23 research outputs found

    Convection and the Extracellular Matrix Dictate Inter- and Intra-Biofilm Quorum Sensing Communication in Environmental Systems.

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    The mechanisms and impact of bacterial quorum sensing (QS) for the coordination of population-level behaviors are well studied under laboratory conditions. However, it is unclear how, in otherwise open environmental systems, QS signals accumulate to sufficient concentration to induce QS phenotypes, especially when quorum quenching (QQ) organisms are also present. We explore the impact of QQ activity on QS signaling in spatially organized biofilms in scenarios that mimic open systems of natural and engineered environments. Using a functionally differentiated biofilm system, we show that the extracellular matrix, local flow, and QQ interact to modulate communication. In still aqueous environments, convection facilitates signal dispersal while the matrix absorbs and relays signals to the cells. This process facilitates inter-biofilm communication even at low extracellular signal concentrations. Within the biofilm, the matrix further regulates the transport of the competing QS and QQ molecules, leading to heterogenous QS behavior. Importantly, only extracellular QQ enzymes can effectively control QS signaling, suggesting that the intracellular QQ enzymes may not have evolved to degrade environmental QS signals for competition

    Building behavior scoring model using genetic algorithm and support vector machines

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    In the increasingly competitive credit industry, one of the most interesting and challenging problems is how to manage existing customers. Behavior scoring models have been widely used by financial institutions to forecast customer's future credit performance. In this paper, a hybrid GA+SVM model, which uses genetic algorithm (GA) to search the promising subsets of features and multi-class support vector machines (SVM) to make behavior scoring prediction, is presented. A real life credit data set in a major Chinese commercial bank is selected as the experimental data to compare the classification accuracy rate with other traditional behavior scoring models. The experimental results show that GA+SVM can obtain better performance than other models

    HIV Reservoirs and Immune Surveillance Evasion Cause the Failure of Structured Treatment Interruptions: A Computational Study

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    Continuous antiretroviral therapy is currently the most effective way to treat HIV infection. Unstructured interruptions are quite common due to side effects and toxicity, among others, and cannot be prevented. Several attempts to structure these interruptions failed due to an increased morbidity compared to continuous treatment. The cause of this failure is poorly understood and often attributed to drug resistance. Here we show that structured treatment interruptions would fail regardless of the emergence of drug resistance. Our computational model of the HIV infection dynamics in lymphoid tissue inside lymph nodes, demonstrates that HIV reservoirs and evasion from immune surveillance themselves are sufficient to cause the failure of structured interruptions. We validate our model with data from a clinical trial and show that it is possible to optimize the schedule of interruptions to perform as well as the continuous treatment in the absence of drug resistance. Our methodology enables studying the problem of treatment optimization without having impact on human beings. We anticipate that it is feasible to steer new clinical trials using computational models

    Identifying potential survival strategies of HIV-1 through virus-host protein interaction networks

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    Background: The National Institute of Allergy and Infectious Diseases has launched the HIV-1 Human Protein Interaction Database in an effort to catalogue all published interactions between HIV-1 and human proteins. In order to systematically investigate these interactions functionally and dynamically, we have constructed an HIV-1 human protein interaction network. This network was analyzed for important proteins and processes that are specific for the HIV life-cycle. In order to expose viral strategies, network motif analysis was carried out showing reoccurring patterns in virus-host dynamics.Results: Our analyses show that human proteins interacting with HIV form a densely connected and central sub-network within the total human protein interaction network. The evaluation of this sub-network for connectivity and centrality resulted in a set of proteins essential for the HIV life-cycle. Remarkably, we were able to associate proteins involved in RNA polymerase II transcription with hubs and proteasome formation with bottlenecks. Inferred network motifs show significant over-representation of positive and negative feedback patterns between virus and host. Strikingly, such patterns have never been reported in combined virus-host systems.Conclusions: HIV infection results in a reprioritization of cellular processes reflected by an increase in the relative importance of transcriptional machinery and proteasome formation. We conclude that during the evolution of HIV, some patterns of interaction have been selected for resulting in a system where virus proteins preferably interact with central human proteins for direct control and with proteasomal proteins for indirect control over the cellular processes. Finally, the patterns described by network motifs illustrate how virus and host interact with one another

    Reduced light-scattering properties for mixtures off spherical particles: a simple approximation derived from Mie calculations

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    The reduced scattering cross section per unit of volume SIGMA(s)' = SIGMA(s)(1 - g) is an important parameter to describe light propagation in media with scattering and absorption. Mie calculations of the asymmetry factor g for nonabsorbing spheres and Q(sca), the ratio of the scattering cross section SIGMA(s) and the particle cross section, show that Q(sca)(1 - g) = 3.28x0.37 (m - 1)2.09 is true to within a few percent, when the Mie parameters for relative refractive index m and size x are in the ranges of 1 <m less-than-or-equal-to 1.1 and 5 <x <50, respectively. A ratio of reduced scattering cross sections for radiation at two wavelengths is also independent of the size within the range mentioned, even for mixtures of different size spheres. The results seem promising for biomedical applications
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