The SWAP EUV Imaging Telescope Part I: Instrument Overview and Pre-Flight Testing

The Sun Watcher with Active Pixels and Image Processing (SWAP) is an EUV solar telescope on board ESA's Project for Onboard Autonomy 2 (PROBA2) mission launched on 2 November 2009. SWAP has a spectral bandpass centered on 17.4 nm and provides images of the low solar corona over a 54x54 arcmin field-of-view with 3.2 arcsec pixels and an imaging cadence of about two minutes. SWAP is designed to monitor all space-weather-relevant events and features in the low solar corona. Given the limited resources of the PROBA2 microsatellite, the SWAP telescope is designed with various innovative technologies, including an off-axis optical design and a CMOS-APS detector. This article provides reference documentation for users of the SWAP image data.Comment: 26 pages, 9 figures, 1 movi

Effect of Dietary Components on Larval Life History Characteristics in the Medfly (Ceratitis capitata: Diptera, Tephritidae)

Background: The ability to respond to heterogenous nutritional resources is an important factor in the adaptive radiation of insects such as the highly polyphagous Medfly. Here we examined the breadth of the Medfly’s capacity to respond to different developmental conditions, by experimentally altering diet components as a proxy for host quality and novelty. Methodology/Principal Findings: We tested responses of larval life history to diets containing protein and carbohydrate components found in and outside the natural host range of this species. A 40% reduction in the quantity of protein caused a significant increase in egg to adult mortality by 26.5%±6% in comparison to the standard baseline diet. Proteins and carbohydrates had differential effects on larval versus pupal development and survival. Addition of a novel protein source, casein (i.e. milk protein), to the diet increased larval mortality by 19.4%±3% and also lengthened the duration of larval development by 1.93±0.5 days in comparison to the standard diet. Alteration of dietary carbohydrate, by replacing the baseline starch with simple sugars, increased mortality specifically within the pupal stage (by 28.2%±8% and 26.2%±9% for glucose and maltose diets, respectively). Development in the presence of the novel carbohydrate lactose (milk sugar) was successful, though on this diet there was a decrease of 29.8±1.6 µg in mean pupal weight in comparison to pupae reared on the baseline diet. Conclusions: The results confirm that laboratory reared Medfly retain the ability to survive development through a wide range of fluctuations in the nutritional environment. We highlight new facets of the responses of different stages of holometabolous life histories to key dietary components. The results are relevant to colonisation scenarios and key to the biology of this highly invasive species

Preparation of novel optical fibre-based Cocaine sensors using a molecular imprinted polymer approach

Novel chemical sensors using fibre optic-based techniques for the detection of Cocaine have been developed, utilising molecularly imprinted polymers (MIPs) containing fluorescein moieties as the signalling groups. The fluorescent MIPs were formed and covalently attached to the distal end of specially chosen optical fibres to create fibre optic probe-based sensors. These sensors exhibited are producible and quantifiable change in the intensity of the fluorescence signal received from the sensor in response to Cocaine in aqueous acetonitrile mixtures. High selectivity for Cocaine over Codeine and a range of known Cocaine interferants has been demonstrated for one of the sensors developed in this work

How to identify essential genes from molecular networks?

<p>Abstract</p> <p>Background</p> <p>The prediction of essential genes from molecular networks is a way to test the understanding of essentiality in the context of what is known about the network. However, the current knowledge on molecular network structures is incomplete yet, and consequently the strategies aimed to predict essential genes are prone to uncertain predictions. We propose that simultaneously evaluating different network structures and different algorithms representing gene essentiality (centrality measures) may identify essential genes in networks in a reliable fashion.</p> <p>Results</p> <p>By simultaneously analyzing 16 different centrality measures on 18 different reconstructed metabolic networks for <it>Saccharomyces cerevisiae</it>, we show that no single centrality measure identifies essential genes from these networks in a statistically significant way; however, the combination of at least 2 centrality measures achieves a reliable prediction of most but not all of the essential genes. No improvement is achieved in the prediction of essential genes when 3 or 4 centrality measures were combined.</p> <p>Conclusion</p> <p>The method reported here describes a reliable procedure to predict essential genes from molecular networks. Our results show that essential genes may be predicted only by combining centrality measures, revealing the complex nature of the function of essential genes.</p

NOMAD spectrometer on the ExoMars trace gas orbiter mission: part 2—design, manufacturing, and testing of the ultraviolet and visible channel

NOMAD is a spectrometer suite on board the ESA/Roscosmos ExoMars Trace Gas Orbiter, which launched in March 2016. NOMAD consists of two infrared channels and one ultraviolet and visible channel, allowing the instrument to perform observations quasi-constantly, by taking nadir measurements at the day- and night-side, and during solar occultations. Here, in part 2 of a linked study, we describe the design, manufacturing, and testing of the ultraviolet and visible spectrometer channel called UVIS. We focus upon the optical design and working principle where two telescopes are coupled to a single grating spectrometer using a selector mechanism

Modeling allosteric signal propagation using protein structure networks

Allosteric communication in proteins can be induced by the binding of effective ligands, mutations or covalent modifications that regulate a site distant from the perturbed region. To understand allosteric regulation, it is important to identify the remote sites that are affected by the perturbation-induced signals and how these allosteric perturbations are transmitted within the protein structure. In this study, by constructing a protein structure network and modeling signal transmission with a Markov random walk, we developed a method to estimate the signal propagation and the resulting effects. In our model, the global perturbation effects from a particular signal initiation site were estimated by calculating the expected visiting time (EVT), which describes the signal-induced effects caused by signal transmission through all possible routes. We hypothesized that the residues with high EVT values play important roles in allosteric signaling. We applied our model to two protein structures as examples, and verified the validity of our model using various types of experimental data. We also found that the hot spots in protein binding interfaces have significantly high EVT values, which suggests that they play roles in mediating signal communication between protein domains

Computer-Based Screening of Functional Conformers of Proteins

A long-standing goal in biology is to establish the link between function, structure, and dynamics of proteins. Considering that protein function at the molecular level is understood by the ability of proteins to bind to other molecules, the limited structural data of proteins in association with other bio-molecules represents a major hurdle to understanding protein function at the structural level. Recent reports show that protein function can be linked to protein structure and dynamics through network centrality analysis, suggesting that the structures of proteins bound to natural ligands may be inferred computationally. In the present work, a new method is described to discriminate protein conformations relevant to the specific recognition of a ligand. The method relies on a scoring system that matches critical residues with central residues in different structures of a given protein. Central residues are the most traversed residues with the same frequency in networks derived from protein structures. We tested our method in a set of 24 different proteins and more than 260,000 structures of these in the absence of a ligand or bound to it. To illustrate the usefulness of our method in the study of the structure/dynamics/function relationship of proteins, we analyzed mutants of the yeast TATA-binding protein with impaired DNA binding. Our results indicate that critical residues for an interaction are preferentially found as central residues of protein structures in complex with a ligand. Thus, our scoring system effectively distinguishes protein conformations relevant to the function of interest

Surface-Enhanced Nitrate Photolysis on Ice

Heterogeneous nitrates photolysis is the trigger for many chemical processes occurring in the polar boundary layer and is widely believed to occur in a quasi-liquid layer (QLL) at the surface of ice. The dipole forbidden character of the electronic transition relevant to boundary layer atmospheric chemistry and the small photolysis/photoproducts quantum yields in ice (and in water) may confer a significant enhancement and interfacial specificity to this important photochemical reaction at the surface of ice. Using amorphous solid water films at cryogenic temperatures as models for the disordered interstitial air/ice interface within the snowpack suppresses the diffusive uptake kinetics thereby prolonging the residence time of nitrate anions at the surface of ice. This approach allows their slow heterogeneous photolysis kinetics to be studied providing the first direct evidence that nitrates adsorbed onto the first molecular layer at the surface of ice are photolyzed more effectively than those dissolved within the bulk. Vibrational spectroscopy allows the ~3-fold enhancement in photolysis rates to be correlated with the nitrates’ distorted intramolecular geometry thereby hinting at the role played by the greater chemical heterogeneity in their solvation environment at the surface of ice than in the bulk. A simple 1D kinetic model suggests 1-that a 3(6)-fold enhancement in photolysis rate for nitrates adsorbed onto the ice surface could increase the photochemical NO[subscript 2] emissions from a 5(8) nm thick photochemically active interfacial layer by 30%(60)%, and 2-that 25%(40%) of the NO[subscript 2] photochemical emissions to the snowpack interstitial air are released from the top-most molecularly thin surface layer on ice. These findings may provide a new paradigm for heterogeneous (photo)chemistry at temperatures below those required for a QLL to form at the ice surface

Exploiting residue-level and profile-level interface propensities for usage in binding sites prediction of proteins

<p>Abstract</p> <p>Background</p> <p>Recognition of binding sites in proteins is a direct computational approach to the characterization of proteins in terms of biological and biochemical function. Residue preferences have been widely used in many studies but the results are often not satisfactory. Although different amino acid compositions among the interaction sites of different complexes have been observed, such differences have not been integrated into the prediction process. Furthermore, the evolution information has not been exploited to achieve a more powerful propensity.</p> <p>Result</p> <p>In this study, the residue interface propensities of four kinds of complexes (homo-permanent complexes, homo-transient complexes, hetero-permanent complexes and hetero-transient complexes) are investigated. These propensities, combined with sequence profiles and accessible surface areas, are inputted to the support vector machine for the prediction of protein binding sites. Such propensities are further improved by taking evolutional information into consideration, which results in a class of novel propensities at the profile level, i.e. the binary profiles interface propensities. Experiment is performed on the 1139 non-redundant protein chains. Although different residue interface propensities among different complexes are observed, the improvement of the classifier with residue interface propensities can be negligible in comparison with that without propensities. The binary profile interface propensities can significantly improve the performance of binding sites prediction by about ten percent in term of both precision and recall.</p> <p>Conclusion</p> <p>Although there are minor differences among the four kinds of complexes, the residue interface propensities cannot provide efficient discrimination for the complicated interfaces of proteins. The binary profile interface propensities can significantly improve the performance of binding sites prediction of protein, which indicates that the propensities at the profile level are more accurate than those at the residue level.</p

Cerebrospinal fluid biomarker candidates associated with human WNV neuroinvasive disease

During the last decade, the epidemiology of WNV in humans has changed in the southern regions of Europe, with high incidence of West Nile fever (WNF) cases, but also of West Nile neuroinvasive disease (WNND). The lack of human vaccine or specific treatment against WNV infection imparts a pressing need to characterize indicators associated with neurological involvement. By its intimacy with central nervous system (CNS) structures, modifications in the cerebrospinal fluid (CSF) composition could accurately reflect CNS pathological process. Until now, few studies investigated the association between imbalance of CSF elements and severity of WNV infection. The aim of the present study was to apply the iTRAQ technology in order to identify the CSF proteins whose abundances are modified in patients with WNND. Forty-seven proteins were found modified in the CSF of WNND patients as compared to control groups, and most of them are reported for the first time in the context of WNND. On the basis of their known biological functions, several of these proteins were associated with inflammatory response. Among them, Defensin-1 alpha (DEFA1), a protein reported with anti-viral effects, presente