John Day

Deep learning models detect neuromuscular disease and quantify functional impairment from video-derived biomechanics data

This paper develops deep learning models to detect neuromuscular diseases and quantify movement impairment using video-derived biomechanics data from smartphone recordings.

KIF5A downregulation in spinal muscular atrophy links axonal regeneration defects with ALS

This study shows that SMN deficiency reduces KIF5A in SMA, impairing axon regeneration, and links SMA and ALS through KIF5A stabilization by SMN.

Video-based biomechanical analysis captures disease-specific movement signatures of different neuromuscular diseases

Smartphone-video biomechanics (OpenCap) reproduced four timed function tests (r > 0.98) and separated facioscapulohumeral from myotonic dystrophy better than test times (balanced accuracy 82% vs 50%; 129 participants).

Transcriptome Alterations in Myotonic Dystrophy Frontal Cortex

The paper analyzes RNA-seq transcriptomes from frontal cortex tissue of DM1 and DM2 patients to identify splicing changes and their implications for CNS dysfunction.