Evidence map›Paper›PMID 34634413›Full record

ReviewExperimental gerontology2021

Parkinson's disease and microRNAs - Lessons from model organisms and human studies.

Brian Evans, Howard A Furlong, Alexandre de Lencastre

Open access · greenAbstract readReview
In one paragraph

Review in Experimental gerontology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.4field-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

3 citing papers in PubMed, 7 citations in OpenAlex.

  1. Review
  2. Article
  3. 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

3 authors at 1 institution in 1 country.

Brian EvansDepartment of Biological Sciences, Quinnipiac University, Hamden, CT 06518, USA.
Howard A FurlongFrank H. Netter MD School of Medicine at Quinnipiac University, North Haven, CT 06473, USA.
Alexandre de LencastreDepartment of Biological Sciences, Quinnipiac University, Hamden, CT 06518, USA. Electronic address: alexandre.delencastre@quinnipiac.edu.
Quinnipiac University · US

Funding

Molecular Mechanisms of miRNA Function in Stress Response and in Models of Diseases of Aging in C. elegansR15AG051132 · NIA · QUINNIPIAC UNIVERSITY · PI DE LENCASTRE, ALEXANDRE · 2015 to 2015
$278k
NIA NIH HHS R15 AG051132
6 · The paper itself

Abstract

Parkinson's disease (PD) is a progressive, age-associated neurodegenerative disorder that affects an estimated 10 million people worldwide. PD is characterized by proteinaceous, cytoplasmic inclusions containing α-synuclein, called Lewy Bodies, which form in dopaminergic neurons in an age-dependent manner, and are associated with the emergence of characteristic PD symptoms such as resting tremor, rigidity, slow movements and postural instability. Although considerable progress has been made in recent years in identifying genetic and environmental factors that are associated with PD, early diagnosis and therapeutic options remain severely lacking. Recently, microRNAs (miRNAs) have emerged as novel therapeutic targets in various diseases, such as cancer and neurodegenerative diseases. MiRNAs have been shown to play roles in various aging and neurodegenerative disease models across phyla. More recently, studies have identified specific roles for miRNAs and their targets in the pathogenesis and progression of PD in several model organisms. Here, we discuss the evolving field of miRNAs, their association with PD, and the outlook for the future.

Indexed as

MicroRNAsNeurodegenerative DiseasesParkinson DiseaseDopaminergic NeuronsHumansMicroRNAsAgingMicroRNAsNeurodegenerationParkinson's disease

Identifiers

PMID34634413
PMCPMC8596463
OpenAlexW3206574934

What OpenQuestion holds

Textmetadata
LicenceTDM
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.