ArticlePloS one2015
Representative Sinusoids for Hepatic Four-Scale Pharmacokinetics Simulations.
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.
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Who cites it
19 citing papers in PubMed, 46 citations in OpenAlex.
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- Digital twin demonstrates significance of biomechanical growth control in liver regeneration after partial hepatectomy.iScience · 2023Article
- Illuminating HBV with multi-scale modeling.Frontiers in systems biology · 2023Article
- Automated Detection of Portal Fields and Central Veins in Whole-Slide Images of Liver Tissue.Journal of pathology informatics · 2022Article
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- Impact of tumor-parenchyma biomechanics on liver metastatic progression: a multi-model approach.Scientific reports · 2021Article
- Liver Bioreactor Design Issues of Fluid Flow and Zonation, Fibrosis, and Mechanics: A Computational Perspective.Journal of functional biomaterials · 2020Review
- Modeling of Nanotherapy Response as a Function of the Tumor Microenvironment: Focus on Liver Metastasis.Frontiers in bioengineering and biotechnology · 2020Review
- Benchmark problems for dynamic modeling of intracellular processes.Bioinformatics (Oxford, England) · 2019Article
- Effects of a high protein diet and liver disease in an in silico model of human ammonia metabolism.Theoretical biology & medical modelling · 2019Article
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- Stereological analysis of size and density of hepatocytes in the porcine liver.Journal of anatomy · 2017Article
- Facing the challenges of multiscale modelling of bacterial and fungal pathogen-host interactions.Briefings in functional genomics · 2017Review
- Computational Modeling in Liver Surgery.Frontiers in physiology · 2017Review
- A multi-scale spatial model of hepatitis-B viral dynamics.PloS one · 2017Article
- A physiologically-based flow network model for hepatic drug elimination III: 2D/3D DLA lobule models.Theoretical biology & medical modelling · 2016Article
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Corrections and comments
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Authors and funding
7 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The mammalian liver plays a key role for metabolism and detoxification of xenobiotics in the body. The corresponding biochemical processes are typically subject to spatial variations at different length scales. Zonal enzyme expression along sinusoids leads to zonated metabolization already in the healthy state. Pathological states of the liver may involve liver cells affected in a zonated manner or heterogeneously across the whole organ. This spatial heterogeneity, however, cannot be described by most computational models which usually consider the liver as a homogeneous, well-stirred organ. The goal of this article is to present a methodology to extend whole-body pharmacokinetics models by a detailed liver model, combining different modeling approaches from the literature. This approach results in an integrated four-scale model, from single cells via sinusoids and the organ to the whole organism, capable of mechanistically representing metabolization inhomogeneity in livers at different spatial scales. Moreover, the model shows circulatory mixing effects due to a delayed recirculation through the surrounding organism. To show that this approach is generally applicable for different physiological processes, we show three applications as proofs of concept, covering a range of species, compounds, and diseased states: clearance of midazolam in steatotic human livers, clearance of caffeine in mouse livers regenerating from necrosis, and a parameter study on the impact of different cell entities on insulin uptake in mouse livers. The examples illustrate how variations only discernible at the local scale influence substance distribution in the plasma at the whole-body level. In particular, our results show that simultaneously considering variations at all relevant spatial scales may be necessary to understand their impact on observations at the organism scale.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.