In this project the influences on human adult mesenchymal stem cells using nanomechanical stimulation techniques has been explored. It is expected that human mesenchymal stem cells will find use in many autologous regenerative therapies and in tissue engineering. However, the ability to control stem cell growth and differentiation is presently limited, and this is a major hurdle to the clinical use of these multipotent cells especially when considering the desire not to use soluble factors or complex media formulations in culture. Also, unpredictable number of cells required to be clinically useful is currently a hurdle to using materials-based (stiffness, chemistry, nanotopography, etc.) culture substrates. According to known cellular reactions to environmental stimuli, it was expected that human cells show some reactions to nanoscale vibration that in the case of stem cells it could be a differentiation response. This thesis gives a first demonstration of using nanoscale mechanotransductive protocols (10-14 nm vertical displacements at 1 kHz frequency), “nanokicking”, to promote osteoblastogenesis in human mesenchymal stem cell cultures. On the basis of application of the reverse piezo effect, laser interferometry was used to develop the optimal stem cell stimulation conditions, allowing delivery of nanoscale cues across the entire surface of the Petri dishes used. A combination of biological techniques has then been used to demonstrate osteoblastogenesis. Furthermore, RhoA has been implicated as being central to osteoblastic differentiation in agreement with materials-based strategies. We validate this with pharmacological inhibition of RhoA kinase. It is easy to envisage such stimulation protocols being up-scaled to form large-scale osteoblast bioreactors as standard cell culture plates and incubators are used in the protocol.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:586842 |
| Date | January 2013 |
| Creators | Nikukar, Habib |
| Publisher | University of Glasgow |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://theses.gla.ac.uk/4752/ |
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