Evidence map›Paper›PMID 25628647›Full record

ReviewFrontiers in genetics2014

Regulation of IGF -1 signaling by microRNAs.

Hwa Jin Jung, Yousin Suh

Open access · goldAbstract readReview
In one paragraph

Review in Frontiers in genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 67 papers.

0numbers the graph read from it
0cells of the map it votes in
67citing papers in PubMed
5.2field-weighted citation impact, top 4% 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

67 citing papers in PubMed, 116 citations in OpenAlex.

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7 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

2 authors at 1 institution in 1 country.

Hwa Jin JungDepartment of Genetics, Albert Einstein College of Medicine New York, NY, USA.
Yousin SuhDepartment of Genetics, Albert Einstein College of Medicine New York, NY, USA ; Department of Medicine, Albert Einstein College of Medicine New York, NY, USA ; Institute for Aging Research, Diabetes Research and Training Center, Albert Einstein College of Medicine New York, NY, USA.
Albert Einstein College of Medicine · US

Funding

THE IMPACT OF CELLULAR DEFENSE ON THE ROLE OF Ku80 IN GENOME MAINTENANCE AND LONGP01AG017242 · NIA · UNIVERSITY OF TEXAS HLTH SCI CTR SAN ANT · PI VIJG, JAN · 1999 to 2023
$46.1M
(PQB4) Age-cancer interplay of genome and epi-genome in human lungR01CA180126 · NCI · ALBERT EINSTEIN COLLEGE OF MEDICINE, INC · PI AUTON, ADAM, SPIVACK, SIMON D · 2013 to 2016
$2.8M
NCI NIH HHS R01 CA180126NIA NIH HHS P01 AG017242
6 · The paper itself

Abstract

The insulin-like growth factor 1 (IGF-1) signaling pathway regulates critical biological processes including development, homeostasis, and aging. Dysregulation of this pathway has been implicated in a myriad of diseases such as cancers, neurodegenerative diseases, and metabolic disorders, making the IGF-1 signaling pathway a prime target to develop therapeutic and intervention strategies. Recently, small non-coding RNA molecules in ∼22 nucleotide length, microRNAs (miRNAs), have emerged as a new regulator of biological processes in virtually all organ systems and increasing studies are linking altered miRNA function to disease mechanisms. A miRNA binds to 3'UTRs of multiple target genes and coordinately downregulates their expression, thereby exerting a profound influence on gene regulatory networks. Here we review the components of the IGF-1 signaling pathway that are known targets of miRNA regulation, and highlight recent studies that suggest therapeutic potential of these miRNAs against various diseases.

Indexed as

agingaging-related diseaseIGF-1 signalingmicroRNAstherapeutic agents

Identifiers

PMID25628647
PMCPMC4292735
OpenAlexW2051090964

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.