The aim of the project is the development of robust multiple parallel analytical methodologies allowing for comprehensive and comparative metabolomic descriptions of both control and diabetic rats.
Simultaneously, the development of rapid, user- friendly chemometric "packages" capable of dealing with raw data derived from the above methods and producing meaningful sample classifications and identification of analytes responsible for biochemical perturbations.
The Analytical Challenges are: the management of
- multiple sample preparation and separation/resolution strategies which will include for example CE (with UV-DAD, conductivity or MS detection), HPLC (with coulometric electrochemical array (EC), UV-DAD or MS detection), GC-MS and NMR and
- the data de rived from these techniques in such a way as to produce protocols suitable for comprehensive sample classification and or analyte identification.
Multiple techniques will be combined to yield a multi-dimensional representation for a single sample. Furthermore, chemometric data analysis development of integrated software which can perform rapid analysis of multiple sets of analytical data is a particularly important challenge which will be addressed.
This methodology has multiple applications, but the final objective in this particular project is the knowledge of diabetic rat metabolome in depth, and the effect of antioxidant treatments. It will permit to develop improved strategies for the management of pathologies associated with a major disease such as diabetes.
Field of science
- /natural sciences/computer and information sciences/data science/data analysis
- /natural sciences/chemical sciences/electrochemistry/electrophoresis
- /medical and health sciences/clinical medicine/endocrinology/diabetes
- /medical and health sciences/clinical medicine/cardiology/cardiovascular diseases
Call for proposal
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