Materials preparation and longevity in hyperthermal atomic oxygen

Flight hardware fabrication, the design and fabrication of an atom beam source, construction of a surface science laboratory, and progress in research on processes and mechanisms of interaction of hyperthermal atoms at solid surfaces are discussed

Measurement of Untruncated Nuclear Spin Interactions via Zero- to Ultra-Low-Field Nuclear Magnetic Resonance

Zero- to ultra-low-field nuclear magnetic resonance (ZULF NMR) provides a new regime for the measurement of nuclear spin-spin interactions free from effects of large magnetic fields, such as truncation of terms that do not commute with the Zeeman Hamiltonian. One such interaction, the magnetic dipole-dipole coupling, is a valuable source of spatial information in NMR, though many terms are unobservable in high-field NMR, and the coupling averages to zero under isotropic molecular tumbling. Under partial alignment, this information is retained in the form of so-called residual dipolar couplings. We report zero- to ultra-low-field NMR measurements of residual dipolar couplings in acetonitrile-2-$^{13}$C aligned in stretched polyvinyl acetate gels. This represents the first investigation of dipolar couplings as a perturbation on the indirect spin-spin $J$-coupling in the absence of an applied magnetic field. As a consequence of working at zero magnetic field, we observe terms of the dipole-dipole coupling Hamiltonian that are invisible in conventional high-field NMR. This technique expands the capabilities of zero- to ultra-low-field NMR and has potential applications in precision measurement of subtle physical interactions, chemical analysis, and characterization of local mesoscale structure in materials.Comment: 6 pages, 3 figure

Global alignment of protein-protein interaction networks by graph matching methods

Aligning protein-protein interaction (PPI) networks of different species has drawn a considerable interest recently. This problem is important to investigate evolutionary conserved pathways or protein complexes across species, and to help in the identification of functional orthologs through the detection of conserved interactions. It is however a difficult combinatorial problem, for which only heuristic methods have been proposed so far. We reformulate the PPI alignment as a graph matching problem, and investigate how state-of-the-art graph matching algorithms can be used for that purpose. We differentiate between two alignment problems, depending on whether strict constraints on protein matches are given, based on sequence similarity, or whether the goal is instead to find an optimal compromise between sequence similarity and interaction conservation in the alignment. We propose new methods for both cases, and assess their performance on the alignment of the yeast and fly PPI networks. The new methods consistently outperform state-of-the-art algorithms, retrieving in particular 78% more conserved interactions than IsoRank for a given level of sequence similarity. Availability:http://cbio.ensmp.fr/proj/graphm\_ppi/, additional data and codes are available upon request. Contact: [email protected]: Preprint versio

Collective dynamics in crystalline polymorphs of ZnCl2_{2}: potential modelling and inelastic neutron scattering study

We report a phonon density of states measurement of $\alpha$-ZnCl$_{2}$ using the coherent inelastic neutron scattering technique and a lattice dynamical calculation in four crystalline phases of ZnCl$_{2}$ using a transferable interatomic potential. The model calculations agree reasonably well with the available experimental data on the structures, specific heat, Raman frequencies and their pressure variation in various crystalline phases. The calculated results have been able to provide a fair description of the vibrational as well as the thermodynamic properties of ZnCl$_{2}$ in all its four phases.Comment: Accepted in J. Phys.: Condens. Matte

Does inter-vertebral range of motion increase after spinal manipulation? A prospective cohort study.

Background: Spinal manipulation for nonspecific neck pain is thought to work in part by improving inter-vertebral range of motion (IV-RoM), but it is difficult to measure this or determine whether it is related to clinical outcomes. Objectives: This study undertook to determine whether cervical spine flexion and extension IV-RoM increases after a course of spinal manipulation, to explore relationships between any IV-RoM increases and clinical outcomes and to compare palpation with objective measurement in the detection of hypo-mobile segments. Method: Thirty patients with nonspecific neck pain and 30 healthy controls matched for age and gender received quantitative fluoroscopy (QF) screenings to measure flexion and extension IV-RoM (C1-C6) at baseline and 4-week follow-up between September 2012-13. Patients received up to 12 neck manipulations and completed NRS, NDI and Euroqol 5D-5L at baseline, plus PGIC and satisfaction questionnaires at follow-up. IV-RoM accuracy, repeatability and hypo-mobility cut-offs were determined. Minimal detectable changes (MDC) over 4 weeks were calculated from controls. Patients and control IV-RoMs were compared at baseline as well as changes in patients over 4 weeks. Correlations between outcomes and the number of manipulations received and the agreement (Kappa) between palpated and QF-detected of hypo-mobile segments were calculated. Results: QF had high accuracy (worst RMS error 0.5o) and repeatability (highest SEM 1.1o, lowest ICC 0.90) for IV-RoM measurement. Hypo-mobility cut offs ranged from 0.8o to 3.5o. No outcome was significantly correlated with increased IV-RoM above MDC and there was no significant difference between the number of hypo-mobile segments in patients and controls at baseline or significant increases in IV-RoMs in patients. However, there was a modest and significant correlation between the number of manipulations received and the number of levels and directions whose IV-RoM increased beyond MDC (Rho=0.39, p=0.043). There was also no agreement between palpation and QF in identifying hypo-mobile segments (Kappa 0.04-0.06). Conclusions: This study found no differences in cervical sagittal IV-RoM between patients with non-specific neck pain and matched controls. There was a modest dose-response relationship between the number of manipulations given and number of levels increasing IV-RoM - providing evidence that neck manipulation has a mechanical effect at segmental levels. However, patient-reported outcomes were not related to this

Altered postural sway in patients suffering from non-specific neck pain and whiplash associated disorder - A systematic review of the literature

To assess differences in center of pressure (COP) measures in patients suffering from non-specific neck pain (NSNP) or whiplash-associated disorder (WAD) compared to healthy controls and any relationship between changes in postural sway and the presence of pain, its intensity, previous pain duration and the perceived level of disability. Summary of Background data: Over the past 20 years, the center of pressure (COP) has been commonly used as an index of postural stability in standing. While several studies investigated COP excursions in neck pain and WAD patients and compared these to healthy individuals, no comprehensive analysis of the reported differences in postural sway pattern exists. Search methods: Six online databases were systematically searched followed by a manual search of the retrieved papers. Selection Criteria: Papers comparing COP measures derived from bipedal static task conditions on a force plate of non-specific neck pain and WAD sufferers to those of healthy controls. Data collection and analysis: Two reviewers independently screened titles and abstracts for relevance. Screening for final inclusion, data extraction and quality assessment were carried out with a third reviewer to reconcile differences

Collaborative annotation of genes and proteins between UniProtKB/Swiss-Prot and dictyBase

UniProtKB/Swiss-Prot, a curated protein database, and dictyBase, the Model Organism Database for Dictyostelium discoideum, have established a collaboration to improve data sharing. One of the major steps in this effort was the ‘Dicty annotation marathon’, a week-long exercise with 30 annotators aimed at achieving a major increase in the number of D. discoideum proteins represented in UniProtKB/Swiss-Prot. The marathon led to the annotation of over 1000 D. discoideum proteins in UniProtKB/Swiss-Prot. Concomitantly, there were a large number of updates in dictyBase concerning gene symbols, protein names and gene models. This exercise demonstrates how UniProtKB/Swiss-Prot can work in very close cooperation with model organism databases and how the annotation of proteins can be accelerated through those collaborations

Dirichlet Multinomial Mixtures: Generative Models for Microbial Metagenomics

We introduce Dirichlet multinomial mixtures (DMM) for the probabilistic modelling of microbial metagenomics data. This data can be represented as a frequency matrix giving the number of times each taxa is observed in each sample. The samples have different size, and the matrix is sparse, as communities are diverse and skewed to rare taxa. Most methods used previously to classify or cluster samples have ignored these features. We describe each community by a vector of taxa probabilities. These vectors are generated from one of a finite number of Dirichlet mixture components each with different hyperparameters. Observed samples are generated through multinomial sampling. The mixture components cluster communities into distinct ‘metacommunities’, and, hence, determine envirotypes or enterotypes, groups of communities with a similar composition. The model can also deduce the impact of a treatment and be used for classification. We wrote software for the fitting of DMM models using the ‘evidence framework’ (http://code.google.com/p/microbedmm/). This includes the Laplace approximation of the model evidence. We applied the DMM model to human gut microbe genera frequencies from Obese and Lean twins. From the model evidence four clusters fit this data best. Two clusters were dominated by Bacteroides and were homogenous; two had a more variable community composition. We could not find a significant impact of body mass on community structure. However, Obese twins were more likely to derive from the high variance clusters. We propose that obesity is not associated with a distinct microbiota but increases the chance that an individual derives from a disturbed enterotype. This is an example of the ‘Anna Karenina principle (AKP)’ applied to microbial communities: disturbed states having many more configurations than undisturbed. We verify this by showing that in a study of inflammatory bowel disease (IBD) phenotypes, ileal Crohn's disease (ICD) is associated with a more variable community

Prediction of catalytic residues using Support Vector Machine with selected protein sequence and structural properties

BACKGROUND: The number of protein sequences deriving from genome sequencing projects is outpacing our knowledge about the function of these proteins. With the gap between experimentally characterized and uncharacterized proteins continuing to widen, it is necessary to develop new computational methods and tools for functional prediction. Knowledge of catalytic sites provides a valuable insight into protein function. Although many computational methods have been developed to predict catalytic residues and active sites, their accuracy remains low, with a significant number of false positives. In this paper, we present a novel method for the prediction of catalytic sites, using a carefully selected, supervised machine learning algorithm coupled with an optimal discriminative set of protein sequence conservation and structural properties. RESULTS: To determine the best machine learning algorithm, 26 classifiers in the WEKA software package were compared using a benchmarking dataset of 79 enzymes with 254 catalytic residues in a 10-fold cross-validation analysis. Each residue of the dataset was represented by a set of 24 residue properties previously shown to be of functional relevance, as well as a label {+1/-1} to indicate catalytic/non-catalytic residue. The best-performing algorithm was the Sequential Minimal Optimization (SMO) algorithm, which is a Support Vector Machine (SVM). The Wrapper Subset Selection algorithm further selected seven of the 24 attributes as an optimal subset of residue properties, with sequence conservation, catalytic propensities of amino acids, and relative position on protein surface being the most important features. CONCLUSION: The SMO algorithm with 7 selected attributes correctly predicted 228 of the 254 catalytic residues, with an overall predictive accuracy of more than 86%. Missing only 10.2% of the catalytic residues, the method captures the fundamental features of catalytic residues and can be used as a "catalytic residue filter" to facilitate experimental identification of catalytic residues for proteins with known structure but unknown function