Evidence map›Paper›PMID 29686685›Full record

ReviewFrontiers in immunology2018

Posttranscriptional (Re)programming of Cell Fate: Examples in Stem Cells, Progenitor, and Differentiated Cells.

Chrysi Kanellopoulou, Stefan A Muljo

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in immunology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.1field-weighted citation impact, top 53% 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

1 citing paper in PubMed, 3 citations in OpenAlex.

  1. Fibroblast Reprogramming in Cardiac Repair.JACC. Basic to translational science · 2024
    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

2 authors at 2 institutions in 1 country.

Chrysi KanellopoulouLaboratory of Immunology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States.
Stefan A MuljoLaboratory of Immunology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States.
National Institute of Allergy and Infectious Diseases · USNational Institutes of Health · US

Funding

Roles of non-Coding RNAs in Programming Lymphocyte Differentiation and FunctionZIAAI001131 · NIAID · NATIONAL INSTITUTE OF ALLERGY AND INFECTIOUS DISEASES · PI MULJO, STEFAN · 2010 to 2025
$11.0M
6 · The paper itself

Abstract

How a single genome can give rise to many different transcriptomes and thus all the different cell lineages in the human body is a fundamental question in biology. While signaling pathways, transcription factors, and chromatin architecture, to name a few determinants, have been established to play critical roles, recently, there is a growing appreciation of the roles of non-coding RNAs and RNA-binding proteins in controlling cell fates posttranscriptionally. Thus, it is vital that these emerging players are also integrated into models of gene regulatory networks that underlie programs of cellular differentiation. Sometimes, we can leverage knowledge about such posttranscriptional circuits to reprogram patterns of gene expression in meaningful ways. Here, we review three examples from our work.

Indexed as

RNA Processing, Post-TranscriptionalAnimalsCell DifferentiationCellular ReprogrammingChromatinHematopoiesisHumansInduced Pluripotent Stem CellsRNA-Binding ProteinsStem CellsTh17 CellsChromatinLIN28B protein, humanRNA-Binding Proteinsembryonic stem cellfetal hematopoiesisgene regulatory networkhematopoietic stem and progenitor cellsmicroRNAposttranscriptional regulationRNA-binding proteinTh17

Identifiers

PMID29686685
PMCPMC5900001
OpenAlexW2796632256

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.