Evidence mapPaperPMID 39322221Full record

SynthesisJournal of gastroenterology and hepatology2025

Rodent model of metabolic dysfunction-associated fatty liver disease: a systematic review.

Xiao-Shan Cui, Hong-Zheng Li, Liang Li, Cheng-Zhi Xie, Jia-Ming Gao, Yuan-Yuan Chen, Hui-Yu Zhang, Wei Hao, Jian-Hua Fu, Hao Guo

Abstract readSystematic Review
In one paragraph

Synthesis in Journal of gastroenterology and hepatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed, 1 pooled it
field-weighted citation impact
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

17 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
  3. Mechanisms and therapeutic insights into MASH-associated fibrosis.Trends in endocrinology and metabolism: TEM · 2026
    Review
  4. Article
  5. Review
  6. Article
  7. Article
  8. Review
  9. Capsinoids treatment reduces steatosis with consequent attenuation in the progression of metabolic dysfunction-associated steatotic liver disease in obese rats.Brazilian journal of medical and biological research = Revista brasileira de pesquisas medicas e biologicas · 2026
    Article
  10. Article
  11. Review
  12. Article
  13. Review
  14. Article
  15. Review
  16. Article
  17. Article
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

10 authors.

Xiao-Shan CuiInstitute of Basic Medical Sciences, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China.ORCID https://orcid.org/0009-0009-1347-5009
Hong-Zheng LiGuang'an men Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Liang LiInstitute of Basic Medical Sciences, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Cheng-Zhi XieInstitute of Basic Medical Sciences, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Jia-Ming GaoInstitute of Basic Medical Sciences, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Yuan-Yuan ChenInstitute of Basic Medical Sciences, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Hui-Yu ZhangInstitute of Basic Medical Sciences, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Wei HaoInstitute of Basic Medical Sciences, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Jian-Hua FuInstitute of Basic Medical Sciences, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China.
Hao GuoSafety Laboratory, Xiyuan Hospital, China Academy of Chinese Medical Sciences, Beijing, China.

Funding

Capacity Enhancement Project of Xiyuan Hospital, Chinese Academy of Traditional Chinese Medicine XYZX0304-02China Academy of Traditional Chinese Medicine Science and Technology Innovation Engineering Project CI2021A04602National Natural Science Foundation General Project 82074060
6 · The paper itself

Abstract

Although significant progress has been made in developing preclinical models for metabolic dysfunction-associated steatotic liver disease (MASLD), few have encapsulated the essential biological and clinical outcome elements reflective of the human condition. We conducted a comprehensive literature review of English-language original research articles published from 1990 to 2023, sourced from PubMed, Embase, and Web of Science, aiming to collate studies that provided a comparative analysis of physiological, metabolic, and hepatic histological characteristics between MASLD models and control groups. The establishment of a robust metabolic dysfunction-associated steatotic liver rodent model hinges on various factors, including animal species and strains, sex, induction agents and methodologies, and the duration of induction. Through this review, we aim to guide researchers in selecting suitable induction methods and animal species for constructing preclinical models aligned with their specific research objectives and laboratory conditions. Future studies should strive to develop simple, reliable, and reproducible models, considering the model's sensitivity to factors such as light-dark cycles, housing conditions, and environmental temperature. Additionally, the potential of diverse in vitro models, including 3D models and liver organ technology, warrants further exploration as valuable tools for unraveling the cellular mechanisms underlying fatty liver disease.

Indexed as

Disease Models, AnimalFatty LiverMetabolic DiseasesNon-alcoholic Fatty Liver DiseaseAnimalsHumansLiverMiceRatsanimal modelinduction typein vitroin vivometabolic dysfunction‐associated fatty liver diseaserodent

Identifiers

PMID39322221
PMCPMC11771679

What Socratic holds

Textmetadata
LicenceCC BY-NC
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.