Evidence map›Paper›PMID 34526653›Full record

ArticleCommunications biology2021

Modelling human liver fibrosis in the context of non-alcoholic steatohepatitis using a microphysiological system.

Tomasz Kostrzewski, Sophie Snow, Anya Lindström Battle, Samantha Peel, Zahida Ahmad, Jayati Basak, Manasa Surakala, Aurelie Bornot, Julia Lindgren, Maria Ryaboshapkina and 7 more

Open access · goldAbstract read
In one paragraph

Article in Communications biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
4.8field-weighted citation impact, top 4% 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

28 citing papers in PubMed, 44 citations in OpenAlex.

  1. Article
  2. Review
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  6. Review
  7. Bridging the Gap Between Static Histology and Dynamic Organ-on-a-Chip Models.Pathophysiology : the official journal of the International Society for Pathophysiology · 2026
    Review
  8. Article
  9. Article
  10. Review
  11. In vitro liver models for toxicological research.Drug metabolism and pharmacokinetics · 2025
    Review
  12. Review
  13. Article
  14. Article
  15. Article
  16. Review
  17. Review
  18. Article
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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

17 authors at 4 institutions in 3 countries.

Tomasz KostrzewskiCN Bio Innovations Ltd, Cambridge, UK. tomasz.kostrzewski@cn-bio.com.ORCID http://orcid.org/0000-0001-6309-628X
Sophie SnowCN Bio Innovations Ltd, Cambridge, UK.
Anya Lindström BattleCN Bio Innovations Ltd, Cambridge, UK.ORCID http://orcid.org/0000-0001-6356-4688
Samantha PeelDiscovery Biology, Discovery Sciences, R&D, AstraZeneca, Cambridge, UK.
Zahida AhmadTranslational Biomarkers and Bioanalysis, Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK.
Jayati BasakTranslational Biomarkers and Bioanalysis, Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK.
Manasa SurakalaR&D IT, AstraZeneca, Chennai, India.ORCID http://orcid.org/0000-0002-6158-3460
Aurelie BornotQuantitative Biology and Data Science, Discovery Sciences, R&D, AstraZeneca, Cambridge, UK.
Julia LindgrenTranslational Genomics, Discovery Biology, Discovery Sciences, R&D, AstraZeneca, Gothenburg, Sweden.ORCID http://orcid.org/0000-0002-3566-2069
Maria RyaboshapkinaTranslational Science and Experimental Medicine, Research and Early Development Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden.ORCID http://orcid.org/0000-0003-1385-8869
Maryam ClausenTranslational Genomics, Discovery Biology, Discovery Sciences, R&D, AstraZeneca, Gothenburg, Sweden.
Daniel LindénBioscience Metabolism, Research and Early Development Cardiovascular, Renal and Metabolism (CVRM), BioPharmaceuticals R&D, AstraZeneca, Gothenburg, Sweden.
Christian MaassCertara, Quantitative Systems Pharmacology Unit, Sheffield, UK.
Lucy May YoungCN Bio Innovations Ltd, Cambridge, UK.
Adam CorriganQuantitative Biology and Data Science, Discovery Sciences, R&D, AstraZeneca, Cambridge, UK.
Lorna EwartTranslational Biomarkers and Bioanalysis, Clinical Pharmacology and Safety Sciences, BioPharmaceuticals R&D, AstraZeneca, Cambridge, UK.ORCID http://orcid.org/0000-0002-8258-7460
David HughesCN Bio Innovations Ltd, Cambridge, UK.
AstraZeneca (United Kingdom) · GBCN Bio Innovations (United Kingdom) · GBAstraZeneca (Sweden) · SEAstraZeneca (India) · IN

Funding

Innovate UK Ref: 103598
6 · The paper itself

Abstract

Non-alcoholic steatohepatitis (NASH) is a common form of chronic liver disease characterised by lipid accumulation, infiltration of immune cells, hepatocellular ballooning, collagen deposition and liver fibrosis. There is a high unmet need to develop treatments for NASH. We have investigated how liver fibrosis and features of advanced clinical disease can be modelled using an in vitro microphysiological system (MPS). The NASH MPS model comprises a co-culture of primary human liver cells, which were cultured in a variety of conditions including+/- excess sugar, fat, exogenous TGFβ or LPS. The transcriptomic, inflammatory and fibrotic phenotype of the model was characterised and compared using a system biology approach to identify conditions that mimic more advanced clinical disease. The transcriptomic profile of the model was shown to closely correlate with the profile of patient samples and the model displayed a quantifiable fibrotic phenotype. The effects of Obeticholic acid and Elafibranor, were evaluated in the model, as wells as the effects of dietary intervention, with all able to significantly reduce inflammatory and fibrosis markers. Overall, we demonstrate how the MPS NASH model can be used to model different aspects of clinical NASH but importantly demonstrate its ability to model advanced disease with a quantifiable fibrosis phenotype.

Indexed as

AnimalsDisease Models, AnimalHumansLiver CirrhosisMiceNon-alcoholic Fatty Liver Disease

Identifiers

PMID34526653
PMCPMC8443589
OpenAlexW3199014335

What Socratic 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 Socratic graph.