University of Colorado Denver

About: University of Colorado Denver is a education organization based out in Denver, Colorado, United States. It is known for research contribution in the topics: Population & Health care. The organization has 27444 authors who have published 57213 publications receiving 2539937 citations. The organization is also known as: CU Denver & UCD.

Management of COPD exacerbations: a European Respiratory Society/American Thoracic Society guideline

Abstract: This document provides clinical recommendations for treatment of chronic obstructive pulmonary disease (COPD) exacerbations.Comprehensive evidence syntheses, including meta-analyses, were performed to summarise all available evidence relevant to the Task Force's questions. The evidence was appraised using the Grading of Recommendations, Assessment, Development and Evaluation approach and the results were summarised in evidence profiles. The evidence syntheses were discussed and recommendations formulated by a multidisciplinary Task Force of COPD experts.After considering the balance of desirable and undesirable consequences, quality of evidence, feasibility, and acceptability of various interventions, the Task Force made: 1) a strong recommendation for noninvasive mechanical ventilation of patients with acute or acute-on-chronic respiratory failure; 2) conditional recommendations for oral corticosteroids in outpatients, oral rather than intravenous corticosteroids in hospitalised patients, antibiotic therapy, home-based management, and the initiation of pulmonary rehabilitation within 3 weeks after hospital discharge; and 3) a conditional recommendation against the initiation of pulmonary rehabilitation during hospitalisation.The Task Force provided recommendations related to corticosteroid therapy, antibiotic therapy, noninvasive mechanical ventilation, home-based management, and early pulmonary rehabilitation in patients having a COPD exacerbation. These recommendations should be reconsidered as new evidence becomes available.

CAIM discretization algorithm

Abstract: The task of extracting knowledge from databases is quite often performed by machine learning algorithms. The majority of these algorithms can be applied only to data described by discrete numerical or nominal attributes (features). In the case of continuous attributes, there is a need for a discretization algorithm that transforms continuous attributes into discrete ones. We describe such an algorithm, called CAIM (class-attribute interdependence maximization), which is designed to work with supervised data. The goal of the CAIM algorithm is to maximize the class-attribute interdependence and to generate a (possibly) minimal number of discrete intervals. The algorithm does not require the user to predefine the number of intervals, as opposed to some other discretization algorithms. The tests performed using CAIM and six other state-of-the-art discretization algorithms show that discrete attributes generated by the CAIM algorithm almost always have the lowest number of intervals and the highest class-attribute interdependency. Two machine learning algorithms, the CLIP4 rule algorithm and the decision tree algorithm, are used to generate classification rules from data discretized by CAIM. For both the CLIP4 and decision tree algorithms, the accuracy of the generated rules is higher and the number of the rules is lower for data discretized using the CAIM algorithm when compared to data discretized using six other discretization algorithms. The highest classification accuracy was achieved for data sets discretized with the CAIM algorithm, as compared with the other six algorithms.

Hormone-Induced Morphogenesis and Growth: Role of Mesenchymal–Epithelial Interactions

Abstract: Publisher Summary This chapter explains the role of mesenchymal–epithelial interactions in hormone induced morphogenesis and growth. The mechanism of steroid hormone action is thought to involve specific high-affinity receptor proteins. The hormone enters the cell, binds to the cytoplasmic receptor, which after activation translocates to the nucleus. The hormone–receptor complex in turn binds to nuclear acceptor sites on the chromatin. This activates a variety of metabolic processes, the most important being the stimulation of messenger RNA (mRNA) synthesis and the ultimate production of new proteins. The first indication that androgens can elicit their effects upon epithelial morphogenesis via the mediation of mesenchymal cells comes from studies in which urogenital epithelia from the embryonic seminal vesicle or urogenital sinus are grown in association with either urogenital mesenchyme or with non-target integumental mesenchyme. Urogenital mesenchyme induces specific epithelial morphogenesis, growth, and function within the genital tract and that the hormonal sensitivity of these morphogenetic processes resides in the mesenchyme that invariably contains nuclear hormone receptors. As morphogenetic processes are cyclic in adult genital tracts of many species, developmental properties are expressed in adulthood and, for this reason, appear to play a regulatory role in abnormal epithelial differentiation including carcinogenesis.

New Results from the Search for Low-Mass Weakly Interacting Massive Particles with the CDMS Low Ionization Threshold Experiment

Abstract: The CDMS low ionization threshold experiment (CDMSlite) uses cryogenic germanium detectors operated at a relatively high bias voltage to amplify the phonon signal in the search for weakly interacting massive particles (WIMPs). Results are presented from the second CDMSlite run with an exposure of 70 kg day, which reached an energy threshold for electron recoils as low as 56 eV. A fiducialization cut reduces backgrounds below those previously reported by CDMSlite. New parameter space for the WIMP-nucleon spin-independent cross section is excluded for WIMP masses between 1.6 and 5.5 GeV/c^{2}.