945 resultados para Stable


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Transient and continuous recombinant protein expression by HEK cells was evaluated in a perfused monolithic bioreactor. Highly porous synthetic cryogel scaffolds (10ml bed volume) were characterised by scanning electron microscopy and tested as cell substrates. Efficient seeding was achieved (94% inoculum retained, with 91-95% viability). Metabolite monitoring indicated continuous cell growth, and endpoint cell density was estimated by genomic DNA quantification to be 5.2x108, 1.1x109 and 3.5x1010 at day 10, 14 and 18. Culture of stably transfected cells allowed continuous production of the Drosophila cytokine Spätzle by the bioreactor at the same rate as in monolayer culture (total 1.2 mg at d18) and this protein was active. In transient transfection experiments more protein was produced per cell compared with monolayer culture. Confocal microscopy confirmed homogenous GFP expression after transient transfection within the bioreactor. Monolithic bioreactors are thus shown to be a flexible and powerful tool for manufacturing recombinant proteins.

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The stable signal peptide (SSP) of the lymphocytic choriomeningitis virus surface glycoprotein precursor has several unique characteristics. The SSP is unusually long, at 58 amino acids, and contains two hydrophobic domains, and its sequence is highly conserved among both Old and New World arenaviruses. To better understand the functions of the SSP, a panel of point and deletion mutants was created by in vitro mutagenesis to target the highly conserved elements within the SSP. We were also able to confirm critical residues required for separate SSP functions by trans-complementation. Using these approaches, it was possible to resolve functional domains of the SSP. In characterizing our SSP mutants, we discovered that the SSP is involved in several distinct functions within the viral life cycle, beyond translocation of the viral surface glycoprotein precursor into the endoplasmic reticulum lumen. The SSP is required for efficient glycoprotein expression, posttranslational maturation cleavage of GP1 and GP2 by SKI-1/S1P protease, glycoprotein transport to the cell surface plasma membrane, formation of infectious virus particles, and acid pH-dependent glycoprotein-mediated cell fusion.

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A prerequisite for the enrichment of antibodies screened from phage display libraries is their stable expression on a phage during multiple selection rounds. Thus, if stringent panning procedures are employed, selection is simultaneously driven by antigen affinity, stability and solubility. To take advantage of robust pre-selected scaffolds of such molecules, we grafted single-chain Fv (scFv) antibodies, previously isolated from a human phage display library after multiple rounds of in vitro panning on tumor cells, with the specificity of the clinically established murine monoclonal anti-CD22 antibody RFB4. We show that a panel of grafted scFvs retained the specificity of the murine monoclonal antibody, bound to the target antigen with high affinity (6.4-9.6 nM), and exhibited exceptional biophysical stability with retention of 89-93% of the initial binding activity after 6 days of incubation in human serum at 37degreesC. Selection of stable human scaffolds with high sequence identity to both the human germline and the rodent frameworks required only a small number of murine residues to be retained within the human frameworks in order to maintain the structural integrity of the antigen binding site. We expect this approach may be applicable for the rapid generation of highly stable humanized antibodies with low immunogenic potential.

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A colloidal stable silica-encapsulated magnetic nano-composite of a controlled dimension is, for the first time, employed to carry beta-lactamase via chemical linkage on the silica overlayer: activity study reflects that this new type of immobilisation allows site (enzyme) isolation, accessibility as good as free enzyme and recovery & reusability upon application of magnetic separation.

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Two dipeptides containing an N-terminally positioned omega-amino acid residue (beta-alanine/delta-amino valeric acid) self-assembles to form nanotubes in the solid state as well as in aqueous solution. In spite of having hollow nanotubular structures in the solid state and in solution, their self-assembling nature in these two states are different and this leads to the formation of different internal diameters of these nanotubes in solution and in solid state structure. These nanotubes are stable proteolytically, thermally, and over a wide range of pH values (1-13). The role of water molecules in nanotube formation has been investigated in the solid state. These nanotubes can be considered as a new class of dipeptide nanotubes as they are consisting of N-terminally located protease resistant omega-amino acid residues and C-terminally positioned alpha-amino acid residues. These dipeptides can form an interesting class of short peptidic structure that can give rise to stable nanotubular structure upon self-assembly and these nanotubes can be explored in future for potential nanotechnological applications.

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The adsorption of water and coadsorption with oxygen on the missing-row reconstructed Pt{110}-(1x2) surface was studied by using temperature-programmed desorption (TPD) and X-ray photoelectron spectroscopy. Coadsorbed oxygen below saturation (<0.65 +/- 0.05 ML) leads to the formation of 014, which occupies sites near the ridge Pt atoms, In contrast to the more closely packed Pt{111} Surface, OH appears not to form hydrogen bonds with coadsorbed water molecules and is stable after the desorption of water tip to about 205 K (as determined by TPD). Because OH and atomic oxygen compete for adsorption sites, water dissociation is only observed for oxygen coverages below saturation. In the absence of coadsorbed oxygen, water stays intact at all temperatures and forms a strongly bound layer of 2 ML coverage oil the clean Pt{110}-(1x2) surface at temperatures between 140 and 175 K.

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As we move through the world, our eyes acquire a sequence of images. The information from this sequence is sufficient to determine the structure of a three-dimensional scene, up to a scale factor determined by the distance that the eyes have moved [1, 2]. Previous evidence shows that the human visual system accounts for the distance the observer has walked [3,4] and the separation of the eyes [5-8] when judging the scale, shape, and distance of objects. However, in an immersive virtual-reality environment, observers failed to notice when a scene expanded or contracted, despite having consistent information about scale from both distance walked and binocular vision. This failure led to large errors in judging the size of objects. The pattern of errors cannot be explained by assuming a visual reconstruction of the scene with an incorrect estimate of interocular separation or distance walked. Instead, it is consistent with a Bayesian model of cue integration in which the efficacy of motion and disparity cues is greater at near viewing distances. Our results imply that observers are more willing to adjust their estimate of interocular separation or distance walked than to accept that the scene has changed in size.

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An analysis of Stochastic Diffusion Search (SDS), a novel and efficient optimisation and search algorithm, is presented, resulting in a derivation of the minimum acceptable match resulting in a stable convergence within a noisy search space. The applicability of SDS can therefore be assessed for a given problem.

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The binding of NO to iron is involved in the biological function of many heme proteins. Contrary to ligands like CO and O-2, which only bind to ferrous (Fe-II) iron, NO binds to both ferrous and ferric (Fe-II) iron. In a particular protein, the natural oxidation state can therefore be expected to be tailored to the required function. Herein, we present an ob initio potential-energy surface for ferric iron interacting with NO. This potential-energy surface exhibits three minima corresponding to eta'-NO coordination (the global minimum), eta(1)-ON coordination and eta(2) coordination. This contrasts with the potential-energy surface for Fe-II-NO, which ex- hibits only two minima (the eta(2) coordination mode for Fe-II is a transition state, not a minimum). In addition, the binding energies of NO are substantially larger for Fe-III than for Fe-II. We have performed molecular dynamics simulations for NO bound to ferric myoglobin (Mb(III)) and compare these with results obtained for Mb(II). Over the duration of our simulations (1.5 ns), all three binding modes are found to be stable at 200 K and transiently stable at 300 K, with eventual transformation to the eta(1)-NO global-minimum conformation. We discuss the implication of these results related to studies of rebinding processes in myoglobin.

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In this paper stability of one-step ahead predictive controllers based on non-linear models is established. It is shown that, under conditions which can be fulfilled by most industrial plants, the closed-loop system is robustly stable in the presence of plant uncertainties and input–output constraints. There is no requirement that the plant should be open-loop stable and the analysis is valid for general forms of non-linear system representation including the case out when the problem is constraint-free. The effectiveness of controllers designed according to the algorithm analyzed in this paper is demonstrated on a recognized benchmark problem and on a simulation of a continuous-stirred tank reactor (CSTR). In both examples a radial basis function neural network is employed as the non-linear system model.

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The last decade has seen the re-emergence of artificial neural networks as an alternative to traditional modelling techniques for the control of nonlinear systems. Numerous control schemes have been proposed and have been shown to work in simulations. However, very few analyses have been made of the working of these networks. The authors show that a receding horizon control strategy based on a class of recurrent networks can stabilise nonlinear systems.

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The main limitation of linearization theory that prevents its application in practical problems is the need for an exact knowledge of the plant. This requirement is eliminated and it is shown that a multilayer network can synthesise the state feedback coefficients that linearize a nonlinear control affine plant. The stability of the linearizing closed loop can be guaranteed if the autonomous plant is asymptotically stable and the state feedback is bounded.

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The Routh-stability method is employed to reduce the order of discrete-time system transfer functions. It is shown that the Routh approximant is well suited to reduce both the denominator and the numerator polynomials, although alternative methods, such as PadÃ�Â(c)-Markov approximation, are also used to fit the model numerator coefficients.

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Metabolic stable isotope labeling is increasingly employed for accurate protein (and metabolite) quantitation using mass spectrometry (MS). It provides sample-specific isotopologues that can be used to facilitate comparative analysis of two or more samples. Stable Isotope Labeling by Amino acids in Cell culture (SILAC) has been used for almost a decade in proteomic research and analytical software solutions have been established that provide an easy and integrated workflow for elucidating sample abundance ratios for most MS data formats. While SILAC is a discrete labeling method using specific amino acids, global metabolic stable isotope labeling using isotopes such as (15)N labels the entire element content of the sample, i.e. for (15)N the entire peptide backbone in addition to all nitrogen-containing side chains. Although global metabolic labeling can deliver advantages with regard to isotope incorporation and costs, the requirements for data analysis are more demanding because, for instance for polypeptides, the mass difference introduced by the label depends on the amino acid composition. Consequently, there has been less progress on the automation of the data processing and mining steps for this type of protein quantitation. Here, we present a new integrated software solution for the quantitative analysis of protein expression in differential samples and show the benefits of high-resolution MS data in quantitative proteomic analyses.

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