Mechanobiological modeling of regeneration and degeneration of soft musculoskeletal tissues
General description: The research in the biomechanics group is focused on understanding the link between mechanics and biology in the musculoskeletal system, including related pathologies and repair of skeletal tissues. Experimental studies, tissue characterisation, imaging and computational simulation techniques are used. The research is applied to problems in orthopaedics to develop better methods to understand and improve repair of musculoskeletal tissues.
Soft musculoskeletal tissues (knee joint tissues and tendons) all connect or transmit forces during movement in the body. Despite having specialized mechanical functions and tailored microstructures, they present with a similar gross composition based on a collagen network, small amounts of proteoglycans, and an extensive amount of water. In these projects we are looking to develop adaptive computational models of how the tissues respond and adapt to mechanical loading over time, and specifically how mechanical stimulation affects the tissue’s regenerative capacity after damage and the degenerative degradation in response to injury. We are looking for 2 PhD students to be dedicated to the following projects:
Project 1: Tendons connect muscles to bones and enable energy-efficient locomotion. The Achilles tendon is the largest and the most injured tendon in the human body. Ruptures often occur during recreational sport activities but can also be a result of ageing. Mechanical loading is a prerequisite for tendon healing. Controversial and often unsuccessful treatments of tendon ruptures could be improved by elucidating how loading affects the mechanobiological aspects of tendon healing. This position is within a larger project with the scope to elucidate how mechanical loading affects tendon regeneration.
The aim for PhD student 1 is to investigate how mechanical loading influences healing tendon function, structure and composition. The project includes to further develop and validate an existing adaptive mechanoregulatory model for tendon repair. This will be conducted based on collected experimental data from ongoing studies. The developed computational mechanobiological scheme will be key in the project to elucidate the mechanobiological mechanisms at play.
PhD student 1 would be actively working within the group and with collaborators within the TENDON_MECHBIO project funded by the European Research Council.
Project 2: Osteoarthritis (OA) is a common joint disease affecting over 40 million Europeans. The number of patients with OA will increase by over 70% in developed countries during the next 20 years, while direct and indirect costs are estimated to increase by over 300%. The most cost-effective and helpful treatment for the disease would simply be prevention. Since the progression of OA is highly subject-specific, prevention of the disease can only be possible when the progression can be predicted for an individual patient. The position is within a project with the overall aim to develop a tool to predict the onset and progression of osteoarthritis in the knee joint tissues due to daily loading conditions. The consortium will combine patient-specific motion analysis and computational modelling approaches for OA diagnostics, personalized prediction, and optimal treatment.
The goal for PhD student 2 is to develop and implement constitutive material models and mechanobiological adaptive models of knee joint tissues in a finite element based mechanobiological framework of the knee. The framework will be validated against tissue specific experimental and clinical data available within the collaborative network and overall prediction of tissue degeneration during OA.
PhD student 2 would be actively working with international collaborators within the MathKOA project funded by NovoNordisk Foundation.
Approach: Both projects include designing and developing numerical framework, followed by simulations and data analysis. Understanding and utilizing experimentally available data is important.
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