4 results match your criteria: "University of Medicine Goettingen[Affiliation]"
J Cancer Res Clin Oncol
April 2023
Chair of Healthcare Management and Health Services Research, University of Bayreuth, Parsifalstraße 25, 95445, Bayreuth, Germany.
Purpose: Targeted therapies are effective therapeutic approaches in advanced stages of NSCLC and require precise molecular profiling to identify oncogenic drivers. Differential diagnosis on a molecular level contributes to clinical decision making. Liquid biopsy (LB) use has demonstrated its potential to serve as an alternative to tissue biopsy (TB) particularly in cases where tissue sampling is not feasible or insufficient.
View Article and Find Full Text PDFOncotarget
August 2020
Department of Neurosurgery, University of Medicine Goettingen, Goettingen, Germany.
Background: Metastatic brain disease continues to have a dismal prognosis. Previous studies achieved a reduction of local recurrence rates by aggressively resecting the peritumoral zone (supramarginal resection) or using 5-aminolaevulinic acid (5-ALA) fluorescence. The aim of the present study is to assess whether the use of 5-ALA has an impact on local recurrence or survival compared to conventional white light microscopic tumor resection.
View Article and Find Full Text PDFJ Mol Cell Cardiol
October 2015
Innovative Clinical Trials, University of Medicine Goettingen, Department of Cardiology and Pneumology, Goettingen, Germany. Electronic address:
Background: The origin of pro-inflammatory activation in chronic heart failure (HF) remains a matter of debate. Lipopolysaccharide (LPS) may enter the blood stream through the morphologically altered and leaky gut barrier. We hypothesized that lower LPS reactivity would be associated with worse survival as compared to normal or higher LPS reactivity.
View Article and Find Full Text PDFJ Cereb Blood Flow Metab
September 2015
Department of Diagnostic and Interventional Neuroradiology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany.
Benefit of endovascular recanalization beyond established treatment time windows likely exists in select stroke patients. However, there is currently no imaging model that predicts infarction adjusting for elapsed time between the pathologic snapshot of admission imaging until endovascular recanalization. We trained and cross validated a multivariate generalized linear model (GLM) that uses computer tomography perfusion and clinical data to quantify patient-specific dynamic change of tissue infarction depending on degree and time of recanalization.
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