Publications by authors named "A Jacquier"
Exercise preserves neuromuscular function in aging through unknown mechanisms. Skeletal muscle fibroblasts (FIB) and stem cells (MuSC) are abundant in skeletal muscle and reside close to neuromuscular junctions, but their relative roles in motor neuron maintenance remain undescribed. Using direct cocultures of embryonic rat motor neurons with either human MuSC or FIB, RNA sequencing revealed profound differential regulation of the motor neuron transcriptome, with FIB generally favoring neuron growth and cell migration and MuSC favoring production of ribosomes and translational machinery.
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- The study assessed the link between inherited mitochondrial dysfunction and neuromuscular junction (NMJ) remodeling in patients with mitochondrial disorders, analyzing muscle biopsies from 15 patients and 10 controls.
- Results showed that patients with mitochondrial disorders had significantly more remodeled and neoformed NMJ endplates, with a trend towards increased Schwann cell extensions, indicating NMJ alterations even without muscle weakness.
- The findings suggest that mitochondrial disorders may lead to NMJ remodeling as a primary issue, separate from structural muscle damage, though the exact mechanisms and clinical indicators warrant further investigation.
Fully automated epicardial adipose tissue volume quantification with deep learning and relationship with CAC score and micro/macrovascular complications in people living with type 2 diabetes: the multicenter EPIDIAB study.
Cardiovasc Diabetol
September 2024
Background: The aim of this study (EPIDIAB) was to assess the relationship between epicardial adipose tissue (EAT) and the micro and macrovascular complications (MVC) of type 2 diabetes (T2D).
Methods: EPIDIAB is a post hoc analysis from the AngioSafe T2D study, which is a multicentric study aimed at determining the safety of antihyperglycemic drugs on retina and including patients with T2D screened for diabetic retinopathy (DR) (n = 7200) and deeply phenotyped for MVC. Patients included who had undergone cardiac CT for CAC (Coronary Artery Calcium) scoring after inclusion (n = 1253) were tested with a validated deep learning segmentation pipeline for EAT volume quantification.