Cardiovascular disease by diabetes status in five ethnic minority groups compared to ethnic Norwegians

<p>Abstract</p> <p>Background</p> <p>The population in Norway has become multi-ethnic due to migration from Asia and Africa over the recent decades. The aim of the present study was to explore differences in the self-reported prevalence of cardiovascular disease (CVD) and associated risk factors by diabetes status in five ethnic minority groups compared to ethnic Norwegians.</p> <p>Methods</p> <p>Pooled data from three population-based cross-sectional studies conducted in Oslo between 2000 and 2002 was used. Of 54,473 invited individuals 24,749 (45.4%) participated. The participants self-reported health status, underwent a clinical examination and blood samples were drawn. A total of 17,854 individuals aged 30 to 61 years born in Norway, Sri-Lanka, Pakistan, Iran, Vietnam or Turkey were included in the study. Chi-square tests, one-way ANOVAs, ANCOVAs, multiple and logistic regression were used.</p> <p>Results</p> <p>Age- and gender-standardized prevalence of self-reported CVD varied between 5.8% and 8.2% for the ethnic minority groups, compared to 2.9% among ethnic Norwegians (p < 0.001). Prevalence of self-reported diabetes varied from 3.0% to 15.0% for the ethnic minority groups versus 1.8% for ethnic Norwegians (p < 0.001). Among individuals without diabetes, the CVD prevalence was 6.0% versus 2.6% for ethnic minorities and Norwegians, respectively (p < 0.001). Corresponding CVD prevalence rates among individuals with diabetes were 15.3% vs. 12.6% (p = 0.364). For individuals without diabetes, the odds ratio (OR) for CVD in the ethnic minority groups remained significantly higher (range 1.5-2.6) than ethnic Norwegians (p < 0.05), after adjustment for age, gender, education, employment, and body height, except for Turkish individuals. Regardless of diabetes status, obesity and physical inactivity were prevalent in the majority of ethnic minority groups, whereas systolic- and diastolic- blood pressures were higher in Norwegians. In nearly all ethnic groups, individuals with diabetes had higher triglycerides, waist-to-hip ratio (WHR), and body mass index compared to individuals without diabetes. Age, diabetes, hypertension, hypercholesterolemia, and WHR were significant predictors of CVD in both ethnic Norwegians and ethnic minorities, but significant ethnic differences were found for age, diabetes, and hypercholesterolemia.</p> <p>Conclusions</p> <p>Ethnic differences in the prevalence of CVD were prominent for individuals without diabetes. Primary CVD prevention including identification of undiagnosed diabetes should be prioritized for ethnic minorities without known diabetes.</p

Machine Learning Approach for Prescriptive Plant Breeding

We explored the capability of fusing high dimensional phenotypic trait (phenomic) data with a machine learning (ML) approach to provide plant breeders the tools to do both in-season seed yield (SY) prediction and prescriptive cultivar development for targeted agro-management practices (e.g., row spacing and seeding density). We phenotyped 32 SoyNAM parent genotypes in two independent studies each with contrasting agro-management treatments (two row spacing, three seeding densities). Phenotypic trait data (canopy temperature, chlorophyll content, hyperspectral reflectance, leaf area index, and light interception) were generated using an array of sensors at three growth stages during the growing season and seed yield (SY) determined by machine harvest. Random forest (RF) was used to train models for SY prediction using phenotypic traits (predictor variables) to identify the optimal temporal combination of variables to maximize accuracy and resource allocation. RF models were trained using data from both experiments and individually for each agro-management treatment. We report the most important traits agnostic of agro-management practices. Several predictor variables showed conditional importance dependent on the agro-management system. We assembled predictive models to enable in-season SY prediction, enabling the development of a framework to integrate phenomics information with powerful ML for prediction enabled prescriptive plant breeding

Search for the X(5568) State Decaying into B-s(0)pi(+/-) in Proton-Proton Collisions at root s=8 TeV

A search for resonancelike structures in the B-s(0)pi(+/-) invariant mass spectrum is performed using proton-proton collision data collected by the CMS experiment at the LHC at root s = 8 TeV, corresponding to an integrated luminosity of 19.7 fb(-1). The B-s(0) mesons are reconstructed in the decay chain B-s(0) -> J/Psi phi, with J/Psi -> mu(+) mu(-) and phi -> K+K-. The B-s(0)pi(+/-) invariant mass distribution shows no statistically significant peaks for different selection requirements on the reconstructed B-s(0) and pi(+/-) candidates. Upper limits are set on the relative production rates of the X(5568) and B-s(0) states times the branching fraction of the decay X(5568)(+/-) -> B-s(0)pi(+/-). In addition, upper limits are obtained as a function of the mass and the natural width of possible exotic states decaying into B-s(0)pi(+/-).Peer reviewe

Measurement of inclusive very forward jet cross sections in proton-lead collisions at \sqrt{sNN} = 5:02 TeV

Measurements of differential cross sections for inclusive very forward jet production in proton-lead collisions as a function of jet energy are presented. The data were collected with the CMS experiment at the LHC in the laboratory pseudorapidity range −6.6 < η < −5.2. Asymmetric beam energies of 4 TeV for protons and 1.58 TeV per nucleon for Pb nuclei were used, corresponding to a center-of-mass energy per nucleon pair of \sqrt{sNN} = 5:02 TeV. Collisions with either the proton (p+Pb) or the ion (Pb+p) traveling towards the negative η hemisphere are studied. The jet cross sections are unfolded to stable-particle level cross sections with p_{T} ≳ 3 GeV, and compared to predictions from various Monte Carlo event generators. In addition, the cross section ratio of p+Pb and Pb+p data is presented. The results are discussed in terms of the saturation of gluon densities at low fractional parton momenta. None of the models under consideration describes all the data over the full jet-energy range and for all beam configurations. Discrepancies between the differential cross sections in data and model predictions of more than two orders of magnitude are observed

Search for strongly interacting massive particles generating trackless jets in proton-proton collisions at s = 13 TeV

A search for dark matter in the form of strongly interacting massive particles (SIMPs) using the CMS detector at the LHC is presented. The SIMPs would be produced in pairs that manifest themselves as pairs of jets without tracks. The energy fraction of jets carried by charged particles is used as a key discriminator to suppress efficiently the large multijet background, and the remaining background is estimated directly from data. The search is performed using proton-proton collision data corresponding to an integrated luminosity of 16.1 fb - 1 , collected with the CMS detector in 2016. No significant excess of events is observed above the expected background. For the simplified dark matter model under consideration, SIMPs with masses up to 100 GeV are excluded and further sensitivity is explored towards higher masses

Programmed cell death and its role in inflammation

Cell death plays an important role in the regulation of inflammation and may be the result of inflammation. The maintenance of tissue homeostasis necessitates both the recognition and removal of invading microbial pathogens as well as the clearance of dying cells. In the past few decades, emerging knowledge on cell death and inflammation has enriched our molecular understanding of the signaling pathways that mediate various programs of cell death and multiple types of inflammatory responses. This review provides an overview of the major types of cell death related to inflammation. Modification of cell death pathways is likely to be a logical therapeutic target for inflammatory diseases

Measurement of nuclear modification factors of ϒ(1S), ϒ(2S), and ϒ(3S) mesons in PbPb collisions at √sNN = 5.02 TeV

The cross sections for ϒ(1S), ϒ(2S), and ϒ(3S) production in lead–lead (PbPb) and proton–proton (pp) collisions at √sNN = 5.02 TeV have been measured using the CMS detector at the LHC. The nuclear modification factors, RAA, derived from the PbPb-to-pp ratio of yields for each state, are studied as functions of meson rapidity and transverse momentum, as well as PbPb collision centrality. The yields of all three states are found to be significantly suppressed, and compatible with a sequential ordering of the suppression, RAA(ϒ(1S)) > RAA(ϒ(2S)) > RAA(ϒ(3S)). The suppression of ϒ(1S) is larger than that seen at √sNN = 2.76 TeV, although the two are compatible within uncertainties. The upper limit on the RAA of ϒ(3S) integrated over pT, rapidity and centrality is 0.096 at 95% confidence level, which is the strongest suppression observed for a quarkonium state in heavy ion collisions to date

Measurement of prompt ψ(2S) production cross sections in proton–lead and proton–proton collisions at √sNN = 5.02 TeV

Measurements of prompt ψ(2S) meson production cross sections in proton–lead (pPb) and proton–proton (pp) collisions at a nucleon–nucleon center-of-mass energy of √sNN = 5.02 TeV are reported. The results are based on pPb and pp data collected by the CMS experiment at the LHC, corresponding to integrated luminosities of 34.6 nb−1 and 28.0 pb−1, respectively. The nuclear modification factor RpPb is measured for prompt ψ(2S) in the transverse momentum range 4 < pT < 30 GeV/c and the center-of-mass rapidity range −2.4 < yCM < 1.93. The results on ψ(2S) RpPb are compared to the corresponding modification factor for prompt J/ψ mesons. The results point to different nuclear effects at play in the production of the excited charmonium state compared to the ground state, in the region of backward rapidity and for pT < 10 GeV/c