ArticlePloS one2017
A multi-scale spatial model of hepatitis-B viral dynamics.
Article in PloS one, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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Who cites it
11 citing papers in PubMed, 17 citations in OpenAlex.
- Analysis and simulation of a stochastic reaction-diffusion model for HBV infection under antiviral treatment.BMC infectious diseases · 2026Article
- Spatio-temporal modelling of in vitro influenza A virus infection: The impact of defective interfering particles on the type I interferon response.PLoS computational biology · 2026Article
- A Quantitative Systems Pharmacology (QSP) Model of Acute Hepatitis B Virus Infection: Mechanistic Insights and Foundations for Future Extensions.CPT: pharmacometrics & systems pharmacology · 2026Article
- Spatially structured models of viral dynamics: a scoping review.Microbiology and molecular biology reviews : MMBR · 2025Article
- Spatio-temporal modelling ofbioRxiv : the preprint server for biology · 2025Article
- Disease Progression Mathematical Modeling With a Case Study on Hepatitis B Virus Infection.CPT: pharmacometrics & systems pharmacology · 2025Review
- A computational spatial whole-Cell model for hepatitis B viral infection and drug interactions.Scientific reports · 2023Article
- Illuminating HBV with multi-scale modeling.Frontiers in systems biology · 2023Article
- Global sensitivity analysis of a single-cell HBV model for viral dynamics in the liver.Infectious Disease Modelling · 2021Article
- Mathematical Modeling for Hepatitis B Virus: Would Spatial Effects Play a Role and How to Model It?Frontiers in physiology · 2020Article
- Virtual Lobule Models Are the Key for Multiscale Biomechanical and Pharmacological Modeling for the Liver.Frontiers in physiology · 2020Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Chronic hepatitis B viral infection (HBV) afflicts around 250 million individuals globally and few options for treatment exist. Once infected, the virus entrenches itself in the liver with a notoriously resilient colonisation of viral DNA (covalently-closed circular DNA, cccDNA). The majority of infections are cleared, yet we do not understand why 5% of adult immune responses fail leading to the chronic state with its collateral morbid effects such as cirrhosis and eventual hepatic carcinoma. The liver environment exhibits particularly complex spatial structures for metabolic processing and corresponding distributions of nutrients and transporters that may influence successful HBV entrenchment. We assembled a multi-scaled mathematical model of the fundamental hepatic processing unit, the sinusoid, into a whole-liver representation to investigate the impact of this intrinsic spatial heterogeneity on the HBV dynamic. Our results suggest HBV may be exploiting spatial aspects of the liver environment. We distributed increased HBV replication rates coincident with elevated levels of nutrients in the sinusoid entry point (the periportal region) in tandem with similar distributions of hepatocyte transporters key to HBV invasion (e.g., the sodium-taurocholate cotransporting polypeptide or NTCP), or immune system activity. According to our results, such co-alignment of spatial distributions may contribute to persistence of HBV infections, depending on spatial distributions and intensity of immune response as well. Moreover, inspired by previous HBV models and experimentalist suggestions of extra-hepatic HBV replication, we tested in our model influence of HBV blood replication and observe an overall nominal effect on persistent liver infection. Regardless, we confirm prior results showing a solo cccDNA is sufficient to re-infect an entire liver, with corresponding concerns for transplantation and treatment.
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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.