Publications

657 Publications visible to you, out of a total of 657

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

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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

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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

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BACKGROUND The effect of risk-reducing salpingo-oophorectomy (RRSO) on breast cancer risk for BRCA1 and BRCA2 mutation carriers is uncertain. Retrospective analyses have suggested a protective effectt but may be substantially biased. Prospective studies have had limited power, particularly for BRCA2 mutation carriers. Further, previous studies have not considered the effect of RRSO in the context of natural menopause. METHODS A multi-centre prospective cohort of 2272 BRCA1 and 1605 BRCA2 mutation carriers was followed for a mean of 5.4 and 4.9 years, respectively; 426 women developed incident breast cancer. RRSO was modelled as a time-dependent covariate in Cox regression, and its effect assessed in premenopausal and postmenopausal women. RESULTS There was no association between RRSO and breast cancer for BRCA1 (HR = 1.23; 95% CI 0.94-1.61) or BRCA2 (HR = 0.88; 95% CI 0.62-1.24) mutation carriers. For BRCA2 mutation carriers, HRs were 0.68 (95% CI 0.40-1.15) and 1.07 (95% CI 0.69-1.64) for RRSO carried out before or after age 45 years, respectively. The HR for BRCA2 mutation carriers decreased with increasing time since RRSO (HR = 0.51; 95% CI 0.26-0.99 for 5 years or longer after RRSO). Estimates for premenopausal women were similar. CONCLUSION We found no evidence that RRSO reduces breast cancer risk for BRCA1 mutation carriers. A potentially beneficial effect for BRCA2 mutation carriers was observed, particularly after 5 years following RRSO. These results may inform counselling and management of carriers with respect to RRSO.

Authors: Nasim Mavaddat, Antonis C. Antoniou, Thea M. Mooij, Maartje J. Hooning, Bernadette A. Heemskerk-Gerritsen, Catherine Noguès, Marion Gauthier-Villars, Olivier Caron, Paul Gesta, Pascal Pujol, Alain Lortholary, Daniel Barrowdale, Debra Frost, D. Gareth Evans, Louise Izatt, Julian Adlard, Ros Eeles, Carole Brewer, Marc Tischkowitz, Alex Henderson, Jackie Cook, Diana Eccles, Klaartje van Engelen, Marian J. E. Mourits, Margreet G. E. M. Ausems, Linetta B. Koppert, John L. Hopper, Esther M. John, Wendy K. Chung, Irene L. Andrulis, Mary B. Daly, Saundra S. Buys, Javier Benitez, Trinidad Caldes, Anna Jakubowska, Jacques Simard, Christian F. Singer, Yen Tan, Edith Olah, Marie Navratilova, Lenka Foretova, Anne-Marie Gerdes, Marie-José Roos-Blom, Flora E. van Leeuwen, Brita Arver, Håkan Olsson, Rita K. Schmutzler, Christoph Engel, Karin Kast, Kelly-Anne Phillips, Mary Beth Terry, Roger L. Milne, David E. Goldgar, Matti A. Rookus, Nadine Andrieu, Douglas F. Easton

Date Published: 1st Dec 2020

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

Abstract

After publication of the original article [1], we were notified that columns in Table 2 were erroneously displayed.

Authors: Nasim Mavaddat, Antonis C. Antoniou, Thea M. Mooij, Maartje J. Hooning, Bernadette A. Heemskerk-Gerritsen, Catherine Noguès, Marion Gauthier-Villars, Olivier Caron, Paul Gesta, Pascal Pujol, Alain Lortholary, Daniel Barrowdale, Debra Frost, D. Gareth Evans, Louise Izatt, Julian Adlard, Ros Eeles, Carole Brewer, Marc Tischkowitz, Alex Henderson, Jackie Cook, Diana Eccles, Klaartje van Engelen, Marian J. E. Mourits, Margreet G. E. M. Ausems, Linetta B. Koppert, John L. Hopper, Esther M. John, Wendy K. Chung, Irene L. Andrulis, Mary B. Daly, Saundra S. Buys, Javier Benitez, Trinidad Caldes, Anna Jakubowska, Jacques Simard, Christian F. Singer, Yen Tan, Edith Olah, Marie Navratilova, Lenka Foretova, Anne-Marie Gerdes, Marie-José Roos-Blom, Flora E. van Leeuwen, Brita Arver, Håkan Olsson, Rita K. Schmutzler, Christoph Engel, Karin Kast, Kelly-Anne Phillips, Mary Beth Terry, Roger L. Milne, David E. Goldgar, Matti A. Rookus, Nadine Andrieu, Douglas F. Easton

Date Published: 1st Dec 2020

Publication Type: Journal article

Human Diseases: hereditary breast ovarian cancer syndrome

Abstract (Expand)

Anaemia therapy or perisurgical support of erythropoiesis often require both, EPO and iron medication. However, excessive iron medication can result in iron overload and it is challenging to control haemoglobin levels in a desired range. To support this task, we develop a biomathematical model to simulate EPO- and iron medication in humans. We combine our previously established model of human erythropoiesis including comprehensive pharmacokinetic models of EPO applications with a newly developed model of iron metabolism including iron supplementation. Equations were derived by translating known biological mechanisms into ordinary differential equations. Qualitative model behaviour is studied in detail considering a variety of interventions such as bleeding, iron malnutrition and medication. The model can explain time courses of erythrocytes, reticulocytes, haemoglobin, haematocrit, red blood cells, EPO, serum iron, ferritin, transferrin saturation, and transferrin under a variety of scenarios including EPO and iron application into healthy volunteers or chemotherapy patients. Unknown model parameters were determined by fitting the predictions of the model to time series data from literature. We demonstrate how the model can be used to make predictions of untested therapy options such as cytotoxic chemotherapy supported by iron and EPO. Following our ultimate goal of establishing a model of anaemia treatment in chronic kidney disease, we aim at translating our model to this pathological condition in the near future.

Authors: Sibylle Schirm, Markus Scholz

Date Published: 1st Dec 2020

Publication Type: Journal article

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