University of Duisburg-Essen

About: University of Duisburg-Essen is a education organization based out in Essen, Nordrhein-Westfalen, Germany. It is known for research contribution in the topics: Population & Transplantation. The organization has 16072 authors who have published 39972 publications receiving 1109199 citations.

When do we need to care about the caregiver? Supportive care needs, anxiety, and depression among informal caregivers of patients with cancer and cancer survivors

Abstract: Background Cancer not only affects patients but also their caregivers. The objective of the current study was to assess the unmet needs of cancer caregivers and to identify possible predictors of their supportive care needs. Methods In a cross-sectional survey, 188 dyads of patients diagnosed with lung, urological, or gastrointestinal cancer and their primary caregivers were recruited. Caregivers were asked to complete the Supportive Care Needs Survey self-report questionnaire (for partners and caregivers); patients completed the corresponding questionnaire. Both groups provided information regarding their distress (National Comprehensive Cancer Network Distress Thermometer), anxiety, and depression (Patient Health Questionnaire-4). Clinical characteristics were obtained from medical records. Results The mean age of the caregivers was 57.8 years. Approximately 72.3% were female. Patients had an average age of 62.5 years, with 33.0% being male. Caregivers were more distressed (P Conclusions A substantial percentage of caregivers have unmet needs for support, mainly with regard to fears concerning the patient's condition, receiving disease-related information, and emotional support for themselves. Prediction of unmet needs in caregivers from other clinical and psychological variables was rather poor. Therefore, by means of the frequency and disparity of caregivers unmet needs, they should be systematically assessed to direct specific offers.

Evolutionary genomics of the cold-adapted diatom Fragilariopsis cylindrus

Abstract: The Southern Ocean houses a diverse and productive community of organisms. Unicellular eukaryotic diatoms are the main primary producers in this environment, where photosynthesis is limited by low concentrations of dissolved iron and large seasonal fluctuations in light, temperature and the extent of sea ice. How diatoms have adapted to this extreme environment is largely unknown. Here we present insights into the genome evolution of a cold-adapted diatom from the Southern Ocean, Fragilariopsis cylindrus, based on a comparison with temperate diatoms. We find that approximately 24.7 per cent of the diploid F. cylindrus genome consists of genetic loci with alleles that are highly divergent (15.1 megabases of the total genome size of 61.1 megabases). These divergent alleles were differentially expressed across environmental conditions, including darkness, low iron, freezing, elevated temperature and increased CO2. Alleles with the largest ratio of non-synonymous to synonymous nucleotide substitutions also show the most pronounced condition-dependent expression, suggesting a correlation between diversifying selection and allelic differentiation. Divergent alleles may be involved in adaptation to environmental fluctuations in the Southern Ocean.

Circulating Tumor DNA Measurements As Early Outcome Predictors in Diffuse Large B-Cell Lymphoma

Abstract: PurposeOutcomes for patients with diffuse large B-cell lymphoma remain heterogeneous, with existing methods failing to consistently predict treatment failure. We examined the additional prognostic value of circulating tumor DNA (ctDNA) before and during therapy for predicting patient outcomes.Patients and MethodsWe studied the dynamics of ctDNA from 217 patients treated at six centers, using a training and validation framework. We densely characterized early ctDNA dynamics during therapy using cancer personalized profiling by deep sequencing to define response-associated thresholds within a discovery set. These thresholds were assessed in two independent validation sets. Finally, we assessed the prognostic value of ctDNA in the context of established risk factors, including the International Prognostic Index and interim positron emission tomography/computed tomography scans.ResultsBefore therapy, ctDNA was detectable in 98% of patients; pretreatment levels were prognostic in both front-line and salvage se...

Theory of adaptive finite element methods: An introduction

Abstract: This is a survey on the theory of adaptive finite element methods (AFEM), which are fundamental in modern computational science and engineering. We present a self-contained and up-to-date discussion of AFEM for linear second order elliptic partial differential equations (PDEs) and dimension d>1, with emphasis on the differences and advantages of AFEM over standard FEM. The material is organized in chapters with problems that extend and complement the theory. We start with the functional framework, inf-sup theory, and Petrov-Galerkin method, which are the basis of FEM. We next address four topics of essence in the theory of AFEM that cannot be found in one single article: mesh refinement by bisection, piecewise polynomial approximation in graded meshes, a posteriori error analysis, and convergence and optimal decay rates of AFEM. The first topic is of geometric and combinatorial nature, and describes bisection as a rather simple and efficient technique to create conforming graded meshes with optimal complexity. The second topic explores the potentials of FEM to compensate singular behavior with local resolution and so reach optimal error decay. This theory, although insightful, is insufficient to deal with PDEs since it relies on knowing the exact solution. The third topic provides the missing link, namely a posteriori error estimators, which hinge exclusively on accessible data: we restrict ourselves to the simplest residual-type estimators and present a complete discussion of upper and lower bounds, along with the concept of oscillation and its critical role. The fourth topic refers to the convergence of adaptive loops and its comparison with quasi-uniform refinement. We first show, under rather modest assumptions on the problem class and AFEM, convergence in the natural norm associated to the variational formulation. We next restrict the problem class to coercive symmetric bilinear forms, and show that AFEM is a contraction for a suitable error notion involving the induced energy norm. This property is then instrumental to prove optimal cardinality of AFEM for a class of singular functions, for which the standard FEM is suboptimal.