Pathomechanisms and biomarkers in facioscapulohumeral muscular dystrophy: roles of DUX4 and PAX7

CRS Banerji, PS Zammit - EMBO molecular medicine, 2021 - embopress.org
Facioscapulohumeral muscular dystrophy (FSHD) is characterised by progressive skeletal
muscle weakness and wasting. FSHD is linked to epigenetic derepression of the …

Update on the molecular aspects and methods underlying the complex architecture of FSHD

V Caputo, D Megalizzi, C Fabrizio, A Termine… - Cells, 2022 - mdpi.com
Despite the knowledge of the main mechanisms involved in facioscapulohumeral muscular
dystrophy (FSHD), the high heterogeneity and variable penetrance of the disease …

[HTML][HTML] Deep learning-based quantification of osteonecrosis using magnetic resonance images in Gaucher disease

B Yu, T Whitmarsh, P Riede, S McDonald, JD Kaggie… - Bone, 2024 - Elsevier
Gaucher disease is one of the most common lysosomal storage disorders. Osteonecrosis is
a principal clinical manifestation of Gaucher disease and often leads to joint collapse and …

Assessing facial weakness in myasthenia gravis with facial recognition software and deep learning

AM Ruiter, Z Wang, Z Yin, WC Naber… - Annals of Clinical …, 2023 - Wiley Online Library
Objective Myasthenia gravis (MG) is an autoimmune disease leading to fatigable muscle
weakness. Extra‐ocular and bulbar muscles are most commonly affected. We aimed to …

Outcome measures in facioscapulohumeral muscular dystrophy clinical trials

M Ghasemi, CP Emerson Jr, LJ Hayward - Cells, 2022 - mdpi.com
Facioscapulohumeral muscular dystrophy (FSHD) is a debilitating muscular dystrophy with a
variable age of onset, severity, and progression. While there is still no cure for this disease …

Application of DCE-MRI radiomics signature analysis in differentiating molecular subtypes of luminal and non-luminal breast cancer

T Huang, B Fan, Y Qiu, R Zhang, X Wang… - Frontiers in …, 2023 - frontiersin.org
Background The goal of this study was to develop and validate a radiomics signature based
on dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) preoperatively …

[HTML][HTML] Artificial intelligence applications in the diagnosis of neuromuscular diseases: a narrative review

MC Piñeros-Fernández - Cureus, 2023 - ncbi.nlm.nih.gov
The accurate diagnosis of neuromuscular diseases (NMD) is in many cases difficult; the
starting point is the clinical approach based on the course of the disease and a careful …

MRI for the diagnosis of limb girdle muscular dystrophies

C Bolano-Díaz, J Verdú-Díaz… - Current Opinion in …, 2024 - journals.lww.com
Muscle MRI continues being a useful tool supporting the diagnosis of patients with LGMD
and other neuromuscular diseases. However, the huge variety of patterns described makes …

Two decades of advances in muscle imaging in children: from pattern recognition of muscle diseases to quantification and machine learning approaches

D Gómez-Andrés, A Oulhissane… - Neuromuscular Disorders, 2021 - Elsevier
Muscle imaging has progressively gained popularity in the neuromuscular field. Together
with detailed clinical examination and muscle biopsy, it has become one of the main tools for …

[HTML][HTML] Differentiation of Early Sacroiliitis Using Machine-Learning-Supported Texture Analysis

Q Zhu, Q Wang, X Hu, X Dang, X Yu, L Chen… - Diagnostics, 2025 - pmc.ncbi.nlm.nih.gov
Objectives: We wished to compare the diagnostic performance of texture analysis (TA)
against that of a visual qualitative assessment in identifying early sacroiliitis (nr-axSpA) …