Larissa Rix Name: Larissa Rix

Supervisory Team: Dr Karina Wright, Professor Ying Yang

Funding source: Part funding from The Orthopaedic Institute Ltd and Versus Arthritis Tissue Engineering Centre

Project resume:
(1) To improve current understanding of the underlying biology of PFPS:
- A range of PFPS patients will be characterised at differing disease stage pathogenesis using knee function assessments, clinical imaging modalities, synovial fluid proteomics, targeted biomarker assessments, and cellular analysis.
(2) To improve and develop new PFPS cell-based therapies:
- To assess the current clinical outcome success of patients who have undergone autologous chondrocyte implantation (ACI) treatment within the patellofemoral joint.
- To develop an in vitro model which mimics the patellofemoral joint to evaluate the cellular response and better target cell-based therapy.

Personal resume: Prior to undertaking my PhD, I graduated from Manchester Metropolitan University with MBioMedSci (Hons) Biomedical Science degree. During my degree, I deferred my studies to work at AstraZeneca as a Microbiologist. Upon completion of my degree, I worked as a senior laboratory technician. By having a variety of industry experience, I believe it has given me valuable skills of which I can incorporate into my PhD research, alongside the ability to collaborate with colleagues and work efficiently to time restraints. Having suffered from lifelong patellofemoral joint issues, I understand what it feels like to be the patient with very little successful treatment options. Thus, this research is a personally invested area of interest to me.

Jade Perry Name: Jade Perry

Supervisory team: Professor Sally Roberts

Funding source: Orthopaedic Institute

Project resume: This project aims to evaluate the ability ofhuman UC-MSCsto prevent/ delay osteoarthritis progression in anovine medial meniscectomy model of early-stage OA,to elucidate their potential as a clinical therapeutic.

Personal resume: Genome Sequencing; Histology; Imaging- clinical and pre-clinical; MRI; X-ray; CT; Micro CT; Animal models; Biomarkers in animal models.

Jade Perry Name: Jade Perry

Supervisory team: Professor Sally Roberts

Funding source: Orthopaedic Institute

Project resume: This project aims to investigate the possibility of using nanopore DNA sequencing technology for the real time identification of pathogens in infected arthroplasty, including antimicrobial resistance.

Personal resume: Genome Sequencing; Histology; Imaging- clinical and pre-clinical; MRI; X-ray; CT; Micro CT; Animal models; Biomarkers in animal models.

Jade Perry Name: Jade Perry

Supervisory team: Professor Sally Roberts

Funding source: Orthopaedic Institute

Project resume: This project aims to identify the bacteria(-um) responsible for Modic type 1 change and locate its site of origin in the body.

Personal resume: Genome Sequencing; Histology; Imaging- clinical and pre-clinical; MRI; X-ray; CT; Micro CT; Animal models; Biomarkers in animal models.

Charlotte Hulme Name: Charlotte Hulme

Supervisory team: Dr Karina Wright

Funding source: Medical Research Council

Project resume: The study aims to identify optimal allogeneic chondrocyte tissue sources, such as from juvenile, healthy donors. Further to characterise these chondrocytes sources following up-scale expansion in the Quantum bioreactor and to assess their potency for the treatment of cartilage injury in the development of up-scale GMP protocols for orthopaedics.

Personal resume: Proteomics; Transcriptomics; Metabolomics; Developing allogeneic chondrocyte therapies; GMP cell manufacture; predictive/prognostic biomarkers for Orthopaedics and Spinal Cord Injury; Understanding clinical outcomes following orthopaedic surgeries e.g. Autologous Chondrocyte Implantation; microfracture; osteotomy; developing organ-on-a-chip models for orthopaedics.

Kurt Foster Name: Kurt Foster

Supervisors: Professor Peter Ogrodnik, Jan-Herman Kuiper, Peter B M Thomas

Project resume:The current focus of blood flow modelling using CFD is on using patient specific models created from CT-scans. This presents a challenge in assessing the results and comparing them to other flow models as the results will be heavily dependent on the specific geometry and boundary conditions for that patient.[ This project aims to develop a design methodology for blood flow modelling using dimensionless groups and assess if it can improve intervention design by making the model non-dimensional thereby taking away that dependence on geometry and boundary conditions. If successful this methodology could be used to make generalised flow models for stent design and conditions such as atherosclerosis or blood clot formation.

Personal resume: Kurt is a PhD student studying at Keele University working on CFD analysis of blood flow. Having previously completed a Bsc in Physics with Mathematics and Msc in Medical Engineering Design; they are currently looking to develop a methodology for modelling pulsatile, non-Newtonian blood flow within flexible walls using dimensionless groups, in order to assess if this will improve intervention design and allow for the generalisation of blood flow modelling. In addition they have been working with a local charity ENG-4 and ANSYS on modelling Covid-19 particle dispersion within hospital rooms and how the ANSYS’ simulation software can be used to fight against airborne viruses.

Through the universities internship scheme Kurt worked with a fellow PhD student Jack Salmon and a local manufacturer ROBUST.Ltd on developing a report to reduce scrap metal waste within the business after the two of them identified the main causes of waste.

Also while a student at keele university they were president of the physics society organising events for students such as study groups and workshops. Through this they have also worked as a representative for the university on open days and lab technician to foundation year students providing one to one help with experiments and class work.

Areas of interest:
• CFD modelling of blood flow
• CFD modelling of particulates in air

shoulder replacement Study group: D McClelland, Professor Peter Ogrodnik, J Blackwell, S O’Beirne, N Grocott and W Nedin

Project resume: The aim of this project is to re-examine the established osteotomy angle for stemless total shoulder replacement. A cadaveric study has been completed and this showed that for optimum circularity the cut angle should be between 18-23 degrees. This has been published. We have now determined the cut-to-cuff distance and are currently starting a retrospective study of over 260 patients and their shoulders to determine whether our predictions are correct. In addition, we are developing a machine learning model that may be used to predict patient specific cut to cuff distance.

Study group: D McClelland, Professor Peter Ogrodnik, A Shafqat, N Grocott and W Nedin

Project resume: The aim of this project is to determine if machine learning can predict classification of tibial plateau fractures after training. A questionnaire containing numerous fracture patterns has been developed for completion by qualified orthopaedic surgeons and registrars. When complete this data will be used to train a machine learning model. Already the team have been able to use AI to determine the specific features required from normal AP and LM x-rays.

Study team: D Griffiths, Professor Peter Ogrodnik, N Wragg

Project resume: D Griffiths is a practicing orthopaedic surgeon specialising in the knee. Over the years he has noticed the need for patients to be able to undertake physiotherapy at home but without the need for a specialist physiotherapist to be in place. This project aims to use his experience to develop a system that will allow prescribed physiotherapy to be conducted at home whilst be monitored by the clinician remotely. This is the first time, that we are aware of, that a clinician will be in the forefront of the development of the technology rather than as a potential end user. It is an example of how OBRG intends to move the clinical – engineering team model to new levels of integration.

William Nedin Name: William Nedin

SupervisorsProfessor Peter Ogrodnik, Nicholas Wragg, Damian McClelland, Peter Thomas

Project resume: An investigation of machine learning for the prediction of outcomes in orthopaedic trauma. Preliminary work has shown machine learning to be a powerful tool for predicting surgical parameters and outcomes. Through a series of case studies, I am working to develop a methodology for the implementation of machine learning into orthopaedic clinic to enhance the assessment of patients, thus reducing waiting times and pressure on surgeons. These case studies include shoulder arthroplasty, gait analysis, image segmentation and pattern recognition and are carried out in the hospital setting alongside other professionals within the hospital and from Europe.

Personal resume: I have a bachelor’s degree in neuroscience, it was during a computational neuroscience lecture on neural networks that I discovered my passion for machine learning. This led me to obtain a master’s degree in biomedical engineering where my dissertation was in machine learning. Outside of my studies I have several hobbies that include reading, painting, weight training and I am also part of a local gaming society.

Kyle Goodwin Name: Kyle Goodwin

Supervisors: Professor Peter Ogrodnik, Dr Sandra Wooley, Peter Thomas, Damian McClelland

Project resume: I am currently studying a PhD at Keele University which aims to develop a methodology capable of assessing joint health through the utilisation of smart sensors. Currently, joint health assessment methods require the use of expensive, large, and timely motion capture systems. The intent of this research is to produce a methodology in which portable, cheap, and reliable devices can be designed to replace these large systems. Once designed, a database that is generalisable across all medical settings will be developed, capable of storing patient data. This information will give clinicians the numerical data they need as an aid when assessing patients, resulting in more accurate and reliable assessments.

Personal resume: I have previously completed a Sports Engineering degree at Loughborough University and am currently undertaking a PhD at Keele University in Biomedical Science. I enjoy playing sports, particularly handball and football. I have represented England in various international handball competitions and currently play semi-professional football. In my spare time, I direct a company that focuses on renovating properties.

Funded to 2024.

Principal investigator: Professor Glenn Morris

Other investigators: Dr LE Thanh Lam, Dr Ian Holt and Dr Heidi Fuller.

Project summary: The CIND Monoclonal Antibody Resource has an important function in supplying reagents for national and international mobility research and was set up using £900,000 from the Muscular Dystrophy Association USA between 2004 and 2018. Among its successes are collaborations with Sarepta Therapeutics USA and REGENEXBIO Inc USA in the development of novel, FDA-approved treatments for Duchenne muscular dystrophy and contributions to the US « SMA Project » which has resulted in new effective treatments for severe spinal muscular atrophy, including gene therapy. This proposal aims to develop the Resource further by continuing characterization of existing antibodies and to make it self-sustaining using income from direct antibody sales and royalties.

Principal investigator: Professor Glenn Morris

Other investigators: Dr Le Thanh Lam and Professor Caroline Sewry

Project summary: Nebulin is a very important protein in normal muscle function and human mobility, but its large size has impeded biochemical understanding of its function and how genetic mutations cause inherited neuromuscular disease. Nebulin molecules contain either exon 143 or exon 144, never both. We have produced mAbs against these specific regions (143 and 144) have shown that the exon 143 isoform appears late in muscle development and is found mainly in fast-twitch fibres in mature muscle (manuscript submitted). We propose to

(a) investigate the relationship between exon 143 and fast-twitch muscles and
(b) to identify proteins that bind the exon 143 isoform only, using successful proteomics techniques, and thus to understand its function in muscle.