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958 Publications visible to you, out of a total of 958
Automated macrophage counting in DLBCL tissue samples: a ROF filter based approach
MMML Demonstrators - Molecular Mechanisms in Malignant Lymphomas - Demonstrators of Personalized Medicine

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

On the Cooperation between Epigenetics and Transcription Factor Networks in the Specification of Tissue Stem Cells
LHA - Leipzig Health Atlas

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

The Influence of Down-Sampling Strategies on SVD Word Embedding Stability.
SMITH - Smart Medical Information Technology for Healthcare

Abstract

Not specified

Authors: B. Kampe, U. Hahn

Date Published: No date defined

Publication Type: Proceedings

Modellierung eines Anwendungssystems zur Unterstützung der Pflegedokumentation unter Berücksichtigung der Integration in ein klinisches Arbeitsplatzsystem
Management of health information systems

Abstract

Not specified

Authors: A. Lagemann, Reinhold Haux, Alfred Winter

Date Published: No date defined

Publication Type: Misc

Multi-omics cartography of glioma heterogeneity
GGN - German Glioma Network

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

Skin single-cell transcriptomics reveals a core of sebaceous gland-relevant genes shared by mice and humans
scRNAseq sebaceous gland

Abstract

submitted

Author: Torsten Thalheim

Date Published: No date defined

Publication Type: Journal article

Prediction of Intensive Care Unit Length of Stay in the MIMIC-IV Dataset
Prediction model of Length of Stay and probability of rehospitalization

Abstract (Expand)

Accurately estimating the length of stay (LOS) of patients admitted to the intensive care unit (ICU) in relation to their health status helps healthcare management allocate appropriate resources and … resources and better plan for the future. This paper presents predictive models for the LOS of ICU patients from the MIMIC-IV database based on typical demographic and administrative data, as well as early vital signs and laboratory measurements collected on the first day of ICU stay. The goal of this study was to demonstrate a practical, stepwise approach to predicting patient’s LOS in the ICU using machine learning and early available typical clinical data. The results show that this approach significantly improves the performance of models for predicting actual LOS in a pragmatic framework that includes only data with short stays predetermined by a prior classification.

Authors: Lars Hempel, Sina Sadeghi, Toralf Kirsten

Date Published: 1st Jun 2023

Publication Type: Journal article

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