931 resultados para Model free kinetics
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Folding of the Tetrahymena self-splicing RNA into its active conformation involves a set of discrete intermediate states. The Mg2+-dependent equilibrium transition from the intermediates to the native structure is more cooperative than the formation of the intermediates from the unfolded states. We show that the degree of cooperativity is linked to the free energy of each transition and that the rate of the slow transition from the intermediates to the native state decreases exponentially with increasing Mg2+ concentration. Monovalent salts, which stabilize the folded RNA nonspecifically, induce states that fold in less than 30 s after Mg2+ is added to the RNA. A simple model is proposed that predicts the folding kinetics from the Mg2+-dependent change in the relative stabilities of the intermediate and native states.
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Intramolecular chain diffusion is an elementary process in the conformational fluctuations of the DNA hairpin-loop. We have studied the temperature and viscosity dependence of a model DNA hairpin-loop by FRET (fluorescence resonance energy transfer) fluctuation spectroscopy (FRETfs). Apparent thermodynamic parameters were obtained by analyzing the correlation amplitude through a two-state model and are consistent with steady-state fluorescence measurements. The kinetics of closing the loop show non-Arrhenius behavior, in agreement with theoretical prediction and other experimental measurements on peptide folding. The fluctuation rates show a fractional power dependence (β = 0.83) on the solution viscosity. A much slower intrachain diffusion coefficient in comparison to that of polypeptides was derived based on the first passage time theory of SSS [Szabo, A., Schulten, K. & Schulten, Z. (1980) J. Chem. Phys. 72, 4350–4357], suggesting that intrachain interactions, especially stacking interaction in the loop, might increase the roughness of the free energy surface of the DNA hairpin-loop.
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Understanding the mechanism of protein secondary structure formation is an essential part of the protein-folding puzzle. Here, we describe a simple statistical mechanical model for the formation of a β-hairpin, the minimal structural element of the antiparallel β-pleated sheet. The model accurately describes the thermodynamic and kinetic behavior of a 16-residue, β-hairpin-forming peptide, successfully explaining its two-state behavior and apparent negative activation energy for folding. The model classifies structures according to their backbone conformation, defined by 15 pairs of dihedral angles, and is further simplified by considering only the 120 structures with contiguous stretches of native pairs of backbone dihedral angles. This single sequence approximation is tested by comparison with a more complete model that includes the 215 possible conformations and 15 × 215 possible kinetic transitions. Finally, we use the model to predict the equilibrium unfolding curves and kinetics for several variants of the β-hairpin peptide.
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Scrapie is a transmissible neurodegenerative disease that appears to result from an accumulation in the brain of an abnormal protease-resistant isoform of prion protein (PrP) called PrPsc. Conversion of the normal, protease-sensitive form of PrP (PrPc) to protease-resistant forms like PrPsc has been demonstrated in a cell-free reaction composed largely of hamster PrPc and PrPsc. We now report studies of the species specificity of this cell-free reaction using mouse, hamster, and chimeric PrP molecules. Combinations of hamster PrPc with hamster PrPsc and mouse PrPc with mouse PrPsc resulted in the conversion of PrPc to protease-resistant forms. Protease-resistant PrP species were also generated in the nonhomologous reaction of hamster PrPc with mouse PrPsc, but little conversion was observed in the reciprocal reaction. Glycosylation of the PrPc precursors was not required for species specificity in the conversion reaction. The relative conversion efficiencies correlated with the relative transmissibilities of these strains of scrapie between mice and hamsters. Conversion experiments performed with chimeric mouse/hamster PrPc precursors indicated that differences between PrPc and PrPsc at residues 139, 155, and 170 affected the conversion efficiency and the size of the resultant protease-resistant PrP species. We conclude that there is species specificity in the cell-free interactions that lead to the conversion of PrPc to protease-resistant forms. This specificity may be the molecular basis for the barriers to interspecies transmission of scrapie and other transmissible spongiform encephalopathies in vivo.
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Support for this work was provided by PROMETEO/2009/043/FEDER of Generalitat Valenciana (Spain) and CTQ2008-05520 (Spanish MCI/research).
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The Free Core Nutation (FCN) is a free mode of the Earth's rotation caused by the different material characteristics of the Earth's core and mantle. This causes the rotational axes of those layers to slightly diverge from each other, resulting in a wobble of the Earth's rotation axis comparable to nutations. In this paper we focus on estimating empirical FCN models using the observed nutations derived from the VLBI sessions between 1993 and 2013. Assuming a fixed value for the oscillation period, the time-variable amplitudes and phases are estimated by means of multiple sliding window analyses. The effects of using different a priori Earth Rotation Parameters (ERP) in the derivation of models are also addressed. The optimal choice of the fundamental parameters of the model, namely the window width and step-size of its shift, is searched by performing a thorough experimental analysis using real data. The former analyses lead to the derivation of a model with a temporal resolution higher than the one used in the models currently available, with a sliding window reduced to 400 days and a day-by-day shift. It is shown that this new model increases the accuracy of the modeling of the observed Earth's rotation. Besides, empirical models determined from USNO Finals as a priori ERP present a slightly lower Weighted Root Mean Square (WRMS) of residuals than IERS 08 C04 along the whole period of VLBI observations, according to our computations. The model is also validated through comparisons with other recognized models. The level of agreement among them is satisfactory. Let us remark that our estimates give rise to the lowest residuals and seem to reproduce the FCN signal in more detail.
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The appealing feature of the arbitrage-free Nelson-Siegel model of the yield curve is the ability to capture movements in the yield curve through readily interpretable shifts in its level, slope or curvature, all within a dynamic arbitrage-free framework. To ensure that the level, slope and curvature factors evolve so as not to admit arbitrage, the model introduces a yield-adjustment term. This paper shows how the yield-adjustment term can also be decomposed into the familiar level, slope and curvature elements plus some additional readily interpretable shape adjustments. This means that, even in an arbitrage-free setting, it continues to be possible to interpret movements in the yield curve in terms of level, slope and curvature influences. © 2014 © 2014 Taylor & Francis.
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In studies of complex heterogeneous networks, particularly of the Internet, significant attention was paid to analysing network failures caused by hardware faults or overload. There network reaction was modelled as rerouting of traffic away from failed or congested elements. Here we model network reaction to congestion on much shorter time scales when the input traffic rate through congested routes is reduced. As an example we consider the Internet where local mismatch between demand and capacity results in traffic losses. We describe the onset of congestion as a phase transition characterised by strong, albeit relatively short-lived, fluctuations of losses caused by noise in input traffic and exacerbated by the heterogeneous nature of the network manifested in a power-law load distribution. The fluctuations may result in the network strongly overreacting to the first signs of congestion by significantly reducing input traffic along the communication paths where congestion is utterly negligible. © 2013 IEEE.
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Recent changes to the legislation on chemicals and cosmetics testing call for a change in the paradigm regarding the current 'whole animal' approach for identifying chemical hazards, including the assessment of potential neurotoxins. Accordingly, since 2004, we have worked on the development of the integrated co-culture of post-mitotic, human-derived neurons and astrocytes (NT2.N/A), for use as an in vitro functional central nervous system (CNS) model. We have used it successfully to investigate indicators of neurotoxicity. For this purpose, we used NT2.N/A cells to examine the effects of acute exposure to a range of test chemicals on the cellular release of brain-derived neurotrophic factor (BDNF). It was demonstrated that the release of this protective neurotrophin into the culture medium (above that of control levels) occurred consistently in response to sub-cytotoxic levels of known neurotoxic, but not non-neurotoxic, chemicals. These increases in BDNF release were quantifiable, statistically significant, and occurred at concentrations below those at which cell death was measureable, which potentially indicates specific neurotoxicity, as opposed to general cytotoxicity. The fact that the BDNF immunoassay is non-invasive, and that NT2.N/A cells retain their functionality for a period of months, may make this system useful for repeated-dose toxicity testing, which is of particular relevance to cosmetics testing without the use of laboratory animals. In addition, the production of NT2.N/A cells without the use of animal products, such as fetal bovine serum, is being explored, to produce a fully-humanised cellular model.
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The role of computer modeling has grown recently to integrate itself as an inseparable tool to experimental studies for the optimization of automotive engines and the development of future fuels. Traditionally, computer models rely on simplified global reaction steps to simulate the combustion and pollutant formation inside the internal combustion engine. With the current interest in advanced combustion modes and injection strategies, this approach depends on arbitrary adjustment of model parameters that could reduce credibility of the predictions. The purpose of this study is to enhance the combustion model of KIVA, a computational fluid dynamics code, by coupling its fluid mechanics solution with detailed kinetic reactions solved by the chemistry solver, CHEMKIN. As a result, an engine-friendly reaction mechanism for n-heptane was selected to simulate diesel oxidation. Each cell in the computational domain is considered as a perfectly-stirred reactor which undergoes adiabatic constant- volume combustion. The model was applied to an ideally-prepared homogeneous- charge compression-ignition combustion (HCCI) and direct injection (DI) diesel combustion. Ignition and combustion results show that the code successfully simulates the premixed HCCI scenario when compared to traditional combustion models. Direct injection cases, on the other hand, do not offer a reliable prediction mainly due to the lack of turbulent-mixing model, inherent in the perfectly-stirred reactor formulation. In addition, the model is sensitive to intake conditions and experimental uncertainties which require implementation of enhanced predictive tools. It is recommended that future improvements consider turbulent-mixing effects as well as optimization techniques to accurately simulate actual in-cylinder process with reduced computational cost. Furthermore, the model requires the extension of existing fuel oxidation mechanisms to include pollutant formation kinetics for emission control studies.
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This paper provides an agent-based software exploration of the wellknown free market efficiency/equality trade-off. Our study simulates the interaction of agents producing, trading and consuming goods in the presence of different market structures, and looks at how efficient the producers/consumers mapping turn out to be as well as the resulting distribution of welfare among agents at the end of an arbitrarily large number of iterations. Two market mechanisms are compared: the competitive market (a double auction market in which agents outbid each other in order to buy and sell products) and the random one (in which products are allocated randomly). Our results confirm that the superior efficiency of the competitive market (an effective and never stopping producers/consumers mapping and a superior aggregative welfare) comes at a very high price in terms of inequality (above all when severe budget constraints are in play).
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In the presented thesis work, the meshfree method with distance fields was coupled with the lattice Boltzmann method to obtain solutions of fluid-structure interaction problems. The thesis work involved development and implementation of numerical algorithms, data structure, and software. Numerical and computational properties of the coupling algorithm combining the meshfree method with distance fields and the lattice Boltzmann method were investigated. Convergence and accuracy of the methodology was validated by analytical solutions. The research was focused on fluid-structure interaction solutions in complex, mesh-resistant domains as both the lattice Boltzmann method and the meshfree method with distance fields are particularly adept in these situations. Furthermore, the fluid solution provided by the lattice Boltzmann method is massively scalable, allowing extensive use of cutting edge parallel computing resources to accelerate this phase of the solution process. The meshfree method with distance fields allows for exact satisfaction of boundary conditions making it possible to exactly capture the effects of the fluid field on the solid structure.