Sketch-To-Solution: An Exploration of Viscous CFD with Automatic Grids

Numerical simulation of the Reynolds-averaged NavierStokes (RANS) equations has become a critical tool for the design of aerospace vehicles. However, the issues that affect the grid convergence of three dimensional RANS solutions are not completely understood, as documented in the AIAA Drag Prediction Workshop series. Grid adaption methods have the potential for increasing the automation and discretization error control of RANS solutions to impact the aerospace design and certification process. The realization of the CFD Vision 2030 Study includes automated management of errors and uncertainties of physics-based, predictive modeling that can set the stage for ensuring a vehicle is in compliance with a regulation or specification by using analysis without demonstration in flight test (i.e., certification or qualification by analysis). For example, the Cart3D inviscid analysis package has automated Cartesian cut-cell gridding with output-based error control. Fueled by recent advances in the fields of anisotropic grid adaptation, error estimation, and geometry modeling, a similar work flow is explored for viscous CFD simulations; where a CFD application engineer provides geometry, boundary conditions, and flow parameters, and the sketch-to-solution process yields a CFD simulation through automatic, error-based, grid adaptation

Parallel, Gradient-Based Anisotropic Mesh Adaptation for Re-entry Vehicle Configurations

Two gradient-based adaptation methodologies have been implemented into the Fun3d refine GridEx infrastructure. A spring-analogy adaptation which provides for nodal movement to cluster mesh nodes in the vicinity of strong shocks has been extended for general use within Fun3d, and is demonstrated for a 70 sphere cone at Mach 2. A more general feature-based adaptation metric has been developed for use with the adaptation mechanics available in Fun3d, and is applicable to any unstructured, tetrahedral, flow solver. The basic functionality of general adaptation is explored through a case of flow over the forebody of a 70 sphere cone at Mach 6. A practical application of Mach 10 flow over an Apollo capsule, computed with the Felisa flow solver, is given to compare the adaptive mesh refinement with uniform mesh refinement. The examples of the paper demonstrate that the gradient-based adaptation capability as implemented can give an improvement in solution quality

Adsorption of Toxic Metal Ions From Solution by Inactivated Cells of Larrea Tridentata Creosote Bush

Larrea tridentata (creosote bush) is a plant that grows abundantly in the desert environment. This desert plant has been found naturally growing in heavy-metal contaminated soils. Previous experiments showed that the inactivated biomass of creosote bush was able to adsorb Cu(II) ions from aqueous solutions. The copper-binding capacity of the bush biomass that grows in heavy-metal uncontaminated soils was higher than the biomass that grows in heavy-metal contaminated soils. Experiments were performed to determine the ability of creosote bush biomass (grown in heavy metal uncontaminated soils) to adsorb Pb(II), Cd(II), Zn(II), Cr(III), Cr(VI), and Ni(II) ions from aqueous solutions. Batch pH profile experiments for these metal ions showed that the metal ion binding was different for every metal tested but increased as the pH was raised from 2.0 to 6.0. The metal ion uptake by the roots, stems, and leaves was quite fast. Binding capacity experiments showed a more significant binding capacity for lead(II) and chromium(III) ions and in general, the leaves bound more metal ions than the stems and roots. A great portion of the metal ions adsorbed by the creosote’s roots, stems, and leaves was desorbed by treatment with 0.1 M HCl (up to 99% in some cases). Biomass of creosote bush may prove to be useful to remove and recover metal ions from contaminated waters

Exposure to mild blast forces induces neuropathological effects, neurophysiological deficits and biochemical changes

Direct or indirect exposure to an explosion can induce traumatic brain injury (TBI) of various severity levels. Primary TBI from blast exposure is commonly characterized by internal injuries, such as vascular damage, neuronal injury, and contusion, without external injuries. Current animal models of blast-induced TBI (bTBI) have helped to understand the deleterious effects of moderate to severe blast forces. However, the neurological effects of mild blast forces remain poorly characterized. Here, we investigated the effects caused by mild blast forces combining neuropathological, histological, biochemical and neurophysiological analysis. For this purpose, we employed a rodent blast TBI model with blast forces below the level that causes macroscopic neuropathological changes. We found that mild blast forces induced neuroinflammation in cerebral cortex, striatum and hippocampus. Moreover, mild blast triggered microvascular damage and axonal injury. Furthermore, mild blast caused deficits in hippocampal short-term plasticity and synaptic excitability, but no impairments in long-term potentiation. Finally, mild blast exposure induced proteolytic cleavage of spectrin and the cyclin-dependent kinase 5 activator, p35 in hippocampus. Together, these findings show that mild blast forces can cause aberrant neurological changes that critically impact neuronal functions. These results are consistent with the idea that mild blast forces may induce subclinical pathophysiological changes that may contribute to neurological and psychiatric disorders

Synthetic RNA Silencing of Actinorhodin Biosynthesis in Streptomyces coelicolor A3(2)

We demonstrate the first application of synthetic RNA gene silencers in Streptomyces coelicolor A3(2). Peptide nucleic acid and expressed antisense RNA silencers successfully inhibited actinorhodin production. Synthetic RNA silencing was target-specific and is a new tool for gene regulation and metabolic engineering studies in Streptomyces.Peer reviewe

A Mathematical model for Astrocytes mediated LTP at Single Hippocampal Synapses

Many contemporary studies have shown that astrocytes play a significant role in modulating both short and long form of synaptic plasticity. There are very few experimental models which elucidate the role of astrocyte over Long-term Potentiation (LTP). Recently, Perea & Araque (2007) demonstrated a role of astrocytes in induction of LTP at single hippocampal synapses. They suggested a purely pre-synaptic basis for induction of this N-methyl-D- Aspartate (NMDA) Receptor-independent LTP. Also, the mechanisms underlying this pre-synaptic induction were not investigated. Here, in this article, we propose a mathematical model for astrocyte modulated LTP which successfully emulates the experimental findings of Perea & Araque (2007). Our study suggests the role of retrograde messengers, possibly Nitric Oxide (NO), for this pre-synaptically modulated LTP.Comment: 51 pages, 15 figures, Journal of Computational Neuroscience (to appear

Actinomycete integrative and conjugative elements

This paper reviews current knowledge on actinomycete integrative and conjugative elements (AICEs). The best characterised AICEs, pSAM2 of Streptomyces ambofaciens (10.9 kb), SLP1 (17.3 kb) of Streptomyces coelicolor and pMEA300 of Amycolatopsis methanolica (13.3 kb), are present as integrative elements in specific tRNA genes, and are capable of conjugative transfer. These AICEs have a highly conserved structural organisation, with functional modules for excision/integration, replication, conjugative transfer, and regulation. Recently, it has been shown that pMEA300 and the related elements pMEA100 of Amycolatopsis mediterranei and pSE211 of Saccharopolyspora erythraea form a novel group of AICEs, the pMEA-elements, based on the unique characteristics of their replication initiator protein RepAM. Evaluation of a large collection of Amycolatopsis isolates has allowed identification of multiple pMEA-like elements. Our data show that, as AICEs, they mainly coevolved with their natural host in an integrated form, rather than being dispersed via horizontal gene transfer. The pMEA-like elements could be separated into two distinct populations from different geographical origins. One group was most closely related to pMEA300 and was found in isolates from Australia and Asia and pMEA100-related sequences were present in European isolates. Genome sequence data have enormously contributed to the recent insight that AICEs are present in many actinomycete genera. The sequence data also provide more insight into their evolutionary relationships, revealing their modular composition and their likely combined descent from bacterial plasmids and bacteriophages. Evidence is accumulating that AICEs act as modulators of host genome diversity and are also involved in the acquisition of secondary metabolite clusters and foreign DNA via horizontal gene transfer. Although still speculative, these AICEs may play a role in the spread of antibiotic resistance factors into pathogenic bacteria. The novel insights on AICE characteristics presented in this review may be used for the effective construction of new vectors that allows us to engineer and optimise strains for the production of commercially and medically interesting secondary metabolites, and bioactive proteins

Genome-wide analysis of the role of GlnR in Streptomyces venezuelae provides new insights into global nitrogen regulation in actinomycetes

<p>Abstract</p> <p>Background</p> <p>GlnR is an atypical response regulator found in actinomycetes that modulates the transcription of genes in response to changes in nitrogen availability. We applied a global <it>in vivo </it>approach to identify the GlnR regulon of <it>Streptomyces venezuelae</it>, which, unlike many actinomycetes, grows in a diffuse manner that is suitable for physiological studies. Conditions were defined that facilitated analysis of GlnR-dependent induction of gene expression in response to rapid nitrogen starvation. Microarray analysis identified global transcriptional differences between <it>glnR</it>⁺and <it>glnR </it>mutant strains under varying nitrogen conditions. To differentiate between direct and indirect regulatory effects of GlnR, chromatin immuno-precipitation (ChIP) using antibodies specific to a FLAG-tagged GlnR protein, coupled with microarray analysis (ChIP-chip), was used to identify GlnR binding sites throughout the <it>S. venezuelae </it>genome.</p> <p>Results</p> <p>GlnR bound to its target sites in both transcriptionally active and apparently inactive forms. Thirty-six GlnR binding sites were identified by ChIP-chip analysis allowing derivation of a consensus GlnR-binding site for <it>S. venezuelae</it>. GlnR-binding regions were associated with genes involved in primary nitrogen metabolism, secondary metabolism, the synthesis of catabolic enzymes and a number of transport-related functions.</p> <p>Conclusions</p> <p>The GlnR regulon of <it>S. venezuelae </it>is extensive and impacts on many facets of the organism's biology. GlnR can apparently bind to its target sites in both transcriptionally active and inactive forms.</p

Insights into Ligand–Protein Binding from Local Mechanical Response

Computational studies of ligand–protein binding are crucial for properly designing novel compounds of potential pharmacological interest. In this respect, researchers are increasingly interested in steered molecular dynamics for ligand–protein binding and unbinding studies. In particular, it has been suggested that analyzing the work profiles along the ligand–protein undocking paths could be fruitful. Here, we propose that small portions of work profiles, termed “local mechanical responses” of the system to a steering force, could serve as a universal measure for capturing relevant information about the system under investigation. Specifically, we first collected a high number of steering trajectories using two biological systems of increasing complexity (i.e., alanine dipeptide and (R)-roscovitine/CDK5 complex). Then, we devised a novel postprocessing tool to be applied to the local mechanical responses, to extract structural information related to the biological processes under investigation. Despite the out-of-equilibrium character of the trajectories, the analysis carried out on the work profiles provided pivotal information about the investigated biological processes. This could eventually be applied to drug design