Ising-like dynamical signatures and the end-point of the QCD transition line

An increase in the size of coherent domains in the one component $\Phi^4$ field theory under the influence of a uniformly changing external magnetic field near the critical end-point $T_{\Phi}=T_c, h_{\Phi}=0$ was proposed recently as an estimate also for the variation of the chiral correlation length of QCD near its respective hypothetical end point in the $T_{QCD}-\mu_{QCD}$ plane. The present detailed numerical investigation of the effective model suggests that passing by the critical QCD end point with realistic rate of temperature change will trigger large amplitude oscillations in the temporal variation of the chiral correlation length. A simple mechanism for producing this phenomenon is suggested.Comment: 10 pages, RevTeX, 5 figures. Version accepted for publication in PR

Intestinal Microbiota-Dependent Phosphatidylcholine Metabolites, Diastolic Dysfunction, and Adverse Clinical Outcomes in Chronic Systolic Heart Failure

Background: Trimethylamine-N-oxide (TMAO) has been linked to increased cardiovascular risk. We aimed to determine the prognostic value of TMAO and its dietary precursors, choline and betaine, in heart failure (HF). Methods and Results: In 112 patients with chronic systolic HF with comprehensive echocardiographic evaluation, we measured plasma TMAO, choline, and betaine by mass spectrometry. Median (interquartile range) TMAO levels, choline, and betaine levels were 5.8 (3.6–12.1) μmol/L, 10.9 (8.4–14.0) μmol/L, and 43.8 (37.1–53.0) μmol/L, respectively, and were correlated with each other (all P \u3c .0001 for both). TMAO levels were significantly higher in patients with diabetes mellitus (9.4 [4.9–13.2] vs 4.8 [3.4–9.8] μmol/L; P = .005) and in subjects with New York Heart Association functional class III or greater (7.0 [4.7–14.8] vs 4.7 [3.4–11.3] μmol/L; P = .02). Elevated TMAO, choline, and betaine levels were each associated with higher plasma N-terminal pro–B-type natriuretic peptide (NT-proBNP) levels and more advanced left ventricular diastolic dysfunction, but not systolic dysfunction or inflammatory and endothelial biomarkers. Higher choline (hazard ratio [HR] 1.64, 95% CI 1.22–2.20; P = .001), betaine (HR 1.51, 95% CI 1.10–2.08; P = .01), and TMAO (HR 1.48, 95% CI 1.10–1.96; P = .01) predicted increased risk for 5-year adverse clinical events (death/transplantation). Only higher TMAO levels predicted incident adverse clinical events independently from age, estimated glomerular filtration rate, mitral E/septal Ea, and NT-proBNP levels (HR 1.46, 95% CI 1.03–2.14; P = .03). Conclusion: Elevated plasma TMAO, choline, and betaine levels are each associated with more advanced left ventricular diastolic dysfunction and portend poorer long-term adverse clinical outcomes in chronic systolic HF. However, only higher plasma TMAO was associated with poor prognosis after adjustment for cardiorenal indices

Itinerant electron metamagnetism in LaCo9_9Si4_4

The strongly exchange enhanced Pauli paramagnet LaCo$_9$Si$_4$ is found to exhibit an itinerant metamagnetic phase transition with indications for metamagnetic quantum criticality. Our investigation comprises magnetic, specific heat, and NMR measurements as well as ab-initio electronic structure calculations. The critical field is about 3.5 T for $H||c$ and 6 T for $H\bot c$, which is the lowest value ever found for rare earth intermetallic compounds. In the ferromagnetic state there appears a moment of about 0.2 $\mu_B$/Co at the $16k$ Co-sites, but sigificantly smaller moments at the 4d and $16l$ Co-sites.Comment: 11 pages, 5 figures, PRB Rapid Communication, in prin

Circulating cardiac troponin I levels measured by a novel highly sensitive assay in acute decompensated heart failure: insights from the ASCEND-HF trial

Background: Circulating cardiac troponin levels (cTn), representative of myocardial injury, are commonly elevated in heart failure (HF) and related to adverse clinical events. However, whether cTn represents a spectrum of risk in HF is unclear. Methods: Baseline, 48–72 hour, and 30 day plasma cTnI was measured by a novel highly-sensitive assay in 900 subjects with acute decompensated HF (ADHF) in ASCEND-HF. Multivariable models determined the relationship between cTnI and outcomes. Results: The median(interquartile range) cTnI was 16.4 (9.3-31.6) ng/L at baseline, 14.1 (7.8-29.7) ng/L at 48-72 hours, and 11.6 (6.8-22.5) ng/L at 30 days. After additional adjustment for amino terminal pro-B-type natriuretic peptide (NT-proBNP) to established risk predictors, both baseline and 48-72 hour cTnI were associated with higher risk for death or worsening HF prior to discharge (OR 1.25, P=0.03 and OR 1.43, P=0.001, respectively). However, only cTnI at 30 days was associated 180-day death (HR 1.25, P=0.007). There were no curvilinear associations between changing cTnI and clinical outcomes. Conclusions: Circulating cTnI level was associated with clinical outcomes in ADHF, but these observations diminished with additional adjustment for NT-proBNP. Although they likely represent a spectrum of risk in ADHF, these findings question the implications of changing cTnI levels during treatment

Measurement of the scintillation time spectra and pulse-shape discrimination of low-energy beta and nuclear recoils in liquid argon with DEAP-1

The DEAP-1 low-background liquid argon detector was used to measure scintillation pulse shapes of electron and nuclear recoil events and to demonstrate the feasibility of pulse-shape discrimination (PSD) down to an electron-equivalent energy of 20 keV. In the surface dataset using a triple-coincidence tag we found the fraction of beta events that are misidentified as nuclear recoils to be $<1.4\times 10^{-7}$ (90% C.L.) for energies between 43-86 keVee and for a nuclear recoil acceptance of at least 90%, with 4% systematic uncertainty on the absolute energy scale. The discrimination measurement on surface was limited by nuclear recoils induced by cosmic-ray generated neutrons. This was improved by moving the detector to the SNOLAB underground laboratory, where the reduced background rate allowed the same measurement with only a double-coincidence tag. The combined data set contains $1.23\times10^8$ events. One of those, in the underground data set, is in the nuclear-recoil region of interest. Taking into account the expected background of 0.48 events coming from random pileup, the resulting upper limit on the electronic recoil contamination is $<2.7\times10^{-8}$ (90% C.L.) between 44-89 keVee and for a nuclear recoil acceptance of at least 90%, with 6% systematic uncertainty on the absolute energy scale. We developed a general mathematical framework to describe PSD parameter distributions and used it to build an analytical model of the distributions observed in DEAP-1. Using this model, we project a misidentification fraction of approx. $10^{-10}$ for an electron-equivalent energy threshold of 15 keV for a detector with 8 PE/keVee light yield. This reduction enables a search for spin-independent scattering of WIMPs from 1000 kg of liquid argon with a WIMP-nucleon cross-section sensitivity of $10^{-46}$ cm$^2$, assuming negligible contribution from nuclear recoil backgrounds.Comment: Accepted for publication in Astroparticle Physic

Relations between lipoprotein(a) concentrations, LPA genetic variants, and the risk of mortality in patients with established coronary heart disease: a molecular and genetic association study

Background: Lipoprotein(a) concentrations in plasma are associated with cardiovascular risk in the general population. Whether lipoprotein(a) concentrations or LPA genetic variants predict long-term mortality in patients with established coronary heart disease remains less clear. Methods: We obtained data from 3313 patients with established coronary heart disease in the Ludwigshafen Risk and Cardiovascular Health (LURIC) study. We tested associations of tertiles of lipoprotein(a) concentration in plasma and two LPA single-nucleotide polymorphisms ([SNPs] rs10455872 and rs3798220) with all-cause mortality and cardiovascular mortality by Cox regression analysis and with severity of disease by generalised linear modelling, with and without adjustment for age, sex, diabetes diagnosis, systolic blood pressure, BMI, smoking status, estimated glomerular filtration rate, LDL-cholesterol concentration, and use of lipid-lowering therapy. Results for plasma lipoprotein(a) concentrations were validated in five independent studies involving 10 195 patients with established coronary heart disease. Results for genetic associations were replicated through large-scale collaborative analysis in the GENIUS-CHD consortium, comprising 106 353 patients with established coronary heart disease and 19 332 deaths in 22 studies or cohorts. Findings: The median follow-up was 9·9 years. Increased severity of coronary heart disease was associated with lipoprotein(a) concentrations in plasma in the highest tertile (adjusted hazard radio [HR] 1·44, 95% CI 1·14–1·83) and the presence of either LPA SNP (1·88, 1·40–2·53). No associations were found in LURIC with all-cause mortality (highest tertile of lipoprotein(a) concentration in plasma 0·95, 0·81–1·11 and either LPA SNP 1·10, 0·92–1·31) or cardiovascular mortality (0·99, 0·81–1·2 and 1·13, 0·90–1·40, respectively) or in the validation studies. Interpretation: In patients with prevalent coronary heart disease, lipoprotein(a) concentrations and genetic variants showed no associations with mortality. We conclude that these variables are not useful risk factors to measure to predict progression to death after coronary heart disease is established. Funding: Seventh Framework Programme for Research and Technical Development (AtheroRemo and RiskyCAD), INTERREG IV Oberrhein Programme, Deutsche Nierenstiftung, Else-Kroener Fresenius Foundation, Deutsche Stiftung für Herzforschung, Deutsche Forschungsgemeinschaft, Saarland University, German Federal Ministry of Education and Research, Willy Robert Pitzer Foundation, and Waldburg-Zeil Clinics Isny

A Study of Cosmic Ray Secondaries Induced by the Mir Space Station Using AMS-01

The Alpha Magnetic Spectrometer (AMS-02) is a high energy particle physics experiment that will study cosmic rays in the $\sim 100 \mathrm{MeV}$ to $1 \mathrm{TeV}$ range and will be installed on the International Space Station (ISS) for at least 3 years. A first version of AMS-02, AMS-01, flew aboard the space shuttle \emph{Discovery} from June 2 to June 12, 1998, and collected $10^8$ cosmic ray triggers. Part of the \emph{Mir} space station was within the AMS-01 field of view during the four day \emph{Mir} docking phase of this flight. We have reconstructed an image of this part of the \emph{Mir} space station using secondary $\pi^-$ and $\mu^-$ emissions from primary cosmic rays interacting with \emph{Mir}. This is the first time this reconstruction was performed in AMS-01, and it is important for understanding potential backgrounds during the 3 year AMS-02 mission.Comment: To be submitted to NIM B Added material requested by referee. Minor stylistic and grammer change

Shrinking a large dataset to identify variables associated with increased risk of Plasmodium falciparum infection in Western Kenya

Large datasets are often not amenable to analysis using traditional single-step approaches. Here, our general objective was to apply imputation techniques, principal component analysis (PCA), elastic net and generalized linear models to a large dataset in a systematic approach to extract the most meaningful predictors for a health outcome. We extracted predictors for Plasmodium falciparum infection, from a large covariate dataset while facing limited numbers of observations, using data from the People, Animals, and their Zoonoses (PAZ) project to demonstrate these techniques: data collected from 415 homesteads in western Kenya, contained over 1500 variables that describe the health, environment, and social factors of the humans, livestock, and the homesteads in which they reside. The wide, sparse dataset was simplified to 42 predictors of P. falciparum malaria infection and wealth rankings were produced for all homesteads. The 42 predictors make biological sense and are supported by previous studies. This systematic data-mining approach we used would make many large datasets more manageable and informative for decision-making processes and health policy prioritization