Evidence map›Paper›PMID 26771648›Full record

ReviewJournal of clinical medicine2016

Emerging Transcriptional Mechanisms in the Regulation of Epithelial to Mesenchymal Transition and Cellular Plasticity in the Kidney.

Letizia De Chiara, John Crean

Abstract readReview
In one paragraph

Review in Journal of clinical medicine, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

12 citing papers in PubMed.

  1. Article
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  3. Article
  4. Review
  5. Review
  6. Article
  7. Article
  8. Article
  9. Review
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  11. Review
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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

2 authors.

Letizia De ChiaraDiabetes Complications Research Centre, UCD School of Biomolecular and Biomedical Science, University College Dublin, Belfield, Dublin 4, Ireland. letizia.dechiara@ucd.ie.
John CreanDiabetes Complications Research Centre, UCD School of Biomolecular and Biomedical Science, University College Dublin, Belfield, Dublin 4, Ireland. john.crean@ucd.ie.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Notwithstanding controversies over the role of epithelial to mesenchymal transition in the pathogenesis of renal disease, the last decade has witnessed a revolution in our understanding of the regulation of renal cell plasticity. Significant parallels undoubtedly exist between ontogenic processes and the initiation and propagation of damage in the diseased kidney as evidenced by the reactivation of developmental programmes of gene expression, in particular with respect to TGFβ superfamily signaling. Indeed, multiple signaling pathways converge on a complex transcriptional regulatory nexus that additionally involves epigenetic activator and repressor mechanisms and microRNA regulatory networks that control renal cell plasticity. It is becoming increasingly apparent that differentiated cells can acquire an undifferentiated state akin to "stemness" which is leading us towards new models of complex cell behaviors and interactions. Here we discuss the latest findings that delineate new and novel interactions between this transcriptional regulatory network and highlight a hitherto poorly recognized role for the Polycomb Repressive Complex (PRC2) in the regulation of renal cell plasticity. A comprehensive understanding of how external stimuli interact with the epigenetic control of gene expression, in normal and diseased contexts, establishes a new therapeutic paradigm to promote the resolution of renal injury and regression of fibrosis.

Indexed as

EMTKidneyplasticityPRC2SMAD3SNAI1TGFβ signaling

Identifiers

PMID26771648
PMCPMC4730131

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.