Laser Machining Surface Topographies for Stem Cell Control

Lead Research Organisation: University of Southampton
Department Name: Optoelectronics Research Centre

Abstract

Recent work has shown that stem-cell differentiation, specifically the transformation of stem cells into bone cells, can be controlled by growing stem cells on specific surface topographies. The use of such topographies holds the potential for using a patient's own stem cells for targeted generation of bone within the body, leading to faster recovery from bone fractures, reduced failure rates for hip implants and potential therapies for Osteoporosis and other bone diseases.

Preliminary results have shown success with surface topographies on the size scale of 100 nanometers to microns, patterned over millimeter sized areas via a lithographic fabrication process. However, this process is expensive and time-consuming and hence, to scale-up to medically useful dimensions, new fabrication processes must be developed.

Femtosecond pulse laser machining offers the potential for high speed and precise fabrication of features that are on the micron-scale and smaller. However, due to the acute sensitivity of the process, even small levels of experimental noise can result in inferior fabrication quality, preventing the ability to scale this process up to the required dimensions.

The proposed project has two objectives. Firstly, the development of an accurate and real-time monitoring system for the laser machining process, taking advantage of recent developments in machine learning, specifically neural networks, in order to enable creation of large-area, high precision fabrication techniques to machine suitable topographic substrates. Secondly, advancing the processes for optimal growth and monitoring of stem cells on these fabricated substrates in order to optimize the size, features, and dimensions of the surface topography for accurate control of stem cell differentiation and proliferation.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/R513325/1 01/10/2018 30/09/2023
2115650 Studentship EP/R513325/1 01/07/2018 28/02/2022 Benita MacKay