Evidence map›Paper›PMID 35681550›Full record

ReviewCells2022

Utility of iPSC-Derived Cells for Disease Modeling, Drug Development, and Cell Therapy.

Martin W Nicholson, Chien-Yu Ting, Darien Z H Chan, Yu-Che Cheng, Yi-Chan Lee, Ching-Chuan Hsu, Ching-Ying Huang, Patrick C H Hsieh

Open access · goldAbstract readReview
In one paragraph

Review in Cells, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 36 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
36citing papers in PubMed, 1 pooled it
4.7field-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

36 citing papers in PubMed, 1 synthesis or guideline pooled it, 58 citations in OpenAlex.

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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

8 authors at 1 institution in 1 country.

Martin W NicholsonInstitute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan.
Chien-Yu TingInstitute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan.ORCID 0000-0002-9168-5820
Darien Z H ChanInstitute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan.ORCID 0000-0001-5591-3059
Yu-Che ChengInstitute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan.
Yi-Chan LeeInstitute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan.ORCID 0000-0003-0276-4664
Ching-Chuan HsuInstitute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan.
Ching-Ying HuangInstitute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan.
Patrick C H HsiehInstitute of Biomedical Sciences, Academia Sinica, Taipei 115, Taiwan.ORCID 0000-0002-8910-3596
Institute of Biomedical Sciences, Academia Sinica · TW

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The advent of induced pluripotent stem cells (iPSCs) has advanced our understanding of the molecular mechanisms of human disease, drug discovery, and regenerative medicine. As such, the use of iPSCs in drug development and validation has shown a sharp increase in the past 15 years. Furthermore, many labs have been successful in reproducing many disease phenotypes, often difficult or impossible to capture, in commonly used cell lines or animal models. However, there still remain limitations such as the variability between iPSC lines as well as their maturity. Here, we aim to discuss the strategies in generating iPSC-derived cardiomyocytes and neurons for use in disease modeling, drug development and their use in cell therapy.

Indexed as

Induced Pluripotent Stem CellsPluripotent Stem CellsAnimalsCell- and Tissue-Based TherapyDrug DevelopmentRegenerative Medicinecardiomyocytescell therapyinduced pluripotent stem cellsneurons

Identifiers

PMID35681550
PMCPMC9180434
OpenAlexW4281701292

What OpenQuestion 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 OpenQuestion graph.