Chiral alpha-branched amines are common substructures of bioactive synthetic targets such as alkaloids and amino acids. Direct asymmetric amine synthesis by addition to the C=N bond of carbonyl imino derivatives is promising and efficient to introduce the stereogenic center and carbon-carbon bond in one step. Furthermore, disconnection of either C-C bond at the amine stereogenic center would be the most versatile method to achieve this objective; we could make the choice depending on the different synthetic strategies, such as the availability of precursors and the presence of complicating structural features. In our group, we disclosed that manganese carbonyl mediates stereoselective photolytic radical addition of alkyl iodides to chiral imino acceptors, which is a powerful tool to form a new C-C bond and generate a chiral center. Qualitative mechanistic studies confirm the importance of free radicals, imply that this is a nonchain (or short chain length) free-radical process, and reveal that organomanganese compounds are not a viable source of alkyl radical for the addition reactions under the conditions in our lab. In my thesis, we have extended the application of our methodology. At the beginning of my research, our Mn-mediated addition methodology was first applied to accomplish the couplings of iodides and ketone N-acylhydrazones, generating quaternary carbon stereocenters and offering access to a variety of alpha-alkylated alanine analogs. These radical additions complement enolate alkylation methodologies, as they occur under nonbasic conditions and permit introduction of both primary and secondary alkyl groups with relative ease. The versatility with respect to the iodide is a distinguishing feature of the Mn-mediated coupling that foreshadows application to more complex targets. Secondly, a Mn-mediated radical-ionic annulation strategy was validated as a synthetic route to quinine. Intermolecular radical addition to C=N bonds has rarely been applied as a strategic bond construction in natural product synthesis; this synthesis of quinine offers the strongest demonstration yet of the utility of such reactions in application toward complex multifunctional targets.

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The abuse of synthetic cathinones, formerly marketed as “bath salts”, has emerged over the last decade. Three common drugs in this class include 3,4-methylenedioxypyrovalerone (MDPV), 4-methylmethcathinone (mephedrone), and 3,4-methylenedioxymethcathinone (methylone). An LC–MS/MS method has been developed and validated for the simultaneous quantification of MDPV, mephedrone, and methylone in brain tissue. Briefly, MDPV, mephedrone, methylone, and their deuterium-labeled analogs were subjected to solid phase extraction (SPE) and separated using an HILIC Silica Column. The HPLC was coupled to a Shimadzu IT-TOF (ion trap-time of flight) system with the electrospray source running in positive mode (+ESI). The method was validated for precision, accuracy, and extraction efficiency. All inter-day and intra-day % RSD (percent relative standard deviation) and % error values were less than 15% and extraction efficiency exceeded 80%. These conditions allowed for limits of detection of 1ng/mL for MDPV, and 5 ng/mL for both mephedrone and methylone. The limits of quantification were determined to be 5ng/mL for MDPV and 10 ng/mL for mephedrone and methylone. The method was utilized to evaluate the pharmacokinetics of these drugs in adult male rats following administration of a drug cocktail including MDPV, mephedrone, and methylone. All three compounds reached peak concentrations in the brain within 15 min. Although methylone and mephedrone were administered at the same dose, the peak concentration (Cmax) of mephedrone in the brain was significantly higher than that for methylone, as was the area under the curve (AUC). In summary, this quick and sensitive method for measuring synthetic cathinones may be used for future pharmacokinetic investigations of these drugs in target tissue.

In 2014, Colorado and Washington legalized the cultivation, sale, and consumption of recreational marijuana for anyone over the age of 21. In doing so, the two states presented the first opportunities for marijuana-specific tourism in the United States. Direct benefits of legalization to these first movers, namely tax revenues generated through the sale of marijuana, have been quantified, but the indirect benefits in the tourism sector are as of yet unquantified. Although there is a large body of informal literature and popular media on marijuana tourism, academic study of the subject is scant. Working with a panel composed of 47 of the contiguous United States over the years 2005-2016, this study utilizes a synthetic control methodology to construct hypothetical time series for various tourism indicators for the cases of non-legalization in Colorado and Washington. Comparison of these hypothetical time series to the actual time series reveals the effects of legalization. A similar methodology is applied to all states to find the “placebo effects” and to establish significance. In traveler expenditures, traveler-generated taxes, tourism industry employment, and tourism industry payroll, Washington shows effects of legalization of greater magnitude and significance than those in Colorado. Only 8% of other states show an effect on tourism revenues as large as that of Washington. Additionally this study finds that each state can be approximated with a weighted average of a small group of peers and that weather, price, and an interacted migration and political orientation variable have low predictive power on tourism indicators. Lastly, this study suggests possible causes and policy implications of the discrepancy between the states.

Cancer is the second leading cause of death in the USA, following cardiovascular disease. Treating cancer using conventional therapies is associated with low response rates and high toxicity, because these therapies usually lack specific tumor accumulation. Loading anticancer drugs into intelligently designed polymeric nanoparticles (NPs) can serve in delivering these drugs specifically to the tumor site, thus boosting their efficacy and reducing any associated off target toxicity. Targeting NPs to the tumor site can occur through either passive or active means. In passive targeting, NPs of specific size and surface characteristics can exploit the tumor’s erratic vasculature and occluded lymphatic drainage to extravasate the systemic circulation and accumulate preferentially at the tumor site. Active targeting mandates grafting the surface of NPs with a ligand that specifically interacts with a protein expressed at higher levels at the tumor site, in comparison to elsewhere in the body. In the current research, we independently investigated the utilization of passive and active targeting strategies to treat aggressive forms of cancer. Initially, passively targeted poly(lactic-co-glycolic acid) (PLGA) NPs to treat aggressive forms of endometrial cancer (EC) were investigated. A novel combination of soluble paclitaxel (PTX), a first line chemotherapy for EC, and soluble BIBF1120 (BIBF, nintedanib), an antiangiogenic molecular inhibitor, was first tested against three EC cell lines bearing different p53 mutations. The results showed that only EC cells with loss of function (LOF) p53 were sensitive to the combination therapy, indicating the potential of this combination to engender synthetic lethality to PTX. Next, NPs loaded with PTX were investigated with respect to the impact of varying the polymer lactic acid to glycolic acid ratio and the surfactant type on the major physicochemical properties of the prepared nanoparticles, drug loading, cellular uptake, cytotoxicity, and drug release. The optimum formulation was then loaded with BIBF and the combination of independently loaded passively targeted NPs were further evaluated for in vivo activity against a xenograft model of LOF p53 EC. The combination of independently loaded NPs exhibited the highest reduction in tumor volume and prolonged survival when compared to soluble PTX, PTX NPs or untreated control. These data highlight this specific combination of NPs as a novel promising therapy for LOF p53 EC. In a second study, the use of actively targeted NPs to treat liver cancer was explored. In this study, a combination of small interfering RNA (siRNA) against astrocyte elevated gene-1 (AEG-1), and all-trans retinoic acid (ATRA) was investigated as a new therapy for hepatocellular carcinoma (HCC). AEG-1 is a highly expressed oncogene that is directly involved in HCC progression and aggressiveness, in addition to reducing the ability of retinoic acid to induce apoptosis in HCC cells. First, a new conjugate was synthesized that was capable of delivering siRNA selectively to HCC cells, using galactose as a targeting moiety. The conjugate was prepared by linking poly(amidoamine) (PAMAM) dendrimers, polyethylene glycol (PEG) and lactobionic acid (Gal, disaccharide containing galactose) (PAMAM-PEG-Gal). We confirmed the synthesis of the conjugate using 1H-NMR, Mass spectrometry and Matrix-Assisted Laser Desorption/Ionization (MALDI) Mass Spectrometry. Next, nanoplexes of the synthesized conjugate, PAMAM-PEG-Gal, and AEG-1 siRNA were prepared. Nanoplexes were further characterized for their size, surface charge, morphology, and electrophoretic mobility to identify the optimum complexation ratio between PAMAM-PEG-Gal and the siRNA. Then, mice bearing orthotopic luciferase expressing HCC cells were treated with the optimum nanoplex formulation. Results showed that a combination of AEG-1 nanoplexes and ATRA results in a significant reduction in luciferase expression, reduced liver weight, lower AEG-1 mRNA levels and increased apoptosis, when compared to utilizing nanoplexes with silencing control (siCon), siCon+ATRA, or AEG-1 nanoplexes alone. The results indicate that the combination of liver-targeted AEG-1 nanoplexes and ATRA may be a potential treatment for aggressive HCC. These data place targeted NPs as a promising efficient delivery system for cancer treatment.

Polyketides are a large group of structurally diverse natural products that have shown a variety of biological activities. These molecules are synthesized by polyketide synthases (PKSs). PKSs are classified into three types based on their sequence, primary structure, and catalytic mechanism. Because of the bioactivities of polyketide natural products, this study is focused on the engineering of PKS pathways for efficient production of useful bioactive molecules or structural modification to create new molecules for drug development. One goal of this research is to create an efficient method to produce pharmaceutically important molecules. Seven biosynthetic genes from plants and bacteria were used to establish a variety of complete biosynthetic pathways in Escherichia coli to make valuable plant natural products, including four phenylpropanoid acids, three bioactive natural stilbenoids, and three natural curcuminoids. A curcumin analog dicafferolmethane was synthesized by removing a methyltransferase from the curcumin biosynthetic pathway. Furthermore, introduction of a fungal flavin-dependent halogenase into the resveratrol biosynthetic pathway yielded a novel chlorinated molecule 2-chloro-resveratrol. This demonstrated that biosynthetic enzymes from different sources can be recombined like legos to make various plant natural products, which is more efficient (2-3 days) than traditional extraction from plants (months to years). Phenylalanine ammonia-lyase (PAL) is a key enzyme involved in the first biosynthetic step of some plant phenylpropanoids. Based on the biosynthetic pathway of curcuminoids, a novel and efficient visible reporter assay was established for screening of phenylalanine ammonia-lyase (PAL) efficiency in Escherichia coli. The other goal of this research is to characterize and engineer natural product biosynthetic pathways for new bioactive molecules. The biosynthetic gene cluster of the antibacterial compound dutomycin was discovered from Streptomyces minoensis NRRL B-5482 through genome sequencing. Confirmation of the involvement of this gene cluster in dutomycin biosynthesis and creation of a series of new molecules were successfully conducted by rationally modifying the biosynthetic pathway. More importantly, a new demethylated analog of dutomycin was found to have much higher antibacterial activity against Staphylococcus aureus and methicillin-resistant Staphylococcus aureus.

Traditional stochastic approaches for synthetic generation of weather variables often assume a prior functional form for the stochastic process, are often not capable of reproducing the probabilistic structure present in the data, and may not be uniformly applicable across sites. In an attempt to find a general framework for stochastic generation of weather variables, this study marks a unique departure from the traditional approaches, and ushers in the use of data-driven nonparametric techniques and demonstrates their utility. Precipitation is one of the key variables that drive hydrologic systems and hence warrants more focus . In this regard, two major aspects of precipitation modeling were considered: (I) resampling traces under the assumption of stationarity in the process, or with some treatment of the seasonality, and (2) investigations into interannual and secular trends in precipitation and their likely implications. A nonparametric seasonal wet/dry spell model was developed for the generation of daily precipitation. In this the probability density functions of interest are estimated using non parametric kernel density estimators. In the course of development of this model, various nonparametric density estimators for discrete and continuous data were reviewed, tested, and documented, which resulted in the development of a nonparametric estimator for discrete probability estimation. Variations in seasonality of precipitation as a function of latitude and topographic factors were seen through the non parametric estimation of the time-varying occurrence frequency. Nonparametric spectral analysis, performed on monthly precipitation, revealed significant interannual frequencies and coherence with known atmospheric oscillations. Consequently, a non parametric, nonhomogeneous Markov chain for modeling daily precipitation was developed that obviated the need to divide the year into seasons. Multivariate nonparametric resampling technique from the nonparametrically fitted probability density functions, which can be likened to a smoothed bootstrap approach, was developed for the simulation of other weather variables (solar radiation, maximum and minimum temperature, average dew point temperature, and average wind speed). In this technique the vector of variables on a day is generated by conditioning on the vector of these variables on the preceding day and the precipitation amount on the current day generated from the wet/dry spell model.

The use of radar often conjures up images of small blobs on a screen. But current synthetic aperture radar (SAR) systems are able to generate near-optical quality images with amazing benefits compared to optical sensors. These SAR sensors work in all weather conditions, day or night, and provide many advanced capabilities to detect and identify targets of interest. These amazing abilities have made SAR sensors a work-horse in remote sensing, and military applications. SAR sensors are ranging instruments that operate in a 3D environment, but unfortunately the results and interpretation of SAR images have traditionally been done in 2D. Three-dimensional SAR images could provide improved target detection and identification along with improved scene interpretability. As technology has increased, particularly regarding our ability to solve difficult optimization problems, the 3D SAR reconstruction problem has gathered more interest. This dissertation provides the SAR and mathematical background required to pose a SAR 3D reconstruction problem. The problem is posed in a way that allows prior knowledge about the target of interest to be integrated into the optimization problem when known. The developed model is demonstrated on simulated data initially in order to illustrate critical concepts in the development. Then once comprehension is achieved the processing is applied to actual SAR data. The 3D results are contrasted against the current gold- standard. The results are shown as 3D images demonstrating the improvement regarding scene interpretability that this approach provides.

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Abstract not available