Evidence map›Paper›PMID 36880210›Full record

ReviewClinical and molecular hepatology2023

A decade of liver organoids: Advances in disease modeling.

Yue Liu, Jian-Ying Sheng, Chun-Fang Yang, Junjun Ding, Yun-Shen Chan

Abstract readReview
In one paragraph

Review in Clinical and molecular hepatology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
–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

18 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Review
  8. Review
  9. Article
  10. Review
  11. Review
  12. "ArmedFrontiers in cell and developmental biology · 2025
    Review
  13. Review
  14. Review
  15. Article
  16. Generation ofRegenerative therapy · 2024
    Review
  17. Article
  18. 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

5 authors.

Yue LiuGuangzhou Laboratory, No. 9 XingDaoHuanBei Road, Guangzhou International Bio Island, Guangzhou, Guangdong, China.
Jian-Ying ShengGuangzhou Laboratory, No. 9 XingDaoHuanBei Road, Guangzhou International Bio Island, Guangzhou, Guangdong, China.
Chun-Fang YangGuangzhou Laboratory, No. 9 XingDaoHuanBei Road, Guangzhou International Bio Island, Guangzhou, Guangdong, China.
Junjun DingZhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, Guangdong, China.
Yun-Shen ChanGuangzhou Laboratory, No. 9 XingDaoHuanBei Road, Guangzhou International Bio Island, Guangzhou, Guangdong, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Liver organoids are three-dimensional cellular tissue models in which cells interact to form unique structures in culture. During the past 10 years, liver organoids with various cellular compositions, structural features, and functional properties have been described. Methods to create these advanced human cell models range from simple tissue culture techniques to complex bioengineering approaches. Liver organoid culture platforms have been used in various research fields, from modeling liver diseases to regenerative therapy. This review discusses how liver organoids are used to model disease, including hereditary liver diseases, primary liver cancer, viral hepatitis, and nonalcoholic fatty liver disease. Specifically, we focus on studies that used either of two widely adopted approaches: differentiation from pluripotent stem cells or epithelial organoids cultured from patient tissues. These approaches have enabled the generation of advanced human liver models and, more importantly, the establishment of patient-tailored models for evaluating disease phenotypes and therapeutic responses at the individual level.

Indexed as

Liver DiseasesOrganoidsCell DifferentiationHumansLiver diseasesOrganoidsPluripotent stem cellsStem cells

Identifiers

PMID36880210
PMCPMC10366802

What OpenQuestion holds

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Registered trials

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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.