Rayna Georgieva

Superficial implantation in pigs is associated with decreased numbers and redistribution of endometrial NK-cell populations.

Problem We evaluated implantation‐associated quantitative changes in endometrial and peripheral natural killer (NK)‐cell populations of pigs.

Docosahexaenoic acid promotes micron scale liquid-ordered domains. A comparison study of docosahexaenoic versus oleic acid containing phosphatidylcholine in raft-like mixtures

The understanding of the functional role of the lipid diversity in biological membranes is a major challenge. Lipid models have been developed to address this issue by using lipid mixtures generating liquid-ordered (Lo)/liquid-disordered (Ld) immiscibility. The present study examined mixtures comprising Egg sphingomyelin (SM), cholesterol (chol) and phosphatidylcholine (PC) either containing docosahexaenoic (PDPC) or oleic acid (POPC). The mixtures were examined in terms of their capability to induce phase separation at the micron- and nano-scales. Fluorescence microscopy, electron spin resonance (ESR), X-ray diffraction (XRD) and calorimetry methods were used to analyze the lateral organization of the mixtures. Fluorescence microscopy of giant vesicles could show that the temperature of the micron-scale Lo/Ld miscibility is higher for PDPC than for POPC ternary mixtures. At 37°C, no micron-scale Lo/Ld phase separation could be identified in the POPC containing mixtures while it was evident for PDPC. In contrast, a phase separation was distinguished for both PC mixtures by ESR and XRD, indicative that PDPC and POPC mixtures differed in micron vs nano domain organization. Compared to POPC, the higher line tension of the Lo domains observed in PDPC mixtures is assumed to result from the higher difference in Lo/Ld order parameter rather than hydrophobic mismatch.

Dynamics of T-suppressor and T-helper lymphocytes and haemolytic plaque-forming cells during normal pregnancy in the sow

T gamma and T mu lymphocytes and haemolytic plaque-forming cells (PFC) were quantitatively determined in peripheral blood and uterine draining lymph nodes ( DLN ) from 36 nonpregnant and 45 pregnant sows. A considerable increase in the number of T gamma cells occurred both in the blood and the DLN during pregnancy (P less than 0.001). This increase was higher at the beginning of pregnancy (20th-40th day) and lower at the end (80th- 110th day). No significant quantitative changes were found in T mu cells. During pregnancy there was a marked drop in the number of cells in the peripheral blood manifesting direct erythrocytolytic activity (DECA), as well as of haemolysin-producing cells.

ORIGINAL ARTICLE: Superficial Implantation in Pigs Is Associated with Decreased Numbers and Redistribution of Endometrial NK-Cell Populations

Problem We evaluated implantation‐associated quantitative changes in endometrial and peripheral natural killer (NK)‐cell populations of pigs.

Establishment of the Porcine Epitheliochorial Placenta Is Associated with Endometrial T-Cell Recruitment

We assessed implantation‐associated quantitative changes in peripheral blood and endometrial T lymphocytes throughout epitheliochorial placenta formation.

Monte Carlo sensitivity analysis of an Eulerian large-scale air pollution model

Abstract Variance-based approaches for global sensitivity analysis have been applied and analyzed to study the sensitivity of air pollutant concentrations according to variations of rates of chemical reactions. The Unified Danish Eulerian Model has been used as a mathematical model simulating a remote transport of air pollutants. Various Monte Carlo algorithms for numerical integration have been applied to compute Sobols global sensitivity indices. A newly developed Monte Carlo algorithm based on Sobols quasi-random points MCA-MSS has been applied for numerical integration. It has been compared with some existing approaches, namely Sobols Λ Π τ sequences, an adaptive Monte Carlo algorithm, the plain Monte Carlo algorithm, as well as, eFAST and Sobols sensitivity approaches both implemented in SIMLAB software. The analysis and numerical results show advantages of MCA-MSS for relatively small sensitivity indices in terms of accuracy and efficiency. Practical guidelines on the estimation of Sobols global sensitivity indices in the presence of computational difficulties have been provided.

Parallel Importance Separation and Adaptive Monte Carlo Algorithms for Multiple Integrals

Monte Carlo Method (MCM) is the only viable method for many high-dimensional problems since its convergence is independent of the dimension. In this paper we develop an adaptive Monte Carlo method based on the ideas and results of the importance separation, a method that combines the idea of separation of the domain into uniformly small subdomains with the Kahn approach of importance sampling. We analyze the error and compare the results with crude Monte Carlo and importance sampling which is the most widely used variance reduction Monte Carlo method. We also propose efficient parallelizations of the importance separation method and the studied adaptive Monte Carlo method. Numerical tests implemented on PowerPC cluster using MPI are provided.

Parallel computation of sensitivity analysis data for the danish eulerian model

Sensitivity Analysis of the Danish Eulerian Model requires an extensive amount of output data from computationally expensive numerical experiments with a specially adapted for the purpose version of the model, called SA-DEM. It has been successfully implemented and run on the most powerful parallel supercomputer in Bulgaria - IBM BlueGene/P. A new enhanced version, capable of using efficiently the full capacity of the mashine, has recently been developed. It will be described in this paper together with some performance analysis and numerical results. The output results are used to construct some mesh-functions of ozone concentrations ratios to be used further in sensitivity analysis of the model by using Monte Carlo algorithms.

Monte Carlo method for numerical integration based on Sobol's sequences

An efficient Monte Carlo method for multidimensional integration is proposed and studied. The method is based on Sobols sequences. Each random point in s-dimensional domain of integration is generated in the following way. A Sobols vector of dimension s (ΛΠτ point) is considered as a centrum of a sphere with a radius ρ. Then a random point uniformly distributed on the sphere is taken and a random variable is defined as a value of the integrand at that random point. It is proven that the mathematical expectation of the random variable is equal to the desired multidimensional integral. This fact is used to define a Monte Carlo algorithm with a low variance. Numerical experiments are performed in order to study the quality of the algorithm depending of the radius ρ and regularity, i.e. smoothness of the integrand.

Air pollution modelling, sensitivity analysis and parallel implementation

A new approach for Sensitivity Analysis (SA) in the field of air pollution modelling is proposed and applied to the Unified Danish Eulerian Model (UNI-DEM), a large-scale air pollution model. The SA requires numerous model experiments with different values of the studied parameters. By simultaneous variation of these parameters we produce a set of multidimensional discrete functions. These huge computational tasks require extensive resources of storage and CPU time. A highly parallel implementation of UNI-DEM has been created for this purpose and implemented on two powerful supercomputers. Some details of this implementation and numerical results on these supercomputers are presented.