Kupffer cells (KCs) are tissue-resident macrophages that colonize the liver early during embryogenesis. Upon liver colonization, KCs rapidly acquire a tissue-specific transcriptional signature, mature alongside the developing liver and adapt to its functions. Throughout development and adulthood, KCs perform distinct core functions that are essential for liver and organismal homeostasis, including supporting fetal erythropoiesis, postnatal erythrocyte recycling and liver metabolism.
View Article and Find Full Text PDFMotivation: The availability of bulk-omic data is steadily increasing, necessitating collaborative efforts between experimental and computational researchers. While software tools with graphical user interfaces (GUIs) enable rapid and interactive data assessment, they are limited to pre-implemented methods, often requiring transitions to custom code for further adjustments. However, the most available tools lack GUI-independent reproducibility such as direct integration with R, resulting in very limited support for transition.
View Article and Find Full Text PDFMotivation: Quantitative dynamical models facilitate the understanding of biological processes and the prediction of their dynamics. The parameters of these models are commonly estimated from experimental data. Yet, experimental data generated from different techniques do not provide direct information about the state of the system but a nonlinear (monotonic) transformation of it.
View Article and Find Full Text PDFDatasets consist of measurement data and metadata. Metadata provides context, essential for understanding and (re-)using data. Various metadata standards exist for different methods, systems and contexts.
View Article and Find Full Text PDFBioinformatics
November 2023
Summary: Mechanistic models are important tools to describe and understand biological processes. However, they typically rely on unknown parameters, the estimation of which can be challenging for large and complex systems. pyPESTO is a modular framework for systematic parameter estimation, with scalable algorithms for optimization and uncertainty quantification.
View Article and Find Full Text PDFSummary: To allow the comprehensive histological analysis of the whole intestine, it is often rolled to a spiral before imaging. This Swiss-rolling technique facilitates robust experimental procedures, but it limits the possibilities to comprehend changes along the intestine. Here, we present IntestLine, a Shiny-based open-source application for processing imaging data of (rolled) intestinal tissues and subsequent mapping onto a line.
View Article and Find Full Text PDFMacrophages supply iron to the breast tumor microenvironment by enforced secretion of lipocalin-2 (Lcn-2)-bound iron as well as the increased expression of the iron exporter ferroportin (FPN). We aimed at identifying the contribution of each pathway in supplying iron for the growing tumor, thereby fostering tumor progression. Analyzing the expression profiles of Lcn-2 and FPN using the spontaneous polyoma-middle-T oncogene (PyMT) breast cancer model as well as mining publicly available TCGA (The Cancer Genome Atlas) and GEO Series(GSE) datasets from the Gene Expression Omnibus database (GEO), we found no association between tumor parameters and Lcn-2 or FPN.
View Article and Find Full Text PDFA dermal absorption model for small and macromolecules was previously proposed by Ibrahim et al. This model estimated absorption of therapeutics from the dermal tissue based on their molecular size and protein binding through blood and lymphatics. Blood absorption followed a two-pore theory and the lymphatic absorption was limited by the constant lymphatic flow rate.
View Article and Find Full Text PDFDuring the course of sepsis in critically ill patients, kidney dysfunction and damage are among the first events of a complex scenario toward multi-organ failure and patient death. Acute kidney injury triggers the release of lipocalin-2 (Lcn-2), which is involved in both renal injury and recovery. Taking into account that Lcn-2 binds and transports iron with high affinity, we aimed at clarifying if Lcn-2 fulfills different biological functions according to its iron-loading status and its cellular source during sepsis-induced kidney failure.
View Article and Find Full Text PDFFront Comput Neurosci
June 2020
Neuron classification is an important component in analyzing network structure and quantifying the effect of neuron topology on signal processing. Current quantification and classification approaches rely on morphology projection onto lower-dimensional spaces. In this paper a 3D visualization and quantification tool is presented.
View Article and Find Full Text PDFOncoimmunology
December 2017
While the importance of iron for tumor development is widely appreciated, the exact sources of tumor-supporting iron largely remain elusive. The possibility that iron might be provided by stromal cells in the tumor microenvironment was not taken into account so far. In the present study, we show that tumor-associated macrophages (TAM) acquire an iron-release phenotype upon their interaction with tumor cells, thereby increasing the availability of iron in the tumor microenvironment.
View Article and Find Full Text PDFTumour cell-secreted factors skew infiltrating immune cells towards a tumour-supporting phenotype, expressing pro-tumourigenic mediators. However, the influence of lipocalin-2 (Lcn2) on the metastatic cascade in the tumour micro-environment is still not clearly defined. Here, we explored the role of stroma-derived, especially macrophage-released, Lcn2 in breast cancer progression.
View Article and Find Full Text PDFThe morphology of neurons and networks plays an important role in processing electrical and biochemical signals. Based on neuronal reconstructions, which are becoming abundantly available through databases such as NeuroMorpho.org, numerical simulations of Hodgkin-Huxley-type equations, coupled to biochemical models, can be performed in order to systematically investigate the influence of cellular morphology and the connectivity pattern in networks on the underlying function.
View Article and Find Full Text PDFInvestigation of cellular and network dynamics in the brain by means of modeling and simulation has evolved into a highly interdisciplinary field, that uses sophisticated modeling and simulation approaches to understand distinct areas of brain function. Depending on the underlying complexity, these models vary in their level of detail, in order to cope with the attached computational cost. Hence for large network simulations, single neurons are typically reduced to time-dependent signal processors, dismissing the spatial aspect of each cell.
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