Detecting recombination in 4-taxa DNA sequence alignments with Bayesian hidden Markov models and Markov chain Monte Carlo

This article presents a statistical method for detecting recombination in DNA sequence alignments, which is based on combining two probabilistic graphical models: (1) a taxon graph (phylogenetic tree) representing the relationship between the taxa, and (2) a site graph (hidden Markov model) representing interactions between different sites in the DNA sequence alignments. We adopt a Bayesian approach and sample the parameters of the model from the posterior distribution with Markov chain Monte Carlo, using a Metropolis-Hastings and Gibbs-within-Gibbs scheme. The proposed method is tested on various synthetic and real-world DNA sequence alignments, and we compare its performance with the established detection methods RECPARS, PLATO, and TOPAL, as well as with two alternative parameter estimation schemes.

Cigarette smokers differ in their handling of natural (RRR) and synthetic (all rac) alpha-tocopherol: a biokinetic study in apoE4 male subjects

We have compared the biokinetics of deuterated natural (RPR) and synthetic (all rac) alpha-tocopherol in male apoE4-carrying smokers and nonsmokers. In a randomized, crossover study subjects underwent two 4-week treatments (400 mg/day) with undeuterated RRR- and all rac-alpha-tocopheryl acetate around a 12-week washout. Before and after each supplementation period subjects underwent a biokinetic protocol (48 h) with 150 mg deuterated RRR- or all rac-alpha-tocopheryl acetate. During the biokinetic protocols, the elimination of endogenous plasma alpha-tocopherol was significantly faster in smokers (P < 0.05). However, smokers had a lower uptake of deuterated RRR than nonsmokers, but there was no difference in uptake of deuterated all rac. The supplementation regimes significantly raised plasma alpha-tocopherol (P < 0.001) with no differences in response between smokers and nonsmokers or between alpha-tocopherol forms. Smokers had significantly lower excretion of alpha-carboxyethyl-hydroxychroman than nonsmokers following supplementation (P < 0.05). Nonsmokers excreted more alpha-carboxyethyl-hydroxychroman following RRR than all rac; however, smokers did not differ in excretion between forms. At baseline, smokers had significantly lower ascorbate (P < 0.01) and higher F(2-)isoprostarres (P < 0.05). F-2-isoprostanes in smokers remained unchanged during the study, but increased in nonsmokers following alpha-tocopherol supplementation. These data suggest that apoE4-carrying smokers and nonsmokers differ in their handling of natural and synthetic alpha-tocopherol. (c) 2006 Elsevier Inc. All rights reserved.

The reaction of flavanols with nitrous acid protects against N-nitrosamine formation and leads to the formation of nitroso derivatives which inhibit cancer cell growth

Studies have suggested that diets rich in polyphenols Such as flavonoids may lead to a reduced risk of gastrointestinal cancers. We demonstrate the ability of monomeric and dimeric flavanols to scavenge reactive nitrogen species derived from nitrous acid. Both epicatechin and dimer B2 (epicatechin dimer) inhibited nitrous acid-induced formation of 3-nitrotyrosine and the formation of the carcinogenic N-nitrosamine, N-nitrosodimethylamine. The reaction of monomeric and dimeric epicatechin with nitrous acid led to the formation of mono- and di-nitroso flavanols, whereas the reaction with hesperetin resulted primarily in the formation of nitrated products. Although, epicatechin was transferred across the jejunum of the small intestine yielding metabolites, its nitroso form was not absorbed. Dimer B2 but not epicatechin monomer inhibited the proliferation of, and triggered apoptosis in, Caco-2 cells. The latter was accompanied by caspase-3 activation and reductions in Akt phosphorylation, suggesting activation of apoptosis via inhibition of prosurvival signaling. Furthermore, the dinitroso derivative of dimer B2, and to a lesser extent the dinitroso-epicatechin, also induced significant toxic effects in Caco-2 cells. The inhibitory effects on cellular proliferation were paralleled by early inhibition of ERK 1/2 phosphorylation and later reductions in cyclin D I levels, indicating modulation of cell cycle regulation in Caco-2 cells. These effects highlight multiple routes in which dietary derived flavanols may exert beneficial effects in the gastrointestinal tract. (c) 2005 Elsevier Inc. All rights reserved.

Nox2 regulates endothelial cell cycle arrest and apoptosis via p21 (cip1) and p53

Endothelial cells (EC) express constitutively two major isofonns (Nox2 and Nox4) of the catalytic subunit of NADPH oxidase, which is a major source of endothelial reactive oxygen species. However, the individual roles of these Noxes in endothelial function remain unclear. We have investigated the role of Nox2 in nutrient deprivation-induced cell cycle arrest and apoptosis. In proliferating human dermal microvascular EC, Nox2 mRNA expression was low relative to Nox4 (Nox2:Nox4 similar to 1:13), but was upregulated 24 It after starvation and increased to 8 +/- 3.5-fold at 36 h of starvation. Accompanying the upregulation of Nox2, there was a 2.28 +/- 0.18-fold increase in O-2(-); production, a dramatic induction of p21(cip1) and p53, cell cycle arrest, and the onset of apoptosis (all p < 0.05). All these changes were inhibited significantly by in vitro deletion of Nox2 expression and in coronary microvascular EC isolated from Nox2 knockout mice. In Nox2 knockout cells, although there was a 3.8 +/- 0.5fold increase in Nox4 mRNA expression after 36 h of starvation (p < 0.01), neither production nor the p21(cip1) or p53 expression was increased significantly and only 0.46% of cells were apoptotic. In conclusion, Nox2-derived O-2(-), through the modulation of p21(cip1) and p53 expression, participates in endothelial cell cycle regulation and apoptosis. (c) 2007 Elsevier Inc. All rights reserved.

Efficient modeling and inference for event-related fMRI data

Event-related functional magnetic resonance imaging (efMRI) has emerged as a powerful technique for detecting brains' responses to presented stimuli. A primary goal in efMRI data analysis is to estimate the Hemodynamic Response Function (HRF) and to locate activated regions in human brains when specific tasks are performed. This paper develops new methodologies that are important improvements not only to parametric but also to nonparametric estimation and hypothesis testing of the HRF. First, an effective and computationally fast scheme for estimating the error covariance matrix for efMRI is proposed. Second, methodologies for estimation and hypothesis testing of the HRF are developed. Simulations support the effectiveness of our proposed methods. When applied to an efMRI dataset from an emotional control study, our method reveals more meaningful findings than the popular methods offered by AFNI and FSL. (C) 2008 Elsevier B.V. All rights reserved.

Blueberry-induced changes in spatial working memory correlate with changes in hippocampal CREB phosphorylation and brain-derived neurotrophic factor (BDNF) levels

Phytochemical-rich foods have been shown to be effective at reversing age-related deficits in memory in both animals and humans. We show that a supplementation with a blueberry diet (2% w/w) for 12 weeks improves the performance of aged animals in spatial working memory tasks. This improvement emerged within 3 weeks and persisted for the remainder of the testing period. Memory performance correlated well with the activation of cAMP-response element-binding protein (CREB) and increases in both pro- and mature levels of brain-derived neurotrophic factor (BDNF) in the hippocampus. Changes in CREB and BDNF in aged and blueberry-supplemented animals were accompanied by increases in the phosphorylation state of extracellular signal-related kinase (ERK1/2), rather than that of calcium calmodulin kinase (CaMKII and CaMKIV) or protein kinase A. Furthermore, age and blueberry supplementation were linked to changes in the activation state of Akt, mTOR, and the levels of Arc/Arg3.1 in the hippocampus, suggesting that pathways involved in de novo protein synthesis may be involved. Although causal relationships cannot be made among supplementation, behavior, and biochemical parameters, the measurement of anthocyanins and flavanols in the brain following blueberry supplementation may indicate that changes in spatial working memory in aged animals are linked to the effects of flavonoids on the ERK-CREB-BDNF pathway. (c) 2008 Elsevier Inc. All Fights reserved.

Advanced scalable algorithms for advanced architectures

With the latest advances in the area of advanced computer architectures we are seeing already large scale machines at petascale level and we are discussing exascale computing. All these require efficient scalable algorithms in order to bridge the performance gap. In this paper examples of various approaches of designing scalable algorithms for such advanced architectures will be given and the corresponding properties of these algorithms will be outlined and discussed. Examples will outline such scalable algorithms applied to large scale problems in the area Computational Biology, Environmental Modelling etc. The key properties of such advanced and scalable algorithms will be outlined.

Optimization algorithms in FMRF model-based segmentation for LIDAR data and co-registered bands

In this paper, a fuzzy Markov random field (FMRF) model is used to segment land-objects into free, grass, building, and road regions by fusing remotely, sensed LIDAR data and co-registered color bands, i.e. scanned aerial color (RGB) photo and near infra-red (NIR) photo. An FMRF model is defined as a Markov random field (MRF) model in a fuzzy domain. Three optimization algorithms in the FMRF model, i.e. Lagrange multiplier (LM), iterated conditional mode (ICM), and simulated annealing (SA), are compared with respect to the computational cost and segmentation accuracy. The results have shown that the FMRF model-based ICM algorithm balances the computational cost and segmentation accuracy in land-cover segmentation from LIDAR data and co-registered bands.

Parallel performance and scalability experiments with the Danish Eulerian Model on the EPCC supercomputers

The Danish Eulerian Model (DEM) is a powerful air pollution model, designed to calculate the concentrations of various dangerous species over a large geographical region (e.g. Europe). It takes into account the main physical and chemical processes between these species, the actual meteorological conditions, emissions, etc.. This is a huge computational task and requires significant resources of storage and CPU time. Parallel computing is essential for the efficient practical use of the model. Some efficient parallel versions of the model were created over the past several years. A suitable parallel version of DEM by using the Message Passing Interface library (AIPI) was implemented on two powerful supercomputers of the EPCC - Edinburgh, available via the HPC-Europa programme for transnational access to research infrastructures in EC: a Sun Fire E15K and an IBM HPCx cluster. Although the implementation is in principal, the same for both supercomputers, few modifications had to be done for successful porting of the code on the IBM HPCx cluster. Performance analysis and parallel optimization was done next. Results from bench marking experiments will be presented in this paper. Another set of experiments was carried out in order to investigate the sensitivity of the model to variation of some chemical rate constants in the chemical submodel. Certain modifications of the code were necessary to be done in accordance with this task. The obtained results will be used for further sensitivity analysis Studies by using Monte Carlo simulation.

Femtosecond evolution of spatially inhomogeneous carrier excitations: part 2: stochastic approach and GRID implementation

We present a stochastic approach for solving the quantum-kinetic equation introduced in Part I. A Monte Carlo method based on backward time evolution of the numerical trajectories is developed. The computational complexity and the stochastic error are investigated numerically. Variance reduction techniques are applied, which demonstrate a clear advantage with respect to the approaches based on symmetry transformation. Parallel implementation is realized on a GRID infrastructure.

Experimental design and model construction algorithms for radial basis function networks

New construction algorithms for radial basis function (RBF) network modelling are introduced based on the A-optimality and D-optimality experimental design criteria respectively. We utilize new cost functions, based on experimental design criteria, for model selection that simultaneously optimizes model approximation, parameter variance (A-optimality) or model robustness (D-optimality). The proposed approaches are based on the forward orthogonal least-squares (OLS) algorithm, such that the new A-optimality- and D-optimality-based cost functions are constructed on the basis of an orthogonalization process that gains computational advantages and hence maintains the inherent computational efficiency associated with the conventional forward OLS approach. The proposed approach enhances the very popular forward OLS-algorithm-based RBF model construction method since the resultant RBF models are constructed in a manner that the system dynamics approximation capability, model adequacy and robustness are optimized simultaneously. The numerical examples provided show significant improvement based on the D-optimality design criterion, demonstrating that there is significant room for improvement in modelling via the popular RBF neural network.

Differential effects of overexpression of ERalpha and ERbeta in MCF10A immortalised, non-transformed human breast epithelail cells

Background: Cellular effects of oestrogen are mediated by two intracellular receptors ERα and ERβ. However, to compare responses mediated through these two receptors, experimental models are needed where ERα and ERβ are individually stably overexpressed in the same cell type. Methods: We compared the effects of stable overexpression of ERα and ERβ in the MCF10A cell line, which is an immortalised but non-transformed breast epithelial cell line without high endogenous ER expression. Results: Clones of MCF10A cells were characterised which stably overexpressed ERα (10A-ERα2, 10A-ERα13) or which stably overexpressed ERβ (10A-ERβ12, 10A-ERβ15). Overexpression of either ERα or ERβ allowed induction of an oestrogen-regulated ERE-LUC reporter gene by oestradiol which was not found in the untransfected cells. Oestradiol also increased proliferation of 10A-ERα13 and 10A-ERβ12 cells, but not untransfected cells, by 1.3-fold over 7 days. The phytoestrogen, genistein, which is reported to bind more strongly to ERβ than to ERα, could induce luciferase gene expression from an ERE-LUC reporter gene at concentrations of 10−6 M and 10−5 M but only in the clones overexpressing ERβ and not in those overexpressing ERα. Clone 10A-ERβ12 also yielded growth stimulation with 10-6 M genistein. Finally, the overexpression of ERα, but not ERβ, gave rise to increased growth in semi-solid methocel suspension culture in the presence of 70 nM oestradiol, suggesting that overexpression of ERα, but not ERβ, produces characteristics of a transformed phenotype. Conclusions: This provides a model system to compare effects of oestradiol with other oestrogenic ligands in cells stably overexpressing individually ERα or ERβ.

Nonlinear model structure design and construction using orthogonal least squares and D-optimality design

A very efficient learning algorithm for model subset selection is introduced based on a new composite cost function that simultaneously optimizes the model approximation ability and model robustness and adequacy. The derived model parameters are estimated via forward orthogonal least squares, but the model subset selection cost function includes a D-optimality design criterion that maximizes the determinant of the design matrix of the subset to ensure the model robustness, adequacy, and parsimony of the final model. The proposed approach is based on the forward orthogonal least square (OLS) algorithm, such that new D-optimality-based cost function is constructed based on the orthogonalization process to gain computational advantages and hence to maintain the inherent advantage of computational efficiency associated with the conventional forward OLS approach. Illustrative examples are included to demonstrate the effectiveness of the new approach.

Epicatechin and its methylated metabolite attenuate UVA-induced oxidative damage to human skin fibroblasts

The ultraviolet A component of sunlight causes both acute and chronic damage to human skin. In this study the potential of epicatechin, an abundant dietary flavanol, and 3'-O-methyl epicatechin, one of its major in vivo metabolites, to protect against UVA-induced damage was examined using cultured human skin fibroblasts as an in vitro model. The results obtained clearly show that both epicatechin and its metabolite protect these fibroblasts against UVA damage and cell death. The hydrogen-donating antioxidant properties of these compounds are probably not the mediators of this protective response. The protection is a consequence of induction of resistance to UVA mediated by the compounds and involves newly synthesized proteins. The study provides clear evidence that this dietary flavanol has the potential to protect human skin against the deleterious effects of sunlight.

The effect of dietary nitrate on salivary, plasma, and urinary nitrate metabolism in humans

Dietary nitrate is metabolized to nitrite by bacterial flora on the posterior surface of the tongue leading to increased salivary nitrite concentrations. In the acidic environment of the stomach, nitrite forms nitrous acid, a potent nitrating/nitrosating agent. The aim of this study was to examine the pharmacokinetics of dietary nitrate in relation to the formation of salivary, plasma, and urinary nitrite and nitrate in healthy subjects. A secondary aim was to determine whether dietary nitrate increases the formation of protein-bound 3-nitrotyrosine in plasma, and if dietary nitrate improves platelet function. The pharmacokinetic profile of urinary nitrate excretion indicates total clearance of consumed nitrate in a 24 h period. While urinary, salivary, and plasma nitrate concentrations increased between 4- and 7-fold, a significant increase in nitrite was only detected in saliva (7-fold). High dietary nitrate consumption does not cause a significant acute change in plasma concentrations of 3-nitrotyrosine or in platelet function.