Nucleosomes in serum as a marker for cell death

The concentration of nucleosomes is elevated in blood of patients with diseases which are associated with enhanced cell death. In order to detect these circulating nucleosomes, we used the Cell Death Detection-ELISA(Plus) (CDDE) from Roche Diagnostics (Mannheim, Germany) (details at http:\textbackslash{}\textbackslash{}biochem.roche.com). For its application in liquid materials we performed various modifications: we introduced a standard curve with nucleosome-rich material, which enabled direct quantification and improved comparability of the values within (CVinterassay:3.0-4.1%) and between several runs (CVinterassay:8.6-13.5%), and tested the analytical specificity of the ELISA. Because of the fast elimination of nucleosomes from circulation and their limited stability, we compared plasma and serum matrix and investigated in detail the pre-analytical handling of serum samples which can considerably influence the test results. Careless venipuncture producing hemolysis, delayed centrifugation and bacterial contamination of the blood samples led to false-positive results; delayed stabilization with EDTA and insufficient storage conditions resulted in false-negative values. At temperatures of -20 degreesC, serum samples which were treated with 10 mM EDTA were stable for at least 6 months. In order to avoid possible interfering factors, we recommend a schedule for the pre-analytical handling of the samples. As the first stage, the possible clinical application was investigated in the sera of 310 persons. Patients with solid tumors (n = 220; mean = 361 Arbitrary Units (AU)) had considerably higher values than healthy persons (n = 50; mean = 30 AU; P = 0.0001) and patients with inflammatory diseases (n = 40; mean = 296 AU; p = 0.096). Within the group of patients with tumors, those in advanced stages (UICC 4) showed significantly higher values than those in early stages (UICC 1-3) (P = 0.0004)

Bright gap solitons of atoms with repulsive interaction

We report on the first experimental observation of bright matter-wave solitons for 87Rb atoms with repulsive atom-atom interaction. This counter intuitive situation arises inside a weak periodic potential, where anomalous dispersion can be realized at the Brillouin zone boundary. If the coherent atomic wavepacket is prepared at the corresponding band edge a bright soliton is formed inside the gap. The strength of our system is the precise control of preparation and real time manipulation, allowing the systematic investigation of gap solitons.Comment: 4 pages, 4 figure

Solitons on H-bonds in proteins

A model for soliton dynamics on a hydrogen-bond network in helical proteins is proposed. It employs in three dimensions the formalism of fully integrable Toda lattices which admits phonons as well as solitons along the hydrogen-bonds of the helices. A simulation of the three dimensional Toda lattice system shows that the solitons are spontaneously created and are stable and moving along the helix axis. A perturbation on one of the three H-bond lines forms solitons on the other H-bonds as well. The robust solitary wave may explain very long-lived modes in the frequency range of 100 cm$^{-1}$ which are found in recent X-ray laser experiments. The dynamics parameters of the Toda lattice are in accordance with the usual Lennard-Jones parameters used for realistic H-bond potentials in proteins.Comment: 6 pages, 7 figure

A network analysis to identify pathophysiological pathways distinguishing ischaemic from non-ischaemic heart failure

Aims Heart failure (HF) is frequently caused by an ischaemic event (e.g. myocardial infarction) but might also be caused by a primary disease of the myocardium (cardiomyopathy). In order to identify targeted therapies specific for either ischaemic or non‐ischaemic HF, it is important to better understand differences in underlying molecular mechanisms. Methods and results We performed a biological physical protein–protein interaction network analysis to identify pathophysiological pathways distinguishing ischaemic from non‐ischaemic HF. First, differentially expressed plasma protein biomarkers were identified in 1160 patients enrolled in the BIOSTAT‐CHF study, 715 of whom had ischaemic HF and 445 had non‐ischaemic HF. Second, we constructed an enriched physical protein–protein interaction network, followed by a pathway over‐representation analysis. Finally, we identified key network proteins. Data were validated in an independent HF cohort comprised of 765 ischaemic and 100 non‐ischaemic HF patients. We found 21/92 proteins to be up‐regulated and 2/92 down‐regulated in ischaemic relative to non‐ischaemic HF patients. An enriched network of 18 proteins that were specific for ischaemic heart disease yielded six pathways, which are related to inflammation, endothelial dysfunction superoxide production, coagulation, and atherosclerosis. We identified five key network proteins: acid phosphatase 5, epidermal growth factor receptor, insulin‐like growth factor binding protein‐1, plasminogen activator urokinase receptor, and secreted phosphoprotein 1. Similar results were observed in the independent validation cohort. Conclusions Pathophysiological pathways distinguishing patients with ischaemic HF from those with non‐ischaemic HF were related to inflammation, endothelial dysfunction superoxide production, coagulation, and atherosclerosis. The five key pathway proteins identified are potential treatment targets specifically for patients with ischaemic HF

Genetic Risk and Atrial Fibrillation in Patients with Heart Failure

Aims: To study the association between an atrial fibrillation (AF) genetic risk score with prevalent AF and all-cause mortality in patients with heart failure. Methods and results: An AF genetic risk score was calculated in 3759 European ancestry individuals (1783 with sinus rhythm, 1976 with AF) from the BIOlogy Study to TAilored Treatment in Chronic Heart Failure (BIOSTAT-CHF) by summing 97 single nucleotide polymorphism (SNP) alleles (ranging from 0–2) weighted by the natural logarithm of the relative SNP risk from the latest AF genome-wide association study. Further, we assessed AF risk variance explained by additive SNP variation, and performance of clinical or genetic risk factors, and the combination in classifying AF prevalence. AF was classified as AF or atrial flutter (AFL) at baseline electrocardiogram and/or a history of AF or AFL. The genetic risk score was associated with AF after multivariable adjustment. Odds ratio for AF prevalence per 1-unit increase genetic risk score was 2.12 (95% confidence interval 1.84–2.45, P = 2.15 × 10−24) in the total cohort, 2.08 (1.72–2.50, P = 1.30 × 10−14) in heart failure with reduced ejection fraction (HFrEF) and 2.02 (1.37–2.99, P = 4.37 × 10−4) in heart failure with preserved ejection fraction (HFpEF). AF-associated loci explained 22.9% of overall AF SNP heritability. Addition of the genetic risk score to clinical risk factors increased the C-index by 2.2% to 0.721. Conclusions: The AF genetic risk score was associated with increased AF prevalence in HFrEF and HFpEF. Genetic variation accounted for 22.9% of overall AF SNP heritability. Addition of genetic risk to clinical risk improved model performance in classifying AF prevalence

Holographic formula for the determinant of the scattering operator in thermal AdS

A 'holographic formula' expressing the functional determinant of the scattering operator in an asymptotically locally anti-de Sitter(ALAdS) space has been proposed in terms of a relative functional determinant of the scalar Laplacian in the bulk. It stems from considerations in AdS/CFT correspondence of a quantum correction to the partition function in the bulk and the corresponding subleading correction at large N on the boundary. In this paper we probe this prediction for a class of quotients of hyperbolic space by a discrete subgroup of isometries. We restrict to the simplest situation of an abelian group where the quotient geometry describes thermal AdS and also the non-spinning BTZ instanton. The bulk computation is explicitly done using the method of images and the answer can be encoded in a (Patterson-)Selberg zeta-function.Comment: 11 pages, published JPA versio