Evidence map›Paper›PMID 33347443›Full record

ArticlePloS one2020

A computational model of liver tissue damage and repair.

Priyom Adhyapok, Xiao Fu, James P Sluka, Sherry G Clendenon, Victoria D Sluka, Zemin Wang, Kenneth Dunn, James E Klaunig, James A Glazier

Open access · goldAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
0.2field-weighted citation impact, top 38% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed, 16 citations in OpenAlex.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Illuminating HBV with multi-scale modeling.Frontiers in systems biology · 2023
    Article
  6. Article
  7. The Indiana O'Brien Center for Advanced Renal Microscopic Analysis.American journal of physiology. Renal physiology · 2021
    Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors at 3 institutions in 2 countries.

Priyom AdhyapokBiocomplexity Institute, Indiana University, Bloomington, IN, United States of America.ORCID 0000-0003-3067-7058
Xiao FuThe Francis Crick Institute, London, United Kingdom.
James P SlukaBiocomplexity Institute, Indiana University, Bloomington, IN, United States of America.
Sherry G ClendenonBiocomplexity Institute, Indiana University, Bloomington, IN, United States of America.ORCID 0000-0002-3353-0919
Victoria D SlukaBiocomplexity Institute, Indiana University, Bloomington, IN, United States of America.ORCID 0000-0003-1724-5007
Zemin WangSchool of Public Health, Indiana University, Bloomington, IN, United States of America.ORCID 0000-0003-4189-578X
Kenneth DunnSchool of Medicine, Indiana University, Indianapolis, IN, United States of America.
James E KlaunigSchool of Public Health, Indiana University, Bloomington, IN, United States of America.
James A GlazierBiocomplexity Institute, Indiana University, Bloomington, IN, United States of America.
Indiana University Bloomington · USIndiana University – Purdue University Indianapolis · USThe Francis Crick Institute · GB

Funding

Development of a Multiscale Mechanistic Simulation of Acetaminophen Induced LiverU01GM111243 · NIGMS · TRUSTEES OF INDIANA UNIVERSITY · PI DUNN, KENNETH W, GLAZIER, JAMES ALEXANDER · 2014 to 2017
$2.1M
Competitive Renewal of Development, Improvement and Extension of the Tissue Simulation Environment - CompuCell3DR01GM122424 · NIGMS · TRUSTEES OF INDIANA UNIVERSITY · PI GLAZIER, JAMES ALEXANDER · 2017 to 2020
$1.7M
Dissemination of libRoadRunner and CompuCell3DU24EB028887 · NIBIB · UNIVERSITY OF WASHINGTON · PI GLAZIER, JAMES ALEXANDER, SAURO, HERBERT M. · 2019 to 2023
$1.5M
NIBIB NIH HHS U24 EB028887NIGMS NIH HHS R01 GM122424NIGMS NIH HHS U01 GM111243
6 · The paper itself

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.

Indexed as

Models, AnimalAcetaminophenAlanine TransaminaseAnimalsApoptosisAspartate AminotransferasesCell ProliferationChemical and Drug Induced Liver InjuryHepatocytesLiverMiceNecrosisAcetaminophenAlanine TransaminaseAspartate Aminotransferases

Identifiers

PMID33347443
PMCPMC7752149
OpenAlexW3114635931

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.