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A liver digital twin for in silico testing of cellular and inter-cellular mechanisms in regeneration after drug-induced damage

This communication presents a mathematical mechanism-based model of the regenerating liver after drug-induced pericentral lobule damage resolving tissue microarchitecture. The consequence of alternative hypotheses about the interplay of different cell types on regeneration was simulated. Regeneratio...

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Hauptverfasser: Zhao, Jieling (VerfasserIn) , Ghallab, Ahmed (VerfasserIn) , Hassan, Reham (VerfasserIn) , Dooley, Steven (VerfasserIn) , Hengstler, Jan Georg (VerfasserIn) , Drasdo, Dirk (VerfasserIn)
Dokumenttyp: Article (Journal)
Sprache:Englisch
Veröffentlicht: 16 February 2024
In: iScience
Year: 2024, Jahrgang: 27, Heft: 2, Pages: 1-25
ISSN:2589-0042
DOI:10.1016/j.isci.2023.108077
Online-Zugang:Verlag, kostenfrei, Volltext: https://doi.org/10.1016/j.isci.2023.108077
Verlag, kostenfrei, Volltext: https://www.sciencedirect.com/science/article/pii/S2589004223021545
Volltext
Verfasserangaben:Jieling Zhao, Ahmed Ghallab, Reham Hassan, Steven Dooley, Jan Georg Hengstler, Dirk Drasdo
Beschreibung
Zusammenfassung:This communication presents a mathematical mechanism-based model of the regenerating liver after drug-induced pericentral lobule damage resolving tissue microarchitecture. The consequence of alternative hypotheses about the interplay of different cell types on regeneration was simulated. Regeneration dynamics has been quantified by the size of the damage-induced dead cell area, the hepatocyte density and the spatial-temporal profile of the different cell types. We use deviations of observed trajectories from the simulated system to identify branching points, at which the systems behavior cannot be explained by the underlying set of hypotheses anymore. Our procedure reflects a successful strategy for generating a fully digital liver twin that, among others, permits to test perturbations from the molecular up to the tissue scale. The model simulations are complementing current knowledge on liver regeneration by identifying gaps in mechanistic relationships and guiding the system toward the most informative (lacking) parameters that can be experimentally addressed.
Beschreibung:Online verfügbar: 28 September 2023, Version of Record 10 February 2024
Gesehen am 13.03.2025
Beschreibung:Online Resource
ISSN:2589-0042
DOI:10.1016/j.isci.2023.108077

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