2,565 research outputs found

    Population model of quorum sensing with multiple parallel pathways

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    Quorum sensing (QS) is a bacterial communication mechanism that uses signal-receptor binding to regulate gene expression based on cell density, resulting in group behaviors such as biofilm formation, bioluminescence and stress response. In certain bacterial species such as Vibrio harveyi, several parallel QS signaling pathways drive a single phosphorylation–dephosphorylation cycle, which in turn regulates QS target genes. In this paper, we investigate the possible role of parallel signaling pathways by developing a mathematical model of QS in V. harveyi at both the single-cell and population levels. First we explore how signal integration may be achieved at the single-cell level, and how different model parameters influence the process. We then consider two examples of signal integration at the population level: a one-population model responding to two environmental cues (cell density and mass transfer), and a two-population model with distinct cell densities. In each case, we use contraction analysis to reduce the population model to an effective single-cell model

    Modeling the role of feedback in the adaptive response of bacterial quorum sensing

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    Bacterial quorum sensing (QS) is a form of intercellular communication that relies on the production and detection of diffusive signaling molecules called autoinducers. Such a mechanism allows the bacteria to track their cell density in order to regulate group behavior, such as biofilm formation and bioluminescence. In a number of bacterial QS systems, including V. harveyi, multiple signaling pathways are integrated into a single phosphorylation–dephosphorylation cycle. In this paper, we propose a weight control mechanism, in which QS uses feedback loops to ‘decode’ the integrated signals by actively changing the sensitivity in different pathways. We first use a slow/fast analysis to reduce a single-cell model to a planar dynamical system involving the concentrations of phosphorylated signaling protein LuxU and a small non-coding RNA. In addition to identifying the weight control mechanism, we show that adding a feedback loop can lead to a bistable QS response in certain parameter regimes. We then combine the slow/fast analysis with a contraction mapping theorem in order to reduce a population model to an effective single-cell model, and show how the weight control mechanism allows bacteria to have a finer discrimination of their social and physical environment

    Node-to-node and node-to-medium synchronization in quorum sensing networks affected by state-dependent noise

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    A quorum sensing network is a form of communication system where nodes talk to each other through a shared environment or medium. Such networks arise in many applications, such as bacterial quorum sensing, where diffusing signaling molecules are exchanged with the extracellular environment, and in social networks, where decisions might be influenced by social media. In this paper, we analyze node-to-node and node-to-medium synchronization in these quorum sensing networks when nodes are affected by relative-state-dependent noise and the medium has a different dynamics from the nodes. By using stochastic Lyapunov arguments, we give a number of sufficient conditions for the stability of the synchronization manifold and compare the synchronization dynamics induced by common (extrinsic) noise and independent (intrinsic) noise. We also carry out a stochastic phase plane analysis of the dynamics on the synchronization manifold by introducing the notion of a stochastic invariant manifold. (The PDF has been corrected.

    Identifying the favored mutation in a positive selective sweep.

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    Most approaches that capture signatures of selective sweeps in population genomics data do not identify the specific mutation favored by selection. We present iSAFE (for "integrated selection of allele favored by evolution"), a method that enables researchers to accurately pinpoint the favored mutation in a large region (∼5 Mbp) by using a statistic derived solely from population genetics signals. iSAFE does not require knowledge of demography, the phenotype under selection, or functional annotations of mutations

    The spectral variability of FSRQs

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    The optical variability of 29 flat spectrum radio quasars in SDSS Stripe 82 region are investigated by using DR7 released multi-epoch data. All FSRQs show variations with overall amplitude ranging from 0.24 mag to 3.46 mag in different sources. About half of FSRQs show a bluer-when-brighter trend, which is commonly observed for blazars. However, only one source shows a redder-when-brighter trend, which implies it is rare in FSRQs. In this source, the thermal emission may likely be responsible for the spectral behavior.Comment: 4 pages, 1 figure, to be published in Journal of Astrophysics and Astronomy, as a proceeding paper of the conference "Multiwavelength Variability of Blazars", Guangzhou, China, September 22-24, 201

    Robot-assisted radical prostatectomy in Hong Kong: a review of 235 cases

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    Flexible Dye-Sensitized Solar Cell Based on Vertical ZnO Nanowire Arrays

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    Flexible dye-sensitized solar cells are fabricated using vertically aligned ZnO nanowire arrays that are transferred onto ITO-coated poly(ethylene terephthalate) substrates using a simple peel-off process. The solar cells demonstrate an energy conversion efficiency of 0.44% with good bending tolerance. This technique paves a new route for building large-scale cost-effective flexible photovoltaic and optoelectronic devices

    Do oral aluminium phosphate binders cause accumulation of aluminium to toxic levels?

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    <p>Abstract</p> <p>Background</p> <p>Aluminium (Al) toxicity was frequent in the 1980s in patients ingesting Al containing phosphate binders (Alucaps) whilst having HD using water potentially contaminated with Al. The aim of this study was to determine the risk of Al toxicity in HD patients receiving Alucaps but never exposed to contaminated dialysate water.</p> <p>Methods</p> <p>HD patients only treated with Reverse Osmosis(RO) treated dialysis water with either current or past exposure to Alucaps were given standardised DFO tests. Post-DFO serum Al level > 3.0 μmol/L was defined to indicate toxic loads based on previous bone biopsy studies.</p> <p>Results</p> <p>39 patients (34 anuric) were studied. Mean dose of Alucap was 3.5 capsules/d over 23.0 months. Pre-DFO Al levels were > 1.0 μmol/L in only 2 patients and none were > 3.0 μmol/L. No patients had a post DFO Al levels > 3.0 μmol/L. There were no correlations between the serum Al concentrations (pre-, post- or the incremental rise after DFO administration) and the total amount of Al ingested.</p> <p>No patients had unexplained EPO resistance or biochemical evidence of adynamic bone.</p> <p>Conclusions</p> <p>Although this is a small study, oral aluminium exposure was considerable. Yet no patients undergoing HD with RO treated water had evidence of Al toxicity despite doses equivalent to 3.5 capsules of Alucap for 2 years. The relationship between the DFO-Al results and the total amount of Al ingested was weak (R<sup>2 </sup>= 0.07) and not statistically significant. In an era of financial prudence, and in view of the recognised risk of excess calcium loading in dialysis patients, perhaps we should re-evaluate the risk of using Al-based phosphate binders in HD patients who remain uric.</p

    A novel route to the coupling of molecular dynamics and phase-field simulations of crystal growth

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    Molecular dynamic simulations, ab initio (DFT) calculations and experimental evidence suggests that there is a liquid-solid transition region which may be characterised by an order parameter. In this interface region the order parameter is not observed to be symmetrical, rather it tends to be steep on the solid side and exponentially decreasing on the liquid side. The order parameter in phase field computations is, to date, always assumed to give a symmetrical interface region. Hence, we ask how to extend the phase field model to give a profile that fits this data, and how such a model affects the simulation
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