Evidence map›Paper›PMID 30486341›Full record

ReviewNutrients2018

Deciphering the Role of the Non-Coding Genome in Regulating Gene-Diet Interactions.

Pui-Pik Law, Michelle L Holland

Open access · goldAbstract readReview
In one paragraph

Review in Nutrients, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 45% 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

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Environmental Exposures around Conception: Developmental Pathways Leading to Lifetime Disease Risk.International journal of environmental research and public health · 2021
    Review
  2. 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.

Pui-Pik LawDepartment of Medical and Molecular Genetics, School of Basic and Medical Biosciences, King's College London, London SE1 9RT, UK. pui.law@kcl.ac.uk.
Michelle L HollandDepartment of Medical and Molecular Genetics, School of Basic and Medical Biosciences, King's College London, London SE1 9RT, UK. michelle.holland@kcl.ac.uk.ORCID 0000-0003-0775-2902
King's College London · GB

Funding

Academy of Medical Sciences SBF003\1026Royal Society RGS\R2\180202
6 · The paper itself

Abstract

Protein encoding genes constitute a small fraction of mammalian genomes. In addition to the protein coding genes, there are other functional units within the genome that are transcribed, but not translated into protein, the so called non-coding RNAs. There are many types of non-coding RNAs that have been identified and shown to have important roles in regulating gene expression either at the transcriptional or post-transcriptional level. A number of recent studies have highlighted that dietary manipulation in mammals can influence the expression or function of a number of classes of non-coding RNAs that contribute to the protein translation machinery. The identification of protein translation as a common target for nutritional regulation underscores the need to investigate how this may mechanistically contribute to phenotypes and diseases that are modified by nutritional intervention. Finally, we describe the state of the art and the application of emerging '-omics' technologies to address the regulation of protein translation in response to diet.

Indexed as

DietEpigenesis, GeneticGene Expression RegulationGenomeProtein BiosynthesisRNA, UntranslatedAnimalsHumansRNA, Untranslatedepigeneticsepitranscriptomegene-diet interactionnon-coding RNAomicsprotein translationribosomeRNA modifications

Identifiers

PMID30486341
PMCPMC6316136
OpenAlexW2903093165

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.