Evidence map›Paper›PMID 34581756›Full record

ReviewBiochemical Society transactions2021

The role of long non-coding RNAs in the regulation of pancreatic beta cell identity.

Maya E Wilson, Timothy J Pullen

Open access · hybridAbstract readReview
In one paragraph

Review in Biochemical Society transactions, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.3field-weighted citation impact, top 52% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Review
  2. Article
  3. Review
  4. Article
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 1 institution in 1 country.

Maya E WilsonDepartment of Diabetes, School of Life Course Sciences, King's College London, London, U.K.
Timothy J PullenDepartment of Diabetes, School of Life Course Sciences, King's College London, London, U.K.ORCID 0000-0002-6853-5701
King's College London · GB

Funding

Diabetes UK 19/0006062
6 · The paper itself

Abstract

Type 2 diabetes (T2D) is a widespread disease affecting millions in every continental population. Pancreatic β-cells are central to the regulation of circulating glucose, but failure in the maintenance of their mass and/or functional identity leads to T2D. Long non-coding RNAs (lncRNAs) represent a relatively understudied class of transcripts which growing evidence implicates in diabetes pathogenesis. T2D-associated single nucleotide polymorphisms (SNPs) have been identified in lncRNA loci, although these appear to function primarily through regulating β-cell proliferation. In the last decade, over 1100 lncRNAs have been catalogued in islets and the roles of a few have been further investigated, definitively linking them to β-cell function. These studies show that lncRNAs can be developmentally regulated and show highly tissue-specific expression. lncRNAs regulate neighbouring β-cell-specific transcription factor expression, with knockdown or overexpression of lncRNAs impacting a network of other key genes and pathways. Finally, gene expression analysis in studies of diabetic models have uncovered a number of lncRNAs with roles in β-cell function. A deeper understanding of these lncRNA roles in maintaining β-cell identity, and its deterioration, is required to fully appreciate the β-cell molecular network and to advance novel diabetes treatments.

Indexed as

Diabetes Mellitus, Type 2Gene Expression ProfilingHumansInsulin-Secreting CellsRNA, Long NoncodingTranscription FactorsRNA, Long NoncodingTranscription Factorscell identityinsulinisletlong non-coding RNA (lncRNA)pancreatic beta cell

Identifiers

PMID34581756
PMCPMC8589412
OpenAlexW3203541144

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.