Browsing by Subject "biomarker"
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Item Combining environmental chemistry, somatic biomarkers, and population genetics: an innovative approach in wildlife ecotoxicology(Texas A&M University, 2004-09-30) Matson, Cole WesleyThe Caspian region and specifically the Apsheron peninsula of Azerbaijan is known to be polluted with a variety of environmental contaminants, making risk assessment difficult. The wetlands of Sumgayit contain particularly complex mixtures of contaminants. Flow cytometry and the micronucleus assay were used to assess chromosomal damage in aquatic turtles and frogs inhabiting contaminated wetlands in Azerbaijan. By evaluating biomarkers that are indicative of somatic effects, elevated chromosomal damage was documented at several sites in Azerbaijan relative to reference sites. Sediment samples were analyzed for polycyclic aromatic hydrocarbons (PAHs), organochlorines (OCs), and mercury to evaluate contaminant associations with genetic damage. Sediment samples revealed heterogeneous patterns of PAH and mercury concentrations throughout Sumgayit. Significant positive correlations were documented between both PAH and mercury sediment concentrations and chromosomal damage. Population genetic methods were employed to study the effects of long-term chronic contaminant exposure in marsh frogs from Sumgayit. The Sumgayit region has reduced levels of genetic diversity, likely due to environmental degradation. One of the most contaminated sites in Sumgayit, WTP, appears to be a source of new mutations as a result of an increased mutation rate. Finally, the Sumgayit region seems to act as an ecological sink, with levels of gene flow into the region exceeding gene flow out of the region. This study provides not only exposure and biomarker data, but also an integrated method for assessing the cumulative population impacts of contaminant exposure by studying both population genetic and evolutionary effects. The results presented here will be used in conjunction with those of ongoing research involving both wildlife and humans to develop comprehensive ecological and human risk assessments.Item Early markers of breast cancer in nipple aspirate fluid(2007-07-12) Yafei Huang; Lee-Jane W Lu; Suzanne AW Fuqua; Karl E Anderson; Jonanthan Ward; Anthony M Haag; Alexander KuroskyNipple aspirate fluid (NAF) refers to the small amount of secretion that is found in breast ducts/lobules of most non-lactating women. This fluid can be collected repeatedly and non-invasively via the nipple using a modified breast pump, and therefore, it is considered to be a potential source for identifying markers of breast cancer. The purpose of this study was to understand factors associated with the ability to secrete fluid and factors associated with the major protein profiles in NAF; and to identify protein profiles of NAF in a group of healthy non-lactating women who were 30-40 years old, not pregnant, not breastfeeding, and not taking contraceptive medications.\r\n\r\nAmong 238 women studied, 66% were secretors of NAF. Using multivariate logistic regression models, higher dietary intake of lactose [Odds Ratio (OR)=2.7; 95% Confidence Interval (CI): 1.5-4.8], earlier menarche (OR=0.8, CI: 0.7-1.0), being parous (OR=2.3, CI: 1.0-5.6), and older at first childbirth (OR=1.5, CI: 1.0-2.1) were found to be independent and positive predictors for being a secretor of NAF. These findings suggest that dietary intake of lactose, a modifiable factor, may be used to change the NAF secretor status of women. \r\n\r\nNAF were analyzed for major proteins. Two major types of protein profiles, type I and type II, were identified. Type I NAF contains proteins found in cystic disease fluid of the breast, whereas type II NAF is enriched in milk-associated proteins. Using multiple logistic regression, type I NAF was predicted independently (P<0.05) by higher body fat mass (Odds Ratio=3.0; CI: 1.5-6.1), more years since last childbirth (OR=2.6; 95% CI: 1.3-5.2) and a higher percentage of calories from saturated fat (OR=4.1; 95% CI: 1.1-14.6). These results suggest that protein profiles of NAF might be influenced by amounts and/or types of dietary and body fat. \r\n\r\nTwo different analytical strategies, 2D gel analysis coupled with MALDI-TOF/TOF, and 1D gel coupled with LC-MS/MS, were used to characterize protein profiles of type I and II NAF. Using these two strategies, a total of 99 proteins were identified: 13 unique to type I NAF, 57 unique to type II NAF, and 29 common to both types. These strategies will be used to characterize proteins in NAF of breast cancer cases. \r\nItem Tracking Oil from the Deepwater Horizon Oil Spill in Barataria Bay Sediments(2013-05-03) Dincer, ZeynepIn April 2010, approximately 4.9 million barrels of oil were accidentally released into the Gulf of Mexico during the Deepwater Horizon Macondo Mc252 Oil Spill. Some of the surface oil was carried by prevailing winds and currents and reached the coast of Louisiana impacting marsh and marine ecosystems. One and a half years after this incident, a set of oiled marsh samples (2 grab samples) coupled with nearby subtidal and intertidal cores (12 cores) were collected from Barataria Bay, Louisiana to determine the probable source of petroleum residues present and to characterize the chemical composition of the oil. Plus, pre-spill core which was collected from Barataria Bay in 2007 was analyzed to identify the background hydrocarbon composition of the area. Polycyclic aromatic hydrocarbons (PAH), total petroleum hydrocarbons (TPH), biomarker, and stable carbon isotope compositions of selected samples were detected using a GC-MS and an elemental analyzer Conflo system coupled to a DeltaPlusXP isotope ratio mass spectrometer. The comprehensive chemical data allowed us to classify the pre and post-spill samples into 4 Groups. According to this classification, Group 1 and Group 2 samples had the highest concentrations of petroleum-derived hydrocarbons. Group 3 and background samples, on the other hand, was dominated by biogenic signatures. Although a direct connection between the detected and spilled Macondo oils results are complicated due to confounding factors (e.g., already present hydrocarbons and weathering processes), our biomarker data indicates that both oils have similar signatures. This close genetic relationship was also identified by stable carbon isotope analysis. The impact of the Macondo Mc252 Oil Spill in Barataria Bay appears to be limited to areas closer to the source. The oil has undergone moderate weathering and has penetrated into, the at least, the top 9 cm sediments. Additionally, to examine the decadal-scale history of sedimentation in these marshes, a sediment core was analyzed for the radioisotope 137Cs. The observed sedimentation rate of 0.39 cm/yr shows that oil pollutant input into Barataria Bay has been ongoing for at least 50-60 years.Item Wavelet methods and statistical applications: network security and bioinformatics(Texas A&M University, 2005-11-01) Kwon, DeukwooWavelet methods possess versatile properties for statistical applications. We would like to explore the advantages of using wavelets in the analyses in two different research areas. First of all, we develop an integrated tool for online detection of network anomalies. We consider statistical change point detection algorithms, for both local changes in the variance and for jumps detection, and propose modified versions of these algorithms based on moving window techniques. We investigate performances on simulated data and on network traffic data with several superimposed attacks. All detection methods are based on wavelet packets transformations. We also propose a Bayesian model for the analysis of high-throughput data where the outcome of interest has a natural ordering. The method provides a unified approach for identifying relevant markers and predicting class memberships. This is accomplished by building a stochastic search variable selection method into an ordinal model. We apply the methodology to the analysis of proteomic studies in prostate cancer. We explore wavelet-based techniques to remove noise from the protein mass spectra. The goal is to identify protein markers associated with prostate-specific antigen (PSA) level, an ordinal diagnostic measure currently used to stratify patients into different risk groups.