ArticlePloS one2020
A computational model of liver tissue damage and repair.
Article in PloS one, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 16 citations in OpenAlex.
- Multiscale zonation-resolved modeling of dose-dependent determinants of acetaminophen-induced liver injury.Frontiers in pharmacology · 2026Article
- A virtual scalable model of the Hepatic Lobule for acetaminophen hepatotoxicity prediction.NPJ digital medicine · 2024Article
- Efferocytosis reprograms the tumor microenvironment to promote pancreatic cancer liver metastasis.Nature cancer · 2024Article
- A liver digital twin for in silico testing of cellular and inter-cellular mechanisms in regeneration after drug-induced damage.iScience · 2024Article
- Illuminating HBV with multi-scale modeling.Frontiers in systems biology · 2023Article
- Unraveling the effect of intra- and intercellular processes on acetaminophen-induced liver injury.NPJ systems biology and applications · 2022Article
- The Indiana O'Brien Center for Advanced Renal Microscopic Analysis.American journal of physiology. Renal physiology · 2021Review
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Authors and funding
9 authors at 3 institutions in 2 countries.
Funding
Abstract
Drug induced liver injury (DILI) and cell death can result from oxidative stress in hepatocytes. An initial pattern of centrilobular damage in the APAP model of DILI is amplified by communication from stressed cells and immune system activation. While hepatocyte proliferation counters cell loss, high doses are still lethal to the tissue. To understand the progression of disease from the initial damage to tissue recovery or death, we computationally model the competing biological processes of hepatocyte proliferation, necrosis and injury propagation. We parametrize timescales of proliferation (α), conversion of healthy to stressed cells (β) and further sensitization of stressed cells towards necrotic pathways (γ) and model them on a Cellular Automaton (CA) based grid of lattice sites. 1D simulations show that a small α/β (fast proliferation), combined with a large γ/β (slow death) have the lowest probabilities of tissue survival. At large α/β, tissue fate can be described by a critical γ/β* ratio alone; this value is dependent on the initial amount of damage and proportional to the tissue size N. Additionally, the 1D model predicts a minimum healthy population size below which damage is irreversible. Finally, we compare 1D and 2D phase spaces and discuss outcomes of bistability where either survival or death is possible, and of coexistence where simulated tissue never completely recovers or dies but persists as a mixture of healthy, stressed and necrotic cells. In conclusion, our model sheds light on the evolution of tissue damage or recovery and predicts potential for divergent fates given different rates of proliferation, necrosis, and injury propagation.
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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.