networks

Collective decision-making on triadic graphs

Many real-world networks exhibit community structures and non-trivial clustering associated with the occurrence of a considerable number of triangular subgraphs known as triadic motifs. Triads are a set of distinct triangles that do not share an edge with any other triangle in the network. Network motifs are subgraphs that occur significantly more often compared to random topologies. Two prominent examples, the feedforward loop and the feedback loop, occur in various real-world networks such as gene-regulatory networks, food webs or neuronal networks. However, as triangular connections are also prevalent in communication topologies of complex collective systems, it is worthwhile investigating the influence of triadic motifs on the collective decision-making dynamics. To this end, we generate networks called Triadic Graphs (TGs) exclusively from distinct triadic motifs. We then apply TGs as underlying topologies of systems with collective dynamics inspired from locust marching bands. We demonstrate that the motif type constituting the networks can have a paramount influence on group decision-making that cannot be explained solely in terms of the degree distribution. We find that, in contrast to the feedback loop, when the feedforward loop is the dominant subgraph, the resulting network is hierarchical and inhibits coherent behavior

The search for black hole binaries using a genetic algorithm

In this work we use genetic algorithm to search for the gravitational wave signal from the inspiralling massive Black Hole binaries in the simulated LISA data. We consider a single signal in the Gaussian instrumental noise. This is a first step in preparation for analysis of the third round of the mock LISA data challenge. We have extended a genetic algorithm utilizing the properties of the signal and the detector response function. The performance of this method is comparable, if not better, to already existing algorithms.Comment: 11 pages, 4 figures, proceeding for GWDAW13 (Puerto Rico