Evidence map›Paper›PMID 32947786›Full record

ArticleJournal of personalized medicine2020

Molecular Diagnosis and Novel Therapies for Neuromuscular Diseases.

Rika Maruyama, Toshifumi Yokota

Open access · goldAbstract readEditorial
In one paragraph

Article in Journal of personalized medicine, 2020. 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
0.3field-weighted citation impact, top 46% 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, 6 citations in OpenAlex.

  1. 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.

Rika MaruyamaDepartment of Medical Genetics, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB T6G 2H7, Canada.ORCID 0000-0002-5656-6930
Toshifumi YokotaDepartment of Medical Genetics, Faculty of Medicine and Dentistry, University of Alberta, Edmonton, AB T6G 2H7, Canada.
University of Alberta · CA

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

With the development of novel targeted therapies, including exon skipping/inclusion and gene replacement therapy, the field of neuromuscular diseases has drastically changed in the last several years. Until 2016, there had been no FDA-approved drugs to treat Duchenne muscular dystrophy (DMD), the most common muscular dystrophy. However, several new personalized therapies, including antisense oligonucleotides eteplirsen for DMD exon 51 skipping and golodirsen and viltolarsen for DMD exon 53 skipping, have been approved in the last 4 years. We are witnessing the start of a therapeutic revolution in neuromuscular diseases. However, the studies also made clear that these therapies are still far from a cure. Personalized genetic medicine for neuromuscular diseases faces several key challenges, including the difficulty of obtaining appropriate cell and animal models and limited its applicability. This Special Issue "Molecular Diagnosis and Novel Therapies for Neuromuscular/Musculoskeletal Diseases" highlights key areas of research progress that improve our understanding and the therapeutic outcomes of neuromuscular diseases in the personalized medicine era.

Indexed as

amyotrophic lateral sclerosis (ALS)CRISPR (clustered regularly interspaced short palindromic repeat)/Cas9 (CRISPR associated protein 9)-mediated genome editingDuchenne/Becker muscular dystrophy (DMD/BMD)eteplirsenexon skippinggolodirsenmultiplex ligation amplification (MLPA)next-generation sequencing (NGS)phosphorodiamidate morpholino oligomers (PMOs)viltolarsen

Identifiers

PMID32947786
PMCPMC7564006
OpenAlexW3086558954

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.