196 resultados para Contact models


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To study the interaction of the TCR with its ligand, the complex of a MHC molecule and an antigenic peptide, we modified a TCR contact residue of a H-2Kd-restricted antigenic peptide with photoreactive 4-azidobenzoic acid. The photoreactive group was a critical component of the epitope recognized by CTL clones derived from mice immunized with such a peptide derivative. The majority of these clones expressed V beta 1-encoded beta chains that were paired with J alpha TA28-encoded alpha chains. For one of these TCR, the photoaffinity labeled sites were mapped on the alpha chain as a J alpha TA28-encoded tryptophan and on the beta chain as a residue of the C' strand of V beta 1. Molecular modeling of this TCR suggested the presence of a hydrophobic pocket that harbors this tryptophan as well as a tyrosine on the C' strand of V beta 1 between which the photoreactive side chain inserts. It is concluded that this avid binding principle may account for the preferential selection of V beta 1 and J alpha TA28-encoded TCR.

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In this research, we analyse the contact-specific mean of the final cooperation probability, distinguishing on the one hand between contacts with household reference persons and with other eligible household members, and on the other hand between first and later contacts. Data comes from two Swiss Household Panel surveys. The interviewer-specific variance is higher for first contacts, especially in the case of the reference person. For later contacts with the reference person, the contact-specific variance dominates. This means that interaction effects and situational factors are decisive. The contact number has negative effects on the performance of contacts with the reference person, positive in the case of other persons. Also time elapsed since the previous contact has negative effects in the case of reference persons. The result of the previous contact has strong effects, especially in the case of the reference person. These findings call for a quick completion of the household grid questionnaire, assigning the best interviewers to conducting the first contact. While obtaining refusals has negative effects, obtaining other contact results has only weak effects on the interviewer's subsequent contact outcome. Using the same interviewer for contacts has no positive effects.

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Over the last decade, the development of statistical models in support of forensic fingerprint identification has been the subject of increasing research attention, spurned on recently by commentators who claim that the scientific basis for fingerprint identification has not been adequately demonstrated. Such models are increasingly seen as useful tools in support of the fingerprint identification process within or in addition to the ACE-V framework. This paper provides a critical review of recent statistical models from both a practical and theoretical perspective. This includes analysis of models of two different methodologies: Probability of Random Correspondence (PRC) models that focus on calculating probabilities of the occurrence of fingerprint configurations for a given population, and Likelihood Ratio (LR) models which use analysis of corresponding features of fingerprints to derive a likelihood value representing the evidential weighting for a potential source.

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Early detection of landslide surface deformation with 3D remote sensing techniques, as TLS, has become a great challenge during last decade. To improve our understanding of landslide deformation, a series of analogue simulation have been carried out on non-rigid bodies coupled with 3D digitizer. All these experiments have been carried out under controlled conditions, as water level and slope angle inclination. We were able to follow 3D surface deformation suffered by complex landslide bodies from precursory deformation still larger failures. These experiments were the basis for the development of a new algorithm for the quantification of surface deformation using automatic tracking method on discrete points of the slope surface. To validate the algorithm, comparisons were made between manually obtained results and algorithm surface displacement results. Outputs will help in understanding 3D deformation during pre-failure stages and failure mechanisms, which are fundamental aspects for future implementation of 3D remote sensing techniques in early warning systems.

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We analyze interviewer related nonresponse differences in face-to-face surveys distinguishing three types of interviewers: those who have previous experience with the same high standard cross-sectional survey ("experienced"), those who were chosen by the survey agency to complete refusal conversions ("seniors"), and usual interviewers. The nonresponse components are obtaining household contact, target person contact, and target person cooperation. In addition we examine if interviewer homogeneity with respect to these components is different across the three interviewer groups. Data come from the European Social Survey (ESS) contact forms from four countries which participated during the three rounds 2002/04/06 and used the same survey agency that in turn used to some extent the same interviewers. To analyze interviewer effects, we use discrete two-level models. We find some evidence of better performance by both senior and experienced interviewers and indications of greater homogeneity for nonresponse components, especially for those that contain room for improvement. Surprisingly, the senior interviewers do not outperform those experienced. We conclude that survey agencies should make more efforts to decrease the comparatively high interviewer turnover.

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CD4(+)CD25(+)Foxp3(+) regulatory T cells (Treg) play an important role in the induction and maintenance of immune tolerance. Although adoptive transfer of bulk populations of Treg can prevent or treat T cell-mediated inflammatory diseases and transplant allograft rejection in animal models, optimal Treg immunotherapy in humans would ideally use antigen-specific rather than polyclonal Treg for greater specificity of regulation and avoidance of general suppression. However, no robust approaches have been reported for the generation of human antigen-specific Treg at a practical scale for clinical use. Here, we report a simple and cost-effective novel method to rapidly induce and expand large numbers of functional human alloantigen-specific Treg from antigenically naive precursors in vitro using allogeneic nontransformed B cells as stimulators. By this approach naive CD4(+)CD25(-) T cells could be expanded 8-fold into alloantigen-specific Treg after 3 weeks of culture without any exogenous cytokines. The induced alloantigen-specific Treg were CD45RO(+)CCR7(-) memory cells, and had a CD4(high), CD25(+), Foxp3(+), and CD62L (L-selectin)(+) phenotype. Although these CD4(high)CD25(+)Foxp3(+) alloantigen-specific Treg had no cytotoxic capacity, their suppressive function was cell-cell contact dependent and partially relied on cytotoxic T lymphocyte antigen-4 expression. This approach may accelerate the clinical application of Treg-based immunotherapy in transplantation and autoimmune diseases.

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Many cells are able to orient themselves in a non-uniform environment by responding to localized cues. This leads to a polarized cellular response, where the cell can either grow or move towards the cue source. Fungal haploid cells secrete pheromones to signal mating, and respond by growing a mating projection towards a potential mate. Upon contact of the two partner cells, these fuse to form a diploid zygote. In this review, we present our current knowledge on the processes of mating signalling, pheromone-dependent polarized growth and cell fusion in Saccharomyces cerevisiae and Schizosaccharomyces pombe, two highly divergent ascomycete yeast models. While the global architecture of the mating response is very similar between these two species, they differ significantly both in their mating physiologies and in the molecular connections between pheromone perception and downstream responses. The use of both yeast models helps enlighten both conserved solutions and species-specific adaptations to a general biological problem.

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Generation of fluids during metamorphism can significantly influence the fluid overpressure, and thus the fluid flow in metamorphic terrains. There is currently a large focus on developing numerical reactive transport models, and with it follows the need for analytical solutions to ensure correct numerical implementation. In this study, we derive both analytical and numerical solutions to reaction-induced fluid overpressure, coupled to temperature and fluid flow out of the reacting front. All equations are derived from basic principles of conservation of mass, energy and momentum. We focus on contact metamorphism, where devolatilization reactions are particularly important owing to high thermal fluxes allowing large volumes of fluids to be rapidly generated. The analytical solutions reveal three key factors involved in the pressure build-up: (i) The efficiency of the devolatilizing reaction front (pressure build-up) relative to fluid flow (pressure relaxation), (ii) the reaction temperature relative to the available heat in the system and (iii) the feedback of overpressure on the reaction temperature as a function of the Clapeyron slope. Finally, we apply the model to two geological case scenarios. In the first case, we investigate the influence of fluid overpressure on the movement of the reaction front and show that it can slow down significantly and may even be terminated owing to increased effective reaction temperature. In the second case, the model is applied to constrain the conditions for fracturing and inferred breccia pipe formation in organic-rich shales owing to methane generation in the contact aureole.

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Background Multiple logistic regression is precluded from many practical applications in ecology that aim to predict the geographic distributions of species because it requires absence data, which are rarely available or are unreliable. In order to use multiple logistic regression, many studies have simulated "pseudo-absences" through a number of strategies, but it is unknown how the choice of strategy influences models and their geographic predictions of species. In this paper we evaluate the effect of several prevailing pseudo-absence strategies on the predictions of the geographic distribution of a virtual species whose "true" distribution and relationship to three environmental predictors was predefined. We evaluated the effect of using a) real absences b) pseudo-absences selected randomly from the background and c) two-step approaches: pseudo-absences selected from low suitability areas predicted by either Ecological Niche Factor Analysis: (ENFA) or BIOCLIM. We compared how the choice of pseudo-absence strategy affected model fit, predictive power, and information-theoretic model selection results. Results Models built with true absences had the best predictive power, best discriminatory power, and the "true" model (the one that contained the correct predictors) was supported by the data according to AIC, as expected. Models based on random pseudo-absences had among the lowest fit, but yielded the second highest AUC value (0.97), and the "true" model was also supported by the data. Models based on two-step approaches had intermediate fit, the lowest predictive power, and the "true" model was not supported by the data. Conclusion If ecologists wish to build parsimonious GLM models that will allow them to make robust predictions, a reasonable approach is to use a large number of randomly selected pseudo-absences, and perform model selection based on an information theoretic approach. However, the resulting models can be expected to have limited fit.

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Cloud computing and its three facets (Software as a Service (SaaS), Platform as a Service (PaaS), and Infrastructure as a Service (IaaS)) are terms that denote new developments in the software industry. In particular, PaaS solutions, also referred to as cloud platforms, are changing the way software is being produced, distributed, consumed, and priced. Software vendors have started considering cloud platforms as a strategic option but are battling to redefine their offerings to embrace PaaS. In contrast to SaaS and IaaS, PaaS allows for value co-creation with partners to develop complementary components and applications. It thus requires multisided business models that bring together two or more distinct customer segments. Understanding how to design PaaS business models to establish a flourishing ecosystem is crucial for software vendors. This doctoral thesis aims to address this issue in three interrelated research parts. First, based on case study research, the thesis provides a deeper understanding of current PaaS business models and their evolution. Second, it analyses and simulates consumers' preferences regarding PaaS business models, using a conjoint approach to find out what determines the choice of cloud platforms. Finally, building on the previous research outcomes, the third part introduces a design theory for the emerging class of PaaS business models, which is grounded on an extensive action design research study with a large European software vendor. Understanding PaaS business models from a market as well as a consumer perspective will, together with the design theory, inform and guide decision makers in their business model innovation plans. It also closes gaps in the research related to PaaS business model design and more generally related to platform business models.

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Analyses of mitochondrial DNA (mtDNA) control region polymorphism and of variation at 10 nuclear microsatellite loci were used to investigate the mechanisms and genetic consequences of postglacial expansion of Myotis myotis in Europe. Initial sampling consisted of 480 bats genotyped in 24 nursery colonies arranged along a transect of approximately 3000 km. The phylogeographical survey based on mtDNA sequences revealed the existence of major genetic subdivisions across this area, with several suture zones between haplogroups. Such zones of secondary contact were found in the Alps and Rhodopes, whereas other potential barriers to gene flow, like the Pyrenees, did not coincide with genetic discontinuities. Areas of population admixture increased locally the genetic diversity of colonies, which confounded the northward decrease in nucleotide diversity predicted using classical models of postglacial range expansion. However, when analyses were restricted to a subset of 15 nurseries originating from a single presumed glacial refugium, mtDNA polymorphism did indeed support a northwards decrease in diversity. Populations were also highly structured (PhiST = 0.384). Conversely, the same subset of colonies showed no significant latitudinal decrease in microsatellite diversity and much less population structure (FST = 0.010), but pairwise genetic differentiation at these nuclear markers was strongly correlated with increasing geographical distance. Together, this evidence suggests that alleles carried via male bats have maintained enough nuclear gene flow to counteract the effects of recurrent bottlenecks generally associated with recolonization processes. As females are highly philopatric, we argue that the maternally transmitted mtDNA marker better reflects the situation of past, historical gene flow, whereas current levels of gene flow are better reflected by microsatellite markers.

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Species range shifts in response to climate and land use change are commonly forecasted with species distribution models based on species occurrence or abundance data. Although appealing, these models ignore the genetic structure of species, and the fact that different populations might respond in different ways because of adaptation to their environment. Here, we introduced ancestry distribution models, that is, statistical models of the spatial distribution of ancestry proportions, for forecasting intra-specific changes based on genetic admixture instead of species occurrence data. Using multi-locus genotypes and extensive geographic coverage of distribution data across the European Alps, we applied this approach to 20 alpine plant species considering a global increase in temperature from 0.25 to 4 °C. We forecasted the magnitudes of displacement of contact zones between plant populations potentially adapted to warmer environments and other populations. While a global trend of movement in a north-east direction was predicted, the magnitude of displacement was species-specific. For a temperature increase of 2 °C, contact zones were predicted to move by 92 km on average (minimum of 5 km, maximum of 212 km) and by 188 km for an increase of 4 °C (minimum of 11 km, maximum of 393 km). Intra-specific turnover-measuring the extent of change in global population genetic structure-was generally found to be moderate for 2 °C of temperature warming. For 4 °C of warming, however, the models indicated substantial intra-specific turnover for ten species. These results illustrate that, in spite of unavoidable simplifications, ancestry distribution models open new perspectives to forecast population genetic changes within species and complement more traditional distribution-based approaches.

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Gene-on-gene regulations are key components of every living organism. Dynamical abstract models of genetic regulatory networks help explain the genome's evolvability and robustness. These properties can be attributed to the structural topology of the graph formed by genes, as vertices, and regulatory interactions, as edges. Moreover, the actual gene interaction of each gene is believed to play a key role in the stability of the structure. With advances in biology, some effort was deployed to develop update functions in Boolean models that include recent knowledge. We combine real-life gene interaction networks with novel update functions in a Boolean model. We use two sub-networks of biological organisms, the yeast cell-cycle and the mouse embryonic stem cell, as topological support for our system. On these structures, we substitute the original random update functions by a novel threshold-based dynamic function in which the promoting and repressing effect of each interaction is considered. We use a third real-life regulatory network, along with its inferred Boolean update functions to validate the proposed update function. Results of this validation hint to increased biological plausibility of the threshold-based function. To investigate the dynamical behavior of this new model, we visualized the phase transition between order and chaos into the critical regime using Derrida plots. We complement the qualitative nature of Derrida plots with an alternative measure, the criticality distance, that also allows to discriminate between regimes in a quantitative way. Simulation on both real-life genetic regulatory networks show that there exists a set of parameters that allows the systems to operate in the critical region. This new model includes experimentally derived biological information and recent discoveries, which makes it potentially useful to guide experimental research. The update function confers additional realism to the model, while reducing the complexity and solution space, thus making it easier to investigate.