IDEAS home Printed from https://ideas.repec.org/a/plo/pcbi00/1000756.html
   My bibliography  Save this article

Simulating Microdosimetry in a Virtual Hepatic Lobule

Author

Listed:
  • John Wambaugh
  • Imran Shah

Abstract

The liver plays a key role in removing harmful chemicals from the body and is therefore often the first tissue to suffer potentially adverse consequences. To protect public health it is necessary to quantitatively estimate the risk of long-term low dose exposure to environmental pollutants. Animal testing is the primary tool for extrapolating human risk but it is fraught with uncertainty, necessitating novel alternative approaches. Our goal is to integrate in vitro liver experiments with agent-based cellular models to simulate a spatially extended hepatic lobule. Here we describe a graphical model of the sinusoidal network that efficiently simulates portal to centrilobular mass transfer in the hepatic lobule. We analyzed the effects of vascular topology and metabolism on the cell-level distribution following oral exposure to chemicals. The spatial distribution of metabolically inactive chemicals was similar across different vascular networks and a baseline well-mixed compartment. When chemicals were rapidly metabolized, concentration heterogeneity of the parent compound increased across the vascular network. As a result, our spatially extended lobule generated greater variability in dose-dependent cellular responses, in this case apoptosis, than were observed in the classical well-mixed liver or in a parallel tubes model. The mass-balanced graphical approach to modeling the hepatic lobule is computationally efficient for simulating long-term exposure, modular for incorporating complex cellular interactions, and flexible for dealing with evolving tissues.Author Summary: Virtual tissues are emerging as a powerful tool for computational biology. By encoding known biology into a simulation of tissue function, gaps in knowledge can be identified. As a simulation of tissue function, in silico experiments can be performed inexpensively and rapidly. There are over 6000 chemicals produced in large quantities that may be present in our environment, many of which have not been thoroughly examined for human toxicity. Traditional toxicity testing is expensive, lengthy, and relies heavily upon the use of animals. For this reason in vitro toxicity testing techniques are being developed. However, techniques are needed to relate in vitro results to in vivo conditions. The liver is often the first tissue to show signs of toxicity and therefore a predictive liver toxicity simulator would be a powerful tool to reduce the financial and animal cost of toxicity testing. As a first step, we have developed a model for relating environmental exposure to cell-level concentrations; a model for virtual tissue microdosimetry. We identify regimes in which this approach is equivalent to previous techniques, as well as regimes where large cell-to-cell variability exists. This variability should have consequences both for normal liver function and the onset of injury.

Suggested Citation

  • John Wambaugh & Imran Shah, 2010. "Simulating Microdosimetry in a Virtual Hepatic Lobule," PLOS Computational Biology, Public Library of Science, vol. 6(4), pages 1-16, April.
  • Handle: RePEc:plo:pcbi00:1000756
    DOI: 10.1371/journal.pcbi.1000756
    as

    Download full text from publisher

    File URL: https://journals.plos.org/ploscompbiol/article?id=10.1371/journal.pcbi.1000756
    Download Restriction: no

    File URL: https://journals.plos.org/ploscompbiol/article/file?id=10.1371/journal.pcbi.1000756&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pcbi.1000756?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Thomas Hartung, 2009. "Toxicology for the twenty-first century," Nature, Nature, vol. 460(7252), pages 208-212, July.
    2. Leona H. Clark & R. Woodrow Setzer & Hugh A. Barton, 2004. "Framework for Evaluation of Physiologically‐Based Pharmacokinetic Models for Use in Safety or Risk Assessment," Risk Analysis, John Wiley & Sons, vol. 24(6), pages 1697-1717, December.
    3. Merks, Roeland M.H. & Glazier, James A., 2005. "A cell-centered approach to developmental biology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 352(1), pages 113-130.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. James P Sluka & Xiao Fu & Maciej Swat & Julio M Belmonte & Alin Cosmanescu & Sherry G Clendenon & John F Wambaugh & James A Glazier, 2016. "A Liver-Centric Multiscale Modeling Framework for Xenobiotics," PLOS ONE, Public Library of Science, vol. 11(9), pages 1-40, September.
    2. Quentin Cangelosi & Shawn A Means & Harvey Ho, 2017. "A multi-scale spatial model of hepatitis-B viral dynamics," PLOS ONE, Public Library of Science, vol. 12(12), pages 1-28, December.
    3. Xiao Fu & James P Sluka & Sherry G Clendenon & Kenneth W Dunn & Zemin Wang & James E Klaunig & James A Glazier, 2018. "Modeling of xenobiotic transport and metabolism in virtual hepatic lobule models," PLOS ONE, Public Library of Science, vol. 13(9), pages 1-34, September.
    4. Mohammed H Cherkaoui-Rbati & Stuart W Paine & Peter Littlewood & Cyril Rauch, 2017. "A quantitative systems pharmacology approach, incorporating a novel liver model, for predicting pharmacokinetic drug-drug interactions," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-28, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Nicolas Defarge & Eszter Takács & Verónica Laura Lozano & Robin Mesnage & Joël Spiroux de Vendômois & Gilles-Eric Séralini & András Székács, 2016. "Co-Formulants in Glyphosate-Based Herbicides Disrupt Aromatase Activity in Human Cells below Toxic Levels," IJERPH, MDPI, vol. 13(3), pages 1-17, February.
    2. Anja Voss-Böhme, 2012. "Multi-Scale Modeling in Morphogenesis: A Critical Analysis of the Cellular Potts Model," PLOS ONE, Public Library of Science, vol. 7(9), pages 1-14, September.
    3. Deepika Deepika & Vikas Kumar, 2023. "The Role of “Physiologically Based Pharmacokinetic Model (PBPK)” New Approach Methodology (NAM) in Pharmaceuticals and Environmental Chemical Risk Assessment," IJERPH, MDPI, vol. 20(4), pages 1-19, February.
    4. Dustin F Kapraun & John F Wambaugh & R Woodrow Setzer & Richard S Judson, 2019. "Empirical models for anatomical and physiological changes in a human mother and fetus during pregnancy and gestation," PLOS ONE, Public Library of Science, vol. 14(5), pages 1-56, May.
    5. Eva D. McLanahan & Paul White & Lynn Flowers & Paul M. Schlosser, 2014. "The Use of PBPK Models to Inform Human Health Risk Assessment: Case Study on Perchlorate and Radioiodide Human Lifestage Models," Risk Analysis, John Wiley & Sons, vol. 34(2), pages 356-366, February.
    6. Yan, Kexun & Wang, Maoxiang & Hu, Fenglan & Xu, Meng, 2023. "Effect of cellular dedifferentiation on the growth of cell lineages," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 632(P1).
    7. Levada Alexandre L., 2016. "Information geometry, simulation and complexity in Gaussian random fields," Monte Carlo Methods and Applications, De Gruyter, vol. 22(2), pages 81-107, June.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pcbi00:1000756. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ploscompbiol (email available below). General contact details of provider: https://journals.plos.org/ploscompbiol/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.