J. Paul Chapple

This study identifies SOX2+ cells in phaeochromocytomas and paragangliomas as potential tumour-initiating stem cells capable of expansion and metastasis.

This paper develops a network-based atlas of human skeletal muscle aging using transcriptomic data from 1,675 biopsies and multiple single-cell technologies, revealing gene modules and interactions associated with aging and load status.

The paper develops a large-scale blood transcriptomic resource for Alzheimer's disease, identifies sex-specific differences, and models insulin resistance biomarkers using machine learning.

The paper identifies AIP as a regulator that links mTORC1 activation with catabolic metabolism during neonatal development, ensuring metabolic adaptation and survival.

The paper identifies ncRNA genes regulated during skeletal muscle hypertrophy in 144 individuals using transcriptomic analysis and network modelling.

This study shows that biallelic AIP loss causes a severe pediatric disease with proteostasis defects, observed in human and zebrafish models.

The paper uses AlphaFold to predict the structure of sacsin's Hsp90-like domains and identifies key residues for ATPase activity, suggesting sacsin functions as an ATP-driven molecular chaperone.