The ALICE experiment at the CERN LHC

ALICE (A Large Ion Collider Experiment) is a general-purpose, heavy-ion detector at the CERN LHC which focuses on QCD, the strong-interaction sector of the Standard Model. It is designed to address the physics of strongly interacting matter and the quark-gluon plasma at extreme values of energy density and temperature in nucleus-nucleus collisions. Besides running with Pb ions, the physics programme includes collisions with lighter ions, lower energy running and dedicated proton-nucleus runs. ALICE will also take data with proton beams at the top LHC energy to collect reference data for the heavy-ion programme and to address several QCD topics for which ALICE is complementary to the other LHC detectors. The ALICE detector has been built by a collaboration including currently over 1000 physicists and engineers from 105 Institutes in 30 countries. Its overall dimensions are 161626 m3 with a total weight of approximately 10 000 t. The experiment consists of 18 different detector systems each with its own specific technology choice and design constraints, driven both by the physics requirements and the experimental conditions expected at LHC. The most stringent design constraint is to cope with the extreme particle multiplicity anticipated in central Pb-Pb collisions. The different subsystems were optimized to provide high-momentum resolution as well as excellent Particle Identification (PID) over a broad range in momentum, up to the highest multiplicities predicted for LHC. This will allow for comprehensive studies of hadrons, electrons, muons, and photons produced in the collision of heavy nuclei. Most detector systems are scheduled to be installed and ready for data taking by mid-2008 when the LHC is scheduled to start operation, with the exception of parts of the Photon Spectrometer (PHOS), Transition Radiation Detector (TRD) and Electro Magnetic Calorimeter (EMCal). These detectors will be completed for the high-luminosity ion run expected in 2010. This paper describes in detail the detector components as installed for the first data taking in the summer of 2008

One-year changes in glucose and heart disease risk factors among participants in the WISEWOMAN programme

Background: WISEWOMAN provides chronic disease risk factor screening, referrals and lifestyle interventions to low-income, uninsured women, to reduce their heart disease and stroke risk. Participants learn behaviour-changing skills tailored to low-income populations, such as collaborative goal setting, the need to take small steps and other empowerment techniques. Aim: To quantify the baseline prevalence of pre-diabetes (fasting blood glucose 5.5–6.9 mmol/l) and diabetes among WISEWOMAN participants and assess one year changes in glucose levels and other diabetes risk factors. Methods: We used 1998–2005 baseline and one-year follow-up data from WISEWOMAN participants. Using a multilevel regression model, we assessed one-year changes in glucose, blood pressure (BP), total cholesterol and 10-year risk of coronary heart disease (CHD) among participants with baseline pre-diabetes (n=688) or diabetes (n=338). Results: At baseline, 15% of participants had pre-diabetes and 10% had diabetes. Of those with diabetes, 26% were unaware of their condition before baseline screening. During the one-year follow-up period, participants with pre-diabetes experienced statistically significant improvements in glucose (2.9%) and cholesterol (2.1%) levels and 10-year CHD risk (4.3%). Participants with newly diagnosed diabetes experienced statistically significant improvements in glucose (11.5%), BP (3.1%–3.5%) and cholesterol (6.4%) levels. Participants with previously diagnosed diabetes experienced significant improvements in BP (1.9–3.4%), cholesterol level (3.8%), and 10-year CHD risk (8.5%). Conclusions: Implementing patient-centered, comprehensive and multilevel interventions and demonstrating their effectiveness will likely lead to the adoption of this approach on a much broader scale

Psychosocial Predictors of Metabolic Syndrome among Latino Groups in the Multi-Ethnic Study of Atherosclerosis (MESA)

OBJECTIVE:We sought to determine the contribution of psychological variables to risk for metabolic syndrome (MetS) among Latinos enrolled in the Multi-Ethnic Study of Atherosclerosis (MESA), and to investigate whether social support moderates these associations, and whether inflammatory markers mediate the association between psychological variables and MetS. RESEARCH DESIGN AND METHODS:Cross-sectional analyses at study baseline were conducted with a national Latino cohort (n = 1,388) that included Mexican Americans, Dominican Americans, Puerto Rican Americans and Central/South Americans. Hierarchical logistic regression analyses were conducted to test the effects of psychosocial variables (chronic stress, depressive symptoms, and social support) on MetS. In addition, separate subgroup-specific models, controlling for nationality, age, gender, socioeconomic position, language spoken at home, exercise, smoking and drinking status, and testing for the effects of chronic stress, depressive symptoms and inflammation (IL-6, CRP, fibrinogen) in predicting risk for MetS were conducted. RESULTS:In the overall sample, high chronic stress independently predicted risk for MetS, however this association was found to be significant only in Mexican Americans and Puerto Rican Americans. Social support did not moderate the associations between chronic stress and MetS for any group. Chronic stress was not associated with inflammatory markers in either the overall sample or in each group. CONCLUSIONS:Our results suggest a differential contribution of chronic stress to the prevalence of MetS by national groups