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Several epidemiological studies have suggested a role for environmental chemicals in the etiology of neurodegenerative diseases such as Parkinson's disease and Alzheimer's disease. Endosulfan (an organochlorine) and zineb (zinc-ethylene-bis-dithiocarbamate) are used as pesticides on a variety of crops worldwide and pose potential health risks to humans and animals. Both endosulfan and zineb are known to affect nervous system. Because the dopaminergic system continues to develop postnatally, we hypothesized that developmental exposure to endosulfan or zineb alone or in combination would result in alteration of nigrostrial neurotransmitters and would render the nigrostrial dopamine system more susceptible to chemical challenge later in life. The objectives of this study were (1) to determine the effects of endosulfan and zineb individually and in combination on dopaminergic or cholinergic pathways in vivo, (2) to investigate the effects of exposure to endosulfan, zineb and their mixtures administered in early life (during brain development) on subsequent exposure to these pesticides on the dopaminergic and cholinergic systems, in vivo, (3) to investigate the mechanism(s) of induction of neuronal cell death caused by these pesticides using human neuroblastoma SH-SY5Y cells in culture, (4) to define the role of oxidative stress in pesticide-induced neuronal cell death in vitro. Male C57Bl/6 mice of 7-9 months old exposed to zineb (50 and 100 mg/kg), endosulfan (1.55, 3.1 and 6.2 mg/kg) and their mixtures every other day over a 2-week period exhibited higher levels of dopamine accumulation in the striatum. Both pesticide-treated groups displayed significantly lower norepinephrine levels in the striatum (Ï ≤ 0.05) than the controls. The developmental exposure to zineb, endosulfan and their combination enhanced the vulnerability to subsequent neurotoxic challenges occurring later in life. Thus, C57BL/6 mice exposed to zineb, endosulfan and their mixtures as juveniles (postnatal days 5 to 19) and re-exposed at 8 months of age showed a significant depletion of striatal dopamine, to 22%, 16%, and 35% of control, respectively. Acetylcholinesterase activity in the cerebral cortex was found to be significantly increased in all pesticide treated groups. Mice given mixtures of pesticides also showed significantly increased levels of normal and aggregated alpha-synuclein, a hallmark of neurodegenerative diseases such as Parkinson's disease and Alzheimer's disease. The results of these studies indicate that exposure to these pesticides as neonates and re-exposure as adults could result in neurochemical changes that did not reveal at adulthood when the exposure was at juvenile age only. We further investigated the mechanism(s) of activation of pesticide-induced neuronal cell death in vitro. The characteristic of cell death in SH-SY5Y human neuroblastoma cells was examined. These cells are known to retain catecholaminergic phenotype. Cells were exposed to endosulfan, zineb and mixtures of two pesticides, in concentrations ranging from 50 μM to 400 μM. These exposures caused both apoptotic and necrotic cell death in SH-SY5Y cells as evaluated by lactate dehydrogenase release, 7-aminoactinomycin-D and Annexin-V/PI assays. Exposure to mixtures of the pesticides enhanced both the early apoptosis and late apoptosis/necrosis compared to either chemical alone. Visual evaluation using DNA ladder assay and fluorescence Annexin V/PI assay confirmed the contribution of both apoptotic and necrotic events. Furthermore, endosulfan and zineb alone and in combination altered the caspase-3 activity indicating that both pesticides exposure exert their apoptotic effect via the caspase-3 pathway. Because there has been increasing evidence of the role of reactive oxygen species (ROS) and oxidative stress in pesticide-induced neuronal cell death (apoptosis and necrosis), the levels of ROS and antioxidant enzymes were examined. Cells treated with pesticides were found to enhance the generation of superoxide anion and hydrogen peroxide both in a dose- and time-dependent manner. Mixture of pesticides significantly enhanced the production of these reactive oxygen species compared to cells exposed to individual pesticide. Cells treated with pesticides showed a decrease in superoxide dismutase, glutathione peroxidase, and catalase levels. These pesticides also induced lipid peroxides (thiobarbituric acid reactive products) formation in SH-SY5Y cells. Furthermore, cells exposed to these pesticides were found to have increased in the expression of NFkappaB activity in the nucleus. These data support the hypothesis that oxidative stress was induced in neuronal cells by exposing to these pesticides in vitro. Taken together, the results of this study support the above hypothesis and suggest that the cytotoxicity of endosulfan and zineb and their combinations may, at least in part, be associated with the generation of ROS. Furthermore, mice exposed at early age and re-exposed at adulthood become more susceptible to alteration of neurotransmitter levels compared to mice exposed to these pesticides only as juveniles. These findings could add to the growing body of knowledge on the mechanism of pesticide-induced dopaminergic neuronal cell death and could hold tremendous implication for the future understanding of the possible involvement of environmental risk factors in the pathogenesis of Parkinson's disease. / Ph. D.

The immunotoxic effects of multiple pesticide exposure were evaluated. C57BL/6 mouse thymocytes were exposed to lindane, malathion, and permethrin, either separately or in mixtures of two pesticides, in concentrations ranging from 37.5 uM to 1mM. These exposures caused both apoptotic and necrotic cell death in thymocytes as evaluated by 7-aminoactinomycin-D, Annexin-V/PI, and lactate dehydrogenase release assays. When cells were exposed to lindane+malathion, or lindane+permethrin, a significantly greater-than-additive cytotoxicity was observed. The pesticide exposure caused DNA ladder formation with increased laddering in mixtures. Further, the effect of these pesticides on thymocyte oxidative stress was investigated. Thymocytes treated with any of these pesticides generated superoxide and H2O2. The lindane + malathion caused more-than-additive increase in superoxide production compared to single treatments of these pesticides. However, the effect of the lindane + permethrin was not significantly different from individual components of this mixture. The effects of pesticides on antioxidant enzymes were also investigated and only mixtures were found to have significant effects. Alteration in transcription factor NFkB level was measured as an indicator of oxidative stress in thymocytes following 12 h pesticide exposure, in vitro. Only lindane + malathion was found to increase the protein level. Furthermore, the effects of pesticides and their mixtures on immune functions of mice were studied in vivo. Animals (8-12 week old, male mice) were randomly divided into groups of six and injected intraperitoneally with three different doses (one-half, one-third, one-fourth, or one-eight of LD50) of individual pesticides. Exposure to individual pesticides did not alter the thymus/body or spleen/body weight ratios, thymic or splenic cell counts, or CD4/CD8 or CD45/CD90 ratios. However, anti-sRBC plaque forming cell (PFC) counts were significantly lowered with all treatments. Two other groups of animals were injected with lindane + malathion or lindane + permethrin at one-third of the LD50 of each pesticide. Exposure to pesticide mixtures did not alter the CD4/CD8 or CD45/CD90 ratios. However, the thymus/ and spleen/body weight ratios, thymic and splenic cell counts, and PFC counts were significantly lowered. These data indicate that lindane, malathion, and permethrin are immunotoxic and their mixtures can cause higher toxicity compared to individual exposures. In addition, these data support the hypothesis that oxidative stress were induced in thymocytes by exposure to these pesticides in vitro. / Ph. D.

Cover crops (CC) are planted in between cash crops to improve soil quality and to supply nitrogen (N) to cash crops through biological N fixation or soil N scavenging. Most producers use single species CC, in part because potential benefits of using mixtures of three or more CC species are poorly understood. A three-year study was initiated at Painter, Virginia to observe effects of CC mixtures on a no-till (NT) corn (Zea mays), wheat (Triticum aestivum L.), and soybean (Glycine max) rotation to measure CC performance, N cycling, cash crop yield, and soil quality in a sandy, low organic matter soil. Twelve treatments were created with conventional tillage (CT), NT, no CC control, and monoculture or CC mixtures of 3 to 9 species. Corn was grown in year 3 in all 12 treatments and four N rates were applied (0, 56, 112 and 156 kg N ha-1). Cover crop biomass, N accumulation, CC C:N ratio, and corn and soybean yield were measured annually. Soil bulk density, compaction, infiltration rate, pH, electrical conductivity, soil respiration, earthworm counts, soil microbial respiration, and soil microbial biomass carbon (C) after three years of CC. Cover crop biomass production varied significantly each year (5633 kg ha-1 in year 1, 755 kg ha-1 in year 2, 5370 kg ha-1 in year 3) due to climate and agronomic parameters, but a CC mixture always produced the highest biomass at termination. Nitrogen accumulation was strongly correlated with biomass production (R2= 0.94) and followed the same trend due to all CC having C:N < 30:1. Corn and soybean yields in years 1 and 2 were not significantly different, but corn yield was significantly affected by treatment and N fertilizer rate in year 3. After 3 years, soil respiration, earthworm populations and soil microbial biomass C increased in CC compared to CT without CC. However, infiltration rate, bulk density, microbial respiration, pH did not improve or declined compared to CT. In conclusion, adding CC mixtures to crop rotations shows promise for producing high CC biomass, accumulating N, and increasing crop yields, while improving some soil quality parameters on sandy low organic matter soils. / Doctor of Philosophy / Cover crop (CC) are planted in between cash crops to protect the soil from erosion, improve soil quality, and supply N to next cash crop through biological N fixation or soil N scavenging. Traditionally, CC were single species, but new CC methodologies utilize mixtures of three or more species planted together to protect soils as well as produce high biomass to suppress weeds, conserve soil moisture, and improve soil quality. A long-term study was initiated in fall 2014 in Painter, VA to observe CC mixture effects on no-till (NT) corn (Zea mays), wheat (Triticum aestivum L.), and soybean (Glycine max) rotations on CC performance, N cycling, cash crop yield, and soil quality of a sandy, low organic matter soil. Twelve treatments were created that compared NT rotations with CC monocultures, CC mixtures of 3-9 species, and without CC. In the third year corn was grown in all 12 rotations and four N rates were applied (0, 56, 112 and 156 kg N ha-1). To evaluate CC mixture performance in rotations, CC biomass, CC N accumulation and corn and soybean yield was measured over three years. To evaluate changes in soil quality, nine soil physical, chemical and biological soil properties were measured after three years of NT and CC. Biomass production varied significantly each experimental year (5633 kg ha-1 in year 1, 755 kg ha-1 in year 2, 5370 kg ha-1 in year 3) due to climate and agronomic differences, but CC mixtures were the highest biomass producing CC each spring and accumulated the highest amount of N. Cover crop mixtures had equal corn and soybean yield as CC monocultures. In year 3 corn yield and was greater in treatments with CC than in treatments without CC and was greater in legume dominated monocultures and mixtures than majority grass CC mixtures and monocultures. After 3 years of CC and NT, some soil quality parameters improved. Indicators of soil biology (soil respiration, earthworm populations, and soil microbial biomass C) increased in CC treatments. However, some soil physical and chemical properties (infiltration rate, bulk density, pH and EC) did not improve. In conclusion, adding CC mixtures to crop rotations shows promise for producing high CC biomass, accumulating N, and increasing crop yields, while also improving some soil quality parameters that are important for agricultural systems.

Numerical modeling and prediction techniques are used to determine pressure drop, minimum fluidization velocity and segregation for bubbling fluidized beds. The computational fluid dynamics (CFD) code Multiphase Flow with Interphase eXchange (MFIX) is used to study a two-stage reactor geometry with a binary mixture. MFIX is demonstrated to accurately predict pressure drop versus inlet gas velocity for binary mixtures. A new method is developed to predict the pressure drop versus inlet gas velocity and minimum fluidization velocity for multi-component fluidized beds. The mass accounting in the stationary system (MASS) method accounts for the changing bed composition during the fluidization process by using a novel definition for the mass fractions of the bed not yet fluidized. Published experimental data for pressure drop from single-, binary- and ternary-component fluidized bed systems are compared to MFIX simulations and the MASS method, with good agreement between all three approaches. Minimum fluidization velocities predicted using correlations in the literature were compared with the experimental data, MFIX, and the MASS method. The predicted minimum fluidization velocity from the MASS method provided very good results with an average relative error of ±4%. The MASS method is shown to accurately predict when complex multi-component systems of granular material will fluidize. The MASS method and MFIX are also used to explore the occurrence and extent of segregation in multi-component systems. The MASS method and MFIX are both shown to accurately predict the occurrence and extent of segregation in multi-component systems. / Master of Science

No / Experimental solubilities of budesonide, hydrocortisone, and prednisolone in ethanol + water mixtures at 298.2 K are reported. The solubility of drugs was increased with the addition of ethanol and reached the maximum values of the volume fractions of 90 %, 80 %, and 80 % of ethanol. The Jouyban-Acree model was used to fit the experimental data, and the solubilities were reproduced using previously trained versions of the Jouyban-Acree model and the solubility data in monosolvents in which the overall mean relative deviations (OMRDs) of the models were 5.1 %, 6.4 %, 37.7 %, and 35.9 %, respectively, for the fitted model, the trained version for ethanol + water mixtures, and generally trained versions for various organic solvents + water mixtures. Solubilities were also predicted by a previously established log-linear model of Yalkowsky with the OMRD of 53.8 %.

Unlike the conventional "lock-and-key" sensor design in which one sensor is finely tuned to respond to one analyte, the sensor array approach employs multiple sensors in which one sensor responds to many analytes. Consequently, signal processing algorithms must be used to identify the analyte present from the array's response. The analyte identification process becomes significantly more complicated when a mixture of analytes is presented to the sensor array. Conventional methods that are employed in gas mixture identification are plagued by several design issues like: complexity, scalability, and flexibility. This thesis derives and develops a novel method, fingerprint-based ICA (FICA), to extract and identify individual analytes from a sensor array's response to a gas mixture of the analytes. FICA is a simple, flexible, and scalable signal processing system that employs independent components analysis (ICA) to extract and identify individual analytes present in a gas mixture; separation and identification of gas mixtures using ICA has not been investigated previously. FICA takes a fundamentally different approach that reflects the underlying property of gas mixtures: gas mixtures are composed of individual analyte responses. Conventional signal processing methods that identify gas mixtures have been developed and implemented in this work; this helps us understand the drawbacks in the conventional approach. FICA's performance is compared to the performance of conventional methods using metric like error rate and false positives rate. Properties like flexibility, scalability, and the data requirements for both conventional methods and FICA are examined. Results obtained in this work indicates that FICA results in lower error rates, and it's performance is better than conventional methods like multi-stage multi-stage support vector machines, and PCR. Furthermore, FICA provides the most simple, scalable, and flexible signal processing system. / Master of Science