A simple method was developed for detection and differentiation of five Tier 1 bacterial agents, including Bacillus anthracis, Francisella tularensis, Yersinia pestis, Burkholderia pseudomallei and Burkholderia mallei as well as their closely related near neighbors by gas chromatography-mass spectrometry (GC-MS). Generally, different classes of compounds can be used as biomarkers for biowarfare agent detection, including nucleic acids (i.e., DNA or RNA), proteins (i.e., antibodies), carbohydrates (i.e., sugars), lipopolysaccharides, lipids (i.e., fatty acids) and small molecules. One-step thermochemolysis (TCM) was developed to provide GC-MS detectable biomarker signatures, including sugars, fatty acids and small molecules. Solid phase micro-extraction (SPME) was used for biomarker extraction, concentration and introduction into the GC-MS. Statistical algorithms were constructed using a combination of biomarkers for the five agents, which were robust against different growth conditions (medium and temperature). A general GC-MS temperature program was developed for all five Tier 1 bacteria. The total analysis time, including TCM, SPME extraction and GC-MS, is approximately 40 min. The total-ion chromatograms are very different for the five species. The final goal of this research was to develop an accurate, fast, simple, robust and automated method for field application. Therefore, an automated sample preparation system was designed, constructed and tested. The system automatically controls the movement of sample vials from one position to another, crimping of septum caps onto the vials, precise delivery of reagents and TCM reaction times and temperatures. The specific operations of introduction of sample vials, SPME sampling, injection into the GC-MS system and ejection of used vials from the system were performed manually in this study, although they can be integrated into the automated system. Manual SPME sampling is performed by following visual and audible signal prompts for inserting the fiber into and retracting it from the sampling port. A rotating carousel design allows for simultaneous sample collection, reaction, biomarker extraction and analysis of sequential samples. Bacillus species were used to test this autoreactor, and 96% of the samples were correctly identified using a statistical algorithm. This research applies not only to the rapid identification of Tier 1 agents after a biological attack, but should also benefit clinical diagnosis, which is essential to effective treatment.

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Preterm birth is a global health challenge and the leading cause of neonatal mortality. Each year, about 15 million babies are born preterm globally. Traditional tools that have been exploited for the detection of preterm birth biomarkers are expensive, time consuming, or lack multiplexing capabilities. The work described in this dissertation highlights techniques developed to detect preterm birth biomarkers rapidly and accurately in the effort to mitigate preterm birth risk. In this dissertation, I first demonstrated the use of stereolithography digital light processing-based 3D printing and microfluidics for the development of microfluidic devices that had microvalves for fluid control. I then used these devices for microchip electrophoresis and fluorescence detection of five preterm birth biomarkers from a published panel. Next, I presented developments in 3D printed microchip electrophoresis device design. I separated amino acids and preterm birth biomarkers in a serpentine device design, obtaining good resolution, separation efficiency, and improved preterm birth biomarker peak capacity. Finally, I demonstrated the integration of solid-phase extraction with microchip electrophoresis in 3D printed microfluidic devices. These integrated devices enabled a seamless transition from preterm birth biomarker enrichment and labeling to microchip electrophoresis separation and fluorescence detection. The work described in this dissertation shows promise in advancing key tools needed to address preterm birth risk rapidly and effectively.

The relationships between volatile flavor compounds, sensory descriptors and consumer acceptability were determined for eight commercial American dry-cured hams using external preference and flavor mapping. The majority of consumers preferred (p<0.05) hams that had more intense caramelized, smoky, savory and molasses aromas as well as more intense sweet and savory flavors. Sixteen aroma impact compounds were identified from the headspace volatiles of dry-cured hams. The consumers with the highest acceptability scores preferred (p<0.05) hams that were characterized by 4-methyl-2-methoxyphenol (sweet ham), 4-ethyl-2-methoxyphenol (sweet ham), 2-methoxyphenol (smoky, cocoa), 2,6-dimethoxyphenol (smoky ham, savory) and 2uranmethanol (burnt meat, vitamin). Fourteen percent of consumers preferred (p<0.05) two hams that were characterized by methional (baked potato). Consumer acceptability scores were lower for hams either characterized by methanethiol (sulfur), carbon disulfide (sulfur), 2-butanone (sweet), 3-methylbutanal (malty, fermented), 2-heptanone (burnt meat, vitamin), hexanal (cut grass), benzeneacetaldehyde (floral), 1-octen-3-ol (mushroom) or characterized by benzaldehyde (burnt meat, cooked meat) and limonene (citrus).

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