Thesis (M.S.)--University of Texas at El Paso, 2009. / Title from title screen. Vita. CD-ROM. Includes bibliographical references. Also available online.

Uranium has been mined for many years and used for fuel for nuclear reactors and materials for atomic weapons, ammunition, and armor. While the radioactivity associated with uranium mining has been linked to the development of lung and kidney cancers, and leukemia, little is known about the direct chemical genotoxicity of uranium. The overall hypothesis of the current research is that uranium can produce DNA damage by chemical genotoxicity mechanisms. Three specific aims were tested. In Aim 1, specific DNA lesions caused by direct interaction of uranium and DNA were investigated. Chinese Hamster Ovary cells (CHO) with mutations in various DNA repair pathways were exposed to 0 – 300 μM of soluble depleted uranium (DU) as uranyl acetate (UA) for 0 – 48 hr. Results indicate that UA readily enters CHO cells, with the highest concentration localizing in the nucleus. Clonogenics assay shows that UA is cytotoxic in each cell line with the greatest cytotoxicity in the base excision repair deficient EM9 cells and the nuclear excision repair deficient UV5 cells compared to the non-homologous end joining deficient V3.3 cells and the parental AA8 cells after 48 hr. This indicates that UA is forming DNA adducts that may be producing single strand breaks through hydrolysis rather than double strand breaks in CHO cells. Fast Micromethod® results indicate an increased amount of single strand breaks in the EM9 cells after 48 hr UA exposure compared to the V3.3 and AA8 cells. In Aim 2, the role of oxidative stress in producing DNA lesions was determined. Cellular oxidative stress has been implicated in the genotoxicity of many heavy metals as a mechanism of induced DNA damage. To investigate this possible mechanism, human bronchial epithelial cells (16HBE14o⁻) were exposed to 30 ppb (0.13 μM U) UA for 2 – 24 hr. UA did not significantly induce oxidative stress compared to untreated cells at 3 – 4 hr time points. These results suggest that cellular oxidative stress is not a major pathway of DU genotoxicity at low concentrations. In Aim 3, DNA damage response to uranium-induced DNA damage was investigated. It has been widely reported that metals can be genotoxic by inhibiting DNA repair. Cultured cells were co-exposed to 0.13 μM UA in the presence of 0 – 25 μM of etoposide for 0 – 48 hr. Results indicate that UA inhibited double strand break repair. Coexposures of etoposide and UA synergistically induced cytotoxicity compared to individual treatments and untreated cells. Co-exposed UA and etoposide treated 16HBE14o⁻ cells exhibited a decrease in phosphorylation of DNA repair proteins compared to etoposide treatments. Untreated and UA-treated 16HBE14o⁻ cells did not induce phosphorylation of DNA repair proteins. These results suggest that DU inhibits double strand break DNA repair at low concentrations in the presence of a known DNA double-strand damaging agent, etoposide. The inhibition of DNA repair by DU at environmentally relevant concentrations suggests a novel means by which uranium may exert its genotoxic effects. Results found at low dose exposures are not consistent with alterations seen with radioactivity, suggesting that the effects of uranium at low doses are due to its chemical genotoxic effects. Understanding how uranium reacts with DNA is important to better understand how this suspected carcinogen induces cancer and to help to elucidate mechanisms that produce cancers in people exposed to uranium.

The quality of the spectral data collected by radiological survey systems depends on many factors including the survey environment, configuration of the system and its detectors, and the radionuclides in question. Algorithms in the field of machine learning have the potential to classify data that would be difficult and time-intensive for a human to analyze. Depleted and natural uranium spectra are of particular interest due to known contamination at domestic sites and world-wide. Several machine learning classifiers were developed with data collected from laboratory experiments. This thesis demonstrates the potential of machine learning algorithms to discriminate gamma-ray emitting sources using sparse, or low-count statistic, data. Effectiveness has been demonstrated for discriminating chemical forms of uranium, mixtures with differing uranium isotope distributions, and predicting source masses given certain detector geometries and a known target distribution. All activity has been supported by the U.S. Army Engineering Research and Development Center (ERDC).

Texture evolution of depleted uranium is investigated using a viscoplastic self-consistent model. Depleted uranium, which has the same structure as alpha-uranium, is difficult to model as it has an orthorhombic symmetry structure, as well as many twin systems which must be addressed in order to properly simulate the textural evolution. The VPSC method allowed for a flexible model which could not only encompass the low symmetry component but also the twinning components of depleted uranium. The model focuses on the viscoplastic regime only, neglecting the elastic regime of deformation, and uses a self-consistent method to solve the model. Different deformation processes, such as torsion, rolling, and swaging, are simulated and the theoretical textures, plotted as pole figures or inverse pole figures, are compared with previous experimental textures found for alpha uranium from previous experimental sources. A specific twin system, the (176)[512] system, is also given special consideration. This twin system is a dominant deformation mode for alpha uranium at high strain rates, but is quite elusive in general. Different deformation processes are compared where this twin system is active and not active. This allows comparison on the effect of this twin on the overall texture of depleted uranium. In addition, a sample of depleted uranium from Y12 which was analyzed for (176)[512] twins is compared to theoretical results from a VPSC simulation where the (176)[512] twin is active.

Thesis (M.S.)--Mississippi State University. Department of Electrical and Computer Engineering. / Title from title screen. Includes bibliographical references.

<p>The use of banned toxic weapons in Iraq during Gulf War 1991 started new debates. The increase in cancer cases was the main focus of these issues. The gap in literature motivated this study to find out the correlation between use of DU weapons and its effects on human health. The different probable causes of increase in cancer cases, in Iraq after Gulf War 1991, have been discussed in this study. Three causes; DU, brick kilns smoke near Basra and Kuwait oil fire smoke have been selected. The major emphasis of this study is on use of Depleted Uranium (DU). Different statistical data sets have been used and displayed in the form of maps and graphs using GIS methodologies. It’s hard to say after this GIS based study that the fired Depleted Uranium is the sole cause of increase in cancer incidences in Iraq, while some trends and risk factors at least can be observed where increase in cancer cases in different Governorates in Iraq is clearly visible after Gulf War 1991. After analyzing satellite images of different dates, the second part of this study concludes that Kuwait oil wells smoke is not responsible for increase in cancer incidences in Iraq. A small debate has been initiated regarding smoke in brick kilns near Basra. No study has been found in this regard which can provide evidences that brick kilns smoke is the cause of increase in cancer incidences in southern Iraq.</p><p>It’s not easy to carry out a full fledge GIS based study to prove DU as cause of increase in cancer cases. The main limitation in this regard is unavailability of required data. Therefore a new GIS based methodology has been devised which can be used to prove relationship between exposure to DU and increase in cancer cases in Iraq. This new methodology is also dependent on specific data sets. Hence this methodology also recommends the collection of specific data sets required for this study.</p><p>At the end, a detailed study, with honesty, has been suggested to fill up the gaps found in literature whether use of Depleted Uranium in weapons is harmful for human health or not.</p>

The use of banned toxic weapons in Iraq during Gulf War 1991 started new debates. The increase in cancer cases was the main focus of these issues. The gap in literature motivated this study to find out the correlation between use of DU weapons and its effects on human health. The different probable causes of increase in cancer cases, in Iraq after Gulf War 1991, have been discussed in this study. Three causes; DU, brick kilns smoke near Basra and Kuwait oil fire smoke have been selected. The major emphasis of this study is on use of Depleted Uranium (DU). Different statistical data sets have been used and displayed in the form of maps and graphs using GIS methodologies. It’s hard to say after this GIS based study that the fired Depleted Uranium is the sole cause of increase in cancer incidences in Iraq, while some trends and risk factors at least can be observed where increase in cancer cases in different Governorates in Iraq is clearly visible after Gulf War 1991. After analyzing satellite images of different dates, the second part of this study concludes that Kuwait oil wells smoke is not responsible for increase in cancer incidences in Iraq. A small debate has been initiated regarding smoke in brick kilns near Basra. No study has been found in this regard which can provide evidences that brick kilns smoke is the cause of increase in cancer incidences in southern Iraq. It’s not easy to carry out a full fledge GIS based study to prove DU as cause of increase in cancer cases. The main limitation in this regard is unavailability of required data. Therefore a new GIS based methodology has been devised which can be used to prove relationship between exposure to DU and increase in cancer cases in Iraq. This new methodology is also dependent on specific data sets. Hence this methodology also recommends the collection of specific data sets required for this study. At the end, a detailed study, with honesty, has been suggested to fill up the gaps found in literature whether use of Depleted Uranium in weapons is harmful for human health or not.