|M.Sc Student||Ianovici Ron|
|Subject||Evaluation of Physiological States through Detection of|
Volatile Organic Compounds in Urine via
Flexible Sensors Array
|Department||Department of Chemical Engineering||Supervisor||PROF. Hossam Haick|
|Full Thesis text|
Early detection of diseases has major implications on the ability to overcome the illness. Moreover, in case of a contagious diseases, it can be the difference between regional health control and global epidemic. On top of all the physiological implications of an illness, there's the economic impact that can vary from buying drugs at the local drug store, to global economic crisis, as we all experienced in the COVID-19 pandemic. Hence, the demand for advanced health monitoring that are fast, accurate and ergonomic for integration in daily life becomes pressing.
Illnesses disrupt the chemical balance in the body. Therefore, by measuring chemical components from the body of sick patients and comparing them to healthy ones, a pattern may emerge to detect the chemical signature that characterizes an illness and its stage. Those chemicals are called Biomarkers. Biomarkers can be either in gas, liquid, or solid forms, they may be emitted from, or accumulated in the body. In the gaseous phase there has been a lot of progress in detecting biomarkers such as volatile organic compounds (VOCs). According to literature, hundreds of VOCs have been found in body fluids, mostly in urine, and some were found to be biomarkers to severe diseases such as various cancers.
To this end, we demonstrate the use of thiol modified gold nano particle chemiresistors, in a multi-layer composition sensor array, on a flexible base and a custom complementary measuring chamber and a fluid transport system, in detecting four representative VOCs that are correlated with various types of cancers, soluble in human urine. The results show that this type of sensor array could detect the chosen VOCs, the sensors responses to different VOC concentrations showed linear behavior at the measured range, both in water, artificial urine, and human urine samples. Moreover, a COMSOL mass transport simulation was made to evaluate the system's empirical results deviations from the flow and mass transport equilibrium fitted equations. The results show high correlation between the empirical and the simulated results except for low concentration measurements, suggesting a reliability limit (RL) for the simulation. Principal component analysis (PCA) showed good selectivity in differentiating between the various analytes, further heat map analysis showed correlation between the sensors signals magnitude and the solubility and LogP values of the analytes, suggesting that the differentiation between the VOCs is affected by the solubility and logP significantly higher than by the thiol VOC interaction.