Matching Items (28)
Description
The rate of progress in improving survival of patients with solid tumors is slow due to late stage diagnosis and poor tumor characterization processes that fail to effectively reflect the nature of tumor before treatment or the subsequent change in its dynamics because of treatment. Further advancement of targeted therapies relies on advancements in biomarker research. In the context of solid tumors, bio-specimen samples such as biopsies serve as the main source of biomarkers used in the treatment and monitoring of cancer, even though biopsy samples are susceptible to sampling error and more importantly, are local and offer a narrow temporal scope.
Because of its established role in cancer care and its non-invasive nature imaging offers the potential to complement the findings of cancer biology. Over the past decade, a compelling body of literature has emerged suggesting a more pivotal role for imaging in the diagnosis, prognosis, and monitoring of diseases. These advances have facilitated the rise of an emerging practice known as Radiomics: the extraction and analysis of large numbers of quantitative features from medical images to improve disease characterization and prediction of outcome. It has been suggested that radiomics can contribute to biomarker discovery by detecting imaging traits that are complementary or interchangeable with other markers.
This thesis seeks further advancement of imaging biomarker discovery. This research unfolds over two aims: I) developing a comprehensive methodological pipeline for converting diagnostic imaging data into mineable sources of information, and II) investigating the utility of imaging data in clinical diagnostic applications. Four validation studies were conducted using the radiomics pipeline developed in aim I. These studies had the following goals: (1 distinguishing between benign and malignant head and neck lesions (2) differentiating benign and malignant breast cancers, (3) predicting the status of Human Papillomavirus in head and neck cancers, and (4) predicting neuropsychological performances as they relate to Alzheimer’s disease progression. The long-term objective of this thesis is to improve patient outcome and survival by facilitating incorporation of routine care imaging data into decision making processes.
Because of its established role in cancer care and its non-invasive nature imaging offers the potential to complement the findings of cancer biology. Over the past decade, a compelling body of literature has emerged suggesting a more pivotal role for imaging in the diagnosis, prognosis, and monitoring of diseases. These advances have facilitated the rise of an emerging practice known as Radiomics: the extraction and analysis of large numbers of quantitative features from medical images to improve disease characterization and prediction of outcome. It has been suggested that radiomics can contribute to biomarker discovery by detecting imaging traits that are complementary or interchangeable with other markers.
This thesis seeks further advancement of imaging biomarker discovery. This research unfolds over two aims: I) developing a comprehensive methodological pipeline for converting diagnostic imaging data into mineable sources of information, and II) investigating the utility of imaging data in clinical diagnostic applications. Four validation studies were conducted using the radiomics pipeline developed in aim I. These studies had the following goals: (1 distinguishing between benign and malignant head and neck lesions (2) differentiating benign and malignant breast cancers, (3) predicting the status of Human Papillomavirus in head and neck cancers, and (4) predicting neuropsychological performances as they relate to Alzheimer’s disease progression. The long-term objective of this thesis is to improve patient outcome and survival by facilitating incorporation of routine care imaging data into decision making processes.
ContributorsRanjbar, Sara (Author) / Kaufman, David (Thesis advisor) / Mitchell, Joseph R. (Thesis advisor) / Runger, George C. (Committee member) / Arizona State University (Publisher)
Created2017
Description
Background: Twenty-four hour urinary sucrose and fructose (24uSF) has been developed as a dietary biomarker for total sugars intake. Collection of 24-h urine is associated with high costs and heavy participant burden, while collection of spot urine samples can be easily implemented in research protocols. The aim of this thesis is to investigate the utility of uSF biomarker measured in spot urine. Methods: 15 participants age 22 to 49 years completed a 15-day feeding study in which they consumed their usual diet under controlled conditions, and recorded the time each meal was consumed. Two nonconsecutive 24-hour urines, where each urine void was collected in a separate container, were collected. Four timed voids (morning, afternoon, evening, and next day) were identified based on time of void and meal time. Urine samples were measured for sucrose, fructose and creatinine. Variability of uSF excretion was assessed by coefficient of variation (%CV) and variance ratios. Pearson correlation coefficient and multiple linear regression were used to investigate the association between uSF in each timed void and corresponding 24uSF excretion. Results: The two-day mean uSF was 50.6 mg (SD=29.5) for the 24-h urine, and ranged from 4.5 to 7.5 mg/void for the timed voids. The afternoon void uSF had the lowest within-subject variability (49.1%), and lowest within- to between-subject variance ratio (0.2). The morning and afternoon void uSF had the strongest correlation with 24-h uSF for both mg/void (r=0.80 and r=0.72) and mg/creatinine (r=0.72 and r=0.67), respectively. Finally, the afternoon void uSF along with other covariates had the strongest predictive ability of 24-h uSF excretion (mg/void) (Adjusted R2= 0.69; p=0.002), whereas the morning void had the strongest predictive ability of 24-h uSF excretion (mg/g creatinine) (adjusted R2= 0.58; p=0.008). Conclusions: The afternoon void uSF had the most favorable reproducibility estimates, strong correlation with 24uSF excretion, and explained greatest proportion of the variability in 24uSF. USF in mg/void may be better to use than uSF in mg/g creatinine as a biomarker in spot urine. These findings need to be confirmed in a larger study, and in a study population with a wide range of sugars intake.
ContributorsAverill, Annalisa (Author) / Tasevska, Natasha (Thesis advisor) / Shepard, Christina (Committee member) / Johnston, Carol (Committee member) / Arizona State University (Publisher)
Created2018
Description
Background. Effects of lifestyle interventions on early biomarkers of oxidative stress and CVD risk in youth with prediabetes are unknown. Objective. To evaluate the effects of a lifestyle intervention to prevent type 2 diabetes among obese prediabetic Latino adolescents on oxidized lipoproteins. Design: In a quasi-experimental design, 35 adolescents (51.4% male, age 15.5(1.0) y, body mass index (BMI) percentile 98.5(1.2), and glucose 2 hours after an oral glucose tolerance test-OGTT 141.2(12.2) mg/dL) participated in a 12-week intervention that included weekly exercise (three 60 min-sessions) and nutrition education (one 60 min-session). Outcomes measured at baseline and post-intervention were: fasting oxidized LDL and oxidized HDL (oxLDL and oxHDL) as oxidative stress variables; dietary intake of fresh fruit and vegetable (F&V) and fitness (VO2max) as behavioral variables; weight, BMI, body fat, and waist circumference as anthropometric variables; fasting glucose and insulin, 2hour glucose and insulin after an OGTT, insulin resistance (HOMA-IR), and lipid panel (triglycerides, total cholesterol, VLDL-c, LDL-c, HDL-c, and Non-HDL) as cardiometabolic variables. Results. Comparing baseline to post-intervention, significant decreases in oxLDL concentration were shown (51.0(14.0) and 48.7(12.8) U/L, p=0.022); however, the intervention did not decrease oxHDL (395.2(94.6) and 416.1(98.4) ng/mL, p=0.944). F&V dietary intake (116.4(97.0) and 165.8(91.0) g/d, p=0.025) and VO2max (29.7(5.0) and 31.6(4.7) ml*kg-1*min-1, p<0.001) significantly increased. Within-subjects correlations between changes in F&V intake and oxidized lipoproteins, adjusted for VO2max changes, were non-significant (R=-0.15, p=0.52 for oxLDL; R=0.22, p=0.25 for oxHDL). Anthropometric variables were significantly reduced (weight -1.3% p=0.042; BMI -2.2% and BMI percentile -0.4%, p=0.001; body fat -6.6% and waist circumference -1.8%, p=0.025). Cardiometabolic variables significantly improved, including reductions in glucose 2hour (-19.3% p<0.001), fasting insulin (-12.9% p=0.008), insulin 2hour (-53.5% p<0.001), and HOMA-IR (-12.5% p=0.015), with 23 participants (66%) that reverted toward a normal glucose tolerance status. Most lipid panel significantly changed (triglycerides -10.2% p=0.032; total cholesterol -5.4% p=0.002; VLDL-c -10.4% p=0.029; HDL-c -3.2% p=0.022; and Non-HDL -5.5% p=0.0007). Conclusion. The intervention resulted in differential effects on oxidized lipoproteins and significant improvements in behavioral, anthropometric and cardiometabolic variables, reducing the high metabolic risk of obese prediabetic kids.
ContributorsRenteria Mexia, Ana Maria (Author) / Shaibi, Gabriel Q (Thesis advisor) / Vega-Lopez, Sonia (Committee member) / Swan, Pamela D (Committee member) / Olson, Micah L (Committee member) / Lee, Chong (Committee member) / Arizona State University (Publisher)
Created2017
Description
Childhood Apraxia of Speech (CAS) is a severe motor speech disorder that is difficult to diagnose as there is currently no gold-standard measurement to differentiate between CAS and other speech disorders. In the present study, we investigate underlying biomarkers associated with CAS in addition to enhanced phenotyping through behavioral testing. Cortical electrophysiological measures were utilized to investigate differences in neural activation in response to native and non-native vowel contrasts between children with CAS and typically developing peers. Genetic analysis included full exome sequencing of a child with CAS and his unaffected parents in order to uncover underlying genetic variation that may be causal to the child’s severely impaired speech and language. Enhanced phenotyping was completed through extensive behavioral testing, including speech, language, reading, spelling, phonological awareness, gross/fine motor, and oral and hand motor tasks. Results from cortical electrophysiological measures are consistent with previous evidence of a heightened neural response to non-native sounds in CAS, potentially indicating over specified phonological representations in this population. Results of exome sequencing suggest multiple genetic variations contributing to the severely affected phenotype in the child and provide further evidence of heterogeneous genomic pathways associated with CAS. Finally, results of behavioral testing demonstrate significant impairments evident across tasks in CAS, suggesting underlying sequential processing deficits in multiple domains. Overall, these results have the potential to delineate functional pathways from genetic variations to the brain to observable behavioral phenotypes and motivate the development of preventative and targeted treatment approaches.
ContributorsVose, Caitlin (Author) / Peter, Beate (Thesis advisor) / Liu, Li (Committee member) / Brewer, Gene (Committee member) / Arizona State University (Publisher)
Created2018
Description
Extracellular vesicles (EVs) represent a heterogeneous population of small vesicles, consisting of a phospholipidic bilayer surrounding a soluble interior cargo. These vesicles play an important role in cellular communication by virtue of their protein, RNA, and lipid content, which can be transferred among cells. Peripheral blood is a rich source of circulating EVs. An analysis of EVs in peripheral blood could provide access to unparalleled amounts of biomarkers of great diagnostic, prognostic as well as therapeutic value. In the current study, a plasma EV enrichment method based on pluronic co-polymer was first established and characterized. Plasma EVs from breast cancer patients were then enriched, profiled and compared to non-cancer controls. Proteins signatures that contributed to the prediction of cancer samples from non-cancer controls were created by a random-forest based cross-validation approach. We found that a large portion of these signatures were related to breast cancer aggression. To verify such findings, KIAA0100, one of the features identified, was chosen for in vitro molecular and cellular studies in the breast cancer cell line MDA-MB-231. We found that KIAA0100 regulates cancer cell aggression in MDA-MB-231 in an anchorage-independent manner and is particularly associated with anoikis resistance through its interaction with HSPA1A. Lastly, plasma EVs contain not only individual proteins, but also numerous molecular complexes. In order to measure millions of proteins, isoforms, and complexes simultaneously, Adaptive Dynamic Artificial Poly-ligand Targeting (ADAPT) platform was applied. ADAPT employs an enriched library of single-stranded oligodeoxynucleotides to profile complex biological samples, thus achieving a deep coverage of system-wide, native biomolecules. Profiling of EVs from breast cancer patients was able to obtain a prediction AUC performance of 0.73 when compared biopsy-positive cancer patient to healthy controls and 0.64 compared to biopsy-negative controls and such performance was not associated with the physical breast condition indicated by BIRAD scores. Taken together, current research demonstrated the potential of profiling plasma EVs in searching for therapeutic targets as well as diagnostic signatures.
ContributorsZhong, Zhenyu (Author) / Spetzler, David (Thesis advisor) / Yan, Hao (Thesis advisor) / Lake, Douglas (Committee member) / Mangone, Marco (Committee member) / Arizona State University (Publisher)
Created2018
Description
Parkinson’s disease (PD) is a progressive neurodegenerative disorder, diagnosed late in
the disease by a series of motor deficits that manifest over years or decades. It is characterized by degeneration of mid-brain dopaminergic neurons with a high prevalence of dementia associated with the spread of pathology to cortical regions. Patients exhibiting symptoms have already undergone significant neuronal loss without chance for recovery. Analysis of disease specific changes in gene expression directly from human patients can uncover invaluable clues about a still unknown etiology, the potential of which grows exponentially as additional gene regulatory measures are questioned. Epigenetic mechanisms are emerging as important components of neurodegeneration, including PD; the extent to which methylation changes correlate with disease progression has not yet been reported. This collection of work aims to define multiple layers of PD that will work toward developing biomarkers that not only could improve diagnostic accuracy, but also push the boundaries of the disease detection timeline. I examined changes in gene expression, alternative splicing of those gene products, and the regulatory mechanism of DNA methylation in the Parkinson’s disease system, as well as the pathologically related Alzheimer’s disease (AD). I first used RNA sequencing (RNAseq) to evaluate differential gene expression and alternative splicing in the posterior cingulate cortex of patients with PD and PD with dementia (PDD). Next, I performed a longitudinal genome-wide methylation study surveying ~850K CpG methylation sites in whole blood from 189 PD patients and 191 control individuals obtained at both a baseline and at a follow-up visit after 2 years. I also considered how symptom management medications could affect the regulatory mechanism of DNA methylation. In the last chapter of this work, I intersected RNAseq and DNA methylation array datasets from whole blood patient samples for integrated differential analyses of both PD and AD. Changes in gene expression and DNA methylation reveal clear patterns of pathway dysregulation that can be seen across brain and blood, from one study to the next. I present a thorough survey of molecular changes occurring within the idiopathic Parkinson’s disease patient and propose candidate targets for potential molecular biomarkers.
the disease by a series of motor deficits that manifest over years or decades. It is characterized by degeneration of mid-brain dopaminergic neurons with a high prevalence of dementia associated with the spread of pathology to cortical regions. Patients exhibiting symptoms have already undergone significant neuronal loss without chance for recovery. Analysis of disease specific changes in gene expression directly from human patients can uncover invaluable clues about a still unknown etiology, the potential of which grows exponentially as additional gene regulatory measures are questioned. Epigenetic mechanisms are emerging as important components of neurodegeneration, including PD; the extent to which methylation changes correlate with disease progression has not yet been reported. This collection of work aims to define multiple layers of PD that will work toward developing biomarkers that not only could improve diagnostic accuracy, but also push the boundaries of the disease detection timeline. I examined changes in gene expression, alternative splicing of those gene products, and the regulatory mechanism of DNA methylation in the Parkinson’s disease system, as well as the pathologically related Alzheimer’s disease (AD). I first used RNA sequencing (RNAseq) to evaluate differential gene expression and alternative splicing in the posterior cingulate cortex of patients with PD and PD with dementia (PDD). Next, I performed a longitudinal genome-wide methylation study surveying ~850K CpG methylation sites in whole blood from 189 PD patients and 191 control individuals obtained at both a baseline and at a follow-up visit after 2 years. I also considered how symptom management medications could affect the regulatory mechanism of DNA methylation. In the last chapter of this work, I intersected RNAseq and DNA methylation array datasets from whole blood patient samples for integrated differential analyses of both PD and AD. Changes in gene expression and DNA methylation reveal clear patterns of pathway dysregulation that can be seen across brain and blood, from one study to the next. I present a thorough survey of molecular changes occurring within the idiopathic Parkinson’s disease patient and propose candidate targets for potential molecular biomarkers.
ContributorsHenderson, Adrienne Rose (Author) / Huentelman, Matthew J (Thesis advisor) / Newbern, Jason (Thesis advisor) / Dunckley, Travis L (Committee member) / Jensen, Kendall (Committee member) / Wilson, Melissa (Committee member) / Arizona State University (Publisher)
Created2019
Description
Valley Fever (VF), is a potentially lethal fungal pneumonia caused by Coccidioides spp., which is estimated to cause ~15-30% of all community-acquired pneumonias in the highly endemic Greater Phoenix and Tucson areas of Arizona. However, an accurate antigen-based diagnostic is still lacking. In order to identify protein and glycan antigen biomarkers of infection, I used a combination of genomics, proteomics and glycomics analyses to provide evidence of genus-specific proteins and glycosylations. The next goal was to determine if Coccidioides-specific glycans were present in biological samples from VF patients. Urine collected from 77 humans and 63 dogs were enriched for glycans and evaluated by mass spectrometry for Coccidioides-specific glycans and evaluated against a panel of normal donor urines, urines from patients infected with other fungi, and fungal cultures from closely related pneumonia-causing fungi. A combination of 6 glycan biomarkers was 100% sensitive and 100% specific in the diagnosis of human VF subjects, while only 3 glycan biomarkers were needed for 100% sensitivity and 100 specificity in the diagnosis of dog VF subject. Additionally, a blinded trial of 23 human urine samples was correctly able to classify urine samples with 93.3% sensitivity and 100% specificity. The results of this research provides evidence that Coccidioides genus-specific glycosylations have potential as antigens in diagnostic assays.
ContributorsMitchell, Natalie M (Author) / Lake, Douglas F (Thesis advisor) / Bean, Heather D (Committee member) / Grys, Thomas E (Committee member) / Magee, Dewey M (Committee member) / Arizona State University (Publisher)
Created2019
Description
Quiescin sulfhydryl oxidase 1 (QSOX1) is an enzyme that catalyzes disulfide bond formation by oxidizing two free sulfhydryl groups. QSOX1 consists of a thioredoxin (Trx) and an ERV (essential for respiration and viability)/ALR (augmenter of liver regeneration) domain which each contain CxxC motifs that work to bind to substrates and shuttle electrons to a flavin adenine dinucleotide (FAD) cofactor that accepts the electrons and reduces molecular oxygen to hydrogen peroxide. Investigation of the role of QSOX1 in cancer progression started when it was found at higher abundance in pancreatic ductal adenocarcinoma (PDA) patient plasma compared to healthy normal donor plasma. Increased expression in QSOX1 has been further identified in breast, lung, kidney, prostate, and other cancers. QSOX1 expression is associated with cell proliferation and invasion in vitro and tumor growth in vivo. Additionally, the enzymatic activity of QSOX1 in the extracellular matrix (ECM) is important for cell invasion in vitro. Small molecule inhibitors of QSOX1 have been shown to have antitumorigenic properties in vitro and in vivo. It was hypothesized that monoclonal antibodies (mAbs) against QSOX1 would inhibit cell invasion in vitro. In this work, mice were immunized with eukaryotic-derived rQSOX1 for generation of hybridomas. Hundreds of hybridoma clones were screened by enzyme-linked immunosorbent assay (ELISA) and a fluorescent QSOX1 activity assay. Multiple rounds of subcloning and screening identified 2F1.14 and 3A10.6 as mAbs of interest. The genes for the variable regions of the antibodies were rescued and sequenced. The sequences were aligned with the variable region sequences of another published αQSOX1 mAb scFv492.1. 2F1.14 inhibits the enzymatic activity of QSOX1 by binding to the active site of QSOX1, which was determined by epitope mapping against mutants of QSOX1 that contained mutations in the active site. 3A10.6 did not appear to inhibit the function of QSOX1 in the activity assay; however, it, along with 2F1.14, suppressed tumor invasion in a 3D invasion model. These findings support the developing idea that QSOX1 is a viable target for cancer treatment because targeted inhibition of QSOX1 extracellularly reduced invasive activity. The mAbs and rQSOX1 variants produced here can serve as tools in furthering the characterization of QSOX1 and its role in cancer.
ContributorsKoelbel, Calvin John (Author) / Lake, Douglas (Thesis advisor) / Chen, Qiang "Shawn" (Committee member) / Ho, Thai (Committee member) / Arizona State University (Publisher)
Created2019
Description
Biological fluids, in particular blood plasma, provide a vital source of information on the state of human health. While specific detection of biomarker species can aid in disease diagnostics, the complexity of plasma makes analysis challenging. Despite the challenge of complex sample analysis, biomarker quantification has become a primary interest in biomedical analysis. Due to the extremely specific interaction between antibody and analyte, immunoassays are attractive for the analysis of these samples and have gained popularity since their initial introduction several decades ago. Current limitations to diagnostics through blood testing include long incubation times, interference from non-specific binding, and the requirement for specialized instrumentation and personnel. Optimizing the features of immunoassay for diagnostic testing and biomarker quantification would enable early and accurate detection of disease and afford rapid intervention, potentially improving patient outcomes. Improving the limit of quantitation for immunoassay has been the primary goal of many diverse experimental platforms. While the ability to accurately quantify low abundance species in a complex biological sample is of the utmost importance in diagnostic testing, models illustrating experimental limitations have relied on mathematical fittings, which cannot be directly related to finite analytical limits or fundamental relationships. By creating models based on the law of mass action, it is demonstrated that fundamental limitations are imposed by molecular shot noise, creating a finite statistical limitation to quantitative abilities. Regardless of sample volume, 131 molecules are necessary for quantitation to take place with acceptable levels of uncertainty. Understanding the fundamental limitations of the technique can aid in the design of immunoassay platforms, and assess progress toward the development of optimal diagnostic testing. A sandwich-type immunoassay was developed and tested on three separate human protein targets: myoglobin, heart-type fatty acid binding protein, and cardiac troponin I, achieving superior limits of quantitation approaching ultimate limitations. Furthermore, this approach is compatible with upstream sample separation methods, enabling the isolation of target molecules from a complex biological sample. Isolation of target species prior to analysis allows for the multiplex detection of biomarker panels in a microscale device, making the full optimization of immunoassay techniques possible for clinical diagnostics.
ContributorsWoolley, Christine F (Author) / Hayes, Mark A. (Thesis advisor) / Ros, Alexandra (Committee member) / LaBaer, Joshua (Committee member) / Arizona State University (Publisher)
Created2015
Description
The search for life on Mars is a major NASA priority. A Mars Sample Return
(MSR) mission, Mars 2020, will be NASA's next step towards this goal, carrying an instrument suite that can identify samples containing potential biosignatures. Those samples will be later returned to Earth for detailed analysis. This dissertation is intended to inform strategies for fossil biosignature detection in Mars analog samples targeted for their high biosignature preservation potential (BPP) using in situ rover-based instruments. In chapter 2, I assessed the diagenesis and BPP of one relevant analog habitable Martian environment: a playa evaporite sequence within the Verde Formation, Arizona. Coupling outcrop-scale observations with laboratory analyses, results revealed four diagenetic pathways, each with distinct impacts on BPP. When MSR occurs, the sample mass returned will be restricted, highlighting the importance of developing instruments that can select the most promising samples for MSR. Raman spectroscopy is one favored technique for this purpose. Three Raman instruments will be sent onboard two upcoming Mars rover missions for the first time. In chapters 3-4, I investigated the challenges of Raman to identify samples for MSR. I examined two Raman systems, each optimized in a different way to mitigate a major problem commonly suffered by Raman instruments: background fluorescence. In Chapter 3, I focused on visible laser excitation wavelength (532 nm) gated (or time-resolved Raman, TRR) spectroscopy. Results showed occasional improvement over conventional Raman for mitigating fluorescence in samples. It was hypothesized that results were wavelength-dependent and that greater fluorescence reduction was possible with UV laser excitation. In Chapter 4, I tested this hypothesis with a time-resolved UV (266 nm) gated Raman and UV fluorescence spectroscopy capability. I acquired Raman and fluorescence data sets on samples and showed that the UV system enabled identifications of minerals and biosignatures in samples with high confidence. The results obtained in this dissertation may inform approaches for MSR by: (1) refining models for biosignature preservation in habitable Mars environments; (2) improving sample selection and caching strategies, which may increase the success of Earth-based biogenicity studies; and (3) informing the development of Raman instruments for upcoming rover-based missions.
(MSR) mission, Mars 2020, will be NASA's next step towards this goal, carrying an instrument suite that can identify samples containing potential biosignatures. Those samples will be later returned to Earth for detailed analysis. This dissertation is intended to inform strategies for fossil biosignature detection in Mars analog samples targeted for their high biosignature preservation potential (BPP) using in situ rover-based instruments. In chapter 2, I assessed the diagenesis and BPP of one relevant analog habitable Martian environment: a playa evaporite sequence within the Verde Formation, Arizona. Coupling outcrop-scale observations with laboratory analyses, results revealed four diagenetic pathways, each with distinct impacts on BPP. When MSR occurs, the sample mass returned will be restricted, highlighting the importance of developing instruments that can select the most promising samples for MSR. Raman spectroscopy is one favored technique for this purpose. Three Raman instruments will be sent onboard two upcoming Mars rover missions for the first time. In chapters 3-4, I investigated the challenges of Raman to identify samples for MSR. I examined two Raman systems, each optimized in a different way to mitigate a major problem commonly suffered by Raman instruments: background fluorescence. In Chapter 3, I focused on visible laser excitation wavelength (532 nm) gated (or time-resolved Raman, TRR) spectroscopy. Results showed occasional improvement over conventional Raman for mitigating fluorescence in samples. It was hypothesized that results were wavelength-dependent and that greater fluorescence reduction was possible with UV laser excitation. In Chapter 4, I tested this hypothesis with a time-resolved UV (266 nm) gated Raman and UV fluorescence spectroscopy capability. I acquired Raman and fluorescence data sets on samples and showed that the UV system enabled identifications of minerals and biosignatures in samples with high confidence. The results obtained in this dissertation may inform approaches for MSR by: (1) refining models for biosignature preservation in habitable Mars environments; (2) improving sample selection and caching strategies, which may increase the success of Earth-based biogenicity studies; and (3) informing the development of Raman instruments for upcoming rover-based missions.
ContributorsShkolyar, Svetlana (Author) / Farmer, Jack (Thesis advisor) / Semken, Steven (Committee member) / Sharp, Thomas (Committee member) / Shim, Sang-Heon Dan (Committee member) / Youngbull, Aaron Cody (Committee member) / Arizona State University (Publisher)
Created2016