iPSC-Derived Hepatocytes as a Platform for Disease Modeling and Drug Discovery
Frontiers in Medicine, ISSN: 2296-858X, Vol: 6, Page: 265
2019
- 101Citations
- 267Captures
Metric Options: CountsSelecting the 1-year or 3-year option will change the metrics count to percentiles, illustrating how an article or review compares to other articles or reviews within the selected time period in the same journal. Selecting the 1-year option compares the metrics against other articles/reviews that were also published in the same calendar year. Selecting the 3-year option compares the metrics against other articles/reviews that were also published in the same calendar year plus the two years prior.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Metrics Details
- Citations101
- Citation Indexes101
- 101
- Captures267
- Readers267
- 267
Review Description
The liver is one of the largest organs in the body and is responsible for a diverse repertoire of metabolic processes. Such processes include the secretion of serum proteins, carbohydrate and lipid metabolism, bile acid and urea synthesis, detoxification of drugs and metabolic waste products, and vitamin and carbohydrate storage. Currently, liver disease is one of the most prevalent causes of mortality in the USA with congenital liver defects contributing to a significant proportion of these deaths. Historically the study of liver disease has been hampered by a shortage of organ donors, the subsequent scarcity of healthy tissue, and the failure of animal models to fully recapitulate human liver function. In vitro culture of hepatocytes has also proven difficult because primary hepatocytes rapidly de-differentiate in culture. Recent advances in stem cell technology have facilitated the generation of induced pluripotent stem cells (iPSCs) from various somatic cell types from patients. Such cells can be differentiated to a liver cell fate, essentially providing a limitless supply of cells with hepatocyte characteristics that can mimic the pathophysiology of liver disease. Furthermore, development of the CRISPR-Cas9 system, as well as advancement of miniaturized differentiation platforms has facilitated the development of high throughput models for the investigation of hepatocyte differentiation and drug discovery. In this review, we will explore the latest advances in iPSC-based disease modeling and drug screening platforms and examine how this technology is being used to identify new pharmacological interventions, and to advance our understanding of liver development and mechanisms of disease. We will cover how iPSC technology is being used to develop predictive models for rare diseases and how information gained from large in vitro screening experiments can be used to directly inform clinical investigation.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85075988779&origin=inward; http://dx.doi.org/10.3389/fmed.2019.00265; http://www.ncbi.nlm.nih.gov/pubmed/31803747; https://www.frontiersin.org/article/10.3389/fmed.2019.00265/full; https://dx.doi.org/10.3389/fmed.2019.00265; https://www.frontiersin.org/journals/medicine/articles/10.3389/fmed.2019.00265/full
Frontiers Media SA
Provide Feedback
Have ideas for a new metric? Would you like to see something else here?Let us know