Simulations of electrophoretic collisions of DNA knots with gel obstacles

Gel electrophoresis can be used to separate nicked circular DNA molecules of equal length but forming different knot types. At low electric fields, complex knots drift faster than simpler knots. However, at high electric field the opposite is the case and simpler knots migrate faster than more complex knots. Using Monte Carlo simulations we investigate the reasons of this reversal of relative order of electrophoretic mobility of DNA molecules forming different knot types. We observe that at high electric fields the simulated knotted molecules tend to hang over the gel fibres and require passing over a substantial energy barrier to slip over the impeding gel fibre. At low electric field the interactions of drifting molecules with the gel fibres are weak and there are no significant energy barriers that oppose the detachment of knotted molecules from transverse gel fibres.

Magnetic structure of Li2CuO2: From ab initio calculations to macroscopic simulations

The magnetic structure of the edge-sharing cuprate compound Li2CuO2 has been investigated with highly correlated ab initio electronic structure calculations. The first- and second-neighbor in-chain magnetic interactions are calculated to be 142 and -22 K, respectively. The ratio between the two parameters is smaller than suggested previously in the literature. The interchain interactions are antiferromagnetic in nature and of the order of a few K only. Monte Carlo simulations using the ab initio parameters to define the spin model Hamiltonian result in a Nel temperature in good agreement with experiment. Spin population analysis situates the magnetic moment on the copper and oxygen ions between the completely localized picture derived from experiment and the more delocalized picture based on local-density calculations.

Understanding and modulating the competitive surface-adsorption of proteins through coarse-grained molecular dynamics simulations

It is now well accepted that cellular responses to materials in a biological medium reflect greatly the adsorbed biomolecular layer, rather than the material itself. Here, we study by molecular dynamics simulations the competitive protein adsorption on a surface (Vroman effect), i.e. the non-monotonic behavior of the amount of protein adsorbed on a surface in contact with plasma as functions of contact time and plasma concentration. We find a complex behavior, with regimes during which small and large proteins are not necessarily competing between them, but are both competing with others in solution ("cooperative" adsorption). We show how the Vroman effect can be understood, controlled and inverted.

DnaSP, DNA polymorphism analyses by the coalescent and other methods

DnaSP is a software package for the analysis of DNA polymorphism data. Present version introduces several new modules and features which, among other options allow: (1) handling big data sets (~5 Mb per sequence); (2) conducting a large number of coalescent-based tests by Monte Carlo computer simulations; (3) extensive analyses of the genetic differentiation and gene flow among populations; (4) analysing the evolutionary pattern of preferred and unpreferred codons; (5) generating graphical outputs for an easy visualization of results. Availability: The software package, including complete documentation and examples, is freely available to academic users from: http://www.ub.es/dnasp

Simulations in Evolution. III. Randomness as a Generator of Opportunities.

In Neo-Darwinism, variation and natural selection are the two evolutionary mechanisms which propel biological evolution. Our previous reports presented a histogram model to simulate the evolution of populations of individuals classified into bins according to an unspecified, quantifiable phenotypic character, and whose number in each bin changed generation after generation under the influence of fitness, while the total population was maintained constant. The histogram model also allowed Shannon entropy (SE) to be monitored continuously as the information content of the total population decreased or increased. Here, a simple Perl (Practical Extraction and Reporting Language) application was developed to carry out these computations, with the critical feature of an added random factor in the percent of individuals whose offspring moved to a vicinal bin. The results of the simulations demonstrate that the random factor mimicking variation increased considerably the range of values covered by Shannon entropy, especially when the percentage of changed offspring was high. This increase in information content is interpreted as facilitated adaptability of the population.

Magnetic structure of Li2CuO2: From ab initio calculations to macroscopic simulations

The magnetic structure of the edge-sharing cuprate compound Li2CuO2 has been investigated with highly correlated ab initio electronic structure calculations. The first- and second-neighbor in-chain magnetic interactions are calculated to be 142 and -22 K, respectively. The ratio between the two parameters is smaller than suggested previously in the literature. The interchain interactions are antiferromagnetic in nature and of the order of a few K only. Monte Carlo simulations using the ab initio parameters to define the spin model Hamiltonian result in a Nel temperature in good agreement with experiment. Spin population analysis situates the magnetic moment on the copper and oxygen ions between the completely localized picture derived from experiment and the more delocalized picture based on local-density calculations.

A guide for easy- and difficult-to-treat hypertension.

Although the blood pressure (BP) of many patients can be controlled using standard combinations, treatment of hypertension frequently represents a clinical challenge to the primary care physician. This article will review best practices for managing patients with easy- and difficult-to-treat hypertension, including preferred antihypertensive combinations, optimizing adherence and persistence, recognizing white-coat hypertension, and intensifying therapy for treatment-resistant patients. Each physician must decide based on his or her own level of experience at what point a patient becomes too challenging and would benefit from referral to a hypertension specialist for more intensive management and to complete the exclusion of secondary forms of arterial hypertension. With intensive pharmacotherapy, many patients with difficult-to-treat hypertension can achieve BP control. If it fails, interventional strategies (e.g., renal denervation) are a valid option to get BP controlled.

Phosphorus saturation of Finnish soils : evaluating an easy oxalate extraction method

Selostus: Alumiini- ja rautaoksidien fosforikyllästysasteen arvioiminen suomalaisista peltomaista

Predicting the deleterious effects of mutation load in fragmented populations.

Human-induced habitat fragmentation constitutes a major threat to biodiversity. Both genetic and demographic factors combine to drive small and isolated populations into extinction vortices. Nevertheless, the deleterious effects of inbreeding and drift load may depend on population structure, migration patterns, and mating systems and are difficult to predict in the absence of crossing experiments. We performed stochastic individual-based simulations aimed at predicting the effects of deleterious mutations on population fitness (offspring viability and median time to extinction) under a variety of settings (landscape configurations, migration models, and mating systems) on the basis of easy-to-collect demographic and genetic information. Pooling all simulations, a large part (70%) of variance in offspring viability was explained by a combination of genetic structure (F(ST)) and within-deme heterozygosity (H(S)). A similar part of variance in median time to extinction was explained by a combination of local population size (N) and heterozygosity (H(S)). In both cases the predictive power increased above 80% when information on mating systems was available. These results provide robust predictive models to evaluate the viability prospects of fragmented populations.

Desarrollo CUDA en Java y Python

Análisis de desarrollo paralelo CUDA en lenguajes Java y Python, utilizando JCuda, RootBeer, PyCuda y Anaconda Accelerate.