University of Copenhagen

About: University of Copenhagen is a education organization based out in Copenhagen, Denmark. It is known for research contribution in the topics: Population & Medicine. The organization has 57645 authors who have published 149740 publications receiving 5903093 citations. The organization is also known as: Copenhagen University & Københavns Universitet.

Reproductive and larval ecology of marine bottom invertebrates.

Abstract: 1. In analysing the ecological conditions of an animal population we have above all to focus our attention upon the most sensitive stages within the life cycle of the animal, that is, the period of breeding and larval development.

Genome-wide association study identifies novel breast cancer susceptibility loci

Abstract: Breast cancer exhibits familial aggregation, consistent with variation in genetic susceptibility to the disease. Known susceptibility genes account for less than 25% of the familial risk of breast cancer, and the residual genetic variance is likely to be due to variants conferring more moderate risks. To identify further susceptibility alleles, we conducted a two-stage genome-wide association study in 4,398 breast cancer cases and 4,316 controls, followed by a third stage in which 30 single nucleotide polymorphisms (SNPs) were tested for confirmation in 21,860 cases and 22,578 controls from 22 studies. We used 227,876 SNPs that were estimated to correlate with 77% of known common SNPs in Europeans at r2.0.5. SNPs in five novel independent loci exhibited strong and consistent evidence of association with breast cancer (P,1027). Four of these contain plausible causative genes (FGFR2, TNRC9, MAP3K1 and LSP1). At the second stage, 1,792 SNPs were significant at the P,0.05 level compared with an estimated 1,343 that would be expected by chance, indicating that many additional common susceptibility alleles may be identifiable by this approach.

Diagnostic Criteria for Temporomandibular Disorders (DC/TMD) for Clinical and Research Applications: recommendations of the International RDC/TMD Consortium Network* and Orofacial Pain Special Interest Group†

Abstract: Temporomandibular disorders (TMD) are a significant public health problem affecting approximately 5% to 12% of the population.1 TMD is the second most common musculoskeletal condition (after chronic low back pain) resulting in pain and disability.1 Pain-related TMD can impact the individual's daily activities, psychosocial functioning, and quality of life. Overall, the annual TMD management cost in the USA, not including imaging, has doubled in the last decade to $4 billion.1 Patients often seek consultation with dentists for their TMD, especially for pain-related TMD. Diagnostic criteria for TMD with simple, clear, reliable, and valid operational definitions for the history, examination, and imaging procedures are needed to render physical diagnoses in both clinical and research settings. In addition, biobehavioral assessment of pain-related behavior and psychosocial functioning—an essential part of the diagnostic process—is required and provides the minimal information whereby one can determine whether the patient's pain disorder, especially when chronic, warrants further multidisciplinary assessment. Taken together, a new dual-axis Diagnostic Criteria for TMD (DC/TMD) will provide evidence-based criteria for the clinician to use when assessing patients, and will facilitate communication regarding consultations, referrals, and prognosis.2 The research community benefits from the ability to use well-defined and clinically relevant characteristics associated with the phenotype in order to facilitate more generalizable research. When clinicians and researchers use the same criteria, taxonomy, and nomenclature, then clinical questions and experience can be more easily transferred into relevant research questions, and research findings are more accessible to clinicians to better diagnose and manage their patients. The Research Diagnostic Criteria for Temporomandibular Disorders (RDC/TMD) have been the most widely employed diagnostic protocol for TMD research since its publication in 1992.3 This classification system was based on the biopsychosocial model of pain4 that included an Axis I physical assessment, using reliable and well-operationalized diagnostic criteria, and an Axis II assessment of psychosocial status and pain-related disability. The intent was to simultaneously provide a physical diagnosis and identify other relevant characteristics of the patient that could influence the expression and thus management of their TMD. Indeed, the longer the pain persists, the greater the potential for emergence and amplification of cognitive, psychosocial, and behavioral risk factors, with resultant enhanced pain sensitivity, greater likelihood of additional pain persistence, and reduced probability of success from standard treatments.5 The RDC/TMD (1992) was intended to be only a first step toward improved TMD classification, and the authors stated the need for future investigation of the accuracy of the Axis I diagnostic algorithms in terms of reliability and criterion validity—the latter involving the use of credible reference standard diagnoses. Also recommended was further assessment of the clinical utility of the Axis II instruments. The original RDC/TMD Axis I physical diagnoses have content validity based on the critical review by experts of the published diagnostic approach in use at that time and were tested using population-based epidemiologic data.6 Subsequently, a multicenter study showed that, for the most common TMD, the original RDC/TMD diagnoses exhibited sufficient reliability for clinical use.7 While the validity of the individual RDC/TMD diagnoses has been extensively investigated, assessment of the criterion validity for the complete spectrum of RDC/TMD diagnoses had been absent until recently.8 For the original RDC/TMD Axis II instruments, good evidence for their reliability and validity for measuring psychosocial status and pain-related disability already existed when the classification system was published.9–13 Subsequently, a variety of studies have demonstrated the significance and utility of the original RDC/TMD biobehavioral measures in such areas as predicting outcomes of clinical trials, escalation from acute to chronic pain, and experimental laboratory settings.14–20 Other studies have shown that the original RDC/TMD biobehavioral measures are incomplete in terms of prediction of disease course.21–23 The overall utility of the biobehavioral measures in routine clinical settings has, however, yet to be demonstrated, in part because most studies have to date focused on Axis I diagnoses rather than Axis II biobehavioral factors.24 The aims of this article are to present the evidence-based new Axis I and Axis II DC/TMD to be used in both clinical and research settings, as well as present the processes related to their development.

The Atomic Simulation Environment - A Python library for working with atoms

Abstract: The Atomic Simulation Environment (ASE) is a software package written in the Python programming language with the aim of setting up, steering, and analyzing atomistic simula- tions. In ASE, tasks are fully scripted in Python. The powerful syntax of Python combined with the NumPy array library make it possible to perform very complex simulation tasks. For example, a sequence of calculations may be performed with the use of a simple "for-loop" construction. Calculations of energy, forces, stresses and other quantities are performed through interfaces to many external electronic structure codes or force fields using a uniform interface. On top of this calculator interface, ASE provides modules for performing many standard simulation tasks such as structure optimization, molecular dynamics, handling of constraints and performing nudged elastic band calculations.