Thesis (Ph. D.)--Earth and Atmospheric Sciences, Georgia Institute of Technology, 2007. / Wang Yuhang, Committee Chair ; Cunnold Derek, Committee Member ; Weber Rodney, Committee Member ; Nenes Athanasios, Committee Member ; Guillas Serge, Committee Member.

Thesis (Ph. D.)--Chemical and Biomolecular Engineering, Georgia Institute of Technology, 2008. / Teja, Amyn S., Committee Chair ; Frederick, James, Committee Member ; Wine, Paul H., Committee Member ; Eckert, Charles A., Committee Member ; Nenes, Athanasios, Committee Member.

Thesis (Ph.D.)--Montana State University--Bozeman, 2007. / Typescript. Chairperson, Graduate Committee: Walter B. Knighton. Includes bibliographical references (leaves 131-145).

Thesis (I.M.E.S.)--Baylor University, 2009. / Includes bibliographical references (p. 107-118).

The ability to quickly and efficiently locate concealed human remains is crucial in forensic investigations and when locating disaster victims. On occasions when human remains are recovered, correctly assigning a postmortem interval (PMI) may become necessary to corroborate statements or make an identification. While Human Remains Detection canines (HRD canines) provide rapid and sensitive searches, the mechanisms behind their sense of smell remain poorly understood. Over the past ten years, volatile organic compounds (VOCs) have been investigated in an effort to address questions concerning PMI, optimization of training aids, and portable 'sniffing' devices. The approaches taken for investigating VOCs emitted from decomposing tissues buried or otherwise have been diverse. They range from burying entire human bodies and sampling the above-ground volatiles using triple-sorbent traps (TSTs) to isolating small amounts of tissue into glass vials whereby the volatiles are sampled by Solid Phase Microextraction (SPME). The resulting studies have led to large quantities of data that are difficult to interpret and compare between studies. Furthermore, the restrictions surrounding access to human remains have caused many studies to use other animals, (pigs, chickens, cows, and deer) in particular the domestic pig, due to its similarities in hair coverage and tissue ratios. There have been several studies that attempt to address the effects that burial has on the resulting VOCs. However, the addition of a complex matrix to a process that already has many variables has caused difficulty in data interpretation. The purpose of this study was to identify how freezing and the presence of soil affect the VOC profiles of various tissue types (blood, bone, fat, small intestine, muscle, and skin) obtained over six weeks of decomposition. In order to accomplish this, the study was performed in three parts. The first part used fresh pig samples obtained only hours after euthanization, the second part utilized tissues from the same areas of the pig after the samples had been frozen for 6 weeks and the third part combined soil with three of the tissue types (blood, bone, muscle). SPME was employed at room temperature using a 65 µm PDMS/DVB coated fiber as the adsorbent material to extract the VOCs from the headspace. The use of SPME as the extraction method allowed for direct desorption and subsequent analysis into the injection port of the GC/MS. User-defined integration parameters were applied to each resulting chromatogram in an effort to identify what impact, if any, freezing and soil had on the resulting VOC profiles. The results obtained in this study suggest that the freezing and thawing of tissue samples have varying effects on the resulting chromatograms based on the complexity of the tissue-type. This implies that prolonged use and storage of some, commonly utilized, training aids may not be providing the most reliable scent profile for the HRD canines. Results obtained from the soil study were complex, but several overall trends were observed in the release and production of different compound classes. Comparisons to previous studies using similar extraction procedures demonstrate the need for a standardized protocol for future decomposition studies.

No description available.

In certain European countries and the United States of America, canines have been successfully used in human scent identification. There is however, limited scientific knowledge on the composition of human scent and the detection mechanism that produces an alert from canines. This lack of information has resulted in successful legal challenges to human scent evidence in the courts of law. The main objective of this research was to utilize science to validate the current practices of using human scent evidence in criminal cases. The goals of this study were to utilize Headspace Solid Phase Micro Extraction Gas Chromatography Mass Spectrometry (HS-SPME-GC/MS) to determine the optimum collection and storage conditions for human scent samples, to investigate whether the amount of DNA deposited upon contact with an object affects the alerts produced by human scent identification canines, and to create a prototype pseudo human scent which could be used for training purposes. Hand odor samples which were collected on different sorbent materials and exposed to various environmental conditions showed that human scent samples should be stored without prolonged exposure to UVA/UVB light to allow minimal changes to the overall scent profile. Various methods of collecting human scent from objects were also investigated and it was determined that passive collection methods yields ten times more VOCs by mass than active collection methods. Through the use of polymerase chain reaction (PCR) no correlation was found between the amount of DNA that was deposited upon contact with an object and the alerts that were produced by human scent identification canines. Preliminary studies conducted to create a prototype pseudo human scent showed that it is possible to produce fractions of a human scent sample which can be presented to the canines to determine whether specific fractions or the entire sample is needed to produce alerts by the human scent identification canines.

Please read the abstract in the section 00front of this document / Dissertation (MSc)--University of Pretoria, 2010. / Chemistry / unrestricted

Indiana University-Purdue University Indianapolis (IUPUI) / The aim of this study is to identify metabolic transformations in breast cancer through urinary volatile organic compounds in mammary pad or bone tumor mice models. Subsequently, it focuses on investigating the efficacy of therapeutic intervention through identified potential biomarkers. Methods for monitoring tumor development and treatment responses have technologically advanced over the years leading to significant increase in percent survival rates. Although these modalities are reliable, it would be beneficial to observe disease progression from a new perspective to gain greater understanding of cancer pathogenesis. Analysis of cellular energetics affected by cancer using bio-fluids can non-invasively help in prognosis and selection of treatment regimens. The hypothesis is altered profiles of urinary volatile metabolites is directly related to disrupted metabolic pathways. Additionally, effectiveness of treatments can be indicated through changes in concentration of metabolites. In this ancillary experiment, mouse urine specimens were analyzed using gas chromatography-mass spectrometry, an analytical chemistry tool in identifying volatile organic compounds. Female BALB/c mice were injected with 4T1.2 murine breast tumor cells in the mammary fat pad. Consecutively, 4T1.2 cells were injected in the right iliac artery of BALB/c mice and E0771 tumor cells injected in the tibia of C57BL/6 mice to model bone tumor. The effect of two different modes of treatment: chemical drug and mechanical stimulation was investigated through changes in compound profiles. Chemical drug therapy was conducted with dopamine agents, Triuoperazine, Fluphenazine and a statin, Pitavastatin. Mechanical stimulation included tibia and knee loading at the site of tumor cell injection were given to mice. A biological treatment mode included administration of A5 osteocyte cell line. A set of potential volatile organic compounds biomarkers differentiating mammary pad or bone confined tumors from healthy controls was identified using forward feature selection. Effect of treatments was demonstrated through hierarchical heat maps and multivariate data analysis. Compounds identified in series of experiments belonged to the class of terpenoids, precursors of cholesterol molecules. Terpene synthesis is a descending step of mevalonate pathway suggesting its potential role in cancer pathogenesis. This thesis demonstrates the ability of urine volatilomics to indicate signaling pathways inflicted in tumors. It proposes a concept of using urine to detect tumor developments at two distinct locations as well as to monitor treatment efficacy.

Indiana University-Purdue University Indianapolis (IUPUI) / Volatile organic compounds (VOCs) are endogenous byproducts of metabolic pathways that can be altered by a disease or condition, leading to an associated and unique VOC profile or signature. Current methodologies for VOC detection include canines, gas chromatography-mass spectrometry (GC-MS), and electronic nose (eNose). Some of the challenges for canines and GC-MS are cost-effectiveness, extensive training, expensive instrumentation. On the other hand, a significant downfall of the eNose is low selectivity. This thesis proposes to design a breathalyzer using chemiresistive gas sensors that detects VOCs from human breath, and subsequently create an interface to process and deliver the results via Bluetooth Low Energy (BLE). Breath samples were collected from patients with hypoglycemia, COVID-19, and healthy controls for both. Samples were processed, analyzed using GC-MS, and probed through statistical analysis. A panel of 6 VOC biomarkers distinguished between hypoglycemia (HYPO) and Normal samples with a training AUC of 0.98 and a testing AUC of 0.93. For COVID-19, a panel of 3 VOC biomarkers distinguished between COVID-19 positive symptomatic (COVID-19) and healthy Control samples with a training area under the curve (AUC) of receiver operating characteristic (ROC) of 1.0 and cross-validation (CV) AUC of 0.99. The model was validated with COVID-19 Recovery samples. The discovery of these biomarkers enables the development of selective gas sensors to detect the VOCs. Polyethylenimine-ether functionalized gold nanoparticle (PEI-EGNP) gas sensors were designed and fabricated in the lab and metal oxide (MOX) semiconductor gas sensors were obtained from Nanoz (Chip 1: SnO2 and Chip 2: WO3). These sensors were tested at different relative humidity (RH) levels and VOC concentrations. The contact angle which measures hydrophobicity was 84° and the thickness of the PEI-EGNP coating was 11 µ m. The PEI-EGNP sensor response at RH 85% had a signal 10x higher than at RH 0%. Optimization of the MOX sensor was performed by changing the heater voltage and concentration of VOCs. At RH 85% and heater voltage of 2500 mV, the performance of the sensors increased. Chip 2 had higher sensitivity towards VOCs especially for one of the VOC biomarkers identified for COVID-19. PCA distinguished VOC biomarkers of HYPO, COVID-19, and healthy human breath using the Nanoz. A sensor interface was created to integrate the PEI-EGNP sensors with the printed circuit board (PCB) and Bluno Nano to perform machine learning. The sensor interface can currently process and make decisions from the data whether the breath is HYPO (-) or Normal (+). This data is then sent via BLE to the Hypo Alert app to display the decision.