ReviewFrontiers in neurology2018
Review in Frontiers in neurology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 33 papers.
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.
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.
Who cites it
33 citing papers in PubMed, 46 citations in OpenAlex.
- Article
- CELF family of RNA-binding proteins: roles in disease biology and potential for therapeutic intervention.Cell communication and signaling : CCS · 2026Review
- Enhanced muscle uptake of chemically optimized miR-23b antisense oligonucleotides as lead compounds for myotonic dystrophy type 1.American journal of human genetics · 2026Article
- In Vivo Evaluation of CTG Repeat-Affected Muscle Pathology in a Myotonic Dystrophy Model Mouse Using Electromyography and Fluorescence In Situ Hybridization.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Cardiac Involvement in Myotonic Dystrophy Type 1: Mechanisms, Clinical Perspectives, and Emerging Therapeutic Strategies.International journal of molecular sciences · 2025Review
- Myotonic dystrophy type 1: clinical diversity, molecular insights and therapeutic perspectives.Nature reviews. Neurology · 2025Review
- Altered reversal and extinction learning in the DMSXL mouse model of type I myotonic dystrophy (DM1): An exploratory study.Journal of neuromuscular diseases · 2025Article
- Generation of a Mouse Model of Fuchs Endothelial Corneal Dystrophy by Knock-in of CTG Trinucleotide Repeat Expansion in the TCF4 Gene.Investigative ophthalmology & visual science · 2025Article
- Autism-related traits in myotonic dystrophy type 1 model mice are due to MBNL sequestration and RNA mis-splicing of autism-risk genes.Nature neuroscience · 2025Article
- Heterozygous Tcf4 Deficiency Mitigates Fuchs Endothelial Corneal Dystrophy Progression in a Mouse Model.Investigative ophthalmology & visual science · 2025Article
- Natural Antioxidants Reduce Oxidative Stress and the Toxic Effects of RNA-CUGAntioxidants (Basel, Switzerland) · 2025Article
- Muscle-specific gene editing improves molecular and phenotypic defects in a mouse model of myotonic dystrophy type 1.Clinical and translational medicine · 2025Article
- Nascent transcript O-MAP reveals the molecular architecture of a single-locus subnuclear compartment built by RBM20 and thebioRxiv : the preprint server for biology · 2024Article
- Challenges and Considerations of Preclinical Development for iPSC-Based Myogenic Cell Therapy.Cells · 2024Review
- Studying the Effect of MBNL1 and MBNL2 Loss in Skeletal Muscle Regeneration.International journal of molecular sciences · 2024Article
- Peptide-conjugated antimiRs improve myotonic dystrophy type 1 phenotypes by promoting endogenous MBNL1 expression.Molecular therapy. Nucleic acids · 2023Article
- The Muscleblind-like protein MBL-1 regulates microRNA expression in Caenorhabditis elegans through an evolutionarily conserved autoregulatory mechanism.PLoS genetics · 2023Article
- Pluripotent Stem Cells in Disease Modeling and Drug Discovery for Myotonic Dystrophy Type 1.Cells · 2023Review
- Myotonic dystrophy RNA toxicity alters morphology, adhesion and migration of mouse and human astrocytes.Nature communications · 2022Article
- Hereditary Basis of Coat Color and Excellent Feed Conversion Rate of Red Angus Cattle by Next-Generation Sequencing Data.Animals : an open access journal from MDPI · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Intensive effort has been directed toward the modeling of myotonic dystrophy (DM) in mice, in order to reproduce human disease and to provide useful tools to investigate molecular and cellular pathogenesis and test efficient therapies. Mouse models have contributed to dissect the multifaceted impact of the DM mutation in various tissues, cell types and in a pleiotropy of pathways, through the expression of toxic RNA transcripts. Changes in alternative splicing, transcription, translation, intracellular RNA localization, polyadenylation, miRNA metabolism and phosphorylation of disease intermediates have been described in different tissues. Some of these events have been directly associated with specific disease symptoms in the skeletal muscle and heart of mice, offering the molecular explanation for individual disease phenotypes. In the central nervous system (CNS), however, the situation is more complex. We still do not know how the molecular abnormalities described translate into CNS dysfunction, nor do we know if the correction of individual molecular events will provide significant therapeutic benefits. The variability in model design and phenotypes described so far requires a thorough and critical analysis. In this review we discuss the recent contributions of mouse models to the understanding of neuromuscular aspects of disease, therapy development, and we provide a reflective assessment of our current limitations and pressing questions that remain unanswered.
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What OpenQuestion holds
Registered trials
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.