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    Development of a sampling system for the collection of exhaled breath condensates and its subsequent analysis using 2-dimensional gas chromatography

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    SHASHIDHARASURAPPA-THESIS-2015.pdf (4.786Mb)
    Date
    2015-12-04
    Author
    Shashidhara Surappa, Sushruta
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    Abstract
    Exhaled human breath contains thousands of compounds that provide information about the physiological state of the human body, yet it is not used as extensively as blood or urine samples for medical diagnostics. Some of the major reasons for this include the lack of a standard method of sample collection, control of variability, reliable detection at trace level and quantification. Breath analysis has recently attracted renewed interest in medical diagnostics and for monitoring therapeutic progress because it is a less invasive method of sample collection than is currently used in treatment and it can be sampled as often as required. Breath analysis can be performed in surgery or in intensive care and real time analysis is possible on a stationary cycle or during sleep. The objective of this research is to develop a novel sample collection system that is capable of capturing both the EBC as well as the VOC present in exhaled human breath. Currently, methods of simultaneously capturing both fractions of exhaled breath are not well established and current work focuses on the capture and analysis of either one fraction. Furthermore, the focus is currently on the targeted analysis of specific compounds to monitor ailments such as asthma, cancer etc. In this work, both fractions are successfully collected and analyzed using gas chromatography - mass spectrometry (GC-MS) as well as two-dimensional gas chromatography (GCxGC). This provides analysis of volatile organic compounds as well as proteins and higher molecular weight components present in breath. This broader analysis might find use in medical diagnostics, for detection of markers indicating oxidative stress, detection of lung cancer, monitoring plasma glucose and many more medical applications.
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    http://hdl.handle.net/1853/56228
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    • Georgia Tech Theses and Dissertations [23877]
    • School of Mechanical Engineering Theses and Dissertations [4086]

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