Publications

902 Publications visible to you, out of a total of 902

Abstract (Expand)

PURPOSE: To estimate the incidence density, point prevalence and outcome of severe sepsis and septic shock in German intensive care units (ICUs). METHODS: In a prospective, multicentre, longitudinalservational study, all patients already on the ICU at 0:00 on 4 November 2013 and all patients admitted to a participating ICU between 0:00 on 4 November 2013 and 2359 hours on 1 December 2013 were included. The patients were followed up for the occurrence of severe sepsis or septic shock (SEPSIS-1 definitions) during their ICU stay. RESULTS: A total of 11,883 patients from 133 ICUs at 95 German hospitals were included in the study, of whom 1503 (12.6 %) were diagnosed with severe sepsis or septic shock. In 860 cases (57.2 %) the infections were of nosocomial origin. The point prevalence was 17.9 % (95 % CI 16.3-19.7).The calculated incidence rate of severe sepsis or septic shock was 11.64 (95 % CI 10.51-12.86) per 1000 ICU days. ICU mortality in patients with severe sepsis/septic shock was 34.3 %, compared with 6 % in those without sepsis. Total hospital mortality of patients with severe sepsis or septic shock was 40.4 %. Classification of the septic shock patients using the new SEPSIS-3 definitions showed higher ICU and hospital mortality (44.3 and 50.9 %). CONCLUSIONS: Severe sepsis and septic shock continue to be a frequent syndrome associated with high hospital mortality. Nosocomial infections play a major role in the development of sepsis. This study presents a pragmatic, affordable and feasible method for the surveillance of sepsis epidemiology. Implementation of the new SEPSIS-3 definitions may have a major effect on future epidemiological data.

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Date Published: No date defined

Publication Type: Not specified

Human Diseases: disease by infectious agent

Abstract (Expand)

We describe a Rudin-Osher-Fatemi (ROF) filter based segmentation approach for whole tissue samples, combining floating intensity thresholding and rule-based feature detection. Method is validated against manual counts and compared with two commercial software kits (Tissue Studio 64, Definiens AG, and Halo, Indica Labs) and a straightforward machine-learning approach in a set of 50 test images. Further, the novel method and both commercial packages are applied to a set of 44 whole tissue sections. Outputs are compared with gene expression data available for the same tissue samples. Finally, the ROF based method is applied to 44 expert-specified tumor subregions for testing selection and subsampling strategies. Our method is deterministic, fully automated, externally repeatable, independent on training data and -- in difference to most commercial software kits -- completely documented. Among all tested methods, the novel approach is best correlated with manual count (0.9297). Automated detection of evaluation subregions proved to be fully reliable. Subsampling within tumor subregions is possible with results almost identical to full sampling. Comparison with gene expression data obtained for the same tissue samples reveals only moderate to low correlation levels, thus indicating that image morphometry constitutes an independent source of information about antibody-polarized macrophage occurence and distribution.

Authors: Marcus Wagner, René Hänsel, Sarah Reinke, Julia Richter, Michael Altenbuchinger, Ulf-Dietrich Braumann, Rainer Spang, Markus Löffler, Wolfram Klapper

Date Published: No date defined

Publication Type: Not specified

Human Diseases: diffuse large B-cell lymphoma

Abstract (Expand)

It is generally accepted that epigenetic modifications, such as DNA and histone methylations, affect transcription and that a gene’s transcription feeds back on its epigenetic profile. Depending on the epigenetic modification, positive and negative feedback loops have been described. Here, we study whether such interrelation are mandatory and how transcription factor networks affect it. We apply self-organizing map machine learning to a published data set on the specification and differentiation of murine intestinal stem cells in order to provide an integrative view of gene transcription and DNA, as well as histone methylation during this process. We show that, although gain/loss of H3K4me3 at a gene promoter is generally considered to be associated with its increased/decreased transcriptional activity, such an interrelation is not mandatory, i.e., changes of the modification level do not necessarily affect transcription. Similar considerations hold for H3K27me3. In addition, even strong changes in the transcription of a gene do not necessarily affect its H3K4me3 and H3K27me3 modification profile. We provide a mechanistic explanation of these phenomena that is based on a model of epigenetic regulation of transcription. Thereby, the analyzed data suggest a broad variance in gene specific regulation of histone methylation and support the assumption of an independent regulation of transcription by histone methylation and transcription factor networks. The results provide insights into basic principles of the specification of tissue stem cells and highlight open questions about a mechanistic modeling of this process.

Authors: T. Thalheim, Lydia Hopp, Hans Binder, G. Aust, J. Galle

Date Published: No date defined

Publication Type: Not specified

Abstract

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Authors: B. Kampe, U. Hahn

Date Published: No date defined

Publication Type: Proceedings

Abstract

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Authors: A. Lagemann, Reinhold Haux, Alfred Winter

Date Published: No date defined

Publication Type: Misc

Abstract (Expand)

Molecular mechanisms of lower grade (II- III) diffuse gliomas (LGG) are still poorly understood, mainly because of their heterogeneity. They split into astrocytoma- (IDH-A) and oligodendro-glioma-like (IDH-O) tumors both carrying mutations(s) at the Isocitrate dehydrogenase (IDH) gene and into IDH wild type (IDH-wt) gliomas of glioblastoma-resemblance. We generated de-tailed maps of the transcriptomes and DNA-methylomes revealing that cell functions divide into three major archeotypic hallmarks: (i) increased proliferation in IDH-wt and, to a less degree, IDH-O, (ii) increased inflammation in IDH-A and IDH-wt, and (iii) the loss of synaptic transmis-sion in all subtypes. Immunogenic properties of IDH-A are diverse partly resembling signatures observed in grade IV mesenchymal glioblastomas or in grade I pilocytic astrocytomas. We ana-lyzed details of coregulation between gene expression and DNA-methylation and of the immu-nogenic micro-environment presumably driving tumor development and treatment resistance. Our transcriptome and methylome maps support personalized, case-by-case views to decipher the heterogeneity of glioma states in terms of data portraits. Thereby molecular cartography provides a graphical coordinate system, which links gene-level information with glioma sub-types, their phenotypes and clinical context.

Authors: Hans Binder, Maria Schmidt, Lydia Hopp, Arsen Arakelyan, Henry Löffler-Wirth

Date Published: No date defined

Publication Type: Journal article

Human Diseases: brain glioma

Abstract (Expand)

Numerous prediction models of SARS-CoV-2 pandemic were proposed in the past. Unknown parameters of these models are often estimated based on observational data. However, lag in case-reporting, changing testing policy or incompleteness of data lead to biased estimates. Moreover, parametrization is time-dependent due to changing age-structures, emerging virus variants, non-pharmaceutical interventions, and vaccination programs. To cover these aspects, we propose a principled approach to parametrize a SIR-type epidemiologic model by embedding it as a hidden layer into an input-output non-linear dynamical system (IO-NLDS). Observable data are coupled to hidden states of the model by appropriate data models considering possible biases of the data. This includes data issues such as known delays or biases in reporting. We estimate model parameters including their time-dependence by a Bayesian knowledge synthesis process considering parameter ranges derived from external studies as prior information. We applied this approach on a specific SIR-type model and data of Germany and Saxony demonstrating good prediction performances. Our approach can estimate and compare the relative effectiveness of non-pharmaceutical interventions and provide scenarios of the future course of the epidemic under specified conditions. It can be translated to other data sets, i.e., other countries and other SIR-type models.

Authors: Y. Kheifetz, H. Kirsten, M. Scholz

Date Published: 2nd Jul 2022

Publication Type: Journal article

Human Diseases: COVID-19

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