Enhanced cytotoxicity of silver complexes bearing bidentate N-heterocyclic carbene ligands

A diverse library of cationic silver complexes bearing bis(N-heterocyclic carbene) ligands have been prepared which exhibit cytotoxicity comparable to cisplatin against the adenocarcinomas MCF7 and DLD1. Bidentate ligands show enhanced cytotoxicity over monodentate and macrocyclic ligands

Quickest Paths in Simulations of Pedestrians

This contribution proposes a method to make agents in a microscopic simulation of pedestrian traffic walk approximately along a path of estimated minimal remaining travel time to their destination. Usually models of pedestrian dynamics are (implicitly) built on the assumption that pedestrians walk along the shortest path. Model elements formulated to make pedestrians locally avoid collisions and intrusion into personal space do not produce motion on quickest paths. Therefore a special model element is needed, if one wants to model and simulate pedestrians for whom travel time matters most (e.g. travelers in a station hall who are late for a train). Here such a model element is proposed, discussed and used within the Social Force Model.Comment: revised version submitte

An improved evolutionary algorithm-based framework for identifying in silico metabolic engineering targets

In metabolic engineering problems, due to the complexity of metabolic networks, it is often difficult to identify a priori which genetic manipulations will originate a given desired phenotype. Genome-scale metabolic models, available for several microorganisms, can be used to simulate the metabolic phenotype and therefore help the tasks of metabolic engineering. This simulation can be performed by calculating the fluxes through all metabolic reactions using techniques like the Flux Balance Analysis (FBA) or the MOMA approaches, among others. Several algorithms have been developed that use genome-scale metabolic models to enable the identification of gene knockout strategies for obtaining improved phenotypes. However, the problem of finding optimal gene deletion strategy is combinatorial and consequently the computational time increases exponentially with the size of the problem. In a previous study we reported that evolutionary algorithms (EAs) enable solving large gene knockout problems in relatively short computational time. The proposed algorithm – OptGene - also allows the optimization of non-linear objective functions and additionally provides a family of close to optimal solutions. Given the promising results obtained, this algorithm was modified with two main objectives: improve the predictions obtained and increase the flexibility. For these purposes, a new program was built by the authors using the Java programming language. Regarding the optimization algorithms, in OptGene two distinct encoding schemes had been taken into account, binary and integer representations. The latter is more compact but potentially reduces the search space to a limited number of knockouts. In order to overcome this limitation, in this work a new feature was implemented by allowing the evolution of solutions with variable size. This allows maintaining the potential solutions with a relatively small number of genes while not defining a priori the exact number of knockouts. Furthermore, the EA’s performance was boosted by the introduction of local search operators that look for improved solutions in the neighbourhood of the individual under consideration. The quality of the solutions obtained by the EAs was compared to the ones obtained using a simpler algorithm, the well-known hill-climbing algorithm adapted for the present situation. The local search operator, in this case, considers all neighbours that imply the addition of a single knockout to the present solution and selects the best. The wild-type is considered as the starting solution and the local search operator is applied, until no improvement is possible. Finally, a graphical user interface was developed that allows an easy utilization of any genome-scale metabolic model in SBML or other format, the manual modification of flux bound values, the selection of the appropriate simulation technique (FBA or MOMA) and the corresponding flux to be optimized for FBA. Additionally, the program allows the utilization of any of the optimization algorithms described above and the selection of a suitable (linear or non-linear) objective function, like yield or biomass coupled yield. A tool for the visualization of the flux distribution in the metabolic network is being developed. This modified algorithm was validated using succinate production in both Escherichia coli and Saccharomyces cerevisiae as case studies. Potential metabolic engineering targets were identified and the results suggest that non-intuitive genetic modifications spanning several different pathways may be necessary for solving challenging metabolic engineering problems

Universal behavior of quantum Green's functions

We consider a general one-particle Hamiltonian H = - \Delta_r + u(r) defined in a d-dimensional domain. The object of interest is the time-independent Green function G_z(r,r') = . Recently, in one dimension (1D), the Green's function problem was solved explicitly in inverse form, with diagonal elements of Green's function as prescribed variables. The first aim of this paper is to extract from the 1D inverse solution such information about Green's function which cannot be deduced directly from its definition. Among others, this information involves universal, i.e. u(r)-independent, behavior of Green's function close to the domain boundary. The second aim is to extend the inverse formalism to higher dimensions, especially to 3D, and to derive the universal form of Green's function for various shapes of the confining domain boundary.Comment: 46 pages, the shortened version submitted to J. Math. Phy

Matrix equations and trilinear commutation relations

In this paper we discuss a general algebraic approach to treating static equations of matrix models with a mass-like term. In this approach the equations of motions are considered as consequence of parafermi-like trilinear commutation relations. In this context we consider several solutions, including construction of noncommutative spheres. The equivalence of fuzzy spheres and parafermions is underlined.Comment: 10 pages, an incorrect claim is removed, one reference is adde

Statistics of selectively neutral genetic variation

Random models of evolution are instrumental in extracting rates of microscopic evolutionary mechanisms from empirical observations on genetic variation in genome sequences. In this context it is necessary to know the statistical properties of empirical observables (such as the local homozygosity for instance). Previous work relies on numerical results or assumes Gaussian approximations for the corresponding distributions. In this paper we give an analytical derivation of the statistical properties of the local homozygosity and other empirical observables assuming selective neutrality. We find that such distributions can be very non-Gaussian.Comment: 4 pages, 4 figure

Inaccessible Singularities in Toral Cosmology

The familiar Bang/Crunch singularities of classical cosmology have recently been augmented by new varieties: rips, sudden singularities, and so on. These tend to be associated with final states. Here we consider an alternative possibility for the initial state: a singularity which has the novel property of being inaccessible to physically well-defined probes. These singularities arise naturally in cosmologies with toral spatial sections.Comment: 10 pages, version to appear in Classical and Quantum Gravit

On Non Commutative G2 structure

Using an algebraic orbifold method, we present non-commutative aspects of $G_2$ structure of seven dimensional real manifolds. We first develop and solve the non commutativity parameter constraint equations defining $G_2$ manifold algebras. We show that there are eight possible solutions for this extended structure, one of which corresponds to the commutative case. Then we obtain a matrix representation solving such algebras using combinatorial arguments. An application to matrix model of M-theory is discussed.Comment: 16 pages, Latex. Typos corrected, minor changes. Version to appear in J. Phys.A: Math.Gen.(2005