Angiogenesis by either normal or neoplastic cells involves a delicate balance of both angiogenic and angiostatic regulators. In the ovary, normal physiological angiogenesis occurs around the developing follicle and corpus luteum in response to hormonal shifts. Interestingly, carcinomas arising from the ovary are usually highly vascularized and are commonly clinically observed to produce cyst fluids or ascites which contain both angiostatic and/or angiogenic regulators. However, in contrast to normal angiogenesis, angiogenesis associated with epithelial ovarian cancer usually produces aberrant vasculature that may promote neoplastic progression. Therefore, the ovary and ovarian cancers provide models to study the mechanisms governing the strict balance of angioregulators in both normal and tumor angiogenesis. While most studies to date have focused on angiogenic regulators for normal and aberrant angiogenesis, we investigated the potential for dysregulation of angiostatic regulators to contribute to the etiology of epithelial ovarian cancer. Therefore, in this study, we examined two angiostatic regulators, angiostatin and semaphorin 3F, in epithelial ovarian cancer. Angiostatin, a cleavage product of the circulating zymogen plasminogen, was isolated from serum and urine of mice bearing a Lewis lung carcinoma and in vivo studies have demonstrated its potent angiostatic properties. Thus, we investigated the potential prognostic/diagnostic advantage of aberrant angiostatin expression with epithelial ovarian cancer. We found that urinary angiostatin, compared to other angioregulators in plasma or urine, could serve as an effective biomarker for early detection of epithelial ovarian cancer, especially when used in combination with cancer antigen 125. Additionally, urinary angiostatin correlated with both recurrent disease as well as successful tumor ablation further supporting its potential as a disease biomarker. Alternative biological functions for the axon guidance molecule, semaphorin 3F, have been reported particularly in regard to angiogenesis, tumor progression and metastasis. However, the underlying mechanisms governing semaphorin 3F regulation and dysregulation remain unclear. Therefore, we first investigated the clinical relationship between semaphorin 3F expression and epithelial ovarian cancer progression. These immunohistological studies revealed that, similar to lung cancer, semaphorin 3F expression decreased with progression supporting a tumor suppressor-like role for semaphorin 3F. Additionally, we found that calcium, an essential cellular signaling molecule, could mediate transcriptional suppression of semaphorin 3F expression in a CREB-dependent manner. Lastly, given the antagonistic relationship between semaphorin 3F and vascular endothelial growth factor, we sought to determine whether semaphorin 3F and vascular endothelial growth factor promoted opposing effects on a common downstream target. In the course of these studies we determined that telomerase is a novel molecular target of semaphorin 3F in ovarian cancer cells such that semaphorin 3F suppresses telomerase activity while vascular endothelial growth factor promotes telomerase activity. In addition, we found that the inverse relationship between semaphorin 3F and telomerase was mediated through transcriptional inhibition of the hTERT promoter by semaphorin 3F. In conclusion, this research shows that dysregulation of the angiostatic regulators, angiostatin and semaphorin 3F, may contribute to the etiology of epithelial ovarian cancer. In the future, dysregulation of these and other angiostatic regulators may be exploited for therapeutic intervention or as biomarkers for early detection which would allow women more treatment choices and hopefully, reduce the mortality associated with this insidious disease.

Geological records of past sea ice, such as those contained in Arctic marine sediments, offer an opportunity to strengthen our understanding of long-term sea ice variability, provided unambiguous paleo-sea ice proxies can be developed. One such recently proposed proxy is IP₂₅, a highly branched isoprenoid alkene biosynthesized exclusively by sea-ice dwelling diatoms (Haslea spp.), which is well preserved in marine sediments and could be used to reconstruct past changes in spring sea-ice extent. However, little is known about regional-scale controls on IP₂₅ production in sea ice, limiting its wider applicability as a paleo-sea-ice proxy. To address this issue we examined the distributions of IP₂₅ and the marine productivity biomarkers dinosterol and brassicasterol in a suite of surface sediment samples distributed across the Arctic. We find a statistically significant, logarithmic relationship between IP₂₅ and spring sea ice cover in samples from arctic and subarctic sites in the Pacific (n = 96, r² = 0.67, P < 0.0001) and the Atlantic n = 25, r² = 0.50, P < 0.0001), though the absolute concentrations of IP₂₅ are generally higher in the Atlantic (1.6 - 166.4 [mu]g/g OC) than in the Pacific (0 - 38.5 [mu]g/g OC) for equivalent sea-ice cover, and there are regional and basin-specific differences in the slope of the IP₂₅ - sea ice relationship. After normalization of IP₂₅ concentrations to that of a productivity biomarker (e.g., dinosterol; the PDIP₂₅ index) the proxy-sea ice relationship in greatly improved for all regions (r² = 0.86 and r² = 0.75 for Atlantic and Pacific, respectively) and most of the basin specific differences in the rate of change of IP₂₅ with sea ice are removed. This suggests that productivity plays an important secondary role in controlling IP₂₅ concentrations. However, the use of the PDIP₂₅ index does not change the absolute differences in concentrations seen in the Atlantic and the Pacific, and previously published data from Fram Strait remain anomalous when compared to the rest of our data. This suggests that there are additional, yet unidentified controls on the IP₂₅ proxy - sea ice relationship, which may hinder the development of an Arctic-wide calibration but that the PDIP₂₅ index is a viable tool for local and regional sea ice reconstructions. / text

Recent advancements in nanotechnology create a need for a better understanding of the underlying physical processes that lead to the different behavior of nanoscale structures in comparison to bulk materials. The influence of the surrounding environment on the physical and optical properties of nanoscale objects embedded inside them is of particular interest. This research is focused on the optical properties of semiconductor quantum dots which are zero-dimensional nanostructures. There are many investigation techniques for measuring the local parameters and structural characteristics of Quantum Dot structures. They include X-ray diffraction, Transmission Electron Microscopy, Wavelength Dispersive Spectroscopy, etc. However, none of these is suitable for the study of large areas of quantum dots matrices and substrates. The existence of spatial inhomogeneity in the quantum dots allows for a deeper and better understanding of underlying physical processes responsible in part icular for the observed changes in photoluminescence (PL) characteristics. Spectroscopic PL mapping can reveal areas of improved laser performance of InAs/InGaAs quantum dots structures. Establishing physical mechanisms responsible for two different types of spatial PL inhomogeneity in InAs/InGaAs quantum dots structures for laser applications was the first objective of this research. Most of the bio-applications of semiconductor quantum dots utilize their superior optical properties over organic fluorophores. Therefore, optimization of QD labeling performance with biomolecule attachment was another focus of this research. Semiconductor quantum dots suspended in liquids were investigated, especially the influence of surrounding molecules that may be attached or bio-conjugated to the quantum dots for specific use in biological reactions on the photoluminescence spectrum. Provision of underlying physical mechanisms of optical property instability of CdSe/ZnS quantum dots used for biologi cal applications was in the scope of this research. Bioconjugationand functionalization are the fundamental issues for bio-marker tagging application of semiconductor quantum dots. It was discovered that spatially resolved photoluminescence spectroscopy and PL photo-degradation kinetics can confirm the bioconjugation. Development of a methodology that will allow the spectroscopic confirmation of bio-conjugation of quantum dot fluorescent tags and optimization of their performance was the final goal for this research project.

In the U.S., the number of prostate biopsies increases annually. This is partly due to elevated prostate specific antigen (PSA) values identified during PC screening. This study's goal was improving prostate cancer (PC) detection through developing a clinical decision rule (CDR), based on an elevated PSA and laboratory biomarkers. This decision rule could be used after an elevated PSA, providing the patient and clinician information to consider prior to biopsy. This cross-sectional study evaluated men from the Tampa, Florida, James A. Haley (JH) VA (N=1,378), from January 1, 1998, through April 15, 2005. The study hypothesized that specific lab biomarkers among JH VA PC cases would differ significantly from JH VA patients without PC. The following biomarkers were related to PC: hemoglobin (HGB) (OR=1.42 95%CI 1.27, 1.59); red blood cell count (RBC) (OR=2.52 95%CI 1.67, 3.78); PSA (OR=1.04 95%CI 1.03, 1.05); and, creatinine (OR=1.55 95%CI 1.12, 2.15). This study attempted to determine whether including specific biomarkers (that are related to systemic diseases associated with advancing PC) could improve PC prediction (versus PSA alone). Comparing all PC stages versus non-cancerous conditions, the Receiver Operator Characteristic (ROC) curve area under the curve (AUC) expanded (increasing the probability of correctly classifying PC): PSA (alone) 0.59 (95% CI 0.55, 0.61); CDR model 0.68 (95%CI 0.65, 0.71), and the positive predictive value (PPV) increased: PSA 44.7%; CDR model 61.8%. Comparing PC (stages B, C, D) vs. other, the ROC AUC increased: PSA (alone) 0.63 (95% CI 0.58, 0.66); CDR model 0.68 (95% CI 0.68, 0.75), and the PPV increased: 20.6% (PSA); CDR model 55.3%. These results suggest evaluating certain biomarkers might improve PC prediction prior to biopsy. Moreover, the biomarkers may be more helpful in detecting clinically relevant PC. Follow-up studies should begin with replicating the study on different U.S. VA data-sets involving multiple practices.

In this dissertation, guided surface acoustic wave sensors were investigated theoretically and experimentally in detail for immunosensing applications. Shear horizontal polarized guided surface acoustic wave propagation for mass loading sensing applications was modeled using analytical modeling and characterized by perturbation analysis. The model verification was performed experimentally and a surface acoustic wave immunosensor case study was presented. The results of the immunosensing were also investigated using the perturbation analysis. Guided surface acoustic wave propagation problem was investigated in detail for gravimetric (or mass loading) guided wave sensors, more specifically for immunosensors. The analytical model was developed for multilayer systems taking viscoelasticity into account. The closed form algebraic solutions were obtained by applying appropriate boundary conditions. A numerical approach was used to solve dispersion equation. Detailed parametric investigation of dispersion curves was conducted using typical substrate materials and guiding layers. Substrate types of ST-cut quartz, 41° YX lithium Niobate and 36° YX lithium tantalate with guiding layers of silicon dioxide, metals (chromium and gold), and polymers (Parylene-C and SU-8) were investigated. The effects of frequency and degree of viscoelasticity were also studied. The results showed that frequency only has effect on thickness with same shaped dispersion curves. Dispersion curves were found to be unaffected by the degree of viscoelasticity. It was also observed that when there was a large shear velocity difference between substrate and guiding layer, a transition region with a gradual decrease in phase velocity was obtained. However, when shear velocities were close, a smooth transition was observed. Furthermore, it was observed that, large density differences between substrate and guiding layer resulted in sharp and with nearly constant slope transition. Smooth transition was observed for the cases of minimal density differences. Experimental verification of the model was done using multi-layer photoresists. It was shown that with modifications, the model was able to represent the cases studied. Perturbation equations were developed with first order approximations by relating the slope of the dispersion curves with sensitivity. The equations were used to investigate the sensitivity for material selection (substrate, guiding layer, and mass perturbing layer) and degree of viscoelasticity. The investigations showed that the sensitivity was increased by using guiding layers with lower shear velocities and densities. Among the guiding layers investigated, Parylene C showed the highest sensitivity followed by gold and chrome. The perturbation investigations were also extended to viscoelasticity and to protein layers for immunosensing applications. It was observed that, viscous behavior resulted in slightly higher sensitivity; and sensitivity to protein layers was very close to sensitivity for polymers. The optimum case is found to be ST-cut quartz with Parylene-C guiding layer for protein layer sensing. Finally, an immunosensing case study was presented for selective capture of protein B-cell lymphoma 2 (Bcl-2), which is elevated in many cancer types including ovarian cancer. The immunosensor was designed, fabricated, and experimentally characterized. An application-specific surface functionalization scheme with monoclonal antibodies, ODMS, Protein A/G and Pluronic F127 was developed and applied. Characterization was done using the oscillation frequency shift of with sensor used as the feedback element of an oscillator circuit. Detection of Bcl-2 with target sensitivity of 0.5 ng/ml from buffer solutions was presented. A linear relation between frequency shift and Bcl-2 concentration was observed. The selectivity was shown with experiments by introducing another protein, in addition to Bcl-2, to the buffer. It was seen that similar detection performance of Bcl-2 was obtained even with presence of control protein in very high concentrations. The results were also analyzed with perturbation equations.

Metagenomics holds unyielding potential in uncovering relationships within microbial communities that have yet to be discovered, particularly because the field circumvents the need to isolate and culture microbes from their natural environmental settings. A common research objective is to detect biomarkers, microbes are associated with changes in a status. For instance, determining such microbes across conditions such as healthy and diseased groups for instance allows researchers to identify pathogens and probiotics. This is often achieved via analysis of differential abundance of microbes. The problem is that differential abundance analysis looks at each microbe individually without considering the possible associations the microbes may have with each other. This is not favorable, since microbes rarely act individually but within intricate communities involving other microbes. An alternative would be variable selection techniques such as Lasso or Elastic Net which considers all the microbes simultaneously and conducts selection. However, Lasso often selects only a representative feature of a correlated cluster of features and the Elastic Net may incorrectly select unimportant features too frequently and erratically due to high levels of sparsity and variation in the data.\par In this research paper, the proposed method AdaLassop is an augmented variable selection technique that overcomes the misgivings of Lasso and Elastic Net. It provides researchers with a holistic model that takes into account the effects of selected biomarkers in presence of other important biomarkers. For AdaLassop, variable selection on sparse ultra-high dimensional data is implemented using the Adaptive Lasso with p-values extracted from Zero Inflated Negative Binomial Regressions as augmented weights. Comprehensive simulations involving varying correlation structures indicate that AdaLassop has optimal performance in the presence multicollinearity. This is especially apparent as sample size grows. Application of Adalassop on a Metagenome-wide study of diabetic patients reveals both pathogens and probiotics that have been researched in the medical field.

The research described in this dissertation is divided into two sections. The first section focuses on mass spectrometry-based bottom-up proteomics application to identify fungal protein biomarkers of invasive aspergillosis infection. The second part focuses on instrument development to improve current ionization and dissociation technologies for characterizing topology and substructure of protein complexes. Part I of this dissertation describes the identification and validation of protein biomarkers for Invasive Aspergillosis (IA), a fatal pulmonary infection. Aspergillus fumigatus, the organism responsible for this disease, is an opportunistic fungus. Immunocompromised individuals can suffer from IA due to impaired immune response. The current diagnostic tools are time-consuming and have variable sensitivity and specificity. Hence, treatments for IA are often administered too late. The goal of this research is to use mass spectrometry to identify and validate novel fungal protein biomarkers for IA. To tackle this challenge, several systems were studied. Commercial Aspergillus antigen was used for method development, and to serve as standards for spiking and comparison. Mouse models of different disease manifestations were used in the initial study to compare proteomic differences in carefully controlled disease states. Although it was not successful in providing candidate biomarkers, the mouse samples provided host response protein data. Human patient samples yielded the most promising results. Several Aspergillus proteins have been identified and validated from patient bronchoalveolar lavage fluid, and could have the potential to be later used on a diagnostic platform. Part II describes two instrument development projects: incorporation of a surface-induced dissociation device into a commercial ion mobility time-of-flight mass spectrometer, and the development of a paper spray ionization source. Protein complexes are often studied using collision-induced dissociation (CID), which does not provide enough substructure information. Surface-induced dissociation (SID) allows access to higher energy fragmentation pathways, which generates more useful substructure information. Its potential is demonstrated with three systems here-- one metal cluster and two protein complexes. All systems show that SID can provide more useful structural information than CID under similar conditions. The development of a paper spray (PS) source for protein complex ionization provides another way to study protein complexes. Chapter 9 shows that this ionization method can also be applied to protein complexes. Under the same conditions as its nanospray counterpart, similar mass spectra can be obtained using PS. This exciting result is the first demonstrations that PS can be used for protein complexes while maintaining each protein complex's native structure and conformation.

The objectives of this study was to examine the efficacy and safety of graded doses of c9, t11, t10, c12 CLA isomers on body composition, energy expenditure, lipid profile and hepatic biomarkers in hamsters. Male Golden Syrian hamsters (n=105) were randomized to seven treatments (control; 1, 2, 3% of c9, t11; 1, 2, 3% of t10, c12) for 28 days. Compared with control, 1% and 3% t10, c12 had lowered food intake with all three doses of t10, c12 lowering (p<0.0001) body fat mass (g). Groups fed with 1, 2, 3% t10, c12 and 3% c9, t11 treatments showed higher lean mass compared to control and other treatment groups. However, neither body weights, nor serum HDL or triglyceride levels differed across treatment groups. The 3% t10, c12 groups exhibited higher (p<0.0001) cholesterol and LDL-C levels compared to control or other treatment groups. The 2% and 3% t10, c12 groups also presented elevated ALT level (p<0.05). The present data suggest that 3% t10, c12 possess potential adverse effects on liver and posing unfavorable change in lipid profile.

Statement of Problem Telomere dynamics in the three-dimensional (3D) space of the mammalian nucleus plays an important role in the maintenance of genomic stability. However, the telomere distribution in 3D nuclear space of normal and tumor cells was unknown when the study was initiated. Methods Telomere fluorescence in situ hybridization (FISH) and 3D molecular imaging, deconvolution, and analysis were used to investigate telomere organization in normal, immortalized and tumor cells from mouse and human cell lines, and primary tissues. Results Telomeres are organized in a non-overlapping manner and in a cell-cycle dependant fashion in normal cells. In the late G2 phase of cell cycle, telomeres are assembled into a flattened sphere that is termed the telomeric disk In contrast, the telomeric disk is disrupted in the tumor cells. Moreover, telomeric aggregates (TAs) are found in tumor cells. Conditional c-Myc over-expression induces telomeric aggregation leading to the onset of breakage-bridge-fusion cycles and subsequent chromosomal abnormality. Conclusions Telomeres are distributed in a nonrandom and dynamic fashion in the 3D space of a normal cell. Telomeric aggregates are present in cells with genomic instability such as tumor cells and cells with deregulation of c-Myc. Consequently, TA can be a useful biomarker for research in cancer and other disease processes.

In 2012, more than 1.6 million new cases of breast cancer were diagnosed and about half a million women died of breast cancer. The incidence has increased in the developing world. The mortality, however, has decreased. This is thought to partly be the result of advances in diagnosis and treatment. Studying tissue samples from biopsies through a microscope is an important part of diagnosing breast cancer. Recent techniques include camera-equipped microscopes and whole slide scanning systems that allow for digital high-throughput scanning of tissue samples. The introduction of digital pathology has simplified parts of the analysis, but manual interpretation of tissue slides is still labor intensive and costly, and involves the risk for human errors and inconsistency. Digital image analysis has been proposed as an alternative approach that can assist the pathologist in making an accurate diagnosis by providing additional automatic, fast and reproducible analyses. This thesis addresses the automation of conventional analyses of tissue, stained for biomarkers specific for the diagnosis of breast cancer, with the purpose of complementing the role of the pathologist. In order to quantify biomarker expression, extraction and classification of sub-cellular structures are needed. This thesis presents a method that allows for robust and fast segmentation of cell nuclei meeting the need for methods that are accurate despite large biological variations and variations in staining. The method is inspired by sparse coding and is based on dictionaries of local image patches. It is implemented in a tool for quantifying biomarker expression of various sub-cellular structures in whole slide images. Also presented are two methods for classifying the sub-cellular localization of staining patterns, in an attempt to automate the validation of antibody specificity, an important task within the process of antibody generation.  In addition, this thesis explores methods for evaluation of multimodal data. Algorithms for registering consecutive tissue sections stained for different biomarkers are evaluated, both in terms of registration accuracy and deformation of local structures. A novel region-growing segmentation method for multimodal data is also presented. In conclusion, this thesis presents computerized image analysis methods and tools of potential value for digital pathology applications.