Evidence map›Paper›PMID 23852582›Full record

ReviewJournal of cardiovascular translational research2013

RNA-based tools for nuclear reprogramming and lineage-conversion: towards clinical applications.

Juan A Bernal

Abstract readReview
In one paragraph

Review in Journal of cardiovascular translational research, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers.

0numbers the graph read from it
0cells of the map it votes in
30citing 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

30 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Article
  6. Review
  7. Article
  8. Matrices Activated with Messenger RNA.Journal of functional biomaterials · 2023
    Review
  9. Review
  10. Review
  11. Article
  12. Lipid nanoparticles for delivery of messenger RNA to the back of the eye.Journal of controlled release : official journal of the Controlled Release Society · 2019
    Article
  13. Article
  14. Hepatocyte Transplantation: Quo Vadis?International journal of radiation oncology, biology, physics · 2019
    Review
  15. Review
  16. Article
  17. Article
  18. Review
  19. Article
  20. Review
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

1 author.

Juan A BernalCardiovascular Development and Repair Department, Centro Nacional de Investigaciones Cardiovasculares (CNIC), Melchor Fernández Almagro 3, 28029, Madrid, Spain, jabernal@cnic.es.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The therapeutic potential of induced pluripotent stem cells (iPSCs) is well established. Safety concerns remain, however, and these have driven considerable efforts aimed at avoiding host genome alteration during the reprogramming process. At present, the tools used to generate human iPSCs include (1) DNA-based integrative and non-integrative methods and (2) DNA-free reprogramming technologies, including RNA-based approaches. Because of their combined efficiency and safety characteristics, RNA-based methods have emerged as the most promising tool for future iPSC-based regenerative medicine applications. Here, I will discuss novel recent advances in reprogramming technology, especially those utilizing the Sendai virus (SeV) and synthetic modified mRNA. In the future, these technologies may find utility in iPSC reprogramming for cellular lineage-conversion, and its subsequent use in cell-based therapies.

Indexed as

Gene Transfer TechniquesAnimalsCell DifferentiationCell LineageCellular ReprogrammingEpigenesis, GeneticGene Expression Regulation, DevelopmentalGenetic VectorsHumansInduced Pluripotent Stem CellsMicroRNAsRNARNA, MessengerSendai virusTranscription FactorsMicroRNAsRNARNA, MessengerTranscription Factors

Identifiers

PMID23852582
PMCPMC3838600

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.