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| Content Provider | Springer Nature : BioMed Central |
|---|---|
| Author | Jin, Meixian Yi, Xiao Liao, Wei Chen, Qi Yang, Wanren Li, Yang Li, Shao Gao, Yi Peng, Qing Zhou, Shuqin |
| Abstract | Drug-induced liver injury (DILI) is one of the leading causes of clinical trial failures and high drug attrition rates. Currently, the commonly used hepatocyte models include primary human hepatocytes (PHHs), animal models, and hepatic cell lines. However, these models have disadvantages that include species-specific differences or inconvenient cell extraction methods. Therefore, a novel, inexpensive, efficient, and accurate model that can be applied to drug screening is urgently needed. Owing to their self-renewable ability, source abundance, and multipotent competence, stem cells are stable sources of drug hepatotoxicity screening models. Because 3D culture can mimic the in vivo microenvironment more accurately than can 2D culture, the former is commonly used for hepatocyte culture and drug screening. In this review, we introduce the different sources of stem cells used to generate hepatocyte-like cells and the models for hepatotoxicity testing that use stem cell-derived hepatocyte-like cells. |
| Related Links | https://stemcellres.biomedcentral.com/counter/pdf/10.1186/s13287-021-02152-9.pdf |
| Ending Page | 13 |
| Page Count | 13 |
| Starting Page | 1 |
| File Format | HTM / HTML |
| ISSN | 17576512 |
| DOI | 10.1186/s13287-021-02152-9 |
| Journal | Stem Cell Research & Therapy |
| Issue Number | 1 |
| Volume Number | 12 |
| Language | English |
| Publisher | BioMed Central |
| Publisher Date | 2021-01-25 |
| Access Restriction | Open |
| Subject Keyword | Stem Cells Cell Biology Regenerative Medicine Tissue Engineering Biomedical Engineering and Bioengineering Hepatocyte-like cells Drug screening Drug-induced liver injury 3D cell culture Regenerative Medicine/Tissue Engineering |
| Content Type | Text |
| Resource Type | Review |
| Subject | Cell Biology Medicine Biochemistry, Genetics and Molecular Biology Molecular Medicine |
| Journal Impact Factor | 7.1/2023 |
| 5-Year Journal Impact Factor | 7.9/2023 |
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