A 19-SNP coronary heart disease gene score profile in subjects with type 2 diabetes: the coronary heart disease risk in type 2 diabetes (CoRDia study) study baseline characteristics

Background The coronary risk in diabetes (CoRDia) trial (n = 211) compares the effectiveness of usual diabetes care with a self-management intervention (SMI), with and without personalised risk information (including genetics), on clinical and behavioural outcomes. Here we present an assessment of randomisation, the cardiac risk genotyping assay, and the genetic characteristics of the recruits. Methods Ten-year coronary heart disease (CHD) risk was calculated using the UKPDS score. Genetic CHD risk was determined by genotyping 19 single nucleotide polymorphisms (SNPs) using Randox’s Cardiac Risk Prediction Array and calculating a gene score (GS). Accuracy of the array was assessed by genotyping a subset of pre-genotyped samples (n = 185). Results Overall, 10-year CHD risk ranged from 2–72 % but did not differ between the randomisation groups (p = 0.13). The array results were 99.8 % concordant with the pre-determined genotypes. The GS did not differ between the Caucasian participants in the CoRDia SMI plus risk group (n = 66) (p = 0.80) and a sample of UK healthy men (n = 1360). The GS was also associated with LDL-cholesterol (p = 0.05) and family history (p = 0.03) in a sample of UK healthy men (n = 1360). Conclusions CHD risk is high in this group of T2D subjects. The risk array is an accurate genotyping assay, and is suitable for estimating an individual’s genetic CHD risk. Trial registration This study has been registered at ClinicalTrials.gov; registration identifier NCT0189178

Observation of associated near-side and away-side long-range correlations in √sNN=5.02 TeV proton-lead collisions with the ATLAS detector

Two-particle correlations in relative azimuthal angle (Δϕ) and pseudorapidity (Δη) are measured in √sNN=5.02  TeV p+Pb collisions using the ATLAS detector at the LHC. The measurements are performed using approximately 1  μb-1 of data as a function of transverse momentum (pT) and the transverse energy (ΣETPb) summed over 3.1<η<4.9 in the direction of the Pb beam. The correlation function, constructed from charged particles, exhibits a long-range (2<|Δη|<5) “near-side” (Δϕ∼0) correlation that grows rapidly with increasing ΣETPb. A long-range “away-side” (Δϕ∼π) correlation, obtained by subtracting the expected contributions from recoiling dijets and other sources estimated using events with small ΣETPb, is found to match the near-side correlation in magnitude, shape (in Δη and Δϕ) and ΣETPb dependence. The resultant Δϕ correlation is approximately symmetric about π/2, and is consistent with a dominant cos⁡2Δϕ modulation for all ΣETPb ranges and particle pT

Search for R-parity-violating supersymmetry in events with four or more leptons in sqrt(s) =7 TeV pp collisions with the ATLAS detector

A search for new phenomena in final states with four or more leptons (electrons or muons) is presented. The analysis is based on 4.7 fb−1 of $\sqrt{s}=7\;\mathrm{TeV}$ proton-proton collisions delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in two signal regions: one that requires moderate values of missing transverse momentum and another that requires large effective mass. The results are interpreted in a simplified model of R-parity-violating supersymmetry in which a 95% CL exclusion region is set for charged wino masses up to 540 GeV. In an R-parity-violating MSUGRA/CMSSM model, values of m 1/2 up to 820 GeV are excluded for 10 < tan β < 40

Using Light to Improve Commercial Value

The plasticity of plant morphology has evolved to maximize reproductive fitness in response to prevailing environmental conditions. Leaf architecture elaborates to maximize light harvesting, while the transition to flowering can either be accelerated or delayed to improve an individual's fitness. One of the most important environmental signals is light, with plants using light for both photosynthesis and as an environmental signal. Plants perceive different wavelengths of light using distinct photoreceptors. Recent advances in LED technology now enable light quality to be manipulated at a commercial scale, and as such opportunities now exist to take advantage of plants' developmental plasticity to enhance crop yield and quality through precise manipulation of a crops' lighting regime. This review will discuss how plants perceive and respond to light, and consider how these specific signaling pathways can be manipulated to improve crop yield and quality

Functional mechanisms underlying pleiotropic risk alleles at the 19p13.1 breast-ovarian cancer susceptibility locus

A locus at 19p13 is associated with breast cancer (BC) and ovarian cancer (OC) risk. Here we analyse 438 SNPs in this region in 46,451 BC and 15,438 OC cases, 15,252 BRCA1 mutation carriers and 73,444 controls and identify 13 candidate causal SNPs associated with serous OC (P=9.2 × 10-20), ER-negative BC (P=1.1 × 10-13), BRCA1-associated BC (P=7.7 × 10-16) and triple negative BC (P-diff=2 × 10-5). Genotype-gene expression associations are identified for candidate target genes ANKLE1 (P=2 × 10-3) and ABHD8 (P<2 × 10-3). Chromosome conformation capture identifies interactions between four candidate SNPs and ABHD8, and luciferase assays indicate six risk alleles increased transactivation of the ADHD8 promoter. Targeted deletion of a region containing risk SNP rs56069439 in a putative enhancer induces ANKLE1 downregulation; and mRNA stability assays indicate functional effects for an ANKLE1 3′-UTR SNP. Altogether, these data suggest that multiple SNPs at 19p13 regulate ABHD8 and perhaps ANKLE1 expression, and indicate common mechanisms underlying breast and ovarian cancer risk

Flavor tagged time-dependent angular analysis of the B0s → J/ψϕ decay and extraction of ΔΓs and the weak phase ϕs in ATLAS

A measurement of the B0s→J/ψϕ decay parameters, updated to include flavor tagging is reported using 4.9  fb−¹ of integrated luminosity collected by the ATLAS detector from √s=7  TeV pp collisions recorded in 2011 at the LHC. The values measured for the physical parameters are ϕs=0.12±0.25(stat)±0.05(syst)  rad ΔΓs=0.053±0.021(stat)±0.010(syst)  ps−¹ Γs=0.677±0.007(stat)±0.004(syst)  ps−¹ |A∥(0)|2=0.220±0.008(stat)±0.009(syst) |A0(0)|2=0.529±0.006(stat)±0.012(syst) δ⊥=3.89±0.47(stat)±0.11(syst)  rad where the parameter ΔΓs is constrained to be positive. The S-wave contribution was measured and found to be compatible with zero. Results for ϕs and ΔΓs are also presented as 68% and 95% likelihood contours, which show agreement with the Standard Model expectations

Sustainable conversion of agro-wastes into useful adsorbents

Preparation and characterization of raw andactivated carbon derived from three different selectedagricultural wastes: kola nut pod raw and activated (KNPRand KNPA), bean husk raw and activated (BHR and BHA)and coconut husk raw and activated (CHR and CHA) wereinvestigated, respectively. Influences of carbonization andacid activation on the activated carbon were investigatedusing SEM, FTIR, EDX, pHpzcand Boehm titration tech-niques, respectively. Carbonization was done at 350°C for2 h followed by activation with 0.3 M H3PO4(ortho-phosphoric acid). Results obtained from SEM, FTIR, andEDX revealed that, carbonization followed by acid acti-vation had a significant influence on morphology and ele-mental composition of the samples. SEM showed well-developed pores on the surface of the precursors after acidtreatment, FTIR spectra revealed reduction, broadening,disappearance or appearance of new peaks after acid acti-vation. EDX results showed highest percentage of carbonby atom respectively in the order BHA[KNPA[CHArespectively. The pHpzcwas found to be 5.32, 4.57 and 3.69for KNPA, BHA and CHA, respectively. Boehm titrationresult compliments that of pHpzc, indicating that the sur-faces of the prepared adsorbents are predominantly acidic.This study promotes a sustainable innovative use of agro-wastes in the production of cheap and readily availableactivated carbons, thereby ensuring more affordable waterand effluent treatment adsorbents

A sensing mechanism for the detection of carbon nanotubes using selective photoluminescent probes based on ionic complexes with organic dyes

The multifunctional properties of carbon nanotubes (CNTs) make them a powerful platform for unprecedented innovations in a variety of practical applications. As a result of the surging growth of nanotechnology, nanotubes present a potential problem as an environmental pollutant, and as such, an efficient method for their rapid detection must be established. Here, we propose a novel type of ionic sensor complex for detecting CNTs – an organic dye that responds sensitively and selectively to CNTs with a photoluminescent signal. The complexes are formed through Coulomb attractions between dye molecules with uncompensated charges and CNTs covered with an ionic surfactant in water. We demonstrate that the photoluminescent excitation of the dye can be transferred to the nanotubes, resulting in selective and strong amplification (up to a factor of 6) of the light emission from the excitonic levels of CNTs in the near-infrared spectral range, as experimentally observed via excitation-emission photoluminescence (PL) mapping. The chirality of the nanotubes and the type of ionic surfactant used to disperse the nanotubes both strongly affect the amplification; thus, the complexation provides sensing selectivity towards specific CNTs. Additionally, neither similar uncharged dyes nor CNTs covered with neutral surfactant form such complexes. As model organic molecules, we use a family of polymethine dyes with an easily tailorable molecular structure and, consequently, tunable absorbance and PL characteristics. This provides us with a versatile tool for the controllable photonic and electronic engineering of an efficient probe for CNT detection