Inflammation and bacterial infection are frequently accompanied by increased levels of host and bacterial proteases. Transducer technology for a generic sensing platform capable of monitoring a range of serine proteases and matrix metalloproteinases will b e developed. The sensing platform, a combination of smart materials and an innovative transducer system, will provide a diagnostic tool for studying the mechanisms involved in inflammatory diseases and monitoring of inflammation at the point of care. Detection of proteases will be based on the enzymatic degradation of thin films. To achieve specificity for different proteases, arrays of hydrogels cross-linked with short peptide sequences will be synthesised on the transducer surface.
The rate of degradation is directly related to the enzyme activity. Hydrogel degradation will be monitored using novel transducer technology to be derived from an impedance imaging technique, Scanning Photo-induced Impedance Microscopy (SPIM). SPIM is based on photocurrent measurements at silicon/insulator/electrolyte structures. In this project the sensitivity of this technique will be pushed to its limit by optimising the silicon/insulator substrate. Hydrogel arrays will be produced on the optimised substrate.
The feasibility of the sensor concept will be tested by measuring the response of the hydrogels to mixtures of proteases implicated in periodontal inflammation using SPIM. This technology has the advantage that it enables us to interrogate a number of different polymers, all of which respond differently to various proteases, in parallel and in real time. Data analysis will be carried out using pattern recognition. SPIM is not only useful for sensor applications but also as a research tool for characterisation of new materials and biological samples. An increase in the sensitivity of the technique opens up a range of new areas of applications such as high-throughput screening of the dielectric properties of new materials.
Fields of science
- natural sciencescomputer and information sciencesartificial intelligencepattern recognition
- natural sciencesphysical scienceselectromagnetism and electronicssemiconductivity
- natural scienceschemical sciencespolymer sciences
- natural scienceschemical sciencesinorganic chemistrymetalloids
- natural sciencesbiological sciencesbiochemistrybiomoleculesproteinsenzymes
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