A stochastic network with mobile users in heavy traffic

We consider a stochastic network with mobile users in a heavy-traffic regime. We derive the scaling limit of the multi-dimensional queue length process and prove a form of spatial state space collapse. The proof exploits a recent result by Lambert and Simatos which provides a general principle to establish scaling limits of regenerative processes based on the convergence of their excursions. We also prove weak convergence of the sequences of stationary joint queue length distributions and stationary sojourn times.Comment: Final version accepted for publication in Queueing Systems, Theory and Application

Chemiluminescence activity of neutrophil granulocytes under the influence of magnetic nanoparticles of ferrihydrite (<i>in vitro</i>)

The article presents the results of studying and evaluating the impact of magnetic nanoparticles of ferrihydrite on neutrophil granulocytes in human blood (in vitro) in order to determine their bio compatibility and eco toxicity. The subject soft here search were blood neutrophil granulocytes of 29 conditionally-healthy donors of blood, as well as magnetic nanoparticles of ferrihydrite (NP), the preparation dose in minimum concentration reached 25 mg, in maximum concentration it reached 50 mg per 106 cells/ml. We implemented the sol of magnetic NP, obtained by biogenic synthesis in International Scientific Centre for Studying Extreme States of an Organism. Functional activity of blood neutrophil granulocytes has been determined by luminol-dependent chemiluminescence. Magnetic NP were introduced into pilot samples straight before chemiluminescent analysis, and also after the incubation with in 30 minutes under 37 °С entigrade. As a result of thee stimation of the early response of neutrophil granulocytes to the influence of minimum concentration of magnetic NP in vitro we found statistically true decrease of the intensity (1.6 times), the area under the curve (2.1 times) in zymosan-induced chemiluminescent response, the activation index (2.3 times). When evaluating the late response of neutrophil granulocytes to the influence of maximum concentration of magnetic NP in vitro we have found statistically true lowering of the time of reaching the peak (10 times) of spontaneous chemiluminescence. More over we marked consider able lowering of maximum intensity 6 times and the reduction of the area under the curve of zymosan-induced chemiluminescence 5.6 times under the influence of magnetic NP under the lowering of activation index 3.7 times. The authors determined that magnetic NP were intensively decreasing the functional activity of neutrophil granulocytes. The intensity of the impact is higher under the preliminary incubation of the cells with magnetic NP. At the same time, short effect of magnetic NP to neutrophil granulocytes can be a modulating one and depends on the initial level of cell reactivity. We revealed that magnetic NP influence concerns only activated cells

Genome-wide histone acetylation data improve prediction of mammalian transcription factor binding sites

Motivation: Histone acetylation (HAc) is associated with open chromatin, and HAc has been shown to facilitate transcription factor (TF) binding in mammalian cells. In the innate immune system context, epigenetic studies strongly implicate HAc in the transcriptional response of activated macrophages. We hypothesized that using data from large-scale sequencing of a HAc chromatin immunoprecipitation assay (ChIP-Seq) would improve the performance of computational prediction of binding locations of TFs mediating the response to a signaling event, namely, macrophage activation

The impact of donor factors on the results of kidney transplantation

Kidney transplantation is an optimal method of a renal replacement therapy of end-stage kidney failure. We have done the retrospective research of cohort 350 patients after kidney transplantations to disclose the predictors of the operation outcomes. We used methods of a single-factor and a multi-factor analysis. We found out that the predictors of the results of kidney transplantation are; a donor age, a type of donor kidney removal, perfusion time, reanimation time, kidney’s preservation time etc.Трансплантация почки является оптимальным методом заместительной почечной терапии терминальной почечной недостаточности. Проведено когортное, ретроспективное исследование, включившее 350 пациентов после трансплантации почки, для выявления предикторов исхода трансплантации почки по факторам, связанным с донором почки. Были использованы методы однофакторного и многофакторного анализа. Выявлен ряд предикторов исхода трансплантации почки таких как: возраст донора, тип изъятия донорского органа, длительность перфузии донорского органа, длительность пребывания донора в реанимационном отделении, время консервации почки и другие

On the Complexity of Scheduling in Wireless Networks

We consider the problem of throughput-optimal scheduling in wireless networks subject to interference constraints. We model the interference using a family of K-hop interference models, under which no two links within a K-hop distance can successfully transmit at the same time. For a given K, we can obtain a throughput-optimal scheduling policy by solving the well-known maximum weighted matching problem. We show that for K > 1, the resulting problems are NP-Hard that cannot be approximated within a factor that grows polynomially with the number of nodes. Interestingly, for geometric unit-disk graphs that can be used to describe a wide range of wireless networks, the problems admit polynomial time approximation schemes within a factor arbitrarily close to 1. In these network settings, we also show that a simple greedy algorithm can provide a 49-approximation, and the maximal matching scheduling policy, which can be easily implemented in a distributed fashion, achieves a guaranteed fraction of the capacity region for "all K." The geometric constraints are crucial to obtain these throughput guarantees. These results are encouraging as they suggest that one can develop low-complexity distributed algorithms to achieve near-optimal throughput for a wide range of wireless networksopen1

A stable genetic polymorphism underpinning microbial syntrophy

Syntrophies are metabolic cooperations, whereby two organisms co-metabolize a substrate in an interdependent manner. Many of the observed natural syntrophic interactions are mandatory in the absence of strong electron acceptors, such that one species in the syntrophy has to assume the role of electron sink for the other. While this presents an ecological setting for syntrophy to be beneficial, the potential genetic drivers of syntrophy remain unknown to date. Here, we show that the syntrophic sulfate-reducing species Desulfovibrio vulgaris displays a stable genetic polymorphism, where only a specific genotype is able to engage in syntrophy with the hydrogenotrophic methanogen Methanococcus maripaludis. This 'syntrophic' genotype is characterized by two genetic alterations, one of which is an in-frame deletion in the gene encoding for the ion-translocating subunit cooK of the membrane-bound COO hydrogenase. We show that this genotype presents a specific physiology, in which reshaping of energy conservation in the lactate oxidation pathway enables it to produce sufficient intermediate hydrogen for sustained M. maripaludis growth and thus, syntrophy. To our knowledge, these findings provide for the first time a genetic basis for syntrophy in nature and bring us closer to the rational engineering of syntrophy in synthetic microbial communities

Genome-Scale Modeling of Light-Driven Reductant Partitioning and Carbon Fluxes in Diazotrophic Unicellular Cyanobacterium Cyanothece sp. ATCC 51142

Genome-scale metabolic models have proven useful for answering fundamental questions about metabolic capabilities of a variety of microorganisms, as well as informing their metabolic engineering. However, only a few models are available for oxygenic photosynthetic microorganisms, particularly in cyanobacteria in which photosynthetic and respiratory electron transport chains (ETC) share components. We addressed the complexity of cyanobacterial ETC by developing a genome-scale model for the diazotrophic cyanobacterium, Cyanothece sp. ATCC 51142. The resulting metabolic reconstruction, iCce806, consists of 806 genes associated with 667 metabolic reactions and includes a detailed representation of the ETC and a biomass equation based on experimental measurements. Both computational and experimental approaches were used to investigate light-driven metabolism in Cyanothece sp. ATCC 51142, with a particular focus on reductant production and partitioning within the ETC. The simulation results suggest that growth and metabolic flux distributions are substantially impacted by the relative amounts of light going into the individual photosystems. When growth is limited by the flux through photosystem I, terminal respiratory oxidases are predicted to be an important mechanism for removing excess reductant. Similarly, under photosystem II flux limitation, excess electron carriers must be removed via cyclic electron transport. Furthermore, in silico calculations were in good quantitative agreement with the measured growth rates whereas predictions of reaction usage were qualitatively consistent with protein and mRNA expression data, which we used to further improve the resolution of intracellular flux values

OptCom: A Multi-Level Optimization Framework for the Metabolic Modeling and Analysis of Microbial Communities

Microorganisms rarely live isolated in their natural environments but rather function in consolidated and socializing communities. Despite the growing availability of high-throughput sequencing and metagenomic data, we still know very little about the metabolic contributions of individual microbial players within an ecological niche and the extent and directionality of interactions among them. This calls for development of efficient modeling frameworks to shed light on less understood aspects of metabolism in microbial communities. Here, we introduce OptCom, a comprehensive flux balance analysis framework for microbial communities, which relies on a multi-level and multi-objective optimization formulation to properly describe trade-offs between individual vs. community level fitness criteria. In contrast to earlier approaches that rely on a single objective function, here, we consider species-level fitness criteria for the inner problems while relying on community-level objective maximization for the outer problem. OptCom is general enough to capture any type of interactions (positive, negative or combinations thereof) and is capable of accommodating any number of microbial species (or guilds) involved. We applied OptCom to quantify the syntrophic association in a well-characterized two-species microbial system, assess the level of sub-optimal growth in phototrophic microbial mats, and elucidate the extent and direction of inter-species metabolite and electron transfer in a model microbial community. We also used OptCom to examine addition of a new member to an existing community. Our study demonstrates the importance of trade-offs between species- and community-level fitness driving forces and lays the foundation for metabolic-driven analysis of various types of interactions in multi-species microbial systems using genome-scale metabolic models