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To revitalize the antibiotic pipeline, it is critical to identify and validate new antimicrobial targets. An uncharted area of antibiotic discovery can be explored by inhibiting nutrient biosynthesis. Herein, we investigate the potential of inhibiting biotin biosynthesis in monotherapy and combination therapy approaches to treat multidrug-resistant Gram-negative pathogens. In chapter 2, we validate biotin biosynthesis as a viable target for Gram-negative pathogens. Historically, biotin biosynthesis was overlooked as a target in Gram-negative pathogens as there was no observed fitness cost associated with its inhibition in standard mouse infection models. We discovered traditional mouse models do not accurately represent the biotin levels in humans. We developed an innovative mouse model to account for this discrepancy, validating biotin biosynthesis as an antimicrobial target in the presence of human-mimicking levels of biotin. Exploiting this sensitivity, we show that an inhibitor of biotin biosynthesis, MAC13772, is efficacious against Acinetobacter baumannii in a systemic murine infection model. In chapter 3, we continue to investigate the potential of targeting biotin biosynthesis in a combination therapy approach. In this work, we identify the ability of MAC13772 to synergize with colistin exclusively against colistin-resistant pathogens. The first committed step of fatty acid biosynthesis requires biotin as a cofactor; therefore, it is indirectly inhibited through the action of MAC13772. We propose that the inhibition of fatty acid biosynthesis leads to changes in membrane fluidity and phospholipid composition, restoring colistin sensitivity. The combination of a fatty acid biosynthesis inhibitor and colistin proved superior to either treatment alone against mcr-1 expressing Klebsiella pneumoniae and colistin-resistant Escherichia coli murine infection models. Together, these data suggest that biotin biosynthesis is a robust antibiotic target for further development in monotherapy and combination therapy approaches. / Thesis / Doctor of Philosophy (PhD)

This dissertation is focused on multiple testing procedures to be used in data that are naturally grouped or possess a spatial structure. We propose `Two-Stage' procedure to control the False Discovery Rate (FDR) in situations where one-sided hypothesis testing is appropriate, such as astronomical source detection. Similarly, we propose a `Three-Stage' procedure to control the mixed directional False Discovery Rate (mdFDR) in situations where two-sided hypothesis testing is appropriate, such as vegetation monitoring in remote sensing NDVI data. The Two and Three-Stage procedures have provable FDR/mdFDR control under certain dependence situations. We also present the Adaptive versions which are examined under simulation studies. The `Stages' refer to testing hypotheses both group-wise and individually, which is motivated by the belief that the dependencies among the p-values associated with the spatially oriented hypotheses occur more locally than globally. Thus, these `Staged' procedures test hypotheses in groups that incorporate the local, unknown dependencies of neighboring p-values. If a group is found significant, further investigation is done to the individual p-values within that group. For the vegetation monitoring data, we extend the investigation by providing some spatio-temporal models and forecasts to some regions where significant change was detected through the multiple testing procedure. / Statistics

Broadly, this study focuses on roles of sell-side analysts and examines the determinants and consequences of information discovery and stock timing roles by sell-side analysts. We also re-examine reiterations of prior recommendations by sell-side analysts. In Chapter 1, the contribution is to document that analysts add value by engaging in discovery of private information and this value addition is greater than that due to interpretation of public news or stock timing. The innovation in this Chapter is to read over 3,700 analyst reports from Investext and explicitly identify whether the report contains discovery, interpretation, and/or timing. Analysts discover new information by talking to management sources (personal meetings, investor meetings, and conference calls) or non-management sources (such as channel checks). We find that information discovery is prevalent in 17% of the reports. The cumulative abnormal return (CAR) for reports containing discovery are 6.3% for upgrades and -10.6% for downgrades. The CARs are higher for reports containing discovery relative to those containing interpretation or timing. We find that economic determinants predict whether a report will contain discovery. Discovery from management sources is more likely for reports in the pre-Reg FD period and for reports by optimistic analysts. Discovery from non-management sources is more likely for reports written by All-Star analysts, and for firms that have high information asymmetry and those that are followed by more analysts. In Chapter 2, the contribution is to introduce and document a third role that analysts play that is also valuable to investors, which we term "stock timing." Specifically, we define a timing report as one where the analyst revises his recommendation but does not revise the Price Target or any of the 23 fundamental drivers of stock price (such as EPS, FCF) tracked by I/B/E/S. Because the analyst maintains the same price target as in his prior report but still revises his recommendation, such timing calls are contrarian valuation calls. Analysts issue timing downgrades (upgrades) in response to price increases (declines) since the release of their prior report on the firm. 30% of all revisions are timing reports, indicating the importance of the timing role played by analysts. If analysts have timing ability, then markets should react to the release of the timing report and we should observe that economic determinants explain the cross-sectional variation in timing ability. We find the 3-day announcement return is over 2% in magnitude, 62% of the reports are winners (have announcement returns that have the correct sign), 10% of the reports are large enough to be considered influential, and 37% of the reports are persistent winners. These results suggest that analysts have timing ability. The ability to time is similar is magnitude to information interpretation but smaller compared to information discovery. We find considerable cross-sectional and time-series variation in timing ability. We find that the probability of issuing a timing report is positively related to the opportunities to time the stock provided by potential mispricing. Conditional on issuing a timing report, the probability of issuing a winner, an influential winner, or a persistent winner is positively related to analyst experience and negatively related to the costs associated with issuing a timing report. In Chapter 3, we document that recommendation reiterations are not homogeneous and there is a large subset of reiterations that are as much valued by investors as recommendation revisions. We combine Detail History file containing the measures tracked by I/B/E/S (Price Target, EPS, etc.) and Recommendation file to create the full time series of recommendations (initiations, reiterations, and revisions) made by each analyst for each firm for 14 years from 1999 to 2012. By adopting a modified version of "filling in the holes" method, we find that recommendation reiterations are prevalent, consisting of about 80% of recommendations for our 14-year sample period. Second, market response to recommendation reiterations increases monotonically from Reiteration: Strong Sell to Reiteration: Strong Buy. Third, reiterations coupled with contemporary changes in price targets and/or earning forecasts bring substantial absolute abnormal stock returns to investors. Lastly, when we replicate what Loh and Stulz (2011), we find that the number of reiterations which are influential is more than twice that of recommendation revisions that are influential. / Business Administration/Finance

ONC201 is a novel compound that upregulates endogenous TNF-Related Apoptosis-Inducing Ligand (TRAIL), in tumor and normal cells, restoring autocrine and paracrine anti-tumor activity within tumor cells, and upregulates the DR5 gene by activating the integrated stress response, inducing eIF2-alpha-dependent ATF4 and CHOP [1-3]. ONC201 also demonstrates potent anti-tumor effects on colorectal cancers [4, 5]. ONC201 presented a promising oral bioavailability, wide distribution throughout the body, and ability to cross the blood-brain barrier. Further, the unique ability of its TRAIL-and-DR5-based signaling to induce apoptosis in cancer cells and not normal cells adds to its appeal as an anti-cancer therapeutic and prompted clinical development [1-4, 6]. ONC201 has successfully completed an FDA advanced Phase I/II clinical trial in advanced aggressive refractory solid tumors. Results indicated that ONC201 is well-tolerated and recommended a phase II dose of 625 mg orally every 3 weeks. Several Phase I/II clinical trials are enrolling in multiple solid tumors and hematological malignancies [7, 8]. Chapter two of this study provides evidence that ONC201 dose intensification demonstrates an increased pharmacodynamic effect and an increasing anti-tumor efficacy in vivo while having a safe toxicity profile upon weekly dosing. This data influenced the Phase II clinical trials, which have now been adjusted to include weekly dosing. Given the potential anti-metastatic effects of TRAIL signaling and the role of TRAIL in the immune surveillance of cancer, we hypothesized that ONC201 would suppress metastatic tumor development and engage the immune system in its anti-cancer activity. We also establish that ONC201 provides an important anti-metastatic effect in CRC that should be pursued in both pre-clinical and clinical studies. Tail vein and surgical CRC models demonstrate that ONC201 inhibits the number and size of metastases. Evidence has shown that TRAIL can also inhibit cancer metastasis by possibly inducing cell death or TRAIL-sensitization in the primary tumor when cells undergo extravasation upon detachment from the primary tumor [9-11]. While we show that TRAIL plays a role in ONC201’s ability to inhibit migration/invasion in vitro, further investigation of the role of TRAIL in vivo is necessary. Our data indicates that ONC201 promotes a pro-immune response in CRC subcutaneous tumors with increased NK cells that play a role in ONC201’s efficacy in syngeneic models. Since activated natural killer cells express TRAIL, we established that ON201 can activate and induce TRAIL expression in NK cells [12, 13]. As we did not find any immune infiltrates in the metastases, we suggest that the effect of the micro-environment or in more clinically-relevant models with stromal environments should be pursued. Chapter 3 of this of thesis demonstrates the characterization of ONC201’s core structure and development of ONC201 analogues including their mechanistic differences and potential in vivo efficacy and safety. We have demonstrates the importance of the angular structure of ONC201 to ONC201’s anti-tumor efficacy [14]. The novel pharmacophore has now been called as imipridone and is essential for its anti-tumor activity, as the linear isomer had no anti-tumor effect. We leveraged this unique pharmacophore to synthesize ONC201 analogues with distinct therapeutic properties; namely, targeting ONC201-resistant tumor types or possessing distinct signaling properties. Imipridone R2 analogues have a lower IC50 and are more promising than their lead compound in certain tumor types. ONC212, a halide R2 analogue, demonstrates superior efficacy in vivo in melanoma xenografts, a large therapeutic window; but does have a rapid PK. Oncoceutics is currently developing ONC212 for a first-in human Phase I clinical trial. The fourth chapter of this study demonstrates the potential of a combinational therapy with ONC201 in colorectal cancer with bevacuzimab. Clinical trials in CRC and other tumor types have demonstrated that therapeutics targeting the vascular endothelial growth factor (VEGF) pathway, such as bevacizumab, are effective in combination with certain chemotherapeutic agents. ONC201 in combination with bevacuzimab led to superior results with almost no tumor growth. This result was re-capitulated in syngeneic models. Given that bevacuzimab is approved for metastatic CRC, we suggest that ONC201 in combination with bevacuzimab should be introduced into a combinatorial Phase II clinical trial. This thesis focuses on the importance of dose-intensification of ONC201 on its pre-clinical efficacy; establish an anti-metastatic effect; demonstrate an immune increase in subcutaneous models; and elucidate the role of the core angular structure in efficacy with the development novel ONC201 analogues. The importance of pre-clinical studies, ONC201’s analogues including the successful development of ONC212, and potentially advantageous combinational therapies with anti-angiogenics is explained in the chapters throughout. / Cancer Biology & Genetics

This study examined the use of discovery learning in science and how it affects students' academic performance as well as their self-efficacy in science. It also used a diagnostic tool to identify students' misconceptions about processes in the water cycle and where the misconceptions originated. While the study showed that the treatment group had a statistically significant greater academic gain from the pre-test to the post- test than did the no-treatment comparison group, from a teachers view point the gain would not be enough to benefit a student's performance on high stakes tests. Because the study was able to identify eight common misconceptions, it suggests that the misconceptions that students possess are difficult to uproot even using teaching methods that have been proven successful. / CITE/Mathematics and Science Education

Molecular recognition is an important tool for developing tunable controlled release systems and fabricating biosensors with increased selectivity and sensitivity. The development of polymer-based materials that exploit molecular recognition events such as host-guest complexation, enzyme-substrate and enzyme-inhibitor interactions and nucleic acid hybridization was pursued in this thesis. Using polymers as an anchor for molecular recognition can enhance the affinity, selectivity, and the capacity for immobilization of recognition units, enabling the practical use of affinity-based systems in real applications. To introduce the potential for immobilization while preserving or enhancing the affinity of small molecule recognition units, the affinity of derivatized cyclodextrins for the hydrophobic drug, dexamethasone, was investigated. Cyclodextrins (CDs) are molecules that possess a hydrophilic exterior and a hydrophobic cavity capable of accommodating a wide range of small molecule guests. Analysis of the solubilization capacities, thermodynamic parameters and aggregative potentials of carboxymethyl and hydrazide derivatives of CDs established the dextran-conjugated βCD derivative as an ideal carrier of hydrophobic drugs and the hydrazide βCD derivative as an optimal solubilizer of lipophilic pharmaceuticals, both alone and when incorporated in a polymer-based drug delivery vehicle. To enable non-covalent immobilization and stabilization of biomacromolecular recognition units, a printed layer hydrogel was investigated as a selective diffusion barrier for analyte sensing and enzyme inhibitor recognition. A printable hydrogel platform was developed from an established injectable system composed of aldehyde- and hydrazide-functionalized poly(oligoethylene glycol methacrylate) polymers. The printed layer hydrogel effectively immobilized a wide range of enzymes and protected enzyme activity against time-dependent and protease-induced denaturation, while facilitating the diffusion of small molecules. Furthermore, to demonstrate the potential of the printed film hydrogel immobilization layer to enhance the selectivity of the target, the printable hydrogel platform was used to develop a microarray-based assay for the screening of inhibitors of the model enzyme, β-lactamase. The assay was able to accurately quantify dose-response relationships of a series of established inhibitors, while reducing the required reagent volumes in traditional drug screening campaigns by 95%. Most significantly, the assay demonstrated an ability to discriminate true inhibitors of β-lactamase from a class of non-specific inhibitors called promiscuous aggregating inhibitors. Finally, to enable non-covalent immobilization of DNA recognition units, the printable hydrogel-based microarray was tested for its ability to immobilize DNA recognition sites and promote the detection of DNA hybridization events. A long, concatameric DNA molecule was generated through rolling circle amplification and was used as a sensing material for the detection of a small, fluorophore labeled oligonucleotide. The printable hydrogel was able to effectively entrap the rolling circle amplification product. Properties of the printable hydrogel were investigated for their ability to support the detection of DNA hybridization events. / Thesis / Doctor of Philosophy (PhD) / This thesis describes the development of polymer-based materials that exploit molecular recognition events for drug delivery and biosensing applications. First, cyclodextrins (CDs) are molecules that are capable of binding a wide range of small molecules. A comprehensive analysis of the complexation properties of CD derivatives revealed critical insight regarding their application in polymer-based drug delivery vehicles. Second, a printable hydrogel platform was developed to support the immobilization and activity of biomolecules and establish a biosensing interface that facilitates the diffusion of small molecules but not molecular aggregates. A microarray-based assay was developed by employing the printed hydrogel interface for the screening of inhibitors of the model enzyme, β-lactamase, and the detection of DNA hybridization events.

In this dissertation, we present a novel approach for Web service mining. Web service mining is a new research discipline. It is different from conventional top down service composition approaches that are driven by specific search criteria. Web service mining starts with no such criteria and aims at the discovery of interesting and useful compositions of existing Web services. Web service mining requires the study of three main research topics: semantic description of Web services, efficient bottom up composition of composable services, and interestingness and usefulness evaluation of composed services. We first propose a Web service ontology to describe and organize the constructs of a Web service. We introduce the concept of Web service operation interface for the description of shared Web service capabilities and use Web service domains for grouping Web service capabilities based on these interfaces. We take clues from how Nature solves the problem of molecular composition and introduce the notion of Web service recognition to help devise efficient bottom up service composition strategies. We introduce several service recognition mechanisms that take advantage of the domain-based categorization of Web service capabilities and ontology-based description of operation semantics. We take clues from the drug discovery process and propose a Web service mining framework to group relevant mining activities into a progression of phases that would lead to the eventual discovery of useful compositions. Based on the composition strategies that are derived from recognition mechanisms, we propose a set of algorithms in the screening phase of the framework to automatically identify leads of service compositions. We propose objective interestingness and usefulness measures in the evaluation phase to narrow down the pool of composition leads for further exploration. To demonstrate the effectiveness of our framework and to address challenges faced by existing biological data representation methodologies, we have applied relevant techniques presented in this dissertation to the field of biological pathway discovery. / Ph. D.