Evidence map›Paper›PMID 29806481›Full record

ArticleCell transplantation2018

Combining Induced Pluripotent Stem Cells and Genome Editing Technologies for Clinical Applications.

Chia-Yu Chang, Hsiao-Chien Ting, Hong-Lin Su, Jing-Ren Jeng

Abstract read
In one paragraph

Article in Cell transplantation, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.

0numbers the graph read from it
0cells of the map it votes in
16citing 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

16 citing papers in PubMed.

  1. Review
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  11. Review
  12. Pluripotent Cell Models for Gonadal Research.International journal of molecular sciences · 2019
    Review
  13. Article
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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

4 authors.

Chia-Yu Chang1 Bio-innovation Center, Tzu Chi Foundation, Hualien, Taiwan.
Hsiao-Chien Ting1 Bio-innovation Center, Tzu Chi Foundation, Hualien, Taiwan.
Hong-Lin Su3 Department of Life Sciences, Agricultural Biotechnology Center, National Chung Hsing University, Taichung, Taiwan.
Jing-Ren Jeng4 Division of Cardiology, Department of Internal Medicine, Buddhist Tzu Chi General Hospital, Tzu Chi University, Hualien, Taiwan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this review, we introduce current developments in induced pluripotent stem cells (iPSCs), site-specific nuclease (SSN)-mediated genome editing tools, and the combined application of these two novel technologies in biomedical research and therapeutic trials. The sustainable pluripotent property of iPSCs in vitro not only provides unlimited cell sources for basic research but also benefits precision medicines for human diseases. In addition, rapidly evolving SSN tools efficiently tailor genetic manipulations for exploring gene functions and can be utilized to correct genetic defects of congenital diseases in the near future. Combining iPSC and SSN technologies will create new reliable human disease models with isogenic backgrounds in vitro and provide new solutions for cell replacement and precise therapies.

Indexed as

Gene EditingClustered Regularly Interspaced Short Palindromic RepeatsCRISPR-Associated Protein 9DNA NucleotidyltransferasesHumansInduced Pluripotent Stem CellsPrecision MedicineTranscription Activator-Like Effector NucleasesZinc Finger NucleasesCRISPR-Associated Protein 9DNA NucleotidyltransferasesSite-specific recombinaseTranscription Activator-Like Effector NucleasesZinc Finger Nucleasesclustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated system 9 (Cas9)induced pluripotent stem cells (iPSCs)site-specific nucleases (SSNs)transcription activator-like effector nucleases (TALENs)zinc-finger nucleases (ZFNs)

Identifiers

PMID29806481
PMCPMC6038034

What OpenQuestion holds

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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.