784 resultados para Class switch recombination


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Crash Rates and Crash Densities on Secondary Roads in Iowa by Functional Class produced by the Iowa Department of Transportation.

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The kinetic domain-growth exponent is studied by Monte Carlo simulation as a function of temperature for a nonconserved order-parameter model. In the limit of zero temperature, the model belongs to the n=(1/4 slow-growth unversality class. This is indicative of a temporal pinning in the domain-boundary network of mixed-, zero-, and finite-curvature boundaries. At finite temperature the growth kinetics is found to cross over to the Allen-Cahn exponent n=(1/2. We obtain that the pinning time of the zero-curvature boundary decreases rapidly with increasing temperature.

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NK cells can kill MHC-different or MHC-deficient but not syngeneic MHC-expressing target cells. This MHC class I-specific tolerance is acquired during NK cell development. MHC recognition by murine NK cells largely depends on clonally distributed Ly49 family receptors, which inhibit NK cell function upon ligand engagement. We investigated whether these receptors play a role for the development of NK cells and provide evidence that the expression of a Ly49 receptor transgene on developing NK cells endowed these cells with a significant developmental advantage over NK cells lacking such a receptor, but only if the relevant MHC ligand was present in the environment. The data suggest that the transgenic Ly49 receptor accelerates and/or rescues the development of NK cells which would otherwise fail to acquire sufficient numbers of self-MHC-specific receptors. Interestingly, the positive effect on NK cell development is most prominent when the MHC ligand is simultaneously present on both hemopoietic and nonhemopoietic cells. These findings correlate with functional data showing that MHC class I ligand on all cells is required to generate functionally mature NK cells capable of reacting to cells lacking the respective MHC ligand. We conclude that the engagement of inhibitory MHC receptors during NK cell development provides signals that are important for further NK cell differentiation and/or maturation.

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In a paper in this week's issue of Science, Voloshin et al. (p. 868) show that a 20-amino acid peptide from RecA, a bacterial protein that repairs and recombines DNA, can mediate DNA strand exchange--one of the functions of the RecA protein. Stasiak discusses why this result is surprising and what the rest of the RecA protein is for.

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Sex chromosomes are expected to evolve suppressed recombination, which leads to degeneration of the Y and heteromorphism between the X and Y. Some sex chromosomes remain homomorphic, however, and the factors that prevent degeneration of the Y in these cases are not well understood. The homomorphic sex chromosomes of the European tree frogs (Hyla spp.) present an interesting paradox. Recombination in males has never been observed in crossing experiments, but molecular data are suggestive of occasional recombination between the X and Y. The hypothesis that these sex chromosomes recombine has not been tested statistically, however, nor has the X-Y recombination rate been estimated. Here, we use approximate Bayesian computation coupled with coalescent simulations of sex chromosomes to quantify X-Y recombination rate from existent data. We find that microsatellite data from H. arborea, H. intermedia and H. molleri support a recombination rate between X and Y that is significantly different from zero. We estimate that rate to be approximately 10(5) times smaller than that between X chromosomes. Our findings support the notion that very low recombination rate may be sufficient to maintain homomorphism in sex chromosomes.

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Soil information is needed for managing the agricultural environment. The aim of this study was to apply artificial neural networks (ANNs) for the prediction of soil classes using orbital remote sensing products, terrain attributes derived from a digital elevation model and local geology information as data sources. This approach to digital soil mapping was evaluated in an area with a high degree of lithologic diversity in the Serra do Mar. The neural network simulator used in this study was JavaNNS and the backpropagation learning algorithm. For soil class prediction, different combinations of the selected discriminant variables were tested: elevation, declivity, aspect, curvature, curvature plan, curvature profile, topographic index, solar radiation, LS topographic factor, local geology information, and clay mineral indices, iron oxides and the normalized difference vegetation index (NDVI) derived from an image of a Landsat-7 Enhanced Thematic Mapper Plus (ETM+) sensor. With the tested sets, best results were obtained when all discriminant variables were associated with geological information (overall accuracy 93.2 - 95.6 %, Kappa index 0.924 - 0.951, for set 13). Excluding the variable profile curvature (set 12), overall accuracy ranged from 93.9 to 95.4 % and the Kappa index from 0.932 to 0.948. The maps based on the neural network classifier were consistent and similar to conventional soil maps drawn for the study area, although with more spatial details. The results show the potential of ANNs for soil class prediction in mountainous areas with lithological diversity.

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We study a class of models of correlated random networks in which vertices are characterized by hidden variables controlling the establishment of edges between pairs of vertices. We find analytical expressions for the main topological properties of these models as a function of the distribution of hidden variables and the probability of connecting vertices. The expressions obtained are checked by means of numerical simulations in a particular example. The general model is extended to describe a practical algorithm to generate random networks with an a priori specified correlation structure. We also present an extension of the class, to map nonequilibrium growing networks to networks with hidden variables that represent the time at which each vertex was introduced in the system.

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In this paper we study under which circumstances there exists a general change of gross variables that transforms any FokkerPlanck equation into another of the OrnsteinUhlenbeck class that, therefore, has an exact solution. We find that any FokkerPlanck equation will be exactly solvable by means of a change of gross variables if and only if the curvature tensor and the torsion tensor associated with the diffusion is zero and the transformed drift is linear. We apply our criteria to the Kubo and Gompertz models.

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SUMMARY: A top scoring pair (TSP) classifier consists of a pair of variables whose relative ordering can be used for accurately predicting the class label of a sample. This classification rule has the advantage of being easily interpretable and more robust against technical variations in data, as those due to different microarray platforms. Here we describe a parallel implementation of this classifier which significantly reduces the training time, and a number of extensions, including a multi-class approach, which has the potential of improving the classification performance. AVAILABILITY AND IMPLEMENTATION: Full C++ source code and R package Rgtsp are freely available from http://lausanne.isb-sib.ch/~vpopovic/research/. The implementation relies on existing OpenMP libraries.

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Contains information to be used by teachers in classrooms including history of the the United States flag, the government of Iowa, the Constitution of Iowa, the birth of Americanism, the Declaration of Independence, the Constitution of the United States, Lincoln's Gettysburg Address.

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Mouse-human chimeric monoclonal antibodies (MAbs) of 3 different human IgG sub-classes directed against carcinoembryonic antigen (CEA) have been produced in SP-0 cells transfected with genomic chimeric DNA. F(ab')2 fragments were obtained by pepsin digestion of the purified chimeric MAbs of human IgG1, IgG2 and IgG4 sub-class and of parental mouse MAb IgG1. The 4 F(ab')2 fragments exhibit similar molecular weight by SDS-PAGE. They were labelled with 125I or 131I and high binding (80 to 87%) to purified unsolubilized CEA was observed. In vivo, double labelling experiments indicate that the longest biological half-life and the highest tumour-localization capacity is obtained with F(ab')2 from chimeric MAb of human IgG2 sub-class, whereas F(ab')2 from chimeric MAb IgG4 give very low values for these 2 parameters. F(ab')2 from chimeric MAb IgG1 and from parental mouse MAb yield intermediate results in vivo. Our findings should help to select the appropriate human IgG sub-class to produce chimeric or reshaped MAb F(ab')2 to be used for tumour detection by immunoscintigraphy and for radioimmunotherapy.

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Previous Iowa DOT sponsored research has shown that some Class C fly ashes are ementitious (because calcium is combined as calcium aluminates) while other Class C ashes containing similar amounts of elemental calcium are not (1). Fly ashes from modern power plants in Iowa contain significant amounts of calcium in their glassy phases, regardless of their cementitious properties. The present research was based on these findings and on the hyphothesis that: attack of the amorphous phase of high calcium fly ash could be initiated with trace additives, thus making calcium available for formation of useful calcium-silicate cements. Phase I research was devoted to finding potential additives through a screening process; the likely chemicals were tested with fly ashes representative of the cementitious and non-cementitious ashes available in the state. Ammonium phosphate, a fertilizer, was found to produce 3,600 psi cement with cementitious Neal #4 fly ash; this strength is roughly equivalent to that of portland cement, but at about one-third the cost. Neal #2 fly ash, a slightly cementitious Class C, was found to respond best with ammonium nitrate; through the additive, a near-zero strength material was transformed into a 1,200 psi cement. The second research phase was directed to optimimizing trace additive concentrations, defining the behavior of the resulting cements, evaluating more comprehensively the fly ashes available in Iowa, and explaining the cement formation mechanisms of the most promising trace additives. X-ray diffraction data demonstrate that both amorphous and crystalline hydrates of chemically enhanced fly ash differ from those of unaltered fly ash hydrates. Calciumaluminum- silicate hydrates were formed, rather than the expected (and hypothesized) calcium-silicate hydrates. These new reaction products explain the observed strength enhancement. The final phase concentrated on laboratory application of the chemically-enhanced fly ash cements to road base stabilization. Emphasis was placed on use of marginal aggregates, such as limestone crusher fines and unprocessed blow sand. The nature of the chemically modified fly ash cements led to an evaluation of fine grained soil stabilization where a wide range of materials, defined by plasticity index, could be stabilized. Parameters used for evaluation included strength, compaction requirements, set time, and frost resistance.

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Fly ash was used in this evaluation study to replace 15% of the cement in Class C-3 concrete paving mixes. One Class "c" ash from Iowa approved sources was examined in each mix. Substitution rate was based on 1 to 1 basis, for each pound of cement removed 1.0 pound of ash was added. The freeze/thaw durability of the concrete studied was not adversely affected by the presence of fly ash. This study reveals that the durability of the concrete test specimens made with Class II durability aggregates was slightly increased in all cases by the substitution of cement with 15% Class "c" fly ash. In all cases durability factors either remained the same or slightly improved except for one case where the durability factor decreased from 36 to 34. The expansion decreased in all cases.