Browsing Publications of the AG (ESME) by Journal
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Analysis of Practical Identifiability of a Viral Infection Model.Mathematical modelling approaches have granted a significant contribution to life sciences and beyond to understand experimental results. However, incomplete and inadequate assessments in parameter estimation practices hamper the parameter reliability, and consequently the insights that ultimately could arise from a mathematical model. To keep the diligent works in modelling biological systems from being mistrusted, potential sources of error must be acknowledged. Employing a popular mathematical model in viral infection research, existing means and practices in parameter estimation are exemplified. Numerical results show that poor experimental data is a main source that can lead to erroneous parameter estimates despite the use of innovative parameter estimation algorithms. Arbitrary choices of initial conditions as well as data asynchrony distort the parameter estimates but are often overlooked in modelling studies. This work stresses the existence of several sources of error buried in reports of modelling biological systems, voicing the need for assessing the sources of error, consolidating efforts in solving the immediate difficulties, and possibly reconsidering the use of mathematical modelling to quantify experimental data.
Effect of beta-blocker therapy on the risk of infections and death after acute stroke--a historical cohort study.Infections are a frequent cause for prolonged hospitalization and increased mortality after stroke. Recent studies revealed a stroke-induced depression of the peripheral immune system associated with an increased susceptibility for infections. In a mice model for stroke, this immunosuppressive effect was reversible after beta-blocker administration. The aim of our study was to investigate the effect of beta-blocker therapy on the risk of infections and death after stroke in humans.
Twin and sibling studies using health insurance data: the example of attention deficit/hyperactivity disorder (ADHD).Twin studies are used to assess the contribution of genetic factors to the aetiology of diseases. To show the feasibility of such research on the basis of health insurance data, we analysed twin and sibling data on the attention deficit/hyperactivity disorder (ADHD) in the German Pharmacoepidemiological Research Database (GePaRD).