Evidence map›Paper›PMID 22484851›Full record

ArticleNature methods2012

Small molecules enable highly efficient neuronal conversion of human fibroblasts.

Julia Ladewig, Jerome Mertens, Jaideep Kesavan, Jonas Doerr, Daniel Poppe, Finnja Glaue, Stefan Herms, Peter Wernet, Gesine Kögler, Franz-Josef Müller and 2 more

Open access · greenAbstract read
PubMed Publisher
In one paragraph

Article in Nature methods, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 192 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
192citing papers in PubMed, 1 pooled it
14.0field-weighted citation impact, top 1% 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

192 citing papers in PubMed, 1 synthesis or guideline pooled it, 318 citations in OpenAlex.

  1. Pooled it
  2. Article
  3. Review
  4. Article
  5. Review
  6. Review
  7. Article
  8. Nanotherapy for Neural Retinal Regeneration.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Review
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  15. Next-generation direct reprogramming.Frontiers in cell and developmental biology · 2024
    Review
  16. Review
  17. Review
  18. Article
  19. Article
  20. Article

132 more citing papers are in PubMed but not listed here.

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

12 authors at 6 institutions in 1 country.

Julia LadewigInstitute of Reconstructive Neurobiology, LIFE & BRAIN Center, University of Bonn, Germany.
Jerome Mertens
Jaideep Kesavan
Jonas Doerr
Daniel Poppe
Finnja Glaue
Stefan Herms
Peter Wernet
Gesine Kögler
Franz-Josef Müller
Philipp Koch
Oliver Brüstle
Life & Brain (Germany) · DEUniversity of Bonn · DEHertie Foundation · DEDüsseldorf University Hospital · DEHeinrich Heine University Düsseldorf · DEUniversity Hospital Schleswig-Holstein · DE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Forced expression of proneural transcription factors has been shown to direct neuronal conversion of fibroblasts. Because neurons are postmitotic, conversion efficiencies are an important parameter for this process. We present a minimalist approach combining two-factor neuronal programming with small molecule-based inhibition of glycogen synthase kinase-3β and SMAD signaling, which converts postnatal human fibroblasts into functional neuron-like cells with yields up to >200% and neuronal purities up to >80%.

Indexed as

Cell TransdifferentiationChild, PreschoolFibroblastsGlycogen Synthase Kinase 3Glycogen Synthase Kinase 3 betaHumansInfantInfant, NewbornNeuronsSignal TransductionSmad ProteinsTranscription FactorsGlycogen Synthase Kinase 3Glycogen Synthase Kinase 3 betaGSK3B protein, humanSmad ProteinsTranscription Factors

Identifiers

PMID22484851
OpenAlexW2045997356

What OpenQuestion holds

Textmetadata
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.