Observation of Andreev bound states in YBaCuO/Au/Nb ramp-type Josephson junctions

We report on Josephson and quasiparticle tunneling in YBa2Cu3O7-x(YBCO)/Au/Nb ramp junctions of several geometries. Macroscopically, tunneling occurs in the ab-plane of YBCO either in the (100) and (010) direction, or in the (110) direction. These junctions have a stable and macroscopically well defined geometry. This allows systematic investigations of both quasiparticle and Josephson tunneling over a wide range of temperature and magnetic field. With Nb superconducting, its gap appears in the quasiparticle conductance spectra as Nb coherence peaks and a dip at the center of a broadened zero-bias conductance peak (ZBCP). As we increase the temperature or an applied magnetic field both the Nb coherence peaks and the dip get suppressed and the ZBCP fully develops, while states are conserved. With Nb in the normal state the ZBCP is observed up to about 77 K and is almost unaffected by an increasing field up to 7 T. The measurements are consistent with a convolution of density of states with broadened Andreev bound states formed at the YBCO/Au/Nb junction interfaces. Since junctions with different geometries are fabricated on the same substrate under the same conditions one expects to extract reliable tunneling information that is crystallographic direction sensitive. In high contrast to Josephson tunneling, however, the quasiparticle conductance spectra are crystallographic orientation insensitive: independent whether the tunneling occurs in the (100) or (110) directions, a pronounced ZBCP is always observed, consistent with microscopic roughness of the junction interfaces. Qualitatively, all these particularities regarding quasiparticle spectra hold regardless whether the YBCO thin film is twinned or untwinned.Comment: 13 pages, 10 figure

Dynamical effects of an unconventional current-phase relation in YBCO dc-SQUIDs

The predominant d-wave pairing symmetry in high temperature superconductors allows for a variety of current-phase relations in Josephson junctions, which is to a certain degree fabrication controlled. In this letter we report on direct experimental observations of the effects of a non-sinusoidal current-phase dependence in YBCO dc-SQUIDs, which agree with the theoretical description of the system.Comment: 4 pages, 4 ps figures, to apprear in Phys. Rev. Let

Ground state and bias current induced rearrangement of semifluxons in 0-pi long Josephson junctions

We investigate numerically a long Josephson junction with several phase pi-discontinuity points. Such junctions are usually fabricated as a ramp between an anisotropic cuprate superconductor like YBCO and an isotropic metal superconductor like Nb. From the top, they look like zigzags with pi-jumps of the Josephson phase at the corners. These pi-jumps, at certain conditions, lead to the formation of half-integer flux quanta, which we call semifluxons (SF), pinned at the corners. We show (a) that the spontaneous formation of SFs depends on the junction length, (b) that the ground state without SFs can be converted to a state with SFs by applying a bias current, (c) that the SF configuration can be rearranged by the bias current. All these effects can be observed using a SQUID microscope.Comment: ~8 pages, 6 figures, submitted to PR

A structured overview of simultaneous component based data integration

<p>Abstract</p> <p>Background</p> <p>Data integration is currently one of the main challenges in the biomedical sciences. Often different pieces of information are gathered on the same set of entities (e.g., tissues, culture samples, biomolecules) with the different pieces stemming, for example, from different measurement techniques. This implies that more and more data appear that consist of two or more data arrays that have a shared mode. An integrative analysis of such coupled data should be based on a simultaneous analysis of all data arrays. In this respect, the family of simultaneous component methods (e.g., SUM-PCA, unrestricted PCovR, MFA, STATIS, and SCA-P) is a natural choice. Yet, different simultaneous component methods may lead to quite different results.</p> <p>Results</p> <p>We offer a structured overview of simultaneous component methods that frames them in a principal components setting such that both the common core of the methods and the specific elements with regard to which they differ are highlighted. An overview of principles is given that may guide the data analyst in choosing an appropriate simultaneous component method. Several theoretical and practical issues are illustrated with an empirical example on metabolomics data for <it>Escherichia coli </it>as obtained with different analytical chemical measurement methods.</p> <p>Conclusion</p> <p>Of the aspects in which the simultaneous component methods differ, pre-processing and weighting are consequential. Especially, the type of weighting of the different matrices is essential for simultaneous component analysis. These types are shown to be linked to different specifications of the idea of a fair integration of the different coupled arrays.</p

Fluxoid dynamics in superconducting thin film rings

We have measured the dynamics of individual magnetic fluxoids entering and leaving photolithographically patterned thin film rings of the underdoped high-temperature superconductor Bi$_2$Sr$_2$CaCu$_2$O$_{8+\delta}$, using a variable sample temperature scanning SQUID microscope. These results can be qualitatively described using a model in which the fluxoid number changes by thermally activated nucleation of a Pearl vortex in, and transport of the Pearl vortex across, the ring wall.Comment: 9 pages, 10 figures, fixed typo

Paramagnetic effect in YBaCuO grain boundary junctions

A detailed investigation of the magnetic response of YBaCuO grain boundary Josephson junctions has been carried out using both radio-frequency measurements and Scanning SQUID Microscopy. In a nominally zero-field-cooled regime we observed a paramagnetic response at low external fields for 45 degree asymmetric grain boundaries. We argue that the observed phenomenology results from the d-wave order parameter symmetry and depends on Andreev bound states.Comment: To be published in Phys. Rev.

Prognostic value of galectin-3, a novel marker of fibrosis, in patients with chronic heart failure: data from the DEAL-HF study

Biomarkers are increasingly being used in the management of patients with chronic heart failure (HF). Galectin-3 is a recently developed biomarker associated with fibrosis and inflammation, and it may play a role in cardiac remodeling in HF. We determined its prognostic value in patients with chronic HF. Patients with chronic HF (New York Heart Association functional class III or IV) who participated in the Deventer-Alkmaar heart failure study were studied. Galectin-3 levels were determined at baseline using a novel optimized enzyme-linked immunosorbent assay. Univariate and multivariate analyses were used to determine the prognostic value of this biomarker. We studied 232 patients; their mean age was 71 +/- A 10 years, 72% were male, and 96% were in NYHA class III. During a follow-up period of 6.5 years, 98 patients died. Galectin-3 was a significant predictor of mortality risk after adjustment for age and sex, and severity of HF and renal dysfunction, as assessed by NT-proBNP and estimated glomerular filtration rate, respectively (hazard ratio per standard deviation 1.24, 95% CI 1.03-1.50, P = 0.026). Plasma galectin-3 is a novel prognostic marker in patients with chronic HF. Its prognostic value is independent of severity of HF, as assessed by NT-proBNP levels, and it may potentially be used in the management of such patients

Renal dysfunction is associated with shorter telomere length in heart failure

Renal dysfunction is a frequent comorbidity associated with high mortality in patients with chronic heart failure (CHF). The intrinsic biological age might affect the ability of the kidney to cope with the challenging environment caused by CHF. We explored the association between leukocyte telomere length, a marker for biological age, and renal function in patients with CHF. Telomere length was determined by a real-time quantitative polymerase chain reaction in 866 CHF patients. Renal function was estimated with the simplified Modification of Diet in Renal Disease equation. The median age was 74 (interquartile range 64-79) years, 61% male, left ventricular ejection fraction of 30 (23-44)%, and the estimated glomerular filtration rate was 53 (40-68) ml/min/1.73 m(2). Telomere length was associated with renal function (correlation coefficient 0.123, P <0.001). This relationship remained significant after adjustment for age, gender, age of CHF onset (standardized-beta 0.091, P = 0.007). Also additionally adjusting for the severity of CHF and baseline differences did not change our findings. The association between shorter leukocyte telomere length and reduced renal function in heart failure suggests that intrinsic biological aging affects the ability of the kidney to cope with the systemic changes evoked by heart failure

Dynamic metabolomic data analysis: a tutorial review

In metabolomics, time-resolved, dynamic or temporal data is more and more collected. The number of methods to analyze such data, however, is very limited and in most cases the dynamic nature of the data is not even taken into account. This paper reviews current methods in use for analyzing dynamic metabolomic data. Moreover, some methods from other fields of science that may be of use to analyze such dynamic metabolomics data are described in some detail. The methods are put in a general framework after providing a formal definition on what constitutes a ‘dynamic’ method. Some of the methods are illustrated with real-life metabolomics examples

Simplivariate Models: Uncovering the Underlying Biology in Functional Genomics Data

One of the first steps in analyzing high-dimensional functional genomics data is an exploratory analysis of such data. Cluster Analysis and Principal Component Analysis are then usually the method of choice. Despite their versatility they also have a severe drawback: they do not always generate simple and interpretable solutions. On the basis of the observation that functional genomics data often contain both informative and non-informative variation, we propose a method that finds sets of variables containing informative variation. This informative variation is subsequently expressed in easily interpretable simplivariate components