Kayal, Celine; (2019) Spatial Control of Mechanical Factors: a New Design Rationale for Nerve Tissue Engineering. Doctoral thesis (Ph.D), UCL (University College London).

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Abstract

Peripheral nerve injuries (PNI) result from traumatic injury, surgery or repetitive compression, and are reported in 3-5% of all trauma patients. The impact ranges from severe (major loss of sensory/motor function and/or intractable neuropathic pain) to mild (some sensory and/or motor deficits) and in both cases, is devastating for the patient. PNI affect ∼1M people in Europe and the US p.a. of whom 660,000 have surgery. PNI has high healthcare, unemployment, rehabilitation, societal costs and affects mostly young people. The current surgical practice for nerve gaps >3 cm is to bridge the site of injury with a graft taken from the patient. However, this involves additional time, cost and damage to a healthy nerve, limited supply, and unsatisfactory functional recovery (50% of the cases). For these reasons, research has focused on developing artificial nerve conduits to replace grafts, but to-date those available for clinical use do not match and/or exceed the functional performance of the autograft. This project develops a rational basis for promoting neurite growth through tissue-engineered conduits for peripheral nerve repair, by exploiting the response of cells to spatial variations in mechanical properties of conduits to inform their design. This is achieved through an interdisciplinary approach, that combines in vitro experimentation with mathematical modelling. First of all, the mechanical and structural properties of RAFTStabilised collagen gels (RsC) are explored, physiologically coherent RsC stiffness gradients are fabricated and characterised as well as the neuronal response to them. Finally, a predictive framework to inform the design of nerve conduits is parameterised and tested using experimental results and literature. The use of this multidisciplinary approach can help tissue engineers in the development of novel tissue repair solutions, as well as informing mathematical models of neurite behaviour which can contribute to the design process.

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