191 research outputs found

    The tilted Iceland Plume and its effect on the North Atlantic evolution and magmatism

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    Iceland and the encompassing Northeast Atlantic are characterized by abun- dant volcanism, anomalously high topography and, in many places, anoma- lously thick basaltic crust. This has been attributed to the Iceland Plume, rising from the deep mantle, though its structure and very existence are de- bated. Using seismic waveform tomography with massive datasets, we compute a new, detailed model of the crust and upper mantle beneath Iceland and the surrounding North Atlantic region. The model reveals a large, low-velocity anomaly, indicative of high temperatures, at 400-660 kilometers depth beneath eastern Greenland, where seismic receiver functions also indicate an extensive high-temperature region. The anomaly rises upwards and eastwards toward Ice- land, deflecting around the thick lithosphere of Greenland’s cratons, which we also image in detail. We interpret the major low-velocity anomaly as the Ice- land Plume, ascending from under Greenland and captured by the Mid-Atlantic Ridge. The ascent of the plume beneath the western Northeast Atlantic is con- sistent with its thin lithosphere, documented by our tomography, and abundant seamounts. Our results reconcile previously contrasting views on the structure of the Iceland Plume: while the plume is clearly visible in the transition zone beneath Greenland, it is confined to the upper mantle beneath Iceland

    The dearth of halo dwarf galaxies: is there power on short scales?

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    N-body simulations of structure formation with scale-invariant primordial perturbations show significantly more virialized objects of dwarf-galaxy mass in a typical galactic halo than are observed around the Milky Way. We show that the dearth of observed dwarf galaxies could be explained by a dramatic downturn in the power spectrum at small distance scales. This suppression of small-scale power might also help mitigate the disagreement between cuspy simulated halos and smooth observed halos, while remaining consistent with Lyman-alpha-forest constraints on small-scale power. Such a spectrum could arise in inflationary models with broken scale invariance.Comment: 5 pages LaTeX, 3 figure

    Comparison of analyses of the QTLMAS XII common dataset. I: Genomic selection

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    <p>Abstract</p> <p>A dataset was simulated and distributed to participants of the QTLMAS XII workshop who were invited to develop genomic selection models. Each contributing group was asked to describe the model development and validation as well as to submit genomic predictions for three generations of individuals, for which they only knew the genotypes. The organisers used these genomic predictions to perform the final validation by comparison to the true breeding values, which were known only to the organisers. Methods used by the 5 groups fell in 3 classes 1) fixed effects models 2) BLUP models, and 3) Bayesian MCMC based models. The Bayesian analyses gave the highest accuracies, followed by the BLUP models, while the fixed effects models generally had low accuracies and large error variance. The best BLUP models as well as the best Bayesian models gave unbiased predictions. The BLUP models are clearly sensitive to the assumed SNP variance, because they do not estimate SNP variance, but take the specified variance as the true variance. The current comparison suggests that Bayesian analyses on haplotypes or SNPs are the most promising approach for Genomic selection although the BLUP models may provide a computationally attractive alternative with little loss of efficiency. On the other hand fixed effect type models are unlikely to provide any gain over traditional pedigree indexes for selection.</p

    Discovery of Protein-Protein Interaction Inhibitors by Integrating Protein Engineering and Chemical Screening Platforms

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    Protein-protein interactions (PPIs) govern intracellular life, and identification of PPI inhibitors is challenging. Roadblocks in assay development stemming from weak binding affinities of natural PPIs impede progress in this field. We postulated that enhancing binding affinity of natural PPIs via protein engineering will aid assay development and hit discovery. This proof-of-principle study targets PPI between linear ubiquitin chains and NEMO UBAN domain, which activates NF-ÎșB signaling. Using phage display, we generated ubiquitin variants that bind to the functional UBAN epitope with high affinity, act as competitive inhibitors, and structurally maintain the existing PPI interface. When utilized in assay development, variants enable generation of robust cell-based assays for chemical screening. Top compounds identified using this approach directly bind to UBAN and dampen NF-ÎșB signaling. This study illustrates advantages of integrating protein engineering and chemical screening in hit identification, a development that we anticipate will have wide application in drug discovery

    Performance evaluation of automated urine microscopy as a rapid, non-invasive approach for the diagnosis of non-gonococcal urethritis.

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    OBJECTIVES: Gram-stained urethral smear (GSUS), the standard point-of-care test for non-gonococcal urethritis (NGU) is operator dependent and poorly specific. The performance of rapid automated urine flow cytometry (AUFC) of first void urine (FVU) white cell counts (UWCC) for predicting Mycoplasma genitalium and Chlamydia trachomatis urethral infections was assessed and its application to asymptomatic infection was evaluated. METHODS: Receiver operating characteristic curve analysis, determining FVU-UWCC threshold for predicting M. genitalium or C. trachomatis infection was performed on 208 'training' samples from symptomatic patients and subsequently validated using 228 additional FVUs obtained from prospective unselected patients. RESULTS: An optimal diagnostic threshold of >29 UWC/”L gave sensitivities and specificities for either infection of 81.5% (95% CI 65.1% to 91.6%) and 85.8% (79.5% to 90.4%), respectively, compared with 86.8% (71.1% to 95%) and 64.7% (56.9% to 71.7%), respectively, for GSUS, using the training set samples. FVU-UWCC demonstrated sensitivities and specificities of 69.2% (95% CI 48.1% to 84.9%) and 92% (87.2% to 95.2%), respectively, when using validation samples. In asymptomatic patients where GSUS was not used, AUFC would have enabled more infections to be detected compared with clinical considerations only (71.4% vs 28.6%; p=0.03). The correlation between UWCC and bacterial load was stronger for M. genitalium compared with C. trachomatis (τ=0.426, p≀0.001 vs τ=0.295, p=0.022, respectively). CONCLUSIONS: AUFC offers improved specificity over microscopy for predicting C. trachomatis or M. genitalium infection. Universal AUFC may enable non-invasive diagnosis of asymptomatic NGU at the PoC. The degree of urethral inflammation exhibits a stronger association with pathogen load for M. genitalium compared with C. trachomatis

    Genetic Determinants of Circulating Sphingolipid Concentrations in European Populations

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    Sphingolipids have essential roles as structural components of cell membranes and in cell signalling, and disruption of their metabolism causes several diseases, with diverse neurological, psychiatric, and metabolic consequences. Increasingly, variants within a few of the genes that encode enzymes involved in sphingolipid metabolism are being associated with complex disease phenotypes. Direct experimental evidence supports a role of specific sphingolipid species in several common complex chronic disease processes including atherosclerotic plaque formation, myocardial infarction (MI), cardiomyopathy, pancreatic beta-cell failure, insulin resistance, and type 2 diabetes mellitus. Therefore, sphingolipids represent novel and important intermediate phenotypes for genetic analysis, yet little is known about the major genetic variants that influence their circulating levels in the general population. We performed a genome-wide association study (GWAS) between 318,237 single-nucleotide polymorphisms (SNPs) and levels of circulating sphingomyelin (SM), dihydrosphingomyelin (Dih-SM), ceramide (Cer), and glucosylceramide (GluCer) single lipid species (33 traits); and 43 matched metabolite ratios measured in 4,400 subjects from five diverse European populations. Associated variants (32) in five genomic regions were identified with genome-wide significant corrected p-values ranging down to 9.08 x 10(-66). The strongest associations were observed in or near 7 genes functionally involved in ceramide biosynthesis and trafficking: SPTLC3, LASS4, SGPP1, ATP10D, and FADS1-3. Variants in 3 loci (ATP10D, FADS3, and SPTLC3) associate with MI in a series of three German MI studies. An additional 70 variants across 23 candidate genes involved in sphingolipid-metabolizing pathways also demonstrate association (p = 10(-4) or less). Circulating concentrations of several key components in sphingolipid metabolism are thus under strong genetic control, and variants in these loci can be tested for a role in the development of common cardiovascular, metabolic, neurological, and psychiatric diseases

    New genetic loci implicated in fasting glucose homeostasis and their impact on type 2 diabetes risk.

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    Levels of circulating glucose are tightly regulated. To identify new loci influencing glycemic traits, we performed meta-analyses of 21 genome-wide association studies informative for fasting glucose, fasting insulin and indices of beta-cell function (HOMA-B) and insulin resistance (HOMA-IR) in up to 46,186 nondiabetic participants. Follow-up of 25 loci in up to 76,558 additional subjects identified 16 loci associated with fasting glucose and HOMA-B and two loci associated with fasting insulin and HOMA-IR. These include nine loci newly associated with fasting glucose (in or near ADCY5, MADD, ADRA2A, CRY2, FADS1, GLIS3, SLC2A2, PROX1 and C2CD4B) and one influencing fasting insulin and HOMA-IR (near IGF1). We also demonstrated association of ADCY5, PROX1, GCK, GCKR and DGKB-TMEM195 with type 2 diabetes. Within these loci, likely biological candidate genes influence signal transduction, cell proliferation, development, glucose-sensing and circadian regulation. Our results demonstrate that genetic studies of glycemic traits can identify type 2 diabetes risk loci, as well as loci containing gene variants that are associated with a modest elevation in glucose levels but are not associated with overt diabetes

    Optimal resolution tomography with error tracking and the structure of the crust and upper mantle beneath Ireland and Britain

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    The classical Backus–Gilbert method seeks localized Earth-structure averages at the shortest length scales possible, given a data set, data errors, and a threshold for acceptable model errors. The resolving length at a point is the width of the local averaging kernel, and the optimal averaging kernel is the narrowest one such that the model error is below a specified level. This approach is well suited for seismic tomography, which maps 3-D Earth structure using large sets of seismic measurements. The continual measurement-error decreases and data-redundancy increases have reduced the impact of random errors on tomographic models. Systematic errors, however, are resistant to data redundancy and their effect on the model is difficult to predict. Here, we develop a method for finding the optimal resolving length at every point, implementing it for surface-wave tomography. As in the Backus–Gilbert method, every solution at a point results from an entire-system inversion, and the model error is reduced by increasing the model-parameter averaging. The key advantage of our method stems from its direct, empirical evaluation of the posterior model error at a point. We first measure inter- station phase velocities at simultaneously recording station pairs and compute phase-velocity maps at densely, logarithmically spaced periods. Numerous versions of the maps with varying smoothness are then computed, ranging from very rough to very smooth. Phase-velocity curves extracted from the maps at every point can be inverted for shear-velocity (V S ) profiles. As we show, errors in these phase-velocity curves increase nearly monotonically with the map roughness. We evaluate the error by isolating the roughness of the phase-velocity curve that cannot be explained by any Earth structure and determine the optimal resolving length at a point such that the error of the local phase-velocity curve is below a threshold. A 3-D V S model is then computed by the inversion of the composite phase-velocity maps with an optimal resolution at every point. The estimated optimal resolution shows smooth lateral variations, confirming the robustness of the procedure. Importantly, the optimal resolving length does not scale with the density of the data coverage: some of the best-sampled locations display relatively low lateral resolution, probably due to systematic errors in the data. We apply the method to image the lithosphere and underlying mantle beneath Ireland and Britain. Our very large data set was created using new data from Ireland Array, the Irish National Seismic Network, the UK Seismograph Network and other deployments. A total of 11 238 inter-station dispersion curves, spanning a very broad total period range (4–500 s), yield unprecedented data coverage of the area and provide fine regional resolution from the crust to the deep asthenosphere. The lateral resolution of the 3-D model is computed explicitly and varies from 39 km in central Ireland to over 800 km at the edges of the area, where the data coverage declines. Our tomography reveals pronounced, previously unknown variations in the lithospheric thickness beneath Ireland and Britain, with implications for their Caledonian assembly and for the mechanisms of the British Tertiary Igneous Province magmatism
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