Author
John C. W. Hildyard
Royal Veterinary CollegeORCID 0000-0003-2283-2118Unclaimed ORCID profile · follow to get notified of new preprints
Biology Disciplines
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2020-2026 · peak 2/yrCo-Author Collaboration Network
10 top collaborators · 26 mutual co-author links6 papers
Recent·Most cited
- Cell BiologySkeletal MusclePeer-reviewed
Spatiotemporal analysis of dystrophin expression during muscle repair
John C. W. Hildyard, Liberty E. Roskrow, Dominic J. Wells, Richard J. Piercy
This study investigates dystrophin mRNA and protein expression dynamics during muscle repair, revealing post-transcriptional control mechanisms and suggesting degradation as a therapeutic target.
4 citations - Cell BiologybioRxivPreprint
Myonuclear domain-associated and central nucleation-dependent spatial restriction of dystrophin protein expression in a novel DMD mouse model
Katarzyna Chwalenia, Vivi-Yun Feng, Nicole Hemmer…·Thomas C. Roberts
This paper introduces a novel DMD mouse model with non-uniform dystrophin expression and shows that partial dystrophin expression protects against muscle pathology.
1 citation - Molecular BiologyPLoS ONEPeer-reviewed
Evaluation of suitable reference genes for qPCR normalisation of gene expression in a Achilles tendon injury model.
Neil Marr, Richard Meeson, Richard J. Piercy…·Chavaunne T. Thorpe
The paper evaluates reference genes for qPCR normalization in a rat tendon injury model, identifying stable genes and highlighting unstable ones.
2 citations - Molecular BiologybioRxivPreprint
Rapid histological quantification of muscle fibrosis and lysosomal activity using the HSB colour space
John C. W. Hildyard, Emma M.A. Foster, Dominic J. Wells, Richard J. Piercy
The paper develops a method using the HSB color space to rapidly quantify muscle fibrosis and lysosomal activity in histological images, validated across animal models.
- Molecular BiologybioRxivPreprint
Identification of qPCR reference genes suitable for normalising gene expression in the developing mouse embryo
John C. W. Hildyard, Dominic J. Wells, Richard J. Piercy
The paper identifies suitable reference genes for normalizing qPCR data in developing mouse embryos using multiple algorithms and shows that AP3D1, RPL13A, and PAK1IP1 are consistently reliable.
1 citation