Modulational and Parametric Instabilities of the Discrete Nonlinear Schr\"odinger Equation

We examine the modulational and parametric instabilities arising in a non-autonomous, discrete nonlinear Schr{\"o}dinger equation setting. The principal motivation for our study stems from the dynamics of Bose-Einstein condensates trapped in a deep optical lattice. We find that under periodic variations of the heights of the interwell barriers (or equivalently of the scattering length), additionally to the modulational instability, a window of parametric instability becomes available to the system. We explore this instability through multiple-scale analysis and identify it numerically. Its principal dynamical characteristic is that, typically, it develops over much larger times than the modulational instability, a feature that is qualitatively justified by comparison of the corresponding instability growth rates

Augmented Lagrangian Method for Constrained Nuclear Density Functional Theory

The augmented Lagrangiam method (ALM), widely used in quantum chemistry constrained optimization problems, is applied in the context of the nuclear Density Functional Theory (DFT) in the self-consistent constrained Skyrme Hartree-Fock-Bogoliubov (CHFB) variant. The ALM allows precise calculations of multidimensional energy surfaces in the space of collective coordinates that are needed to, e.g., determine fission pathways and saddle points; it improves accuracy of computed derivatives with respect to collective variables that are used to determine collective inertia; and is well adapted to supercomputer applications.Comment: 6 pages, 3 figures; to appear in Eur. Phys. J.

Comparison of techniques for handling missing covariate data within prognostic modelling studies: a simulation study

Background: There is no consensus on the most appropriate approach to handle missing covariate data within prognostic modelling studies. Therefore a simulation study was performed to assess the effects of different missing data techniques on the performance of a prognostic model. Methods: Datasets were generated to resemble the skewed distributions seen in a motivating breast cancer example. Multivariate missing data were imposed on four covariates using four different mechanisms; missing completely at random (MCAR), missing at random (MAR), missing not at random (MNAR) and a combination of all three mechanisms. Five amounts of incomplete cases from 5% to 75% were considered. Complete case analysis (CC), single imputation (SI) and five multiple imputation (MI) techniques available within the R statistical software were investigated: a) data augmentation (DA) approach assuming a multivariate normal distribution, b) DA assuming a general location model, c) regression switching imputation, d) regression switching with predictive mean matching (MICE-PMM) and e) flexible additive imputation models. A Cox proportional hazards model was fitted and appropriate estimates for the regression coefficients and model performance measures were obtained. Results: Performing a CC analysis produced unbiased regression estimates, but inflated standard errors, which affected the significance of the covariates in the model with 25% or more missingness. Using SI, underestimated the variability; resulting in poor coverage even with 10% missingness. Of the MI approaches, applying MICE-PMM produced, in general, the least biased estimates and better coverage for the incomplete covariates and better model performance for all mechanisms. However, this MI approach still produced biased regression coefficient estimates for the incomplete skewed continuous covariates when 50% or more cases had missing data imposed with a MCAR, MAR or combined mechanism. When the missingness depended on the incomplete covariates, i.e. MNAR, estimates were biased with more than 10% incomplete cases for all MI approaches. Conclusion: The results from this simulation study suggest that performing MICE-PMM may be the preferred MI approach provided that less than 50% of the cases have missing data and the missing data are not MNAR

Coronary–aortic interaction during ventricular isovolumic contraction

In earlier work, we suggested that the start of the isovolumic contraction period could be detected in arterial pressure waveforms as the start of a temporary pre-systolic pressure perturbation (AICstart, start of the Arterially detected Isovolumic Contraction), and proposed the retrograde coronary blood volume flow in combination with a backwards traveling pressure wave as its most likely origin. In this study, we tested this hypothesis by means of a coronary artery occlusion protocol. In six Yorkshire × Landrace swine, we simultaneously occluded the left anterior descending (LAD) and left circumflex (LCx) artery for 5 s followed by a 20-s reperfusion period and repeated this sequence at least two more times. A similar procedure was used to occlude only the right coronary artery (RCA) and finally all three main coronary arteries simultaneously. None of the occlusion protocols caused a decrease in the arterial pressure perturbation in the aorta during occlusion (P > 0.20) nor an increase during reactive hyperemia (P > 0.22), despite a higher deceleration of coronary blood volume flow (P = 0.03) or increased coronary conductance (P = 0.04) during hyperemia. These results show that the pre-systolic aortic pressure perturbation does not originate from the coronary arteries

Secular Evolution and the Formation of Pseudobulges in Disk Galaxies

We review internal processes of secular evolution in galaxy disks, concentrating on the buildup of dense central features that look like classical, merger-built bulges but that were made slowly out of disk gas. We call these pseudobulges. As an existence proof, we review how bars rearrange disk gas into outer rings, inner rings, and gas dumped into the center. In simulations, this gas reaches high densities that plausibly feed star formation. In the observations, many SB and oval galaxies show central concentrations of gas and star formation. Star formation rates imply plausible pseudobulge growth times of a few billion years. If secular processes built dense central components that masquerade as bulges, can we distinguish them from merger-built bulges? Observations show that pseudobulges retain a memory of their disky origin. They have one or more characteristics of disks: (1) flatter shapes than those of classical bulges, (2) large ratios of ordered to random velocities indicative of disk dynamics, (3) small velocity dispersions, (4) spiral structure or nuclear bars in the bulge part of the light profile, (5) nearly exponential brightness profiles, and (6) starbursts. These structures occur preferentially in barred and oval galaxies in which secular evolution should be rapid. So the cleanest examples of pseudobulges are recognizable. Thus a large variety of observational and theoretical results contribute to a new picture of galaxy evolution that complements hierarchical clustering and merging.Comment: 92 pages, 21 figures in 30 Postscript files; to appear in Annual Review of Astronomy and Astrophysics, Vol. 42, 2004, in press; for a version with full resolution figures, see http://chandra.as.utexas.edu/~kormendy/ar3ss.htm

Creatine Protects against Excitoxicity in an In Vitro Model of Neurodegeneration

Creatine has been shown to be neuroprotective in aging, neurodegenerative conditions and brain injury. As a common molecular background, oxidative stress and disturbed cellular energy homeostasis are key aspects in these conditions. Moreover, in a recent report we could demonstrate a life-enhancing and health-promoting potential of creatine in rodents, mainly due to its neuroprotective action. In order to investigate the underlying pharmacology mediating these mainly neuroprotective properties of creatine, cultured primary embryonal hippocampal and cortical cells were challenged with glutamate or H2O2. In good agreement with our in vivo data, creatine mediated a direct effect on the bioenergetic balance, leading to an enhanced cellular energy charge, thereby acting as a neuroprotectant. Moreover, creatine effectively antagonized the H2O2-induced ATP depletion and the excitotoxic response towards glutamate, while not directly acting as an antioxidant. Additionally, creatine mediated a direct inhibitory action on the NMDA receptor-mediated calcium response, which initiates the excitotoxic cascade. Even excessive concentrations of creatine had no neurotoxic effects, so that high-dose creatine supplementation as a health-promoting agent in specific pathological situations or as a primary prophylactic compound in risk populations seems feasible. In conclusion, we were able to demonstrate that the protective potential of creatine was primarily mediated by its impact on cellular energy metabolism and NMDA receptor function, along with reduced glutamate spillover, oxidative stress and subsequent excitotoxicity

Nicotiana benthamiana as a Production Platform for Artemisinin Precursors

Background Production of pharmaceuticals in plants provides an alternative for chemical synthesis, fermentation or natural sources. Nicotiana benthamiana is deployed at commercial scale for production of therapeutic proteins. Here the potential of this plant is explored for rapid production of precursors of artemisinin, a sesquiterpenoid compound that is used for malaria treatment. Methodology/Principal Findings Biosynthetic genes leading to artemisinic acid, a precursor of artemisinin, were combined and expressed in N. benthamiana by agro-infiltration. The first committed precursor of artemisinin, amorpha-4,11-diene, was produced upon infiltration of a construct containing amorpha-4,11-diene synthase, accompanied by 3-hydroxy-3-methylglutaryl-CoA reductase and farnesyl diphosphate synthase. Amorpha-4,11-diene was detected both in extracts and in the headspace of the N. benthamiana leaves. When the amorphadiene oxidase CYP71AV1 was co-infiltrated with the amorphadiene-synthesizing construct, the amorpha-4,11-diene levels strongly decreased, suggesting it was oxidized. Surprisingly, no anticipated oxidation products, such as artemisinic acid, were detected upon GC-MS analysis. However, analysis of leaf extracts with a non-targeted metabolomics approach, using LC-QTOF-MS, revealed the presence of another compound, which was identified as artemisinic acid-12-ß-diglucoside. This compound accumulated to 39.5 mg.kg-1 fwt. Apparently the product of the heterologous pathway that was introduced, artemisinic acid, is further metabolized efficiently by glycosyl transferases that are endogenous to N. benthamiana. Conclusion/Significance This work shows that agroinfiltration of N. bentamiana can be used as a model to study the production of sesquiterpenoid pharmaceutical compounds. The interaction between the ectopically introduced pathway and the endogenous metabolism of the plant is discussed

Interpreting linear support vector machine models with heat map molecule coloring

<p>Abstract</p> <p>Background</p> <p>Model-based virtual screening plays an important role in the early drug discovery stage. The outcomes of high-throughput screenings are a valuable source for machine learning algorithms to infer such models. Besides a strong performance, the interpretability of a machine learning model is a desired property to guide the optimization of a compound in later drug discovery stages. Linear support vector machines showed to have a convincing performance on large-scale data sets. The goal of this study is to present a heat map molecule coloring technique to interpret linear support vector machine models. Based on the weights of a linear model, the visualization approach colors each atom and bond of a compound according to its importance for activity.</p> <p>Results</p> <p>We evaluated our approach on a toxicity data set, a chromosome aberration data set, and the maximum unbiased validation data sets. The experiments show that our method sensibly visualizes structure-property and structure-activity relationships of a linear support vector machine model. The coloring of ligands in the binding pocket of several crystal structures of a maximum unbiased validation data set target indicates that our approach assists to determine the correct ligand orientation in the binding pocket. Additionally, the heat map coloring enables the identification of substructures important for the binding of an inhibitor.</p> <p>Conclusions</p> <p>In combination with heat map coloring, linear support vector machine models can help to guide the modification of a compound in later stages of drug discovery. Particularly substructures identified as important by our method might be a starting point for optimization of a lead compound. The heat map coloring should be considered as complementary to structure based modeling approaches. As such, it helps to get a better understanding of the binding mode of an inhibitor.</p

Behavioral response of dissimilatory perchlorate-reducing bacteria to different electron acceptors

The response behavior of three dissimilatory perchlorate-reducing bacteria to different electron acceptors (nitrate, chlorate, and perchlorate) was investigated with two different assays. The observed response was species-specific, dependent on the prior growth conditions, and was inhibited by oxygen. We observed attraction toward nitrate when Dechloromonas aromatica strain RCB and Azospira suillum strain PS were grown with nitrate. When D. aromatica and Dechloromonas agitata strain CKB were grown with perchlorate, both responded to nitrate, chlorate, and perchlorate. When A. suillum was grown with perchlorate, the organism responded to chlorate and perchlorate but not nitrate. A gene replacement mutant in the perchlorate reductase subunit (pcrA) of D. aromatica resulted in a loss of the attraction response toward perchlorate but had no impact on the nitrate response. Washed-cell suspension studies revealed that the perchlorate grown cells of D. aromatica reduced both perchlorate and nitrate, while A. suillum cells reduced perchlorate only. Based on these observations, energy taxis was proposed as the underlying mechanism for the responses to (per)chlorate by D. aromatica. To the best of our knowledge, this study represents the first investigation of the response behavior of perchlorate-reducing bacteria to environmental stimuli. It clearly demonstrates attraction toward chlorine oxyanions and the unique ability of these organisms to distinguish structurally analogous compounds, nitrate, chlorate, and perchlorate and respond accordingly

Structural basis of outer membrane protein insertion by the BAM complex

All Gram-negative bacteria, mitochondria and chloroplasts have outer membrane proteins (OMPs) that perform many fundamental biological processes. The OMPs in Gram-negative bacteria are inserted and folded into the outer membrane by the β-barrel assembly machinery (BAM). The mechanism involved is poorly understood, owing to the absence of a structure of the entire BAM complex. Here we report two crystal structures of the Escherichia coli BAM complex in two distinct states: an inward-open state and a lateral-open state. Our structures reveal that the five polypeptide transport-associated domains of BamA form a ring architecture with four associated lipoproteins, BamB–BamE, in the periplasm. Our structural, functional studies and molecular dynamics simulations indicate that these subunits rotate with respect to the integral membrane β-barrel of BamA to induce movement of the β-strands of the barrel and promote insertion of the nascent OMP