Pennsylvania State University

About: Pennsylvania State University is a education organization based out in State College, Pennsylvania, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 79763 authors who have published 196876 publications receiving 8318601 citations. The organization is also known as: Penn State & PSU.

A Facile and Template-Free Hydrothermal Synthesis of Mn3O4 Nanorods on Graphene Sheets for Supercapacitor Electrodes with Long Cycle Stability

Abstract: Graphene/Mn3O4 composites were prepared by a simple hydrothermal process from KMnO4 using ethylene glycol as a reducing agent. Mn3O4 nanorods of 100 nm to 1 μm length were observed to be well-dispersed on graphene sheets. To assess the properties of these materials for use in supercapacitors, cyclic voltammetry and galvanostatic charging–discharging measurements were performed. Graphene/Mn3O4 composites could be charged and discharged faster and had higher capacitance than free Mn3O4 nanorods. The capacitance of the composites was 100% retained after 10 000 cycles at a charging rate of 5 A/g.

Graph-based heuristics for recognition of machined features from a 3D solid model

Abstract: The internal representation of the solid modeller provides a description of parts which when used directly is useful for automation of the process planning function. So that the CAD model can be used to provide the information required for manufacturing, techniques to improve machine understanding of the part as required for manufacturing are needed. This paper presents the development of the concept attributed adjacency graph (AAG) for the recognition of machined features from a 3D boundary representation of a solid. Current implementation of the feature recogniser is limited to polyhedral features such as pockets, slots, steps, blind steps, blind slots, and polyhedral holes. Sample results that show the capabilities of the system are presented.

Creation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0

Abstract: Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods.

2011 ACCF/AHA/SCAI Guideline for Percutaneous Coronary Intervention: Executive Summary A Report of the American College of Cardiology Foundation/American Heart Association Task Force on Practice Guidelines and the Society for Cardiovascular Angiography and Interventions

Abstract: Alice K. Jacobs, MD, FACC, FAHA, Chair Jeffrey L. Anderson, MD, FACC, FAHA, Chair-Elect Nancy Albert, PhD, CCNS, CCRN, FAHA Mark A. Creager, MD, FACC, FAHA Steven M. Ettinger, MD, FACC Robert A. Guyton, MD, FACC Jonathan L. Halperin, MD, FACC, FAHA Judith S. Hochman, MD, FACC, FAHA

Understanding the inflammatory cytokine response in pneumonia and sepsis: results of the Genetic and Inflammatory Markers of Sepsis (GenIMS) Study.

Abstract: Background: Severe sepsis is common and frequently fatal, and community-acquired pneumonia (CAP) is the leading cause. Although severe sepsis is often attributed to uncontrolled and unbalanced inflammation, evidence from humans with infection syndromes across the breadth of disease is lacking. In this study we describe the systemic cytokine response to pneumonia and determine if specific patterns, including the balance of proinflammatory and anti-inflammatory markers, are associated with severe sepsis and death. Methods: This is a cohort study of 1886 subjects hospitalized with CAP through the emergency departments in 28 US academic and community hospitals. We defined severe sepsis as CAP complicated by new-onset organ dysfunction, following international consensus conference criteria. We measured plasma tumor necrosis factor, IL-6 (interleukin 6), and IL-10 levels daily for the first week and weekly thereafter. Our main outcome measures were severe sepsis and 90-day mortality. Results: A total of 583 patients developed severe sepsis (31%), of whom 149 died (26%). Systemic cytokine level elevation occurred in 82% of all subjects with CAP. Mean cytokine concentrations were highest at presentation, declined rapidly over the first few days, but remained elevated throughout the first week, beyond resolution of clinical signs of infection. Cytokine levels were highest in fatal severe sepsis and lowest in CAP with no severe sepsis. Unbalanced (high/low) cytokine patterns were unusual (4.6%) and not associated with decreased survival. Highest risk of death was with combined high levels of the proinflammatory IL-6 and anti-inflammatory IL-10 cytokine activity (hazard ratio, 20.5; 95% confidence interval, 10.8-39.0) (P.001). Conclusions: The circulating cytokine response to pneumonia is heterogeneous and continues for more than a week after presentation, with considerable overlap between those who do and do not develop severe sepsis. Unbalanced activation is uncommon, and mortality is highest w hen b oth p roinflammatory a nd a ntiinflammatory cytokine levels are high.