Evidence map›Paper›PMID 39718233›Full record

ArticleAdvanced healthcare materials2025

In Vivo-Like Scaffold-Free 3D In Vitro Models of Muscular Dystrophies: The Case for Anchored Cell Sheet Engineering in Personalized Medicine.

Alireza Shahin-Shamsabadi, John Cappuccitti

Abstract read
In one paragraph

Article in Advanced healthcare materials, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
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

6 citing papers in PubMed.

  1. Review
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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.

Alireza Shahin-ShamsabadiEvolved.Bio, 280 Joseph Street, Kitchener, Ontario, N2G4Z5, Canada.ORCID 0000-0002-8145-2556
John CappuccittiEvolved.Bio, 280 Joseph Street, Kitchener, Ontario, N2G4Z5, Canada.ORCID 0009-0005-7893-1264

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Progress in understanding the underlying mechanisms of muscular dystrophies is hindered by the lack of pathophysiologically relevant in vitro models. Here, an entirely scaffold-free anchored cell sheet engineering platform is used to create patient-specific three-dimensional (3D) skeletal muscle in vitro models. This approach effectively replicates mature muscle phenotypes and tissue- and disease-specific extracellular matric (ECM). Models were developed using primary cells from healthy individuals and patients with Duchenne Muscular Dystrophy and Myotonic Dystrophy Type 1. Through a combination of quantified histological staining (Hematoxylin & Eosin, Movat's Pentachrome, Masson's Trichrome) and immunostaining (desmin, myosin heavy chain, laminin, and dystrophin), it was demonstrated that the models formed mature constructs closely resembling their respective in vivo conditions. Proteomics analysis revealed that the models exhibited appropriate upregulation and downregulation of disease-relevant pathways. Models of diseased tissues accurately reflected key phenotypic features of the diseases, including alterations in muscle fiber integrity and ECM composition. Upon treatment with therapeutically beneficial drugs, significant changes in their proteomic profiles were documented, highlighting the models' potential for drug screening. This novel in vitro modeling approach, unlike other 3D techniques that rely on exogenous biomaterials that interfere with natural cellular behaviors, provides a promising platform for studying muscular dystrophies.

Indexed as

Muscular DystrophiesPrecision MedicineTissue EngineeringCells, CulturedExtracellular MatrixHumansMuscle, SkeletalMuscular Dystrophy, DuchenneProteomicsTissue Scaffoldscell sheet engineeringdrug treatmentdystrophyin vitro modelproteomicsscaffold‐freeskeletal muscle

Identifiers

PMID39718233
PMCPMC12057609

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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.