Development of a novel PCR assay for the identification of the black yeast, Exophiala (Wangiella) dermatitidis from adult patients with cystic fibrosis (CF)

Cystic fibrosis (CF) patients may suffer increased morbidity and mortality through colonisation, allergy and invasive infection from fungi. The black yeast, Exophiala dermatitidis (synonym Wangiella dermatitidis) has been found with increasing frequency in sputum specimens of CF patients, with reported isolation rates ranging from 1.1 to 15.7%. At present, no diagnostic PCR exists to aid with the clinical laboratory detection and identification of this organism. A novel species-specific PCR-based assay was developed for the detection of E. dermatitidis, based on employment of rDNA operons and interspacer (ITS) regions between these rDNA operons. Two novel primers, (designated ExdF & ExdR) were designed in silico with the aid of computer-aided alignment software and with the alignment of multiple species of Exophiala, as well as with other commonly described yeasts and filamentous fungi within CF sputum, including Candida. Aspergillus and Scedosporium. An amplicon of approximately 455 by was generated, spanning the partial ITS I region - the complete 5.8S rDNA region - partial ITS2 region, employing ExdF (forward primer [16-mer], 5'-CCG CCT ATT CAG GTC C-3' and ExdR (reverse primer [16-mer], 5'-TCT CTC CCA CTC CCG C-3', was employed and optimised on extracted genomic DNA from a well characterised culture of E. dermatitidis, as well as with high quality genomic DNA template from a further 16 unrelated fungi, including Candida albicans, C. dubliniensis, C. parapsilosis, C. glabrata, Scedosporium apiospermum, Penicillium sp., Aspergillus fumigatus, Aspergillus versicolor, Pichia guilliermondii, Rhodotorula sp., Trichosporon sp., Aureobasidium pullulans, Fusarium sp., Mucor hiemalis, Bionectria ochroleuca, Gibberella pulicaris. Results demonstrated that only DNA from E. dermatitidis gave an amplification product of the expected sire, whilst none of the other fungi were amplifiable. Subsequent employment of this primer pair detected this yeast from mycological cultures from 2/50 (4%) adult CF patients. These two patients were the only patients who were previously shown to have a cultural history of E. dermatitidis from their sputum. E. dermatitidis is a slow-growing fungus, which usually takes up to two weeks to culture in the microbiology laboratory and therefore is slow to detect conventionally, with the risk of bacterial overgrowth from common co-habiting pan- and multiresistant bacterial pathogens from sputum. namely Pseudomonas aeruginosa and Burkholderia cepacia complex organisms, hence this species-specific PCR assay may help detect this organism from CF sputum more specifically and rapidly. Overall, employment of this novel assay nay help in the understanding of the occurrence. aetiology and epidemiology of E. dermatitidis, as an emerging fungal agent in patients with CF. (C) 2008 European Cystic Fibrosis Society. Published by Elsevier B.V. All rights reserved.

Using Virtual Reality to Analyze Sports Performance

Improving performance in sports requires a better understanding of the perception-action loop employed by athletes. Because of its inherent limitations, video playback doesn't permit this type of in-depth analysis. Interactive, immersive virtual reality can overcome these limitations and foster a better understanding of sports performance.

Rhodopsin and the Others: A Historical Perspective on Structural Studies of G Protein-Coupled Receptors

The role of rhodopsin as a structural prototype for the study of the whole superfamily of G protein-coupled receptors (GPCRs) is reviewed in an historical perspective. Discovered at the end of the nineteenth century, fully sequenced since the early 1980s, and with direct three-dimensional information available since the 1990s, rhodopsin has served as a platform to gather indirect information on the structure of the other superfamily members. Recent breakthroughs have elicited the solution of the structures of additional receptors, namely the beta 1- and beta 2-adrenergic receptors and the A(2A) adenosine receptor, now providing an opportunity to gauge the accuracy of homology modeling and molecular docking techniques and to perfect the computational protocol. Notably, in coordination with the solution of the structure of the A(2A) adenosine receptor, the first "critical assessment of GPCR structural modeling and docking" has been organized, the results of which highlighted that the construction of accurate models, although challenging, is certainly achievable. The docking of the ligands and the scoring of the poses clearly emerged as the most difficult components. A further goal in the field is certainly to derive the structure of receptors in their signaling state, possibly in complex with agonists. These advances, coupled with the introduction of more sophisticated modeling algorithms and the increase in computer power, raise the expectation for a substantial boost of the robustness and accuracy of computer-aided drug discovery techniques in the coming years.

Ligand and structure-based methodologies for the prediction of the activity of G protein-coupled receptor ligands

Accurate in silico models for the quantitative prediction of the activity of G protein-coupled receptor (GPCR) ligands would greatly facilitate the process of drug discovery and development. Several methodologies have been developed based on the properties of the ligands, the direct study of the receptor-ligand interactions, or a combination of both approaches. Ligand-based three-dimensional quantitative structure-activity relationships (3D-QSAR) techniques, not requiring knowledge of the receptor structure, have been historically the first to be applied to the prediction of the activity of GPCR ligands. They are generally endowed with robustness and good ranking ability; however they are highly dependent on training sets. Structure-based techniques generally do not provide the level of accuracy necessary to yield meaningful rankings when applied to GPCR homology models. However, they are essentially independent from training sets and have a sufficient level of accuracy to allow an effective discrimination between binders and nonbinders, thus qualifying as viable lead discovery tools. The combination of ligand and structure-based methodologies in the form of receptor-based 3D-QSAR and ligand and structure-based consensus models results in robust and accurate quantitative predictions. The contribution of the structure-based component to these combined approaches is expected to become more substantial and effective in the future, as more sophisticated scoring functions are developed and more detailed structural information on GPCRs is gathered.

Thermophysical Properties of Amino Acid-Based Ionic Liquids

Ionic liquids (ILs) having either cations or anions derived from naturally occurring amino acids have been synthesized and characterized as amino acid-based ionic liquids (AAILs) In this work, the experimental measurements of the temperature dependence or density. viscosity, heat capacity, and thermal conductivity of several AAILs, namely, tributylmethylammonium serinate ([N-444][Ser], tributylmethylammonium taurmate ([N-444][Tau]) tributylmethylammonium lysinate a [N-444][ Lys]), tributylmethylammonium threonate ([N-444][Thr]), tetrabutylphosphonium serinate ([P-4444][Ser]), tetrabutylphosphonium taurmate ([P-4444][Tau]), tetrabutylphosphonium lysinate ([P-4444][Lys]), tetrabutylphosphonium threonate P-4444 Thr tetrabutylphosphonium prolinate P-4444 ((Pro(), tetrabutylphosphonium valinate ([P-4444][Val]), and tetrabutylphosphonium cysteinate ([P-4444][Cys]), are presented The influence of cations and anions on studied properties is discussed. On the basis of experimental data. the QSPR (quantitative structure property relationship) correlations and group contribution methods for thermophysical properties of AAILs have been developed, which form the basis for the development of the computer-aided molecular design (CAMD) of AAILs It has also been demonstrated that that the predictive data obtained by con elation methods ale in good agreement with the experimental data The correlations developed, herein. can thus be used to evaluate the studied thermophysical properties of AAILs for use in process design or in the CAMD of new AAILs

Automated mixed dimensional modelling from 2D and 3D CAD models

The motivation for this paper is to present procedures for automatically creating idealised finite element models from the 3D CAD solid geometry of a component. The procedures produce an accurate and efficient analysis model with little effort on the part of the user. The technique is applicable to thin walled components with local complex features and automatically creates analysis models where 3D elements representing the complex regions in the component are embedded in an efficient shell mesh representing the mid-faces of the thin sheet regions. As the resulting models contain elements of more than one dimension, they are referred to as mixed dimensional models. Although these models are computationally more expensive than some of the idealisation techniques currently employed in industry, they do allow the structural behaviour of the model to be analysed more accurately, which is essential if appropriate design decisions are to be made. Also, using these procedures, analysis models can be created automatically whereas the current idealisation techniques are mostly manual, have long preparation times, and are based on engineering judgement. In the paper the idealisation approach is first applied to 2D models that are used to approximate axisymmetric components for analysis. For these models 2D elements representing the complex regions are embedded in a 1D mesh representing the midline of the cross section of the thin sheet regions. Also discussed is the coupling, which is necessary to link the elements of different dimensionality together. Analysis results from a 3D mixed dimensional model created using the techniques in this paper are compared to those from a stiffened shell model and a 3D solid model to demonstrate the improved accuracy of the new approach. At the end of the paper a quantitative analysis of the reduction in computational cost due to shell meshing thin sheet regions demonstrates that the reduction in degrees of freedom is proportional to the square of the aspect ratio of the region, and for long slender solids, the reduction can be proportional to the aspect ratio of the region if appropriate meshing algorithms are used.

Regenerative Medicine and New Labour Life Science Policy: Rhetorics of Success, Narratives of Sustainability and Survival

Advances in stem cell science and tissue engineering are being turned into applications and products through a novel medical paradigm known as regenerative medicine. This paper begins by examining the vulnerabilities and risks encountered by the regenerative medicine industry during a pivotal moment in its scientific infancy: the 2000s. Under the auspices of New Labour, British medical scientists and life science innovation firms associated with regenerative medicine, received demonstrative rhetorical pledges of support, aligned with the publication of a number of government initiated reports presaged by Bioscience 2015: Improving National Health, Increasing National Wealth. The Department of Health and the Department of Trade and Industry (and its successors) held industry consultations to determine the best means by which innovative bioscience cultures might be promoted and sustained in Britain. Bioscience 2015 encapsulates the first chapter of this sustainability narrative. By 2009, the tone of this storyline had changed to one of survivability. In the second part of the paper, we explore the ministerial interpretation of the ‘bioscience discussion cycle’ that embodies this narrative of expectation, using a computer-aided content analysis programme. Our analysis notes that the ministerial interpretation of these reports has continued to place key emphasis upon the distinctive and exceptional characteristics of the life science industries, such as their ability to perpetuate innovations in regenerative medicine and the optimism this portends – even though many of the economic expectations associated with this industry have remained unfulfilled.

Binding modes of diketo-acid inhibitors of HIV-1 integrase: A comparative molecular dynamics simulation study

HIV-1 integrase (IN) has become an attractive target since drug resistance against HIV-1 reverse transcriptase (RT) and protease (PR) has appeared. Diketo acid (DKA) inhibitors are potent and selective inhibitors of HIV-1 IN: however the action mechanism is not well understood. Here, to study the inhibition mechanism of DKAs we performed 10 ns comparative molecular dynamics simulations on HIV-1 IN bound with three most representative DMA inhibitors: Shionogi inhibitor, S-1360 and two Merck inhibitors L-731,988 and L-708,906. Our simulations show that the acidic part of S-1360 formed salt bridge and cation-pi interactions with Lys159. In addition, the catalytic Glu152 in S-1360 was pushed away from the active site to form an ion-pair interaction with Arg199. The Merck inhibitors can maintain either one or both of these ion-pair interaction features. The difference in potencies of the DMA inhibitors is thus attributed to the different binding modes at the catalytic site. Such structural information at atomic level, not only demonstrates the action modes of DMA inhibitors but also provides a novel starting point for structural-based design of HIV-1 IN inhibitors.

Determining the parametric effectiveness of a CAD model

The motivation for this paper is to present an approach for rating the quality of the parameters in a computer-aided design model for use as optimization variables. Parametric Effectiveness is computed as the ratio of change in performance achieved by perturbing the parameters in the optimum way, to the change in performance that would be achieved by allowing the boundary of the model to move without the constraint on shape change enforced by the CAD parameterization. The approach is applied in this paper to optimization based on adjoint shape sensitivity analyses. The derivation of parametric effectiveness is presented for optimization both with and without the constraint of constant volume. In both cases, the movement of the boundary is normalized with respect to a small root mean squared movement of the boundary. The approach can be used to select an initial search direction in parameter space, or to select sets of model parameters which have the greatest ability to improve model performance. The approach is applied to a number of example 2D and 3D FEA and CFD problems.

Strategies for adding features to CAD models in order to optimize performance

This paper presents an approach which enables new parameters to be added to a CAD model for optimization purposes. It aims to remove a common roadblock to CAD based optimization, where the parameterization of the model does not offer the shape sufficient flexibility for a truly optimized shape to be created. A technique has been developed which uses adjoint based sensitivity maps to predict
the sensitivity of performance to the addition to a model of four different feature types, allowing the feature providing the greatest benefit to be selected. The optimum position to add the feature is also discussed. It is anticipated that the approach could be used to iteratively add features to a model, providing greater flexibility to the shape of the model, and allowing the newly-added parameters to be used as design variables in a subsequent shape optimization.

Simultaneous, long-term monitoring of valve and cardiac activity in the blue mussel Mytilus edulis exposed to copper

Valve and cardiac activity were simultaneously measured in the blue mussel (Mytilus edulis) in response to 10 d copper exposure. Valve movements, heart rates and heart-rate variability were obtained non-invasively using a Musselmonitor(R) (valve activity) and a modified version of the Computer-Aided Physiological Monitoring system (CAPMON; cardiac activity). After 2 d exposure of mussels (4 individuals per treatment group) to a range of dissolved copper concentrations (0 to 12.5 mu M as CuCl2) median valve positions (% open) and median heart rates (beats per minute) declined as a function of copper concentration. Heart-rate variability (coefficient of variation for interpulse durations) rose in a concentration-dependent manner. The 48 h EC50 values (concentrations of copper causing 50% change) for valve positions, heart rates and heart-rate variability were 2.1, 0.8, and 0.06 mu M, respectively. Valve activity was weakly correlated with both heart rate (r = 0.48 +/- 0.02) and heart-rate variability (r = 0.32 +/- 0.06) for control individuals (0 mu M Cu2+). This resulted from a number of short enclosure events that did not coincide with a change in cardiac activity. Exposure of mussels to increasing copper concentrations (greater than or equal to 0.8 mu M) progressively reduced the correlation between valve activity and heart rates (r = 0 for individuals dosed with greater than or equal to 6.3 mu M Cu2+), while correlations between valve activity and heart-rate variability were unaffected. The poor correlations resulted from periods of valve flapping that were not mimicked by similar fluctuations in heart rate or heart-rate variability. The data suggest that the copper-induced bradycardia observed in mussels is not a consequence of prolonged valve closure.

Chip design for high-performance DSP

Advances in silicon technology have been a key development in the realisation of many telecommunication and signal processing systems. In many cases, the development of application-specific digital signal processing (DSP) chips is the most cost-effective solution and provides the highest performance. Advances made in computer-aided design (CAD) tools and design methodologies now allow designers to develop complex chips within months or even weeks. This paper gives an insight into the challenges and design methodologies of implementing advanced highperformance chips for DSP. In particular, the paper reviews some of the techniques used to develop circuit architectures from high-level descriptions and the tools which are then used to realise silicon layout.

A virtual inspection framework for precision manufacturing of aerofoil components

The finite element method plays an extremely important role in forging process design as it provides a valid means to quantify forging errors and thereby govern die shape modification to improve the dimensional accuracy of the component. However, this dependency on process simulation could raise significant problems and present a major drawback if the finite element simulation results were inaccurate. This paper presents a novel approach to assess the dimensional accuracy and shape quality of aeroengine blades formed from finite element hot-forging simulation. The proposed virtual inspection system uses conventional algorithms adopted by modern coordinate measurement processes as well as the latest free-form surface evaluation techniques to provide a robust framework for virtual forging error assessment. Established techniques for the physical registration of real components have been adapted to localise virtual models in relation to a nominal Design Coordinate System. Blades are then automatically analysed using a series of intelligent routines to generate measurement data and compute dimensional errors. The results of a comparison study indicate that the virtual inspection results and actual coordinate measurement data are highly comparable, validating the approach as an effective and accurate means to quantify forging error in a virtual environment. Consequently, this provides adequate justification for the implementation of the virtual inspection system in the virtual process design, modelling and validation of forged aeroengine blades in industry.