One unique feature of cancer cells that can be exploited for anticancer drug discovery is their dependence on their own cellular stress responses to survive the stressful acidotic, hypoxic and nutrient-deprived conditions within the tumor. Reasoning that desert organisms surviving under stressful conditions may have evolved to produce small molecule metabolites capable of modulating heat shock protein 90 (Hsp90) function, and/or other cell stress responses, we employed the cellular heat shock response in a moderate-throughput phenotypic assay. This strategy has resulted in the isolation and characterization of a number of small molecule natural products with heat shock induction activity from these organisms. Three such natural products are the subject of this study.In a limited structure-activity relationship (SAR) study, a previously known Hsp90 inhibitor radicicol (RAD), and several structurally related molecules including the fungal metabolite monocillin 1 (MON) were found to interact with Hsp90. In addition, RAD and MON were shown to lead to the degradation of Hsp90 client proteins involved in the cancer cell survival the estrogen receptor (ER) and the insulin-like growth factor receptor 1 (IGF-1R).We further characterized MON and showed that by targeting the molecular chaperone Hsp90, this compound induces components of the heat shock response at the transcriptional and translational levels, and leads to the acquisition of a thermotolerant phenotype in seedlings of the plant Arabidopsis thaliana. These findings support our hypothesis that there is ecological significance to the elaboration of small molecules that target stress responses.A number of extracts active in our phenotypic assay contained small molecules with no apparent Hsp90 activity. One such extract afforded terrecyclic acid A (TCA) with significant anti-tumor activity against a panel of human cancer cell lines. To characterize the biological activities of TCA we examined three key stress responsesthe heat shock, oxidative, and inflammatory responsesand show that TCA destabilizes these pathways associated with cancer cell survival through induction of oxidative stress (ROS), and inhibition of NF-kappaB transactivation.The isolation of RAD, MON and TCA from Sonoran desert organisms provides proof of principle that we have developed an effective strategy for the discovery of small molecule modulators of cellular stress responses that can serve as leads for the development of new anticancer drugs with novel mechanisms of action.

In this thesis we study three basic issues related to international black tea markets: Are black tea markets integrated? Where is the price of black tea discovered? Are there leaders and followers in black tea markets? We use two statistical techniques as engines of analysis. First, we use time series methods to capture regularities in time lags among price series. Second, we use directed acyclic graphs to discover how surprises (innovations) in prices from each market are communicated to other markets in contemporaneous time. Weekly time series data on black tea prices from seven markets around the world are studied using time series methods. The study follows two paths. We study these prices in a common currency, the US dollar. We also study prices in each country's local currency. Results from unit root tests suggest that prices from three Indian markets are not generated through random walk-like behavior. We conclude that the Indian markets are not weak form efficient. However, prices from all non-Indian markets cannot be distinguished from random walk-like behavior. These latter markets are weak form efficient. Further analysis on these latter markets is conducted to determine whether information among the markets is shared. Vector Autoregressions (VARs) on the non-Indian markets are studied using directed acyclic graphs, impulse response functions and forecast error decomposition analyses. In both local currencies and dollar-converted series, the Sri Lankan and Indonesian markets are price leaders in contemporaneous time. Kenya is an information sink. It is endogenous in current time. Malawi is an exogenous price leader in dollar terms, but it is endogenous in local currency in contemporaneous time. In the long run, Sri Lanka, Indonesia and Malawi are price leaders in US dollar terms. In local currency series, Indonesia, Kenya and Malawi are price leaders in the long run. We use Theil's U-statistic to test the forecasting ability of the VAR models. We find for most markets in either dollars or on local currencies that a random walk forecast outperforms the VAR generated forecasts. This last result suggests the non-Indian markets are both weak form and semi-strong form efficient.

For a large mixed-mode database, how to discretize its continuous data into interval events is still a practical approach. If there are no class labels for the database, we have nohelpful correlation references to such task Actually a large relational database may contain various correlated attribute clusters. To handle these kinds of problems, we first have to partition the databases into sub-groups of attributes containing some sort of correlated relationship. This process has become known as attribute clustering, and it is an important way to reduce our search in looking for or discovering patterns Furthermore, once correlated attribute groups are obtained, from each of them, we could find the most representative attribute with the strongest interdependence with all other attributes in that cluster, and use it as a candidate like a a class label of that group. That will set up a correlation attribute to drive the discretization of the other continuous data in each attribute cluster. This thesis provides the theoretical framework, the methodology and the computational system to achieve that goal.

Increasing number of software vendors are offering or planning to offer their applications as a Software-as-a-Service (SaaS) to leverage the benefits of cloud computing and Internet-based delivery. Therefore, potential clients will face increasing number of providers that satisfy their requirements to choose from. Consequently, there is an increasing demand for automating such a time-consuming and error-prone task. In this work, we develop an architecture for automated service discovery and selection in cloud computing environment. The system is based on an algorithm that recommends service choices to users based on both functional and non-functional characteristics of available services. The system also derives automated ratings from monitoring results of past service invocations to objectively detect badly-behaving providers. We demonstrate the effectiveness of our approach using an early prototype that was developed following object-oriented methodology and implemented using various open-source Java technologies and frameworks. The prototype uses a Chord DHT as its distributed backing store to achieve scalability.

Genome-wide Association (GWA) studies have become a widely used method for analyzing genetic data. It is useful in detecting associations that may exist between particular alleles and diseases of interest. This thesis investigates the dataset provided from problem 1 of the Genetic Analysis Workshop 16 (GAW 16). The dataset consists of GWA data from the North American Rheumatoid Arthritis Consortium (NARAC). The thesis attempts to determine a set of single nucleotide polymorphisms (SNP) that are associated significantly with rheumatoid arthritis. Moreover, this thesis also attempts to address the question of whether the one-sided alternative hypothesis that the minor allele is positively associated with the disease or the two-sided alternative hypothesis that the genotypes at a locus are associated with the disease is appropriate, or put another way, the question of whether examining both alternative hypotheses yield more information.

Grids are collaborative distributed Internet systems characterized by large scale, heterogeneity, lack of central control, multiple autonomous administrative domains, unreliable components and frequent dynamic change. In such systems, it is desirable to maintain and query dynamic and timely information about active participants such as services, resources and user communities. The web services vision promises that programs are made more flexible, adaptive and powerful by querying Internet databases (registries) at runtime in order to discover information and network attached building blocks, enabling the assembly of distributed higher-level components. In support of this vision, we introduce the Web Service Discovery Architecture (WSDA), we introduce the hyper registry, which is a centralized database node for discovery of dynamic distributed content. It supports XQueries over a tuple set from a dynamic XML data model.

The evolutionary distance of lampreys from humans in conjunction with their distinct antibody architecture is profound. Thus, lampreys may provide antibodies with specificity for antigens unrecognized by conventional mammalian antibodies. This study investigates lamprey based monoclonal variable lymphocyte receptor antibodies (VLRs) for purifying and identifying an antigen by tandem mass spectrometry. VLRs specific for clinically relevant cell populations were isolated. Subsequently, utilizing intrinsic VLR affinity, with or without covalent cross-linking molecules, for immunoprecipitating VLR protein antigens was tested. In one case, CD5 glycoprotein from Jurkat T cells was purified by a VLR; the antigen was identified by tandem mass spectrometry. Antibody specificity was validated by western blotting and flow cytometry. Furthermore, VLR binding to CD5 required multimerization of the antibody, indicating the individual VLR units likely bind antigen with low affinity. The study provides ‘proof of concept’ for human biomarker identification using novel lamprey monoclonal antibodies.

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