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Nano and Micro Technologies

Nano and Micro Technologies - Poster Session D

Poster Z6 - Elucidating the Response of Metal Oxide Gas Sensors Toward Urinary Volatile Organic Compound Biomarkers for Applications in Noninvasive Diagnostics and Health Monitoring

Friday, October 25, 2024
3:30 PM - 4:30 PM EST
Location: Exhibit Hall E, F & G

Introduction:  Volatile organic compounds (VOCs) are low molecular weight chemicals with high vapor pressure that can be produced endogenously inside the human body as byproducts of metabolic processes. VOCs in urine and other biological sample types can be characterized as biomarkers for noninvasive health monitoring of various diseases and urological cancers. The gold standard for VOC profiling is gas chromatography-mass spectrometry (GC-MS), but it is inefficient for rapid or point-of-care testing due to its cost and complex operation. On the other hand, electronic noses, composed of an array of metal oxide (MOX) gas sensors that detect VOCs through redox reactions on the sensing layer, have shown promise as a noninvasive and rapid tool for medical diagnostics. However, it is unknown which specific analytes the MOX sensors respond to and whether the dysregulation of biomarkers can be discerned.

Materials and

Methods:  To understand how urinary VOCs interact with the metal oxide sensors, a urinary headspace sampling method was established and optimized using a homogenized urine sample. Here, aliquots of urine were sparged with dry air and the sample headspace was directed to the sensor chamber housing two Tin oxide arrays. Parameters such as flow rate, exposure time, and volume were optimized to increase sensitivity and reproducibility. Data was analyzed through a feature extraction code developed in Python which assisted in identifying the optimal parameters. The standardized protocol was used to analyze urine samples collected by three healthy volunteers. In parallel, GC-MS assays were run on the same aliquots to determine whether the sensors respond to individual urinary VOCs or show selectivity towards a unique urinary profile.

Results, Conclusions, and Discussions: Sensor output was characterized by peak-to-peak (P2P) and ratio which explores the relationship between the maximum current output from VOC exposure and the baseline current. The P2P and Ratio for two sensors across two chips indicated that exposure time did not significantly affect the current output between the two chips. Similarly, flow rate and sample volume showed no significant effect on sensor output regarding sensor sensitivity. Optimal urinary VOC detection was therefore determined through the reproducibility of the parameters. The standard protocol involves sparging 3 mL of urine at a flow rate of 0.1 standard liters per minute for three minutes. GC-MS identified VOC biomarkers in individual urine samples which were analyzed with the MOX sensor output. The MOX sensors show selectivity towards acetone compared to other VOC markers in the urine samples indicating that the sensors are not responding to the total VOC signal or other analytes in the sample matrix. The selectivity of the sensors towards specific VOCs highlights their potential for integration into nanosensor arrays which can target VOC biomarkers for urological cancers and diseases.

Acknowledgements (Optional):  This work was supported by the Integrated Nanosystems Development Institute (INDI), Indiana University (IU) Indianapolis, Dr. Agarwal’s Lab, and the Research Experience for Undergraduates (REU) program from the National Science Foundation (NSF) (Award #1950672).