Structure and thermal properties of salicylate-based-protic ionic liquids as new heat storage media. COSMO-RS structure characterization and modeling of heat capacities

During this research, we present a study on the thermal properties, such as the melting, cold crystallization, and glass transition temperatures as well as heat capacities from 293.15 K to 323.15 K of nine in-house synthesized protic ionic liquids based on the 3-(alkoxymethyl)-1H-imidazol-3-ium salicylate ([H-Im-C₁OC_n][Sal]) with n = 3–11. The 3D structures, surface charge distributions and COSMO volumes of all investigated ions are obtained by combining DFT calculations and the COSMO-RS methodology. The heat capacity data sets as a function of temperature of the 3-(alkoxymethyl)-1H-imidazol-3-ium salicylate are then predicted using the methodology originally proposed in the case of ionic liquids by Ge et al. 3-(Alkoxymethyl)-1H-imidazol-3-ium salicylate based ionic liquids present specific heat capacities higher in many cases than other ionic liquids that make them suitable as heat storage media and in heat transfer processes. It was found experimentally that the heat capacity increases linearly with increasing alkyl chain length of the alkoxymethyl group of 3-(alkoxymethyl)-1H-imidazol-3-ium salicylate as was expected and predicted using the Ge et al. method with an overall relative absolute deviation close to 3.2% for temperatures up to 323.15 K.

Association and liquid structure of pyridine-acetic acid mixtures determined from neutron scattering using a ‘free proton’ EPSR simulation model

The liquid structure of pyridine-acetic acid mixtures have been investigated using neutron scattering at various mole fractions of acetic acid, χHOAc = 0.33, 0.50, and 0.67, and compared to the structures of neat pyridine and acetic acid. Data has been modelled using Empirical Potential Structure Refinement (EPSR) with a ‘free proton’ reference model, which has no prejudicial weighting towards either the existence of molecular or ionised species. Analysis of the neutron scattering results shows the existence of hydrogen-bonded acetic acid chains with pyridine inclusions, rather than the formation of an ionic liquid by proton transfer.

GPCR structure, function, drug discovery and crystallography: report from Academia-Industry International Conference (UK Royal Society) Chicheley Hall, 1-2 September 2014

G-protein coupled receptors (GPCRs) are the targets of over half of all prescribed drugs today. The UniProt database has records for about 800 proteins classified as GPCRs, but drugs have only been developed against 50 of these. Thus, there is huge potential in terms of the number of targets for new therapies to be designed. Several breakthroughs in GPCRs biased pharmacology, structural biology, modelling and scoring have resulted in a resurgence of interest in GPCRs as drug targets. Therefore, an international conference, sponsored by the Royal Society, with world-renowned researchers from industry and academia was recently held to discuss recent progress and highlight key areas of future research needed to accelerate GPCR drug discovery. Several key points emerged. Firstly, structures for all three major classes of GPCRs have now been solved and there is increasing coverage across the GPCR phylogenetic tree. This is likely to be substantially enhanced with data from x-ray free electron sources as they move beyond proof of concept. Secondly, the concept of biased signalling or functional selectivity is likely to be prevalent in many GPCRs, and this presents exciting new opportunities for selectivity and the control of side effects, especially when combined with increasing data regarding allosteric modulation. Thirdly, there will almost certainly be some GPCRs that will remain difficult targets because they exhibit complex ligand dependencies and have many metastable states rendering them difficult to resolve by crystallographic methods. Subtle effects within the packing of the transmembrane helices are likely to mask and contribute to this aspect, which may play a role in species dependent behaviour. This is particularly important because it has ramifications for how we interpret pre-clinical data. In summary, collaborative efforts between industry and academia have delivered significant progress in terms of structure and understanding of GPCRs and will be essential for resolving problems associated with the more difficult targets in the future.

Efficient Structure Learning of Bayesian Networks using Constraints

This paper addresses the problem of learning Bayesian network structures from data based on score functions that are decomposable. It describes properties that strongly reduce the time and memory costs of many known methods without losing global optimality guarantees. These properties are derived for different score criteria such as Minimum Description Length (or Bayesian Information Criterion), Akaike Information Criterion and Bayesian Dirichlet Criterion. Then a branch-and-bound algorithm is presented that integrates structural constraints with data in a way to guarantee global optimality. As an example, structural constraints are used to map the problem of structure learning in Dynamic Bayesian networks into a corresponding augmented Bayesian network. Finally, we show empirically the benefits of using the properties with state-of-the-art methods and with the new algorithm, which is able to handle larger data sets than before.

Coupled Effects of a Perturbation in a Complex Structure Observed with SDO/AIA, SDO/HMI and ROSA/HARDcam

We study properties of intensity fluctuations in NOAA Active Region 11250 observed on 13 July 2011 starting at UT 13:32. Included are data obtained in the EUV bands of the Atmospheric Imaging Assembly on board the Solar Dynamics Observatory (SDO/AIA) as well as nearly simultaneous observations of the chromosphere made, at much higher spatial and temporal resolution, with the Rapid Oscillations in the Solar Atmosphere (ROSA) and Hydrogen-Alpha Rapid Dynamics camera (HARDcam) systems at the Dunn Solar Telescope. A complex structure seen in both the ROSA/HARDcam and SDO data sets comprises a system of loops extending outward from near the boundary of the leading sunspot umbra. It is visible in the ROSA Ca II K and HARDcam Hα images, as well as the SDO 304 Å, 171 Å and 193 Å channels, and it thus couples the chromosphere, transition region and corona. In the ground-based images the loop structure is 4.1 Mm long. Some 17.5 Mm, can be traced in the SDO/AIA data. The chromospheric emissions observed by ROSA and HARDcam appear to occupy the inner, and apparently cooler and lower, quarter of the loop. We compare the intensity fluctuations of two points within the structure. From alignment with SDO/HMI images we identify a point "A" near the loop structure, which sits directly above a bipolar magnetic feature in the photosphere. Point "B" is characteristic of locations within the loops that are visible in both the ROSA/HARDcam and the SDO/AIA data. The intensity traces for point A are quiet during the first part of the data string. At time ~ 19 min they suddenly begin a series of impulsive brightenings. In the 171 Å and 193 Å coronal lines the brightenings are localized impulses in time, but in the transition region line at 304 Å they are more extended in time. The intensity traces in the 304 Å line for point B shows a quasi-periodic signal that changes properties at about 19 min. The wavelet power spectra are characterized by two periodicities. A 6.7 min period extends from the beginning of the series until about 25 minutes, and another signal with period ~3 min starts at about 20 min. The 193 Å power spectrum has a characteristic period of 5 min, before the 20 min transition and a 2.5 min periodicity afterward. In the case of HARDcam Hα data a localized 4 min periodicity can be found until about 7 min, followed by a quiet regime. After ~20 min a 2.3 min periodicity appears. Interestingly a coronal loop visible in the 94 Å line that is centrally located in the AR, running from the leading umbra to the following polarity, at about time 20 min undergoes a strong brightening beginning at the same moment all along 15 Mm of its length. The fact that these different signals all experience a clear-cut change at time about 20 min suggests an underlying organizing mechanism. Given that point A has a direct connection to the photospheric magnetic bipole, we conjecture that the whole extended structure is connected in a complex manner to the underlying magnetic field. The periodicities in these features may favor the wave nature rather than upflows and interpretations will be discussed.

The geographical structure of British bird distributions:diversity, spatial turnover and scale

1. Using data on the spatial distribution of the British avifauna, we address three basic questions about the spatial structure of assemblages: (i) Is there a relationship between species richness (alpha diversity) and spatial turnover of species (beta diversity)? (ii) Do high richness locations have fewer species in common with neighbouring areas than low richness locations?, and (iii) Are any such relationships contingent on spatial scale (resolution or quadrat area), and do they reflect the operation of a particular kind of species-area relationship (SAR)?

2. For all measures of spatial turnover, we found a negative relationship with species richness. This held across all scales, with the exception of turnover measured as beta (sim).

3. Higher richness areas were found to have more species in common with neighbouring areas.

4. The logarithmic SAR fitted better than the power SAR overall, and fitted significantly better in areas with low richness and high turnover.

5. Spatial patterns of both turnover and richness vary with scale. The finest scale richness pattern (10 km) and the coarse scale richness pattern (90 km) are statistically unrelated. The same is true of the turnover patterns.

6. With coarsening scale, locations of the most species-rich quadrats move north. This observed sensitivity of richness 'hotspot' location to spatial scale has implications for conservation biology, e.g. the location of a reserve selected on the basis of maximum richness may change considerably with reserve size or scale of analysis.

7. Average turnover measured using indices declined with coarsening scale, but the average number of species gained or lost between neighbouring quadrats was essentially scale invariant at 10-13 species, despite mean richness rising from 80 to 146 species (across an 81-fold area increase). We show that this kind of scale invariance is consistent with the logarithmic SAR.

The structure of an unconventional HD-GYP protein from Bdellovibrio reveals the roles of conserved residues in this class of cyclic-di-GMP phosphodiesterases

UNLABELLED: Cyclic-di-GMP is a near-ubiquitous bacterial second messenger that is important in localized signal transmission during the control of various processes, including virulence and switching between planktonic and biofilm-based lifestyles. Cyclic-di-GMP is synthesized by GGDEF diguanylate cyclases and hydrolyzed by EAL or HD-GYP phosphodiesterases, with each functional domain often appended to distinct sensory modules. HD-GYP domain proteins have resisted structural analysis, but here we present the first structural representative of this family (1.28 Å), obtained using the unusual Bd1817 HD-GYP protein from the predatory bacterium Bdellovibrio bacteriovorus. Bd1817 lacks the active-site tyrosine present in most HD-GYP family members yet remains an excellent model of their features, sharing 48% sequence similarity with the archetype RpfG. The protein structure is highly modular and thus provides a basis for delineating domain boundaries in other stimulus-dependent homologues. Conserved residues in the HD-GYP family cluster around a binuclear metal center, which is observed complexed to a molecule of phosphate, providing information on the mode of hydroxide ion attack on substrate. The fold and active site of the HD-GYP domain are different from those of EAL proteins, and restricted access to the active-site cleft is indicative of a different mode of activity regulation. The region encompassing the GYP motif has a novel conformation and is surface exposed and available for complexation with binding partners, including GGDEF proteins.

IMPORTANCE: It is becoming apparent that many bacteria use the signaling molecule cyclic-di-GMP to regulate a variety of processes, most notably, transitions between motility and sessility. Importantly, this regulation is central to several traits implicated in chronic disease (adhesion, biofilm formation, and virulence gene expression). The mechanisms of cyclic-di-GMP synthesis via GGDEF enzymes and hydrolysis via EAL enzymes have been suggested by the analysis of several crystal structures, but no information has been available to date for the unrelated HD-GYP class of hydrolases. Here we present the multidomain structure of an unusual member of the HD-GYP family from the predatory bacterium Bdellovibrio bacteriovorus and detail the features that distinguish it from the wider structural family of general HD fold hydrolases. The structure reveals how a binuclear iron center is formed from several conserved residues and provides a basis for understanding HD-GYP family sequence requirements for c-di-GMP hydrolysis.

CLUSTER LEED - A VERY FAST METHOD FOR SURFACE-STRUCTURE DETERMINATION

A very fast method, cluster low-energy electron diffraction (LEED) is proposed for LEED I-V spectral analysis, in which three appproximations are introduced: the small-atom approximation, omission of the structure factors, and truncation of higher order ( > 2) scattering events. The method has been tested using a total of four sets of I-V spectra calculated by fully dynamic LEED for (i) the simple overlayer system, O on Ni{100}, and (ii) the reconstructed system, Cu on W{100}, and also one set of experimental data from W{100}-c(2 X 2)-Cu. In each case the correct structural parameters are recovered. It is suggested that for complex systems cluster LEED provides an efficient fast route to trial structures, which could be refined by automated tenser LEED.

A DIRECT INVERSION METHOD FOR SURFACE-STRUCTURE DETERMINATION FROM LEED INTENSITIES

LOW-ENERGY electron diffraction (LEED) has become the most successful technique in surface crystallography1, but because of the complexity of the surface-electron scattering interactions, analyses of LEED data are still conducted on a trial-and-error basis: a direct-inversion method for treating LEED intensity data remains an attractive goal2. Building on recent theoretical and experimental developments in electron holography from surface structures3-16, we show here that three-dimensional images with atomic resolution can be obtained by a direct transform of conventional LEED intensity spectra.

Coastal upwelling drives intertidal assemblage structure and trophic ecology

ecosystems. Coastal oceanic upwelling, for example, has been associated with elevatedbiomass and abundance patterns of certain functional groups, e.g., corticated macroalgae.In the upwelling system of Northern Chile, we examined measures of intertidal macrobenthiccomposition, structure and trophic ecology across eighteen shores varying in theirproximity to two coastal upwelling centres, in a hierarchical sampling design (spatial scalesof >1 and >10 km). The influence of coastal upwelling on intertidal communities was confirmedby the stable isotope values (δ13C and δ15N) of consumers, including a dominantsuspension feeder, grazers, and their putative resources of POM, epilithic biofilm, andmacroalgae. We highlight the utility of muscle δ15N from the suspension feeding mussel,Perumytilus purpuratus, as a proxy for upwelling, supported by satellite data and previousstudies. Where possible, we used corrections for broader-scale trends, spatial autocorrelation,ontogenetic dietary shifts and spatial baseline isotopic variation prior to analysis. Ourresults showed macroalgal assemblage composition, and benthic consumer assemblagestructure, varied significantly with the intertidal influence of coastal upwelling, especiallycontrasting bays and coastal headlands. Coastal topography also separated differences inconsumer resource use. This suggested that coastal upwelling, itself driven by coastlinetopography, influences intertidal communities by advecting nearshore phytoplankton populationsoffshore and cooling coastal water temperatures. We recommend the isotopic valuesof benthic organisms, specifically long-lived suspension feeders, as in situ alternativesto offshore measurements of upwelling influence

Urothelial cancer gene regulatory networks inferred from large-scale RNAseq, Bead and Oligo gene expression data

BACKGROUND: Urothelial pathogenesis is a complex process driven by an underlying network of interconnected genes. The identification of novel genomic target regions and gene targets that drive urothelial carcinogenesis is crucial in order to improve our current limited understanding of urothelial cancer (UC) on the molecular level. The inference of genome-wide gene regulatory networks (GRN) from large-scale gene expression data provides a promising approach for a detailed investigation of the underlying network structure associated to urothelial carcinogenesis.

METHODS: In our study we inferred and compared three GRNs by the application of the BC3Net inference algorithm to large-scale transitional cell carcinoma gene expression data sets from Illumina RNAseq (179 samples), Illumina Bead arrays (165 samples) and Affymetrix Oligo microarrays (188 samples). We investigated the structural and functional properties of GRNs for the identification of molecular targets associated to urothelial cancer.

RESULTS: We found that the urothelial cancer (UC) GRNs show a significant enrichment of subnetworks that are associated with known cancer hallmarks including cell cycle, immune response, signaling, differentiation and translation. Interestingly, the most prominent subnetworks of co-located genes were found on chromosome regions 5q31.3 (RNAseq), 8q24.3 (Oligo) and 1q23.3 (Bead), which all represent known genomic regions frequently deregulated or aberated in urothelial cancer and other cancer types. Furthermore, the identified hub genes of the individual GRNs, e.g., HID1/DMC1 (tumor development), RNF17/TDRD4 (cancer antigen) and CYP4A11 (angiogenesis/ metastasis) are known cancer associated markers. The GRNs were highly dataset specific on the interaction level between individual genes, but showed large similarities on the biological function level represented by subnetworks. Remarkably, the RNAseq UC GRN showed twice the proportion of significant functional subnetworks. Based on our analysis of inferential and experimental networks the Bead UC GRN showed the lowest performance compared to the RNAseq and Oligo UC GRNs.

CONCLUSION: To our knowledge, this is the first study investigating genome-scale UC GRNs. RNAseq based gene expression data is the data platform of choice for a GRN inference. Our study offers new avenues for the identification of novel putative diagnostic targets for subsequent studies in bladder tumors.

The Prenatal Distress Questionnaire:An investigation of factor structure in a high risk population

Background: The Prenatal Distress Questionnaire (PDQ) is a short measure designed to assess specific worries and concerns related to pregnancy. The aim of this study was to confirm the factor structure of the PDQ in a group of pregnant women with a small for gestational age infant (< 10th centile). Methods: The first PDQ assessment for each of 337 pregnant women participating in the Prospective Observational Trial to Optimise paediatric health (PORTO) study was analysed. All women enrolled in the study were identified as having a small for gestational age foetus (< 10th centile), thus representing an 'elevated risk' group. Data were analysed using confirmatory factor analysis (CFA). Three models of the PDQ were evaluated and compared in the current study: a theoretical uni-dimensional measurement model, a bi-dimensional model, and a three-factor model solution. Results: The three-factor model offered the best fit to the data while maintaining sound theoretical grounds(χ² (51df) = 128.52; CFI = 0.97; TLI = 0.96; RMSEA = 0.07). Factor 1 contained items reflecting concerns about birth and the baby, factor 2 concerns about physical symptoms and body image and factor 3 concerns about emotions and relationships. Conclusions: CFA confirmed that the three-factor model provided the best fit, with the items in each factor reflecting the findings of an earlier exploratory data analysis. © 2013 Society for Reproductive and Infant Psychology.

Large- and small-scale structure of the intermediate- and high-velocity clouds towards the LMC and SMC.

We employ Ca II K and Na I D interstellar absorption-line spectroscopy of early-type stars in the Large and Small Magellanic Clouds (LMC, SMC) to investigate the large- and small-scale structure in foreground intermediate- and high-velocity clouds (I/HVCs). Data include FLAMES-GIRAFFE Ca II K observations of 403 stars in four open clusters, plus FEROS or UVES spectra of 156 stars in the LMC and SMC. The FLAMES observations are amongst the most extensive probes to date of Ca II structures on ∼20 arcsec scales in Magellanic I/HVCs. From the FLAMES data within a 0 ∘.∘.∘.5 field of view, the Ca II K equivalent width in the I/HVC components towards three clusters varies by factors of ≥10. There are no detections of molecular gas in absorption at intermediate or high velocities, although molecular absorption is present at LMC and Galactic velocities towards some sightlines. The FEROS/UVES data show Ca II K I/HVC absorption in ∼60 per cent of sightlines. The range in the Ca II/Na I ratio in I/HVCs is from –0.45 to +1.5 dex, similar to previous measurements for I/HVCs. In 10 sightlines we find Ca II/O I ratios in I/HVC gas ranging from 0.2 to 1.5 dex below the solar value, indicating either dust or ionization effects. In nine sightlines I/HVC gas is detected in both H I and Ca II at similar velocities, implying that the two elements form part of the same structure.

Can the scaling behavior of electric conductivity be used to probe the self-organizational changes in solution with respect to the ionic liquid structure? The case of [C8MIM][NTf2]

Electrical conductivity of the supercooled ionic liquid [C8MIM][NTf2], determined as a function of temperature and pressure, highlights strong differences in its ionic transport behavior between low and high temperature regions. To date, the crossover effect which is very well known for low molecular van der Waals liquids has been rarely described for classical ionic liquids. This finding highlights that the thermal fluctuations could be dominant mechanisms driving the dramatic slowing down of ion motions near Tg. An alternative way to analyze separately low and high temperature dc-conductivity data using a density scaling approach was then proposed. Based on which a common value of the scaling exponent [gamma] = 2.4 was obtained, indicating that the applied density scaling is insensitive to the crossover effect. By comparing the scaling exponent [gamma] reported herein along with literature data for other ionic liquids, it appears that [gamma] decreases by increasing the alkyl chain length on the 1-alkyl-3-methylimidazolium-based ionic liquids. This observation may be related to changes in the interaction between ions in solution driven by an increase in the van der Waals type interaction by increasing the alkyl chain length on the cation. This effect may be related to changes in the ionic liquid nanostructural organization with the alkyl chain length on the cation as previously reported in the literature based on molecular dynamic simulations. In other words, the calculated scaling exponent [gamma] may be then used as a key parameter to probe the interaction and/or self-organizational changes in solution with respect to the ionic liquid structure.

Towards a general framework for social media research using big data

The increasing adoption of cloud computing, social networking, mobile and big data technologies provide challenges and opportunities for both research and practice. Researchers face a deluge of data generated by social network platforms which is further exacerbated by the co-mingling of social network platforms and the emerging Internet of Everything. While the topicality of big data and social media increases, there is a lack of conceptual tools in the literature to help researchers approach, structure and codify knowledge from social media big data in diverse subject matter domains, many of whom are from nontechnical disciplines. Researchers do not have a general-purpose scaffold to make sense of the data and the complex web of relationships between entities, social networks, social platforms and other third party databases, systems and objects. This is further complicated when spatio-temporal data is introduced. Based on practical experience of working with social media datasets and existing literature, we propose a general research framework for social media research using big data. Such a framework assists researchers in placing their contributions in an overall context, focusing their research efforts and building the body of knowledge in a given discipline area using social media data in a consistent and coherent manner.