947 resultados para density-dependent model


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The product of the von Hippel-Lindau (VHL) tumor suppressor gene, the gene inactivated in VHL disease and in sporadic clear-cell renal carcinomas, has recently been shown to have as a functional target the transcription elongation complex, elongin (also called SIII). Here it is shown that there is a tightly regulated, cell-density-dependent transport of VHL into and/or out of the nucleus. In densely grown cells, the VHL protein is predominantly in the cytoplasm, whereas in sparse cultures, most of the protein can be detected in the nucleus. We have identified a putative nuclear localization signal in the first 60 and first 28 amino acids of the human and rat VHL protein, respectively. Sequences in the C-terminal region of the VHL protein may also be required for localization to the cytosol. These findings provide the initial indication of a novel cell density-dependent pathway that is responsible for the regulation of VHL cellular localization.

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We examine the transport of methane in microporous carbon by performing equilibrium and nonequilibrium molecular dynamics simulations over a range of pore sizes, densities, and temperatures. We interpret these simulation results using two models of the transport process. At low densities, we consider a molecular flow model, in which intermolecular interactions are neglected, and find excellent agreement between transport diffusion coefficients determined from simulation, and those predicted by the model. Simulation results indicate that the model can be applied up to fluid densities of the order to 0.1-1 nm(-3). Above these densities, we consider a slip flow model, combining hydrodynamic theory with a slip condition at the solid-fluid interface. As the diffusion coefficient at low densities can be accurately determined by the molecular flow model, we also consider a model where the slip condition is supplied by the molecular flow model. We find that both density-dependent models provide a useful means of estimating the transport coefficient that compares well with simulation. (C) 2004 American Institute of Physics.

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Applications of the axisymmetric Boussinesq equation to groundwater hydrology and reservoir engineering have long been recognised. An archetypal example is invasion by drilling fluid into a permeable bed where there is initially no such fluid present, a circumstance of some importance in the oil industry. It is well known that the governing Boussinesq model can be reduced to a nonlinear ordinary differential equation using a similarity variable, a transformation that is valid for a certain time-dependent flux at the origin. Here, a new analytical approximation is obtained for this case. The new solution,, which has a simple form, is demonstrated to be highly accurate. (c) 2005 Elsevier Ltd. All rights reserved.

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The effect of the tumour-forming disease, fibropapillomatosis, on the somatic growth dynamics of green turtles resident in the Pala'au foraging grounds (Moloka'i, Hawai'i) was evaluated using a Bayesian generalised additive mixed modelling approach. This regression model enabled us to account for fixed effects (fibropapilloma tumour severity), nonlinear covariate functional form (carapace size, sampling year) as well as random effects due to individual heterogeneity and correlation between repeated growth measurements on some turtles. Somatic growth rates were found to be nonlinear functions of carapace size and sampling year but were not a function of low-to-moderate tumour severity. On the other hand, growth rates were significantly lower for turtles with advanced fibropapillomatosis, which suggests a limited or threshold-specific disease effect. However, tumour severity was an increasing function of carapace size-larger turtles tended to have higher tumour severity scores, presumably due to longer exposure of larger (older) turtles to the factors that cause the disease. Hence turtles with advanced fibropapillomatosis tended to be the larger turtles, which confounds size and tumour severity in this study. But somatic growth rates for the Pala'au population have also declined since the mid-1980s (sampling year effect) while disease prevalence and severity increased from the mid-1980s before levelling off by the mid-1990s. It is unlikely that this decline was related to the increasing tumour severity because growth rates have also declined over the last 10-20 years for other green turtle populations resident in Hawaiian waters that have low or no disease prevalence. The declining somatic growth rate trends evident in the Hawaiian stock are more likely a density-dependent effect caused by a dramatic increase in abundance by this once-seriously-depleted stock since the mid-1980s. So despite increasing fibropapillomatosis risk over the last 20 years, only a limited effect on somatic growth dynamics was apparent and the Hawaiian green turtle stock continues to increase in abundance.

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We describe methods for estimating the parameters of Markovian population processes in continuous time, thus increasing their utility in modelling real biological systems. A general approach, applicable to any finite-state continuous-time Markovian model, is presented, and this is specialised to a computationally more efficient method applicable to a class of models called density-dependent Markov population processes. We illustrate the versatility of both approaches by estimating the parameters of the stochastic SIS logistic model from simulated data. This model is also fitted to data from a population of Bay checkerspot butterfly (Euphydryas editha bayensis), allowing us to assess the viability of this population. (c) 2006 Elsevier Inc. All rights reserved.

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Background The optimisation and scale-up of process conditions leading to high yields of recombinant proteins is an enduring bottleneck in the post-genomic sciences. Typical experiments rely on varying selected parameters through repeated rounds of trial-and-error optimisation. To rationalise this, several groups have recently adopted the 'design of experiments' (DoE) approach frequently used in industry. Studies have focused on parameters such as medium composition, nutrient feed rates and induction of expression in shake flasks or bioreactors, as well as oxygen transfer rates in micro-well plates. In this study we wanted to generate a predictive model that described small-scale screens and to test its scalability to bioreactors. Results Here we demonstrate how the use of a DoE approach in a multi-well mini-bioreactor permitted the rapid establishment of high yielding production phase conditions that could be transferred to a 7 L bioreactor. Using green fluorescent protein secreted from Pichia pastoris, we derived a predictive model of protein yield as a function of the three most commonly-varied process parameters: temperature, pH and the percentage of dissolved oxygen in the culture medium. Importantly, when yield was normalised to culture volume and density, the model was scalable from mL to L working volumes. By increasing pre-induction biomass accumulation, model-predicted yields were further improved. Yield improvement was most significant, however, on varying the fed-batch induction regime to minimise methanol accumulation so that the productivity of the culture increased throughout the whole induction period. These findings suggest the importance of matching the rate of protein production with the host metabolism. Conclusion We demonstrate how a rational, stepwise approach to recombinant protein production screens can reduce process development time.

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2000 Mathematics Subject Classification: primary: 60J80, 60J85, secondary: 62M09, 92D40

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A semi-quantitative model is put forward elucidating the role of spatial inhomogeneity of charge carrier mobility in organic field-effect transistors. The model, based on electrostatic arguments, allows estimating the effective thickness of the conducting channel and its changes in function of source-drain and gate voltages. Local mobility gradients in the direction perpendicular to the insulator/semiconductor interface translate into voltage dependences of the average carrier mobility in the channel, resulting in positive or negative deviations of current-voltage characteristics from their expected shapes. The proposed effect supplements those described in the literature, i.e., density-dependent mobility of charge carriers, short-channel effects, and contribution of contact resistance.

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Successful conservation of migratory birds demands we understand how habitat factors on the breeding grounds influences breeding success. Multiple factors are known to directly influence breeding success in territorial songbirds. For example, greater food availability and fewer predators can have direct effects on breeding success. However, many of these same habitat factors can also result in higher conspecific density that may ultimately reduce breeding success through density dependence. In this case, there is a negative indirect effect of habitat on breeding success through its effects on conspecific density and territory size. Therefore, a key uncertainty facing land managers is whether important habitat attributes directly influence breeding success or indirectly influence breeding success through territory size. We used radio-telemetry, point-counts, vegetation sampling, predator observations, and insect sampling over two years to provide data on habitat selection of a steeply declining songbird species, the Canada Warbler (Cardellina canadensis). These data were then applied in a hierarchical path modeling framework and an AIC model selection approach to determine the habitat attributes that best predict breeding success. Canada Warblers had smaller territories in areas with high shrub cover, in the presence of red squirrels (Tamiasciurus hudsonicus), at shoreline sites relative to forest-interior sites and as conspecific density increased. Breeding success was lower for birds with smaller territories, which suggests competition for limited food resources, but there was no direct evidence that food availability influenced territory size or breeding success. The negative relationship between shrub cover and territory size in our study may arise because these specific habitat conditions are spatially heterogeneous, whereby individuals pack into patches of preferred breeding habitat scattered throughout the landscape, resulting in reduced territory size and an associated reduction in resource availability per territory. Our results therefore highlight the importance of considering direct and indirect effects for Canada warblers; efforts to increase the amount of breeding habitat may ultimately result in lower breeding success if habitat availability is limited and negative density dependent effects occur.

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A self-consistent relativistic two-fluid model is proposed for one-dimensional electron-ion plasma dynamics. A multiple scales perturbation technique is employed, leading to an evolution equation for the wave envelope, in the form of a nonlinear Schrödinger type equation (NLSE). The inclusion of relativistic effects is shown to introduce density-dependent factors, not present in the non-relativistic case - in the conditions for modulational instability. The role of relativistic effects on the linear dispersion laws and on envelope soliton solutions of the NLSE is discussed.

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Thesis (Ph.D.)--University of Washington, 2016-08

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The use of chemical control measures to reduce the impact of parasite and pest species has frequently resulted in the development of resistance. Thus, resistance management has become a key concern in human and veterinary medicine, and in agricultural production. Although it is known that factors such as gene flow between susceptible and resistant populations, drug type, application methods, and costs of resistance can affect the rate of resistance evolution, less is known about the impacts of density-dependent eco-evolutionary processes that could be altered by drug-induced mortality. The overall aim of this thesis was to take an experimental evolution approach to assess how life history traits respond to drug selection, using a free-living dioecious worm (Caenorhabditis remanei) as a model. In Chapter 2, I defined the relationship between C. remanei survival and Ivermectin dose over a range of concentrations, in order to control the intensity of selection used in the selection experiment described in Chapter 4. The dose-response data were also used to appraise curve-fitting methods, using Akaike Information Criterion (AIC) model selection to compare a series of nonlinear models. The type of model fitted to the dose response data had a significant effect on the estimates of LD50 and LD99, suggesting that failure to fit an appropriate model could give misleading estimates of resistance status. In addition, simulated data were used to establish that a potential cost of resistance could be predicted by comparing survival at the upper asymptote of dose-response curves for resistant and susceptible populations, even when differences were as low as 4%. This approach to dose-response modeling ensures that the maximum amount of useful information relating to resistance is gathered in one study. In Chapter 3, I asked how simulations could be used to inform important design choices used in selection experiments. Specifically, I focused on the effects of both within- and between-line variation on estimated power, when detecting small, medium and large effect sizes. Using mixed-effect models on simulated data, I demonstrated that commonly used designs with realistic levels of variation could be underpowered for substantial effect sizes. Thus, use of simulation-based power analysis provides an effective way to avoid under or overpowering a study designs incorporating variation due to random effects. In Chapter 4, I 3 investigated how Ivermectin dosage and changes in population density affect the rate of resistance evolution. I exposed replicate lines of C. remanei to two doses of Ivermectin (high and low) to assess relative survival of lines selected in drug-treated environments compared to untreated controls over 10 generations. Additionally, I maintained lines where mortality was imposed randomly to control for differences in density between drug treatments and to distinguish between the evolutionary consequences of drug treatment versus ecological processes affected by changes in density-dependent feedback. Intriguingly, both drug-selected and random-mortality lines showed an increase in survivorship when challenged with Ivermectin; the magnitude of this increase varied with the intensity of selection and life-history stage. The results suggest that interactions between density-dependent processes and life history may mediate evolved changes in susceptibility to control measures, which could result in misleading conclusions about the evolution of heritable resistance following drug treatment. In Chapter 5, I investigated whether the apparent changes in drug susceptibility found in Chapter 4 were related to evolved changes in life-history of C. remanei populations after selection in drug-treated and random-mortality environments. Rapid passage of lines in the drug-free environment had no effect on the measured life-history traits. In the drug-free environment, adult size and fecundity of drug-selected lines increased compared to the controls but drug selection did not affect lifespan. In the treated environment, drug-selected lines showed increased lifespan and fecundity relative to controls. Adult size of randomly culled lines responded in a similar way to drug-selected lines in the drug-free environment, but no change in fecundity or lifespan was observed in either environment. The results suggest that life histories of nematodes can respond to selection as a result of the application of control measures. Failure to take these responses into account when applying control measures could result in adverse outcomes, such as larger and more fecund parasites, as well as over-estimation of the development of genetically controlled resistance. In conclusion, my thesis shows that there may be a complex relationship between drug selection, density-dependent regulatory processes and life history of populations challenged with control measures. This relationship could have implications for how resistance is monitored and managed if life histories of parasitic species show such eco-evolutionary responses to drug application.

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The outcome of interspecific hybridization between native and invasive species depends on the relative frequencies of parental taxa and viability of hybrid progeny. We investigated individual and population level consequences of hybridization between the Australian native, Senecio pinnatifolius, and the exotic S. madagascariensis, with AFLP markers and used this information to simulate the expected outcome of hybridization.A high frequency (range 8.3-75.6 %) of hybrids was detected in open pollinated seeds of both species, but mature hybrids were absent from sympatric populations indicating that sympatric populations represent tension zones. A hybridization advantage was observed for S. madagascariensis,where significantly more progeny than expected were sired based on proportional representation of the two species in sympatric populations. Simulations indicated S. pinnatifolius could be replaced in sympatric populations if hybridization was density dependent.For this native-exotic pair, prezygotic isolating barriers are weak, but low hybrid viability maintains a strong postzygotic barrier to introgression. Due to asymmetric hybridization, S. pinnatifolius appears under threat from demographic swamping, and local extinction is possible where it occurs in sympatry with S. madagascariensis.

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During invasion and metastasis, cancer cells interact closely with the extracellular matrix molecules by attachment, degradation, and migration. We demonstrated previously the local degradation of fluorescently labeled gelatin matrix by cancer cells at invasive membrane protrusions, called invadopodia. Using the newly developed quantitative fluorescence-activated cell sorting-phagocytosis assay and image analysis of localized degradation of fluorescently labeled matrix, we document here that degradation and site- specific removal of cross-linked gelatin matrix is correlated with the extent of phagocytosis in human breast cancer cells. A higher phagocytic capacity is generally associated with increasing invasiveness, documented in other invasion and motility assays as well. Gelatin phagocytosis is time and cell density dependent, and it is mediated by the actin cytoskeleton. Most of the intracellular gelatin is routed to actively acidified vesicles, as demonstrated by the fluorescent colocalization of gelatin with acidic vesicles, indicating the intracellular degradation of the phagocytosed matrix in lysosomes. We show here that normal intracellular routing is blocked after treatment with acidification inhibitors. In addition, the need for partial proteolytic degradation of the matrix prior to phagocytosis is demonstrated by the inhibition of gelatin phagocytosis with different serine and metalloproteinase inhibitors and its stimulation by conditioned medium containing the matrix metalloproteinases MMP-2 and MMP-9. Our results demonstrate that phagocytosis of extracellular matrix is an inherent feature of breast tumor cells that correlates with and may even directly contribute to their invasive capacity. This assay is useful for screening and evaluating potential anti-invasive agents because it is fast, reproducible, and versatile.