The influence of local field corrections on Thomson scattering in non-ideal two-component plasmas

Thomson scattering in non-ideal (collision-dominated) two-component plasmas is calculated accounting for electron-ion collisions as well as electron-electron correlations. This is achieved by using a novel interpolation scheme for the electron-electron response function generalizing the traditional Mermin approach. Also, ions are treated as randomly distributed inert scattering centers. The collision frequency is taken as a dynamic and complex quantity and is calculated from a microscopic quantum-statistical approach. Implications due to different approximations for the electron-electron correlation, i.e. different forms of the OCP local field correction, are discussed

Single-particle spectral function for the classical one-component plasma

The spectral function for an electron one-component plasma is calculated self-consistently using the GW0 approximation for the single-particle self-energy. In this way, correlation effects which go beyond the mean-field description of the plasma are contained, i.e. the collisional damping of single-particle states, the dynamical screening of the interaction and the appearance of collective plasma modes. Secondly, a novel non-perturbative analytic solution for the on-shell GW0 self-energy as a function of momentum is presented. It reproduces the numerical data for the spectral function with a relative error of less than 10% in the regime where the Debye screening parameter is smaller than the inverse Bohr radius, kappa<1/a_B. In the limit of low density, the non-perturbative self-energy behaves as n^(1/4), whereas a perturbation expansion leads to the unphysical result of a density independent self-energy [W. Fennel and H. P. Wilfer, Ann. Phys. Lpz._32_, 265 (1974)]. The derived expression will greatly facilitate the calculation of observables in correlated plasmas (transport properties, equation of state) that need the spectral function as an input quantity. This is demonstrated for the shift of the chemical potential, which is computed from the analytical formulae and compared to the GW0-result. At a plasma temperature of 100 eV and densities below 10^21 cm^-3, both approaches deviate less than 10% from each other.Comment: 14 pages, 9 figures accepted for publication in Phys. Rev. E v2: added section V (application of presented formalism to chemical potential of the OCP

Primary differentiation in the human blastocyst : comparative molecular portraits of inner cell mass and trophectoderm cells

The primary differentiation event during mammalian development occurs at the blastocyst stage and leads to the delineation of the inner cell mass (ICM) and the trophectoderm (TE). We provide the first global mRNA expression data from immunosurgically dissected ICM cells, TE cells, and intact human blastocysts. Using a cDNA microarray composed of 15,529 cDNAs from known and novel genes, we identify marker transcripts specific to the ICM (e.g., OCT4/POU5F1, NANOG, HMGB1, and DPPA5) and TE (e.g., CDX2, ATP1B3, SFN, and IPL), in addition to novel ICM- and TE-specific expressed sequence tags. The expression patterns suggest that the emergence of pluripotent ICM and TE cell lineages from the morula is controlled by metabolic and signaling pathways, which include inter alia, WNT, mitogen-activated protein kinase, transforming growth factor-beta, NOTCH, integrin-mediated cell adhesion, phosphatidylinositol 3-kinase, and apoptosis. These data enhance our understanding of the first step in human cellular differentiation and, hence, the derivation of both embryonic stem cells and trophoblastic stem cells from these lineages

Dielectric function of a two-component plasma including collisions

A multiple-moment approach to the dielectric function of a dense non-ideal plasma is treated beyond RPA including collisions in Born approximation. The results are compared with the perturbation expansion of the Kubo formula. Sum rules as well as Ward identities are considered. The relations to optical properties as well as to the dc electrical conductivity are pointed out.Comment: latex, 10 pages, 7 figures in ps forma

Self-consistent Spectral Function for Non-Degenerate Coulomb Systems and Analytic Scaling Behaviour

Novel results for the self-consistent single-particle spectral function and self-energy are presented for non-degenerate one-component Coulomb systems at various densities and temperatures. The GW^0-method for the dynamical self-energy is used to include many-particle correlations beyond the quasi-particle approximation. The self-energy is analysed over a broad range of densities and temperatures (n=10^17/cm^3-10^27/cm^3, T=10^2 eV/k_B-10^4 eV/k_B). The spectral function shows a systematic behaviour, which is determined by collective plasma modes at small wavenumbers and converges towards a quasi-particle resonance at higher wavenumbers. In the low density limit, the numerical results comply with an analytic scaling law that is presented for the first time. It predicts a power-law behaviour of the imaginary part of the self-energy, Im Sigma ~ -n^(1/4). This resolves a long time problem of the quasi-particle approximation which yields a finite self-energy at vanishing density.Comment: 28 pages, 9 figure

Modeling of miRNA and Drug Action in the EGFR Signaling Pathway

MicroRNAs have gained significant interest due to their widespread occurrence and diverse functions as regulatory molecules, which are essential for cell division, growth, development and apoptosis in eukaryotes. The epidermal growth factor receptor (EGFR) signaling pathway is one of the best investigated cellular signaling pathways regulating important cellular processes and its deregulation is associated with severe diseases, such as cancer. In this study, we introduce a systems biological model of the EGFR signaling pathway integrating validated miRNA-target information according to diverse studies, in order to demonstrate essential roles of miRNA within this pathway. The model consists of 1241 reactions and contains 241 miRNAs. We analyze the impact of 100 specific miRNA inhibitors (anit-miRNAs) on this pathway and propose that the embedded miRNA-network can help to identify new drug targets of the EGFR signaling pathway and thereby support the development of new therapeutic strategies against cancer

Characterization and simulation of cDNA microarray spots using a novel mathematical model

<p>Abstract</p> <p>Background</p> <p>The quality of cDNA microarray data is crucial for expanding its application to other research areas, such as the study of gene regulatory networks. Despite the fact that a number of algorithms have been suggested to increase the accuracy of microarray gene expression data, it is necessary to obtain reliable microarray images by improving wet-lab experiments. As the first step of a cDNA microarray experiment, spotting cDNA probes is critical to determining the quality of spot images.</p> <p>Results</p> <p>We developed a governing equation of cDNA deposition during evaporation of a drop in the microarray spotting process. The governing equation included four parameters: the surface site density on the support, the extrapolated equilibrium constant for the binding of cDNA molecules with surface sites on glass slides, the macromolecular interaction factor, and the volume constant of a drop of cDNA solution. We simulated cDNA deposition from the single model equation by varying the value of the parameters. The morphology of the resulting cDNA deposit can be classified into three types: a doughnut shape, a peak shape, and a volcano shape. The spot morphology can be changed into a flat shape by varying the experimental conditions while considering the parameters of the governing equation of cDNA deposition. The four parameters were estimated by fitting the governing equation to the real microarray images. With the results of the simulation and the parameter estimation, the phenomenon of the formation of cDNA deposits in each type was investigated.</p> <p>Conclusion</p> <p>This study explains how various spot shapes can exist and suggests which parameters are to be adjusted for obtaining a good spot. This system is able to explore the cDNA microarray spotting process in a predictable, manageable and descriptive manner. We hope it can provide a way to predict the incidents that can occur during a real cDNA microarray experiment, and produce useful data for several research applications involving cDNA microarrays.</p

Trends in modeling Biomedical Complex Systems

In this paper we provide an introduction to the techniques for multi-scale complex biological systems, from the single bio-molecule to the cell, combining theoretical modeling, experiments, informatics tools and technologies suitable for biological and biomedical research, which are becoming increasingly multidisciplinary, multidimensional and information-driven. The most important concepts on mathematical modeling methodologies and statistical inference, bioinformatics and standards tools to investigate complex biomedical systems are discussed and the prominent literature useful to both the practitioner and the theoretician are presented