Thermal Radiation from Nucleons and Mesons

Thermal photon emission rates due to meson-nucleon interactions have been evaluated. An exhaustive set of reactions involving p(\bar p), n(\bar n), rho, omega, a_1, pi and eta is seen to provide a sizeable contribution to the emission rate from hot hadronic matter. Contributions from baryonic resonances are found to be negligibly small

Formation of superdense hadronic matter in high energy heavy-ion collisions

We present the detail of a newly developed relativistic transport model (ART 1.0) for high energy heavy-ion collisions. Using this model, we first study the general collision dynamics between heavy ions at the AGS energies. We then show that in central collisions there exists a large volume of sufficiently long-lived superdense hadronic matter whose local baryon and energy densities exceed the critical densities for the hadronic matter to quark-gluon plasma transition. The size and lifetime of this matter are found to depend strongly on the equation of state. We also investigate the degree and time scale of thermalization as well as the radial flow during the expansion of the superdense hadronic matter. The flow velocity profile and the temperature of the hadronic matter at freeze-out are extracted. The transverse momentum and rapidity distributions of protons, pions and kaons calculated with and without the mean field are compared with each other and also with the preliminary data from the E866/E802 collaboration to search for experimental observables that are sensitive to the equation of state. It is found that these inclusive, single particle observables depend weakly on the equation of state. The difference between results obtained with and without the nuclear mean field is only about 20\%. The baryon transverse collective flow in the reaction plane is also analyzed. It is shown that both the flow parameter and the strength of the ``bounce-off'' effect are very sensitive to the equation of state. In particular, a soft equation of state with a compressibility of 200 MeV results in an increase of the flow parameter by a factor of 2.5 compared to the cascade case without the mean field. This large effect makes it possible to distinguish the predictions from different theoretical models and to detect the signaturesComment: 55 pages, latex, + 39 figures available upon reques

A new flowering time gene on wheat chromosome 3B characterization and genetic mapping

Genes that alter disease risk only in combination with certain environmental exposures may not be detected in genetic association analysis. By using methods accounting for gene-environment (G x E) interaction, we aimed to identify novel genetic loci associated with breast cancer risk. Up to 34,475 cases and 34,786 controls of European ancestry from up to 23 studies in the Breast Cancer Association Consortium were included. Overall, 71,527 single nucleotide polymorphisms (SNPs), enriched for association with breast cancer, were tested for interaction with 10 environmental risk factors using three recently proposed hybrid methods and a joint test of association and interaction. Analyses were adjusted for age, study, population stratification, and confounding factors as applicable. Three SNPs in two independent loci showed statistically significant association: SNPs rs10483028 and rs2242714 in perfect linkage disequilibrium on chromosome 21 and rs12197388 in ARID1B on chromosome 6. While rs12197388 was identified using the joint test with parity and with age at menarche (P-values = 3 x 10(-07)), the variants on chromosome 21 q22.12, which showed interaction with adult body mass index (BMI) in 8,891 postmenopausal women, were identified by all methods applied. SNP rs10483028 was associated with breast cancer in women with a BMI below 25 kg/m(2) (OR = 1.26, 95% CI 1.15-1.38) but not in women with a BMI of 30 kg/m(2) or higher (OR = 0.89, 95% CI 0.72-1.11, P for interaction = 3.2 x 10(-05)). Our findings confirm comparable power of the recent methods for detecting G x E interaction and the utility of using G x E interaction analyses to identify new susceptibility loci

Meta-analysis of 49 549 individuals imputed with the 1000 Genomes Project reveals an exonic damaging variant in ANGPTL4 determining fasting TG levels

Background So far, more than 170 loci have been associated with circulating lipid levels through genomewide association studies (GWAS). These associations are largely driven by common variants, their function is often not known, and many are likely to be markers for the causal variants. In this study we aimed to identify more new rare and low-frequency functional variants associated with circulating lipid levels. Methods We used the 1000 Genomes Project as a reference panel for the imputations of GWAS data from ~60 000 individuals in the discovery stage and ~90 000 samples in the replication stage. Results Our study resu

Refined histopathological predictors of BRCA1 and BRCA2 mutation status: A large-scale analysis of breast cancer characteristics from the BCAC, CIMBA, and ENIGMA consortia

Introduction: The distribution of histopathological features of invasive breast tumors in BRCA1 or BRCA2 germline mutation carriers differs from that of individuals with no known mutation. Histopathological features thus have utility for mutation prediction, including statistical modeling to assess pathogenicity of BRCA1 or BRCA2 variants of uncertain clinical significance. We analyzed large pathology datasets accrued by the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA) and the Breast Cancer Association Consortium (BCAC) to reassess histopathological predictors of BRCA1 and BRCA2 mutation status, and provide robust likelihood ratio (LR) estimates for statistical modeling. Methods: Selection criteria for study/center inclusion were estrogen receptor (ER) status or grade data available for invasive breast cancer diagnosed younger than 70 years. The dataset included 4,477 BRCA1 mutation carriers, 2,565 BRCA2 mutation carriers, and 47,565 BCAC breast cancer cases. Country-stratified estimates of the

The Origin, Early Evolution and Predictability of Solar Eruptions

Coronal mass ejections (CMEs) were discovered in the early 1970s when space-borne coronagraphs revealed that eruptions of plasma are ejected from the Sun. Today, it is known that the Sun produces eruptive flares, filament eruptions, coronal mass ejections and failed eruptions; all thought to be due to a release of energy stored in the coronal magnetic field during its drastic reconfiguration. This review discusses the observations and physical mechanisms behind this eruptive activity, with a view to making an assessment of the current capability of forecasting these events for space weather risk and impact mitigation. Whilst a wealth of observations exist, and detailed models have been developed, there still exists a need to draw these approaches together. In particular more realistic models are encouraged in order to asses the full range of complexity of the solar atmosphere and the criteria for which an eruption is formed. From the observational side, a more detailed understanding of the role of photospheric flows and reconnection is needed in order to identify the evolutionary path that ultimately means a magnetic structure will erupt

Observation of Events with an Energetic Forward Neutron in Deep Inelastic Scattering at HERA

In deep inelastic neutral current scattering of positrons and protons at the center of mass energy of 300 GeV, we observe, with the ZEUS detector, events with a high energy neutron produced at very small scattering angles with respect to the proton direction. The events constitute a fixed fraction of the deep inelastic, neutral current event sample independent of Bjorken x and Q2 in the range 3 · 10-4 \u3c xBJ \u3c 6 · 10-3 and 10 \u3c Q2 \u3c 100 GeV2

ELM mitigation by supersonic molecular beam injection: KSTAR and HL-2A experiments and theory

We report recent experimental results from HL-2A and KSTAR on ELM mitigation by supersonic molecular beam injection (SMBI). Cold particle deposition within the pedestal by SMBI is verified in both machines. The signatures of ELM mitigation by SMBI are an ELM frequency increase and ELM amplitude decrease. These persist for an SMBI influence time τI. Here, τI is the time for the SMBI influenced pedestal profile to refill. An increase in fELMSMBI/fELM0 and a decrease in the energy loss per ELM ΔWELM were achieved in both machines. Physical insight was gleaned from studies of density and vΦ (toroidal rotation velocity) evolution, particle flux and turbulence spectra, divertor heat load. The characteristic gradients of the pedestal density soften and a change in vΦ was observed during a τI time. The spectra of the edge particle flux Γ ∼ 〈ṽrñe〉 and density fluctuation with and without SMBI were measured in HL-2A and in KSTAR, respectively. A clear phenomenon observed is the decrease in divertor heat load during the τI time in HL-2A. Similar results are the profiles of saturation current density Jsat with and without SMBI in KSTAR. We note that τI/τp (particle confinement time) is close to ∼1, although there is a large difference in individual τI between the two machines. This suggests that τI is strongly related to particle-transport events. Experiments and analysis of a simple phenomenological model support the important conclusion that ELM mitigation by SMBI results from an increase in higher frequency fluctuations and transport events in the pedestal. © 2014 IAEA, Vienna

An integrative cross-omics analysis of DNA methylation sites of glucose and insulin homeostasis

Despite existing reports on differential DNA methylation in type 2 diabetes (T2D) and obesity, our understanding of its functional relevance remains limited. Here we show the effect of differential methylation in the early phases of T2D pathology by a blood-based epigenome-wide association study of 4808 non-diabetic Europeans in the discovery phase and 11,750 individuals in the replication. We identify CpGs in LETM1, RBM20, IRS2, MAN2A2 and the 1q25.3 region associated with fasting insulin, and in FCRL6, SLAMF1, APOBEC3H and the 15q26.1 region with fasting glucose. In silico cross-omics analyses highlight the role of differential methylation in the crosstalk between the adaptive immune system and glucose homeostasis. The differential methylation explains at least 16.9% of the association between obesity and insulin. Our study sheds light on the biological interactions between genetic variants driving differential methylation and gene expression in the early pathogenesis of T2D