996 resultados para Persistence Time


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BACKGROUND: The comparison of complete genomes has revealed surprisingly large numbers of conserved non-protein-coding (CNC) DNA regions. However, the biological function of CNC remains elusive. CNC differ in two aspects from conserved protein-coding regions. They are not conserved across phylum boundaries, and they do not contain readily detectable sub-domains. Here we characterize the persistence length and time of CNC and conserved protein-coding regions in the vertebrate and insect lineages. RESULTS: The persistence length is the length of a genome region over which a certain level of sequence identity is consistently maintained. The persistence time is the evolutionary period during which a conserved region evolves under the same selective constraints.Our main findings are: (i) Insect genomes contain 1.60 times less conserved information than vertebrates; (ii) Vertebrate CNC have a higher persistence length than conserved coding regions or insect CNC; (iii) CNC have shorter persistence times as compared to conserved coding regions in both lineages. CONCLUSION: Higher persistence length of vertebrate CNC indicates that the conserved information in vertebrates and insects is organized in functional elements of different lengths. These findings might be related to the higher morphological complexity of vertebrates and give clues about the structure of active CNC elements.Shorter persistence time might explain the previously puzzling observations of highly conserved CNC within each phylum, and of a lack of conservation between phyla. It suggests that CNC divergence might be a key factor in vertebrate evolution. Further evolutionary studies will help to relate individual CNC to specific developmental processes.

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Studies to select one or more species of coverage plants adapted to Amazonian soil and climate conditions of the Amazon are a promising strategy for the improvement of environmental quality, establishing no-till agricultural systems, and thereby reducing the impacts of monoculture farming. The aim of this study was to assess the persistence time, half-life time, macronutrient content and accumulation, and C:N ratio of straw coverage in a Ultisol in northeastern Pará. Experimental design was randomized blocks with five treatments and five replicates. Plants were harvested after 105 days, growth and biomass production was quantified. After 84 days, soil coverage was 97, 85, 52, 50, and 15% for signalgrass (Brachiaria brizantha) (syn. Urochloa), dense crowngrass (Panicum purpurascens), jack bean (Canavalia ensiformes), pearl millet (Pennisetum americanum) and sunn hemp (Crotalaria juncea,), respectively. Signalgrass yielded the greatest dry matter production (9,696 kg ha-1). It also had high C:N ratio (38.4), long half-life (86.5 days) and a high persistence in the field. Jack bean also showed high dry matter production (8,950 kg ha-1), but it had low C:N ratio (17.4) and lower half-life time (39 days) than the grasses. These attributes indicate that signalgrass and jack bean have a high potential for use as cover plants in no-till agricultural systems in the State of Pará.

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The water rat, Nectomys squamipes, closely involved in schistosomiasis transmission in Brazil, has been found naturally infected simultaneously by Schistosoma mansoni and Echinostoma paraensei. Laboratory experiments were conducted to verify parasitic interaction in concurrent infection. It was replicated four times with a total of 42 water rats and essayed two times with 90 mice pre-infected with E. paraensei. Rodents were divided into three groups in each replication. A wild strain recently isolated from Sumidouro, RJ, and a laboratory strain of S. mansoni from Belo Horizonte (BH) was used. Rats infected with E. paraensei were challenged 4 weeks later with S. mansoni and mice 2 or 6 weeks after the infection with S. mansoni. Necropsy took place 8 weeks following S. mansoni infection. The N. squamipes treatment groups challenged with S. mansoni RJ strain showed a significant decrease (80 and 65%) in the S. mansoni parasite load when compared with their respective control groups. There was a significant change or no change in the hosts challenged with the BH strain. The persistence time of E. paraensei within host was extended in relation to control groups, with a consequent enhancement of the number of recovered worm. An E. paraensei strain-specific influence on S. mansoni parasitism is reported. This paper presents some experimental data about this interaction in N. squamipes and Mus musculus.

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An equation is applied for calculating the expected persistence time of an unstructured population of the white-toothed shrew Crocidura russula from Preverenges, a suburban area in western Switzerland. Population abundance data from March and November between 1977 and 1988 were fit to the logistic density dependence model to estimate mean population growth rate as a function of population density. The variance in mean growth rate was approximated with two different models. The largest estimated persistence time was less than a few decades, the smallest less than 10 years. The results are sensitive to the magnitude of variance in population growth rate. Deviations from the logistic density dependence model in November are quite well explained by weather variables but those in March are uncorrelated with weather variables. Variability in population growth rates measured in winter months may be better explained by behavioural mechanisms. Environmental variability, dispersal of juveniles and refugia within the range of the population may contribute to its long-term survival.

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Gas-liquid mass transfer is an important issue in the design and operation of many chemical unit operations. Despite its importance, the evaluation of gas-liquid mass transfer is not straightforward due to the complex nature of the phenomena involved. In this thesis gas-liquid mass transfer was evaluated in three different gas-liquid reactors in a traditional way by measuring the volumetric mass transfer coefficient (kLa). The studied reactors were a bubble column with a T-junction two-phase nozzle for gas dispersion, an industrial scale bubble column reactor for the oxidation of tetrahydroanthrahydroquinone and a concurrent downflow structured bed.The main drawback of this approach is that the obtained correlations give only the average volumetric mass transfer coefficient, which is dependent on average conditions. Moreover, the obtained correlations are valid only for the studied geometry and for the chemical system used in the measurements. In principle, a more fundamental approach is to estimate the interfacial area available for mass transfer from bubble size distributions obtained by solution of population balance equations. This approach has been used in this thesis by developing a population balance model for a bubble column together with phenomenological models for bubble breakage and coalescence. The parameters of the bubble breakage rate and coalescence rate models were estimated by comparing the measured and calculated bubble sizes. The coalescence models always have at least one experimental parameter. This is because the bubble coalescence depends on liquid composition in a way which is difficult to evaluate using known physical properties. The coalescence properties of some model solutions were evaluated by measuring the time that a bubble rests at the free liquid-gas interface before coalescing (the so-calledpersistence time or rest time). The measured persistence times range from 10 msup to 15 s depending on the solution. The coalescence was never found to be instantaneous. The bubble oscillates up and down at the interface at least a coupleof times before coalescence takes place. The measured persistence times were compared to coalescence times obtained by parameter fitting using measured bubble size distributions in a bubble column and a bubble column population balance model. For short persistence times, the persistence and coalescence times are in good agreement. For longer persistence times, however, the persistence times are at least an order of magnitude longer than the corresponding coalescence times from parameter fitting. This discrepancy may be attributed to the uncertainties concerning the estimation of energy dissipation rates, collision rates and mechanisms and contact times of the bubbles.

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The intraseasonal variability (ISV) of the Indian summer monsoon is dominated by a 30–50 day oscillation between “active” and “break” events of enhanced and reduced rainfall over the subcontinent, respectively. These organized convective events form in the equatorial Indian Ocean and propagate north to India. Atmosphere–ocean coupled processes are thought to play a key role the intensity and propagation of these events. A high-resolution, coupled atmosphere–mixed-layer-oceanmodel is assembled: HadKPP. HadKPP comprises the Hadley Centre Atmospheric Model (HadAM3) and the K Profile Parameterization (KPP) mixed-layer ocean model. Following studies that upper-ocean vertical resolution and sub-diurnal coupling frequencies improve the simulation of ISV in SSTs, KPP is run at 1 m vertical resolution near the surface; the atmosphere and ocean are coupled every three hours. HadKPP accurately simulates the 30–50 day ISV in rainfall and SSTs over India and the Bay of Bengal, respectively, but suffers from low ISV on the equator. This is due to the HadAM3 convection scheme producing limited ISV in surface fluxes. HadKPP demonstrates little of the observed northward propagation of intraseasonal events, producing instead a standing oscillation. The lack of equatorial ISV in convection in HadAM3 constrains the ability of KPP to produce equatorial SST anomalies, which further weakens the ISV of convection. It is concluded that while atmosphere–ocean interactions are undoubtedly essential to an accurate simulation of ISV, they are not a panacea for model deficiencies. In regions where the atmospheric forcing is adequate, such as the Bay of Bengal, KPP produces SST anomalies that are comparable to the Tropical Rainfall Measuring Mission Microwave Imager (TMI) SST analyses in both their magnitude and their timing with respect to rainfall anomalies over India. HadKPP also displays a much-improved phase relationship between rainfall and SSTs over a HadAM3 ensemble forced by observed SSTs, when both are compared to observations. Coupling to mixed-layer models such as KPP has the potential to improve operational predictions of ISV, particularly when the persistence time of SST anomalies is shorter than the forecast lead time.

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The consistency of ensemble forecasts from three global medium-range prediction systems with the observed transition behaviour of a three-cluster model of the North Atlantic eddy-driven jet is examined. The three clusters consist of a mid jet cluster taken to represent an undisturbed jet and south and north jet clusters representing southward and northward shifts of the jet. The ensemble forecasts span a period of three extended winters (October–February) from October 2007–February 2010. The mean probabilities of transitions between the clusters calculated from the ensemble forecasts are compared with those calculated from a 23-extended-winter climatology taken from the European Centre for Medium-Range Weather Forecasts 40-Year Re-analysis (ERA40) dataset. No evidence of a drift with increasing lead time of the ensemble forecast transition probabilities towards values inconsistent with the 23-extended-winter climatology is found. The ensemble forecasts of transition probabilities are found to have positive Brier Skill at 15 day lead times. It is found that for the three-extended-winter forecast set, probabilistic forecasts initialized in the north jet cluster are generally less skilful than those initialized in the other clusters. This is consistent with the shorter persistence time-scale of the north jet cluster observed in the ERA40 23-extended-winter climatology. Copyright © 2011 Royal Meteorological Society

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

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A study of the interference of Zn2+ ions on phenol degradation by Fenton reaction (Fe2+/Fe3(+) + H2O2) is reported. One of the first intermediates formed in the reaction, catechol, can reduce Fe3+ to Fe2+ and, in the presence of H2O2 initiates an efficient catalytic redox cycle. In the initial stages of the reaction, this catechol-mediated cycle becomes the principal route of thermal degradation of phenol and its oxidation products. The Zn2+ ion addition enhances the persistence time of catechol, probably by stabilization of the corresponding semiquinone radical via complexation.

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A study of the interference of Zn2+ ions on phenol degradation by Fenton reaction (Fe2+/Fe3+ + H2O2) is reported. One of the first intermediates formed in the reaction, catechol, can reduce Fe3+ to Fe2+ and, in the presence of H2O2 initiates an efficient catalytic redox cycle. In the initial stages of the reaction, this catechol-mediated cycle becomes the principal route of thermal degradation of phenol and its oxidation products. The Zn2+ ion addition enhances the persistence time of catechol, probably by stabilization of the corresponding semiquinone radical via complexation.

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The birth, death and catastrophe process is an extension of the birth-death process that incorporates the possibility of reductions in population of arbitrary size. We will consider a general form of this model in which the transition rates are allowed to depend on the current population size in an arbitrary manner. The linear case, where the transition rates are proportional to current population size, has been studied extensively. In particular, extinction probabilities, the expected time to extinction, and the distribution of the population size conditional on nonextinction (the quasi-stationary distribution) have all been evaluated explicitly. However, whilst these characteristics are of interest in the modelling and management of populations, processes with linear rate coefficients represent only a very limited class of models. We address this limitation by allowing for a wider range of catastrophic events. Despite this generalisation, explicit expressions can still be found for the expected extinction times.

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The cell:cell bond between an immune cell and an antigen presenting cell is a necessary event in the activation of the adaptive immune response. At the juncture between the cells, cell surface molecules on the opposing cells form non-covalent bonds and a distinct patterning is observed that is termed the immunological synapse. An important binding molecule in the synapse is the T-cell receptor (TCR), that is responsible for antigen recognition through its binding with a major-histocompatibility complex with bound peptide (pMHC). This bond leads to intracellular signalling events that culminate in the activation of the T-cell, and ultimately leads to the expression of the immune eector function. The temporal analysis of the TCR bonds during the formation of the immunological synapse presents a problem to biologists, due to the spatio-temporal scales (nanometers and picoseconds) that compare with experimental uncertainty limits. In this study, a linear stochastic model, derived from a nonlinear model of the synapse, is used to analyse the temporal dynamics of the bond attachments for the TCR. Mathematical analysis and numerical methods are employed to analyse the qualitative dynamics of the nonequilibrium membrane dynamics, with the specic aim of calculating the average persistence time for the TCR:pMHC bond. A single-threshold method, that has been previously used to successfully calculate the TCR:pMHC contact path sizes in the synapse, is applied to produce results for the average contact times of the TCR:pMHC bonds. This method is extended through the development of a two-threshold method, that produces results suggesting the average time persistence for the TCR:pMHC bond is in the order of 2-4 seconds, values that agree with experimental evidence for TCR signalling. The study reveals two distinct scaling regimes in the time persistent survival probability density prole of these bonds, one dominated by thermal uctuations and the other associated with the TCR signalling. Analysis of the thermal fluctuation regime reveals a minimal contribution to the average time persistence calculation, that has an important biological implication when comparing the probabilistic models to experimental evidence. In cases where only a few statistics can be gathered from experimental conditions, the results are unlikely to match the probabilistic predictions. The results also identify a rescaling relationship between the thermal noise and the bond length, suggesting a recalibration of the experimental conditions, to adhere to this scaling relationship, will enable biologists to identify the start of the signalling regime for previously unobserved receptor:ligand bonds. Also, the regime associated with TCR signalling exhibits a universal decay rate for the persistence probability, that is independent of the bond length.

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This thesis presents quantitative studies of T cell and dendritic cell (DC) behaviour in mouse lymph nodes (LNs) in the naive state and following immunisation. These processes are of importance and interest in basic immunology, and better understanding could improve both diagnostic capacity and therapeutic manipulations, potentially helping in producing more effective vaccines or developing treatments for autoimmune diseases. The problem is also interesting conceptually as it is relevant to other fields where 3D movement of objects is tracked with a discrete scanning interval. A general immunology introduction is presented in chapter 1. In chapter 2, I apply quantitative methods to multi-photon imaging data to measure how T cells and DCs are spatially arranged in LNs. This has been previously studied to describe differences between the naive and immunised state and as an indicator of the magnitude of the immune response in LNs, but previous analyses have been generally descriptive. The quantitative analysis shows that some of the previous conclusions may have been premature. In chapter 3, I use Bayesian state-space models to test some hypotheses about the mode of T cell search for DCs. A two-state mode of movement where T cells can be classified as either interacting to a DC or freely migrating is supported over a model where T cells would home in on DCs at distance through for example the action of chemokines. In chapter 4, I study whether T cell migration is linked to the geometric structure of the fibroblast reticular network (FRC). I find support for the hypothesis that the movement is constrained to the fibroblast reticular cell (FRC) network over an alternative 'random walk with persistence time' model where cells would move randomly, with a short-term persistence driven by a hypothetical T cell intrinsic 'clock'. I also present unexpected results on the FRC network geometry. Finally, a quantitative method is presented for addressing some measurement biases inherent to multi-photon imaging. In all three chapters, novel findings are made, and the methods developed have the potential for further use to address important problems in the field. In chapter 5, I present a summary and synthesis of results from chapters 3-4 and a more speculative discussion of these results and potential future directions.