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Prediction of shock status using open flow approaches with biosensor detection

Exploitable results

The shock state is characterized by a major disruption of metabolic regulation triggered by tissue hypoxia. The project aims are to develop biosensors for lactate and for interrelated intermediary metabolites (pyruvate, glucose and glutamate) to monitor their tissue levels on a continuous basis and to use this as a route to quantitative, predictive assessment of the critically ill patient. The biosensors under development utilize a range of microfabricated and miniaturized implantable sensors capable of in vivo or ex vivo monitoring. Critical to this development has been new and modified enzyme and polymeric membrane barriers to enable direct metabolite measurement with minimal sample manipulation. This has further stimulated advances in material biocompatibility for biosensors. This technological advance has enable sensor integration with a novel tissue access technique (Open Microflow) whereby tissue is hydrated with pumpless flow of fluid to provide for improved in vivo biosensor performance. In addition, further advances in tissue sampling built upon microdialysis and ultrafiltration techniques have been realized, and have enabled operation of ex vivo biosensors with enhanced reliability. Central to this additional technical advanced has been the appropriate integration of sampling, flow cell and biosensor constructs. In metabolic studies generally, the blood compartment is accessed, but monitoring tissue in this project is likely to provide new insight into the shock state, with better understanding of dynamic interrelationships between vascular and tissue compartments. This will be augmented by registering rapid metabolite changes and by locating biosensors and sampling probes at specific tissue sites to identify site dependant differences. This joint programme has provided a unique collaborative link for critical comparison of the various tissue sampling and access techniques, and will help optimize metabolite monitoring systems. Also at the fundamental level, the modeling of monitored parameters in tissue will enable quantitative kinetic data to be derived as a further objective measure of metabolite regulation in pathophysiological states.