1,634 research outputs found

    Homoclinic standing waves in focussing DNLS equations --Variational approach via constrained optimization

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    We study focussing discrete nonlinear Schr\"{o}dinger equations and present a new variational existence proof for homoclinic standing waves (bright solitons). Our approach relies on the constrained maximization of an energy functional and provides the existence of two one-parameter families of waves with unimodal and even profile function for a wide class of nonlinearities. Finally, we illustrate our results by numerical simulations.Comment: new version with revised introduction and improved condition (A3); 16 pages, several figure

    BAFF selectively enhances the survival of plasmablasts generated from human memory B cells

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    The generation of Ig-secreting cells (ISCs) from memory B cells requires interactions between antigen-specific (Ag-specific) B cells, T cells, and dendritic cells. This process must be strictly regulated to ensure sufficient humoral immunity while avoiding production of pathogenic autoantibodies. BAFF, a member of the TNF family, is a key regulator of B cell homeostasis. BAFF exerts its effect by binding to three receptors — transmembrane activator of and CAML interactor (TACI), B cell maturation antigen (BCMA), and BAFF receptor (BAFF-R). To elucidate the contribution of BAFF to the differentiation of B cells into ISCs, we tracked the fate of human memory B cells stimulated with BAFF or CD40L. BAFF and CD40L significantly increased the overall number of surviving B cells. This was achieved via distinct mechanisms. CD40L induced proliferation of nondifferentiated blasts, while BAFF prevented apoptosis of ISCs without enhancing proliferation. The altered responsiveness of activated memory B cells to CD40L and BAFF correlated with changes in surface phenotype such that expression of CD40 and BAFF-R were reduced on ISCs while BCMA was induced. These results suggest BAFF may enhance humoral immunity in vivo by promoting survival of ISCs via a BCMA-dependent mechanism. These findings have wide-ranging implications for the treatment of human immunodeficiencies as well as autoimmune diseases.This work was supported by the National Health and Medical Research Council of Australia. S.G. Tangye was supported by a U2000 Postdoctoral Fellowship awarded by the University of Sydney. P.D. Hodgkin is a Senior Research Fellow of the National Health and Medical Research Council of Australia. F. Mackay is a Wellcome Trust Senior Research Fellow

    Glomerular filtration rate by differing measures, albuminuria and prediction of cardiovascular disease, mortality and end-stage kidney disease

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    Chronic kidney disease is common in the general population and associated with excess cardiovascular disease (CVD), but kidney function does not feature in current CVD risk-prediction models. We tested three formulae for estimated glomerular filtration rate (eGFR) to determine which was the most clinically informative for predicting CVD and mortality. Using data from 440,526 participants from UK Biobank, eGFR was calculated using serum creatinine, cystatin C (eGFRcys) and creatinine-cystatin C. Associations of each eGFR with CVD outcome and mortality were compared using Cox models and adjusting for atherosclerotic risk factors (per relevant risk scores), and the predictive utility was determined by the C-statistic and categorical net reclassification index. We show that eGFRcys is most strongly associated with CVD and mortality, and, along with albuminuria, adds predictive discrimination to current CVD risk scores, whilst traditional creatinine-based measures are weakly associated with risk. Clinicians should consider measuring eGFRcys as part of cardiovascular risk assessment

    Comparison of conventional lipoprotein tests and apolipoproteins in the prediction of cardiovascular disease: data from UK Biobank

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    Background: Total cholesterol and high-density lipoprotein cholesterol (HDL-C) measurements are central to cardiovascular disease (CVD) risk assessment, but there is continuing debate around the utility of other lipids for risk prediction. Methods: Participants from UK Biobank without baseline CVD and not taking statins, with relevant lipid measurements (n=346 686), were included in the primary analysis. An incident fatal or nonfatal CVD event occurred in 6216 participants (1656 fatal) over a median of 8.9 years. Associations of nonfasting lipid measurements (total cholesterol, HDL-C, non–HDL-C, direct and calculated low-density lipoprotein cholesterol [LDL-C], and apolipoproteins [Apo] A1 and B) with CVD were compared using Cox models adjusting for classical risk factors, and predictive utility was determined by the C-index and net reclassification index. Prediction was also tested in 68 649 participants taking a statin with or without baseline CVD (3515 CVD events). Results: ApoB, LDL-C, and non–HDL-C were highly correlated (r>0.90), while HDL-C was strongly correlated with ApoA1 (r=0.92). After adjustment for classical risk factors, 1 SD increase in ApoB, direct LDL-C, and non–HDL-C had similar associations with composite fatal/nonfatal CVD events (hazard ratio, 1.23, 1.20, 1.21, respectively). Associations for 1 SD increase in HDL-C and ApoA1 were also similar (hazard ratios, 0.81 [both]). Adding either total cholesterol and HDL-C, or ApoB and ApoA, to a CVD risk prediction model (C-index, 0.7378) yielded similar improvement in discrimination (C-index change, 0.0084; 95% CI, 0.0065, 0.0104, and 0.0089; 95% CI, 0.0069, 0.0109, respectively). Once total and HDL-C were in the model, no further substantive improvement was achieved with the addition of ApoB (C-index change, 0.0004; 95% CI, 0.0000, 0.0008) or any measure of LDL-C. Results for predictive utility were similar for a fatal CVD outcome, and in a discordance analysis. In participants taking a statin, classical risk factors (C-index, 0.7118) were improved by non–HDL-C (C-index change, 0.0030; 95% CI, 0.0012, 0.0048) or ApoB (C-index change, 0.0030; 95% CI, 0.0011, 0.0048). However, adding ApoB or LDL-C to a model already containing non–HDL-C did not further improve discrimination. Conclusions: Measurement of total cholesterol and HDL-C in the nonfasted state is sufficient to capture the lipid-associated risk in CVD prediction, with no meaningful improvement from addition of apolipoproteins, direct or calculated LDL-C

    Glycated hemoglobin, prediabetes and the links to cardiovascular disease: data from UK Biobank

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    OBJECTIVE: HbA1c levels are increasingly measured in screening for diabetes; we investigated whether HbA1c may simultaneously improve cardiovascular disease (CVD) risk assessment, using QRISK3, American College of Cardiology/American Heart Association (ACC/AHA), and Systematic COronary Risk Evaluation (SCORE) scoring systems. RESEARCH DESIGN AND METHODS: UK Biobank participants without baseline CVD or known diabetes (n = 357,833) were included. Associations of HbA1c with CVD was assessed using Cox models adjusting for classical risk factors. Predictive utility was determined by the C-index and net reclassification index (NRI). A separate analysis was conducted in 16,596 participants with known baseline diabetes. RESULTS: Incident fatal or nonfatal CVD, as defined in the QRISK3 prediction model, occurred in 12,877 participants over 8.9 years. Of participants, 3.3% (n = 11,665) had prediabetes (42.0–47.9 mmol/mol [6.0–6.4%]) and 0.7% (n = 2,573) had undiagnosed diabetes (≥48.0 mmol/mol [≥6.5%]). In unadjusted models, compared with the reference group (<42.0 mmol/mol [<6.0%]), those with prediabetes and undiagnosed diabetes were at higher CVD risk: hazard ratio (HR) 1.83 (95% CI 1.69–1.97) and 2.26 (95% CI 1.96–2.60), respectively. After adjustment for classical risk factors, these attenuated to HR 1.11 (95% CI 1.03–1.20) and 1.20 (1.04–1.38), respectively. Adding HbA1c to the QRISK3 CVD risk prediction model (C-index 0.7392) yielded a small improvement in discrimination (C-index increase of 0.0004 [95% CI 0.0001–0.0007]). The NRI showed no improvement. Results were similar for models based on the ACC/AHA and SCORE risk models. CONCLUSIONS: The near twofold higher unadjusted risk for CVD in people with prediabetes is driven mainly by abnormal levels of conventional CVD risk factors. While HbA1c adds minimally to cardiovascular risk prediction, those with prediabetes should have their conventional cardiovascular risk factors appropriately measured and managed

    Solitary waves in the Nonlinear Dirac Equation

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    In the present work, we consider the existence, stability, and dynamics of solitary waves in the nonlinear Dirac equation. We start by introducing the Soler model of self-interacting spinors, and discuss its localized waveforms in one, two, and three spatial dimensions and the equations they satisfy. We present the associated explicit solutions in one dimension and numerically obtain their analogues in higher dimensions. The stability is subsequently discussed from a theoretical perspective and then complemented with numerical computations. Finally, the dynamics of the solutions is explored and compared to its non-relativistic analogue, which is the nonlinear Schr{\"o}dinger equation. A few special topics are also explored, including the discrete variant of the nonlinear Dirac equation and its solitary wave properties, as well as the PT-symmetric variant of the model

    Overturning in the Subpolar North Atlantic Program: A New International Ocean Observing System

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    For decades oceanographers have understood the Atlantic meridional overturning circulation (AMOC) to be primarily driven by changes in the production of deep-water formation in the subpolar and subarctic North Atlantic. Indeed, current Intergovernmental Panel on Climate Change (IPCC) projections of an AMOC slowdown in the twenty-first century based on climate models are attributed to the inhibition of deep convection in the North Atlantic. However, observational evidence for this linkage has been elusive: there has been no clear demonstration of AMOC variability in response to changes in deep-water formation. The motivation for understanding this linkage is compelling, since the overturning circulation has been shown to sequester heat and anthropogenic carbon in the deep ocean. Furthermore, AMOC variability is expected to impact this sequestration as well as have consequences for regional and global climates through its effect on the poleward transport of warm water. Motivated by the need for a mechanistic understanding of the AMOC, an international community has assembled an observing system, Overturning in the Subpolar North Atlantic Program (OSNAP), to provide a continuous record of the transbasin fluxes of heat, mass, and freshwater, and to link that record to convective activity and water mass transformation at high latitudes. OSNAP, in conjunction with the Rapid Climate Change–Meridional Overturning Circulation and Heatflux Array (RAPID–MOCHA) at 26°N and other observational elements, will provide a comprehensive measure of the three-dimensional AMOC and an understanding of what drives its variability. The OSNAP observing system was fully deployed in the summer of 2014, and the first OSNAP data products are expected in the fall of 2017
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