925 resultados para Stochastic processes - Computer simulation
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We developed a procedure that combines three complementary computational methodologies to improve the theoretical description of the electronic structure of nickel oxide. The starting point is a Car-Parrinello molecular dynamics simulation to incorporate vibrorotational degrees of freedom into the material model. By means ofcomplete active space self-consistent field second-order perturbation theory (CASPT2) calculations on embedded clusters extracted from the resulting trajectory, we describe localized spectroscopic phenomena on NiO with an efficient treatment of electron correlation. The inclusion of thermal motion into the theoretical description allowsus to study electronic transitions that, otherwise, would be dipole forbidden in the ideal structure and results in a natural reproduction of the band broadening. Moreover, we improved the embedded cluster model by incorporating self-consistently at the complete active space self-consistent field (CASSCF) level a discrete (or direct) reaction field (DRF) in the cluster surroundings. The DRF approach offers an efficient treatment ofelectric response effects of the crystalline embedding to the electronic transitions localized in the cluster. We offer accurate theoretical estimates of the absorption spectrum and the density of states around the Fermi level of NiO, and a comprehensive explanation of the source of the broadening and the relaxation of the charge transferstates due to the adaptation of the environment
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We studied the noctule bat (Nyctalus noctula), in which the mitochondrial F(ST) is about 10 times that revealed by nuclear markers, to address two questions. We first verified whether random dispersal of one sex is compatible with highly contrasted mitochondrial and nuclear population structures. Using computer simulations, we then assessed the power of multilocus population differentiation tests when the expected population structure departs only slightly from panmixia. Using an island model with sex-specific demographic parameters, we found that random male dispersal is consistent with the population structure observed in the noctule. However, other parameter combinations are also compatible with the data. We computed the minimum sex bias in dispersal (at least 69% of the dispersing individuals are males), a result that would not be available if we had used more classical population genetic models. The power of multilocus population differentiation tests was unexpectedly high, the tests being significant in almost 100% of the replicates, although the observed population structure infered from nuclear markers was extremely low (F(ST) = 0.6%).
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We present an experimental and numerical study on the influence that particle aspect ratio has on the mechanical and structural properties of granular packings. For grains with maximal symmetry (squares), the stress propagation in the packing localizes forming chainlike forces analogous to the ones observed for spherical grains. This scenario can be understood in terms of stochastic models of aggregation and random multiplicative processes. As the grains elongate, the stress propagation is strongly affected. The interparticle normal force distribution tends toward a Gaussian, and, correspondingly, the force chains spread leading to a more uniform stress distribution reminiscent of the hydrostatic profiles known for standard liquids
A variational approach for calculating Franck-Condon factors including mode-mode anharmonic coupling
Resumo:
We have implemented our new procedure for computing Franck-Condon factors utilizing vibrational configuration interaction based on a vibrational self-consistent field reference. Both Duschinsky rotations and anharmonic three-mode coupling are taken into account. Simulations of the first ionization band of Cl O2 and C4 H4 O (furan) using up to quadruple excitations in treating anharmonicity are reported and analyzed. A developer version of the MIDASCPP code was employed to obtain the required anharmonic vibrational integrals and transition frequencies
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Bimodal dispersal probability distributions with characteristic distances differing by several orders of magnitude have been derived and favorably compared to observations by Nathan [Nature (London) 418, 409 (2002)]. For such bimodal kernels, we show that two-dimensional molecular dynamics computer simulations are unable to yield accurate front speeds. Analytically, the usual continuous-space random walks (CSRWs) are applied to two dimensions. We also introduce discrete-space random walks and use them to check the CSRW results (because of the inefficiency of the numerical simulations). The physical results reported are shown to predict front speeds high enough to possibly explain Reid's paradox of rapid tree migration. We also show that, for a time-ordered evolution equation, fronts are always slower in two dimensions than in one dimension and that this difference is important both for unimodal and for bimodal kernels
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AIMS: Brugada syndrome (BrS) is characterized by arrhythmias leading to sudden cardiac death. BrS is caused, in part, by mutations in the SCN5A gene, which encodes the sodium channel alpha-subunit Na(v)1.5. Here, we aimed to characterize the biophysical properties and consequences of a novel BrS SCN5A mutation. METHODS AND RESULTS: SCN5A was screened for mutations in a male patient with type-1 BrS pattern ECG. Wild-type (WT) and mutant Na(v)1.5 channels were expressed in HEK293 cells. Sodium currents (I(Na)) were analysed using the whole-cell patch-clamp technique at 37 degrees C. The electrophysiological effects of the mutation were simulated using the Luo-Rudy model, into which the transient outward current (I(to)) was incorporated. A new mutation (C1850S) was identified in the Na(v)1.5 C-terminal domain. In HEK293 cells, mutant I(Na) density was decreased by 62% at -20 mV. Inactivation of mutant I(Na) was accelerated in a voltage-dependent manner and the steady-state inactivation curve was shifted by 11.6 mV towards negative potentials. No change was observed regarding activation characteristics. Altogether, these biophysical alterations decreased the availability of I(Na). In the simulations, the I(to) density necessary to precipitate repolarization differed minimally between the two genotypes. In contrast, the mutation greatly affected conduction across a structural heterogeneity and precipitated conduction block. CONCLUSION: Our data confirm that mutations of the C-terminal domain of Na(v)1.5 alter the inactivation of the channel and support the notion that conduction alterations may play a significant role in the pathogenesis of BrS.
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BACKGROUND: Various centralised mammography screening programmes have shown to reduce breast cancer mortality at reasonable costs. However, mammography screening is not necessarily cost-effective in every situation. Opportunistic screening, the predominant screening modality in several European countries, may under certain circumstances be a cost-effective alternative. In this study, we compared the cost-effectiveness of both screening modalities in Switzerland. METHODS: Using micro-simulation modelling, we predicted the effects and costs of biennial mammography screening for 50-69 years old women between 1999 and 2020, in the Swiss female population aged 30-70 in 1999. A sensitivity analysis on the test sensitivity of opportunistic screening was performed. RESULTS: Organised mammography screening with an 80% participation rate yielded a breast cancer mortality reduction of 13%. Twenty years after the start of screening, the predicted annual breast cancer mortality was 25% lower than in a situation without screening. The 3% discounted cost-effectiveness ratio of organised mammography screening was euro11,512 per life year gained. Opportunistic screening with a similar participation rate was comparably effective, but at twice the costs: euro22,671-24,707 per life year gained. This was mainly related to the high costs of opportunistic mammography and frequent use of imaging diagnostics in combination with an opportunistic mammogram. CONCLUSION: Although data on the performance of opportunistic screening are limited, both opportunistic and organised mammography screening seem effective in reducing breast cancer mortality in Switzerland. However, for opportunistic screening to become equally cost-effective as organised screening, costs and use of additional diagnostics should be reduced.
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In Quantitative Microbial Risk Assessment, it is vital to understand how lag times of individual cells are distributed over a bacterial population. Such identified distributions can be used to predict the time by which, in a growth-supporting environment, a few pathogenic cells can multiply to a poisoning concentration level. We model the lag time of a single cell, inoculated into a new environment, by the delay of the growth function characterizing the generated subpopulation. We introduce an easy-to-implement procedure, based on the method of moments, to estimate the parameters of the distribution of single cell lag times. The advantage of the method is especially apparent for cases where the initial number of cells is small and random, and the culture is detectable only in the exponential growth phase.
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Despite the fact that in living cells DNA molecules are long and highly crowded, they are rarely knotted. DNA knotting interferes with the normal functioning of the DNA and, therefore, molecular mechanisms evolved that maintain the knotting and catenation level below that which would be achieved if the DNA segments could pass randomly through each other. Biochemical experiments with torsionally relaxed DNA demonstrated earlier that type II DNA topoisomerases that permit inter- and intramolecular passages between segments of DNA molecules use the energy of ATP hydrolysis to select passages that lead to unknotting rather than to the formation of knots. Using numerical simulations, we identify here another mechanism by which topoisomerases can keep the knotting level low. We observe that DNA supercoiling, such as found in bacterial cells, creates a situation where intramolecular passages leading to knotting are opposed by the free-energy change connected to transitions from unknotted to knotted circular DNA molecules.
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Meta-analysis of genome-wide association studies (GWASs) has led to the discoveries of many common variants associated with complex human diseases. There is a growing recognition that identifying "causal" rare variants also requires large-scale meta-analysis. The fact that association tests with rare variants are performed at the gene level rather than at the variant level poses unprecedented challenges in the meta-analysis. First, different studies may adopt different gene-level tests, so the results are not compatible. Second, gene-level tests require multivariate statistics (i.e., components of the test statistic and their covariance matrix), which are difficult to obtain. To overcome these challenges, we propose to perform gene-level tests for rare variants by combining the results of single-variant analysis (i.e., p values of association tests and effect estimates) from participating studies. This simple strategy is possible because of an insight that multivariate statistics can be recovered from single-variant statistics, together with the correlation matrix of the single-variant test statistics, which can be estimated from one of the participating studies or from a publicly available database. We show both theoretically and numerically that the proposed meta-analysis approach provides accurate control of the type I error and is as powerful as joint analysis of individual participant data. This approach accommodates any disease phenotype and any study design and produces all commonly used gene-level tests. An application to the GWAS summary results of the Genetic Investigation of ANthropometric Traits (GIANT) consortium reveals rare and low-frequency variants associated with human height. The relevant software is freely available.
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When individuals in a population can acquire traits through learning, each individual may express a certain number of distinct cultural traits. These traits may have been either invented by the individual himself or acquired from others in the population. Here, we develop a game theoretic model for the accumulation of cultural traits through individual and social learning. We explore how the rates of innovation, decay, and transmission of cultural traits affect the evolutionary stable (ES) levels of individual and social learning and the number of cultural traits expressed by an individual when cultural dynamics are at a steady-state. We explore the evolution of these phenotypes in both panmictic and structured population settings. Our results suggest that in panmictic populations, the ES level of learning and number of traits tend to be independent of the social transmission rate of cultural traits and is mainly affected by the innovation and decay rates. By contrast, in structured populations, where interactions occur between relatives, the ES level of learning and the number of traits per individual can be increased (relative to the panmictic case) and may then markedly depend on the transmission rate of cultural traits. This suggests that kin selection may be one additional solution to Rogers's paradox of nonadaptive culture.
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Site-directed mutagenesis and molecular dynamics simulations of the alpha 1B-adrenergic receptor (AR) were combined to explore the potential molecular changes correlated with the transition from R (inactive state) to R (active state). Using molecular dynamics analysis we compared the structural/dynamic features of constitutively active mutants with those of the wild type and of an inactive alpha 1B-AR to build a theoretical model which defines the essential features of R and R. The results of site-directed mutagenesis were in striking agreement with the predictions of the model supporting the following hypothesis. (i) The equilibrium between R and R depends on the equilibrium between the deprotonated and protonated forms, respectively, of D142 of the DRY motif. In fact, replacement of D142 with alanine confers high constitutive activity to the alpha 1B-AR. (ii) The shift of R143 of the DRY sequence out of a conserved 'polar pocket' formed by N63, D91, N344 and Y348 is a feature common to all the active structures, suggesting that the role of R143 is fundamental for mediating receptor activation. Disruption of these intramolecular interactions by replacing N63 with alanine constitutively activates the alpha 1B-AR. Our findings might provide interesting generalities about the activation process of G protein-coupled receptors.
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The methodology for generating a homology model of the T1 TCR-PbCS-K(d) class I major histocompatibility complex (MHC) class I complex is presented. The resulting model provides a qualitative explanation of the effect of over 50 different mutations in the region of the complementarity determining region (CDR) loops of the T cell receptor (TCR), the peptide and the MHC's alpha(1)/alpha(2) helices. The peptide is modified by an azido benzoic acid photoreactive group, which is part of the epitope recognized by the TCR. The construction of the model makes use of closely related homologs (the A6 TCR-Tax-HLA A2 complex, the 2C TCR, the 14.3.d TCR Vbeta chain, the 1934.4 TCR Valpha chain, and the H-2 K(b)-ovalbumine peptide), ab initio sampling of CDR loops conformations and experimental data to select from the set of possibilities. The model shows a complex arrangement of the CDR3alpha, CDR1beta, CDR2beta and CDR3beta loops that leads to the highly specific recognition of the photoreactive group. The protocol can be applied systematically to a series of related sequences, permitting the analysis at the structural level of the large TCR repertoire specific for a given peptide-MHC complex.
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Interspecific competition, life history traits, environmental heterogeneity and spatial structure as well as disturbance are known to impact the successful dispersal strategies in metacommunities. However, studies on the direction of impact of those factors on dispersal have yielded contradictory results and often considered only few competing dispersal strategies at the same time. We used a unifying modeling approach to contrast the combined effects of species traits (adult survival, specialization), environmental heterogeneity and structure (spatial autocorrelation, habitat availability) and disturbance on the selected, maintained and coexisting dispersal strategies in heterogeneous metacommunities. Using a negative exponential dispersal kernel, we allowed for variation of both species dispersal distance and dispersal rate. We showed that strong disturbance promotes species with high dispersal abilities, while low local adult survival and habitat availability select against them. Spatial autocorrelation favors species with higher dispersal ability when adult survival and disturbance rate are low, and selects against them in the opposite situation. Interestingly, several dispersal strategies coexist when disturbance and adult survival act in opposition, as for example when strong disturbance regime favors species with high dispersal abilities while low adult survival selects species with low dispersal. Our results unify apparently contradictory previous results and demonstrate that spatial structure, disturbance and adult survival determine the success and diversity of coexisting dispersal strategies in competing metacommunities.