9,193 research outputs found

    In vitro and in vivo modification of Neisseria gonorrhoeae lipooligosaccharide epitope structure by sialylation.

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    After growth of gonococci in the presence of cytidine monophospho-N-acetyl-neuraminic acid (CMP-NANA), their 4.5-kD lipooligosaccharide (LOS) component was increased by approximately 400 daltons, whereas the LOS of strains lacking the 4.5-kD component were unaffected. Expression of mAb-defined epitopes on the 4.5-kD component was decreased on LOS of strains grown in CMP-NANA, and treatment of the LOS with neuraminidase reversed this affect. Gonococci incubated with human PMNs also had decreased expression of the 4.5-kD+ epitopes. A detergent extract of gonococci incorporated radiolabeled NANA in the LOS, suggesting the presence of a sialyltransferase in gonococci. Exogenous sialyltransferases also could use LOS as an acceptor

    The Overdensity in Virgo, Sagittarius Debris, and the Asymmetric Spheroid

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    We investigate the relationship between several previously identified Galactic halo stellar structures in the direction of Virgo using imaging and spectroscopic observations of F turnoff stars and blue horizontal branch stars from the Sloan Digital Sky Survey (SDSS) and the Sloan Extension for Galactic Understanding and Exploration (SEGUE). We show that the Sagittarius dwarf leading tidal tail does not pass through the solar neighborhood; it misses the Sun by more than 15 kpc, passing through the Galactic plane outside the Solar Circle. It also is not spatially coincident with the large stellar overdensity S297+63-20.5 in the Virgo constellation. S297+63-20.5 has a distinct turnoff color and kinematics. Faint (g ~ 20.3) turnoff stars in S297+63-20.5 have line-of-sight, Galactic standard of rest velocities V(GSR)= 130 +/- 10 km/s, opposite in sign to infalling Sgr tail stars. The path of the Sgr leading tidal tail is also inconsistent with the positions of some of the nearer stars with which it has been associated, and whose velocities have favored models with prolate Milky Way potentials. We additionally show that the number densities of brighter (g ~ 19.8) F turnoff stars are not symmetric about the Galactic center, and that this discrepancy is not primarily due to the S297+63-20.5 moving group. Either the spheroid is asymmetric about the Galactic center, or there are additional substructures that conspire to be on the same side of the Galaxy as S297+63-20.5. The S297+63-20.5 overdensity in Virgo is likely associated with two other previously identified Virgo substructures: the Virgo Stellar Stream (VSS) and the Virgo Overdensity (VOD). However, the velocity difference between the VSS and S297+63-20.5 and the difference in distance estimates between the VOD and S297+63-20.5 must be reconciled.Comment: 10 figures, ApJ in pres

    Test-Retest Reliability of Diffusion Tensor Imaging in Huntington's Disease.

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    Diffusion tensor imaging (DTI) has shown microstructural abnormalities in patients with Huntington's Disease (HD) and work is underway to characterise how these abnormalities change with disease progression. Using methods that will be applied in longitudinal research, we sought to establish the reliability of DTI in early HD patients and controls. Test-retest reliability, quantified using the intraclass correlation coefficient (ICC), was assessed using region-of-interest (ROI)-based white matter atlas and voxelwise approaches on repeat scan data from 22 participants (10 early HD, 12 controls). T1 data was used to generate further ROIs for analysis in a reduced sample of 18 participants. The results suggest that fractional anisotropy (FA) and other diffusivity metrics are generally highly reliable, with ICCs indicating considerably lower within-subject compared to between-subject variability in both HD patients and controls. Where ICC was low, particularly for the diffusivity measures in the caudate and putamen, this was partly influenced by outliers. The analysis suggests that the specific DTI methods used here are appropriate for cross-sectional research in HD, and give confidence that they can also be applied longitudinally, although this requires further investigation. An important caveat for DTI studies is that test-retest reliability may not be evenly distributed throughout the brain whereby highly anisotropic white matter regions tended to show lower relative within-subject variability than other white or grey matter regions

    Associations between alcohol use and accelerated biological ageing

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    Harmful alcohol use is a leading cause of premature death and is associated with age-related disease. Biological ageing is highly variable between individuals and may deviate from chronological ageing, suggesting that biomarkers of biological ageing (derived from DNA methylation or brain structural measures) may be clinically relevant. Here, we investigated the relationships between alcohol phenotypes and both brain and DNA methylation age estimates. First, using data from UK Biobank and Generation Scotland, we tested the association between alcohol consumption (units/week) or hazardous use (Alcohol Use Disorders Identification Test [AUDIT] scores) and accelerated brain and epigenetic ageing in 20,258 and 8051 individuals, respectively. Second, we used Mendelian randomisation (MR) to test for a causal effect of alcohol consumption levels and alcohol use disorder (AUD) on biological ageing. Alcohol use showed a consistent positive association with higher predicted brain age (AUDIT-C: β = 0.053, p = 3.16 × 10−13; AUDIT-P: β = 0.052, p = 1.6 × 10−13; total AUDIT score: β = 0.062, p = 5.52 × 10−16; units/week: β = 0.078, p = 2.20 × 10−16), and two DNA methylation-based estimates of ageing, GrimAge (units/week: β = 0.053, p = 1.48 × 10−7) and PhenoAge (units/week: β = 0.077, p = 2.18x10−10). MR analyses revealed limited evidence for a causal effect of AUD on accelerated brain ageing (β = 0.118, p = 0.044). However, this result should be interpreted cautiously as the significant effect was driven by a single genetic variant. We found no evidence for a causal effect of alcohol consumption levels on accelerated biological ageing. Future studies investigating the mechanisms associating alcohol use with accelerated biological ageing are warranted

    Process evaluation of a school based physical activity related injury prevention programme using the RE-AIM framework

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    <p>Abstract</p> <p>Background</p> <p>In general, only information regarding the effectiveness of an intervention programme is ever published. However, in recent years evaluating the translatability and feasibility of an intervention programme has become more important. Therefore, this paper presents the results of the evaluation of the iPlay programme aimed at preventing physical activity related injuries in primary school children.</p> <p>Methods</p> <p>The iPlay programme targeted injuries gained through physical activity, and consisted of a teacher's manual, informative newsletters and posters, a website, and set exercises to be carried out during physical education (PE) classes. In order to evaluate the iPlay programme for translatability and feasibility, teachers, children and parents who participated in the iPlay programme filled out a questionnaire</p> <p>The objective of this study is to describe the results of the process-evaluation of the iPlay programme based on the five dimensions of the RE-AIM framework.</p> <p>Results</p> <p>The results showed that the participation rate of the children was 100% (reach). Nine percent of the schools who were invited to take part were willing to participate in the study (adoption rate). Teachers stated that they implemented the different elements of the programme partly as intended (implementation). The percentage of children and parents who followed the programme was less than expected. In addition, 52% of the teachers indicated that the current iPlay programme could become standard practice in their teaching routine (maintenance).</p> <p>Conclusion</p> <p>The iPlay programme is a first start in the prevention of physical activity related injuries in children, but further improvements need to be made to the programme on the basis of this process evaluation.</p> <p>Trial registration</p> <p>ISRCTN78846684; <url>http://www.controlled-trials.com</url></p

    Belga B-trees

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    We revisit self-adjusting external memory tree data structures, which combine the optimal (and practical) worst-case I/O performances of B-trees, while adapting to the online distribution of queries. Our approach is analogous to undergoing efforts in the BST model, where Tango Trees (Demaine et al. 2007) were shown to be O(loglogN)O(\log\log N)-competitive with the runtime of the best offline binary search tree on every sequence of searches. Here we formalize the B-Tree model as a natural generalization of the BST model. We prove lower bounds for the B-Tree model, and introduce a B-Tree model data structure, the Belga B-tree, that executes any sequence of searches within a O(loglogN)O(\log \log N) factor of the best offline B-tree model algorithm, provided B=logO(1)NB=\log^{O(1)}N. We also show how to transform any static BST into a static B-tree which is faster by a Θ(logB)\Theta(\log B) factor; the transformation is randomized and we show that randomization is necessary to obtain any significant speedup

    Methodological criteria for the assessment of moderators in systematic reviews of randomised controlled trials : a consensus study

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    Background: Current methodological guidelines provide advice about the assessment of sub-group analysis within RCTs, but do not specify explicit criteria for assessment. Our objective was to provide researchers with a set of criteria that will facilitate the grading of evidence for moderators, in systematic reviews. Method: We developed a set of criteria from methodological manuscripts (n = 18) using snowballing technique, and electronic database searches. Criteria were reviewed by an international Delphi panel (n = 21), comprising authors who have published methodological papers in this area, and researchers who have been active in the study of sub-group analysis in RCTs. We used the Research ANd Development/University of California Los Angeles appropriateness method to assess consensus on the quantitative data. Free responses were coded for consensus and disagreement. In a subsequent round additional criteria were extracted from the Cochrane Reviewers’ Handbook, and the process was repeated. Results: The recommendations are that meta-analysts report both confirmatory and exploratory findings for subgroups analysis. Confirmatory findings must only come from studies in which a specific theory/evidence based apriori statement is made. Exploratory findings may be used to inform future/subsequent trials. However, for inclusion in the meta-analysis of moderators, the following additional criteria should be applied to each study: Baseline factors should be measured prior to randomisation, measurement of baseline factors should be of adequate reliability and validity, and a specific test of the interaction between baseline factors and interventions must be presented. Conclusions: There is consensus from a group of 21 international experts that methodological criteria to assess moderators within systematic reviews of RCTs is both timely and necessary. The consensus from the experts resulted in five criteria divided into two groups when synthesising evidence: confirmatory findings to support hypotheses about moderators and exploratory findings to inform future research. These recommendations are discussed in reference to previous recommendations for evaluating and reporting moderator studies

    Deep generative modeling for single-cell transcriptomics.

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    Single-cell transcriptome measurements can reveal unexplored biological diversity, but they suffer from technical noise and bias that must be modeled to account for the resulting uncertainty in downstream analyses. Here we introduce single-cell variational inference (scVI), a ready-to-use scalable framework for the probabilistic representation and analysis of gene expression in single cells ( https://github.com/YosefLab/scVI ). scVI uses stochastic optimization and deep neural networks to aggregate information across similar cells and genes and to approximate the distributions that underlie observed expression values, while accounting for batch effects and limited sensitivity. We used scVI for a range of fundamental analysis tasks including batch correction, visualization, clustering, and differential expression, and achieved high accuracy for each task
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