Cluster Analysis of Cardiovascular Phenotypes in Patients With Type 2 Diabetes and Established Atherosclerotic Cardiovascular Disease: A Potential Approach to Precision Medicine

OBJECTIVE Phenotypic heterogeneity among patients with type 2 diabetes mellitus (T2DM) and atherosclerotic cardiovascular disease (ASCVD) is ill defined. We used cluster analysis machine-learning algorithms to identify phenotypes among trial participants with T2DM and ASCVD. RESEARCH DESIGN AND METHODS We used data from the Trial Evaluating Cardiovascular Outcomes with Sitagliptin (TECOS) study (n = 14,671), a cardiovascular outcome safety trial comparing sitagliptin with placebo in patients with T2DM and ASCVD (median follow-up 3.0 years). Cluster analysis using 40 baseline variables was conducted, with associations between clusters and the primary composite outcome (cardiovascular death, nonfatal myocardial infarction, nonfatal stroke, or hospitalization for unstable angina) assessed by Cox proportional hazards models. We replicated the results using the Exenatide Study of Cardiovascular Event Lowering (EXSCEL) trial. RESULTS Four distinct phenotypes were identified: Cluster I included Caucasian men with a high prevalence of coronary artery disease; cluster II included Asian patients with a low BMI; cluster III included women with noncoronary ASCVD disease; and cluster IV included patients with heart failure and kidney dysfunction. The primary outcome occurred, respectively, in 11.6%, 8.6%, 10.3%, and 16.8% of patients in clusters I to IV. The crude difference in cardiovascular risk for the highest versus lowest risk cluster (cluster IV vs. II) was statistically significant (hazard ratio 2.74 [95% CI 2.29–3.29]). Similar phenotypes and outcomes were identified in EXSCEL. CONCLUSIONS In patients with T2DM and ASCVD, cluster analysis identified four clinically distinct groups. Further cardiovascular phenotyping is warranted to inform patient care and optimize clinical trial designs

Strategic positioning:an integrated decision process for manufacturers

Purpose – This paper describes research that has sought to create a formal and rational process that guides manufacturers through the strategic positioning decision. Design/methodology/approach – The methodology is based on a series of case studies to develop and test the decision process. Findings – A decision process that leads the practitioner through an analytical process to decide which manufacturing activities they should carryout themselves. Practical implications – Strategic positioning is concerned with choosing those production related activities that an organisations should carry out internally, and those that should be external and under the ownership and control of suppliers, partners, distributors and customers. Originality/value – This concept extends traditional decision paradigms, such as those associated with “make versus buy” and “outsourcing”, by looking at the interactions between manufacturing operations and the wider supply chain networks associated with the organisation

Mixture of latent trait analyzers for model-based clustering of categorical data

Model-based clustering methods for continuous data are well established and commonly used in a wide range of applications. However, model-based clustering methods for categorical data are less standard. Latent class analysis is a commonly used method for model-based clustering of binary data and/or categorical data, but due to an assumed local independence structure there may not be a correspondence between the estimated latent classes and groups in the population of interest. The mixture of latent trait analyzers model extends latent class analysis by assuming a model for the categorical response variables that depends on both a categorical latent class and a continuous latent trait variable; the discrete latent class accommodates group structure and the continuous latent trait accommodates dependence within these groups. Fitting the mixture of latent trait analyzers model is potentially difficult because the likelihood function involves an integral that cannot be evaluated analytically. We develop a variational approach for fitting the mixture of latent trait models and this provides an efficient model fitting strategy. The mixture of latent trait analyzers model is demonstrated on the analysis of data from the National Long Term Care Survey (NLTCS) and voting in the U.S. Congress. The model is shown to yield intuitive clustering results and it gives a much better fit than either latent class analysis or latent trait analysis alone

The On-orbit Calibrations for the Fermi Large Area Telescope

The Large Area Telescope (LAT) on--board the Fermi Gamma ray Space Telescope began its on--orbit operations on June 23, 2008. Calibrations, defined in a generic sense, correspond to synchronization of trigger signals, optimization of delays for latching data, determination of detector thresholds, gains and responses, evaluation of the perimeter of the South Atlantic Anomaly (SAA), measurements of live time, of absolute time, and internal and spacecraft boresight alignments. Here we describe on orbit calibration results obtained using known astrophysical sources, galactic cosmic rays, and charge injection into the front-end electronics of each detector. Instrument response functions will be described in a separate publication. This paper demonstrates the stability of calibrations and describes minor changes observed since launch. These results have been used to calibrate the LAT datasets to be publicly released in August 2009.Comment: 60 pages, 34 figures, submitted to Astroparticle Physic

Search for dark matter produced in association with a hadronically decaying vector boson in pp collisions at sqrt (s) = 13 TeV with the ATLAS detector

A search is presented for dark matter produced in association with a hadronically decaying W or Z boson using 3.2 fb−1 of pp collisions at View the MathML sources=13 TeV recorded by the ATLAS detector at the Large Hadron Collider. Events with a hadronic jet compatible with a W or Z boson and with large missing transverse momentum are analysed. The data are consistent with the Standard Model predictions and are interpreted in terms of both an effective field theory and a simplified model containing dark matter

PHYSICS OF MULTIPLY CHARGED OXYGEN IN THE CONSTANCE B QUADRUPOLE MIRROR

Detailed experimental measurements of multiply-chargered ion densities, endloss currents,and temperatures have been made in a single cell quadrupole mirror. The purpose of these experiments is to determine the confinement physics of ions over a range of charge states in an ECR ion source. The parallel ion confinement times agree well with a theoretical model including Pastukhov and flow confinement for a potential dip of ϕi/Ti ~ 1. The ion endloss currents were found to be up to 50% hollow. Radial transport of ions'was found to be important in limiting the extraction of high charge state ions. In addition, by heating O4+ with ion cyclotron resonance heating we were able to increase its extracted current in the plasma center by 25%