ArticleiScience2024
A liver digital twin for in silico testing of cellular and inter-cellular mechanisms in regeneration after drug-induced damage.
Article in iScience, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
What it found
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
7 citing papers in PubMed.
- Digital Twins in Personalized Medicine: Bridging Innovation and Clinical Reality.Journal of personalized medicine · 2025Review
- A scoping review of human digital twins in healthcare applications and usage patterns.NPJ digital medicine · 2025Article
- A new human autologous hepatocyte/macrophage co-culture system that mimics drug-induced liver injury-like inflammation.Archives of toxicology · 2025Article
- Donor-specific digital twin for living donor liver transplant recovery.Biology methods & protocols · 2025Article
- Digital twins in healthcare: a comprehensive review and future directions.Frontiers in digital health · 2025Review
- A computational model reveals an early transient decrease in fiber cross-linking that unlocks adult regeneration.NPJ Regenerative medicine · 2024Article
- Digital Twins of Biological Systems: A Narrative Review.IEEE open journal of engineering in medicine and biology · 2024Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
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.
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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.