Philosophiae Doctor - PhD / There are over 100 different types of cancer, and each of these cancers are classified by the type of cell that it initially affects. For the purpose of this research we will be focussing on prostate cancer (PC). Prostate cancer is the second most common form of cancer in men around the world and annually approximately 4500 men in South Africa are diagnosed making PC a global epidemic. Prostate cancer is a type of cancer which starts in the prostate it is normally a walnut-sized gland found right below the bladder. PC follows a natural course, starting as a tiny group of cancer cells that can grow into a tumour. In some men if PC is not treated it may spread to surrounding tissue by a process called direct invasion/ spread and could lead to death. Current diagnostic tests for prostate cancer have low specificity and poor sensitivity. Although many PC's are slow growing there is currently no test to distinguish between these and cancers that will become aggressive and life threatening. Therefore the need for a less invasive early detection method with the ability to overcome the lack of specificity and sensitivity of current available diagnostic test is required. Biomarkers have recently been identified as a viable option for early detection of disease for example biological indicators ie. DNA, RNA, proteins and microRNAs (miRNAs). Since first described in the 1990s, circulating miRNAs have provided an active and rapidly evolving area of research that has the potential to transform cancer diagnostics and prognostics. In particular, miRNAs could provide potentially new biomarkers for PC as diagnostic molecules. Circulating miRNAs are highly stable and are both detectable and quantifiable in a range of accessible bio-fluids, having the potential to be useful as diagnostic, prognostic and predictive biomarkers. In this study we aimed to identify miRNAs as potential biomarkers to detect and distinguish between various types of PC in its earliest stage. The major objectives of the study were to identify miRNAs and their gene targets that play a critical role in disease onset and progression to further understand their mechanism of action in PC using several in silico methods, and to validate the potential diagnostic miRNAs using qRT-PCR in several cell lines. The identification of specific miRNAs and their targets was done using an "in-house" designed pipeline. Bioinformatic analyses was done using a number of databases including STRING, DAVID, DIANA and mFold database, and these combined with programming and statistical analyses was used for the identification of potential miRNAs specific to PC. Our study identified 40 miRNAs associated with PC using our "in-house" parameters in comparison to the 20-30 miRNAs known to be involved in PC found in public databases e.g. miRBase. A comparison between our parameters and those used in public databases showed a higher degree of specificity for the identification PC-associated miRNAs. These selected miRNAs were analysed using different bioinformatics tools, and were confirmed to be novel miRNAs associated with PC. The identified miRNAs were experimentally validated using qRT-PCR to generate expression profiles for PC as well as various other cancers. Prostate lines utilised in this study included PNT2C2 (normal) which was compared to BPH1 (Benign) and LNCaP (Metastatic). In the study the expression profiles of eight potential miRNA biomarkers for the detection of PC was determined using qRT-PCR, and to distinguish PC from other cancers. QRT-PCR data showed that miRNA-3 and -5 were up-regulated in the BPH1 and LNCaP when compared to PNT2C2. In addition miRNA-8 was also shown to be up-regulated in LNCaP. Based on these results it was shown that a miRNA profile could be established to distinguish between BPH1 and the LNCaP prostate cell lines. The results suggest that one miRNA as a diagnostic marker may be sufficient to differentiate between different cancer cell lines. Furthermore by creating a unique profile for each cancer cell line by using a combination of miRNAs could be a suitable approach as well. Finally, it was shown that through the use of a single or combination of all eight miRNAs a unique profile for all the cancer cell lines tested in this study can be created. This is an important finding which could have potential diagnostic or prognostic implications in clinical practice.

Pattern Discovery, a popular paradigm in data mining refers to a class of techniques that try and extract some unknown or interesting patterns from data. The work carried out in this thesis concerns frequent episode mining, a popular framework within pattern discovery, with applications in alarm management, fault analysis, network reconstruction etc. The data here is in the form of a single longtime-ordered stream of events. The pattern of interest here, namely episode, is basically a set of event-types with a partial order on it. The task here is to unearth all patterns( episodes here) which have a frequency above a user-defined threshold irrespective of pattern size. Most current discovery algorithms employ a level-wise a priori-based method for mining, which basically adopts a breadth-first search strategy of the space of all episodes. The episode literature has seen multiple ways of defining frequency with each definition having its own set of merits and demerits. The main reason for different frequencies definitions being proposed is that, in general, counting all occurrences of a set of episodes is computationally very expensive. The first part of the thesis gives a unified view of all the apriori-based discovery algorithms for serial episodes(associated with a total order)under these various frequencies. Specifically, the various existing counting algorithms can be viewed as minor modifications of each other. We also provide some novel proofs of correctness for some of the serial episode counting schemes, which in turn can be generalized to episodes with general partial orders. Our unified view helps us derive quantitative relationships between different frequencies. We also discuss all the anti-monotonicity properties satisfied by the various frequencies, a crucial information needed for the candidate generation step. The second part of the thesis proposes discovery algorithms for episodes with general partial orders, for which no algorithms currently exist in literature. The discovery algorithm proposed is apriori-based and generalizes the existing serial and parallel (associated with a trivial order) episode algorithms. The discovery algorithm is a level-wise procedure involving the steps of candidate generation and counting a teach level. In the context of general partial orders, a major problem in a priori-based discovery is to have an efficient candidate generation scheme. We present a novel candidate generation algorithm for mining episodes with general partial orders. The counting algorithm design for general partial order episodes draws ideas from the unified view of counting for serial episodes, presented in the first part of the work. We formally show the correctness of the proposed candidate generation and counting steps for general partial orders. The proposed candidate generation algorithm is flexible enough to be able to mine in certain specialized classes of partial orders (satisfying what we call maximal sub episode property), of which, the serial and parallel class of episodes are two specific instances. Our algorithm design initially restricts itself to the class of general partial order episodes called injective episodes wherein repeated event-types are not allowed. We then generalize this to a larger class of episodes called chain episodes, where episodes can have some repeated event types. The class of chain episodes contains all (including non-injective) serial and parallel episodes and thus our method properly generalizes the existing methods for serial and parallel episode discovery. We also discuss some problems in extending our algorithms to episodes beyond the class of chain episodes. Also, we demonstrate that frequency alone is not a sufficient enough interestingness measure for episodes with unrestricted partial orders. To address this issue, we propose an additional measure called bidirectional evidence to assess interestingness which, along with frequency is found to be extremely effective in unearthing interesting patterns. In the frequent episode framework, the choice of thresholds are most often user-defined and arbitrary. To address this issue, the last part of the work deals with assessing significance of partial order episodes in a statistical sense based on ideas from classical hypothesis testing. We declare an episode to be significant if its observed frequency in the data stream is large enough to be very unlikely, under a random i.i.d model .The key step in the significance analysis involves the mean and variance computation of the the time between successive occurrences of the pattern. This computation can be reformulated as, solving for the mean and variance of the first visit time to a particular stat e in an associated Markov chain. We use a generating function approach to solve for this mean and variance. Using this and a Gaussian approximation to the frequency random variable, we can now calculate a frequency threshold for any partial order episode, beyond which we infer it to be significant. Our significance analysis for general partial order episodes generalizes the existing significance analysis of serial episode patterns. We demonstrate on synthetic data the effectiveness of our significance thresholds.

During the route discovery process, each node receiving the route request packet (RReq) will retransmit it exactly once. A distant neighbor may accidentally receive/loose the only RReq and use it to announce a new route, although that link is inferior/superior for route reply packets (RRep) or actual message routing. Overall, the constructed route may be far from the optimal. All existing route discovery schemes (including DSR/AODV) apply retransmission during route discovery exactly once (1R). Based on a realistic physical layer model, we propose two new route discovery schemes: n-retransmission (nR, retransmitting exactly n times) and n-retransmission c-reception (ncRR), retransmitting until we either reach a total of n own retransmissions or c copies from neighbors are heard. We compare our two new scheme with the traditional one, under otherwise identical conditions (same metric, same packet reception probability on each link) and the same choices about possibly retransmitting again upon discovering a better route (R+) or discarding it (R1), generating route reply packet for every received RRep (B*), or for first and better discovered routes only (B2), and retransmitting RRep exactly once (A1), up to a maximum of three times (A3), or optimally u times decided by link quality (Au). Experimental results show that the proposed ncRR scheme (for n=2 and c=3 or c=4) achieves the best tradeoff between quality of route, success rate and message overhead in the route discovery process, followed by the nR scheme, and both of them are superior to the existing traditional schemes.

The connexins are a family of 21 proteins that represent the structural units of intercellular gap junctions and single membrane hemichannels. These channels provide a means for cells to exchange small metabolites and signaling molecules with adjacent cells and the extracellular space, respectively. Compelling evidence implicates connexins, and the more recently discovered pannexins, in the control of neural progenitor cell proliferation, survival and migration. Moreover, connexin and pannexin dysregulation following central nervous system injuries such as cerebral ischemia, spinal cord injury, and epilepsy contributes to the secondary expansion of lesions days and weeks after the initial insult. While these data suggest that connexins and pannexins represent novel therapeutic targets to both reduce the extent of neural injury and promote neural repair and regeneration, we currently lack the necessary repertoire of therapeutically useful connexin- and pannexin-specific compounds to test these hypotheses. In this thesis, I conducted targeted screening of a large, ethnobotanically-derived library to address my overarching objective of identifying compounds that selectively alter connexin and/or pannexin channel function. To accomplish this, I characterized the repertoire of connexins and pannexins expressed by neural progenitor cell-like NT2/D1 cells, quantified the intercellular flux of calcein through connexin gap junctions, and measured the uptake of lucifer yellow and propidium iodide through pannexin hemichannels. Collectively, these screens identified several promising lead compounds and ethanolic plant extracts that selectively alter connexin and pannexin channel activity.

According to the World Health Organization, malaria has been classified as one of the three most important infectious diseases in Africa. The number of malaria cases is still on the increase in various countries, such as Rwanda and Zambia, which highlights the fragility of malaria control and the need to maintain and improve control programs. An innovative strategy for developing new antimalarial agents is through targeting epigenetic regulatory mechanisms in the malarial parasite, Plasmodium falciparum. Histone posttranslational modifications (PTMs) are factors contributing to epigenetic regulation in P. falciparum parasites. The epigenetic regulatory enzyme, Lysine-specific demethylase 1 (LSD1), has the ability to remove methyl groups from mono- and dimethylated lysine residues and is a regulator of gene expression through the modulation of chromatin structure. Polyamine analogues have been described as epi-drugs that target cell cycle development by blocking epigenetic control mechanisms in mammalian cells. A library of polyamine analogues were tested in cancer cells and found to specifically inhibit LSD1. In addition, these analogues were shown to have antiplasmodial activity against a drug-sensitive parasite strain, with IC50 values ranging from 88-100 nM but were metabolically unstable in vivo. In an attempt to overcome this in vivo hurdle, the leading compound was fluorinated at four different positions and tested for improved antiplasmodial activity and selectivity towards the parasites. Furthermore, the effect of the compounds on epigenetic regulatory mechanisms, through inhibition of LSD1 activity, was investigated. The analogues showed inhibition of parasite proliferation at low nanomolar concentrations and were very selective towards the parasites with low resistance indices. The leading compound showed reversible cytotoxicity towards parasite proliferation in addition to inhibitory activity against LSD1 and therefore, epigenetic regulatory changes. The approach taken in this dissertation is novel as none of the currently available antimalarials target LSD1 and as such, adds valuable information to future perspectives for drug design. / Dissertation (MSc)--University of Pretoria, 2015. / tm2015 / Biochemistry / MSc / Unrestricted

No description available.

Software-De_ned Networking (SDN) proposes a new network architecture inwhich the control plane and forwarding plane are decoupled. SDN can improvenetwork e_ciency and ease of management through the centralization of the controland policy decisions. However, SDN deployments are currently limited todata-center and experimental environments. This thesis surveys the deploymentof SDN from the perspective of a telecommunication network operator. We discussthe strategies which enable the operator to migrate to a network in whichboth SDN and legacy devices interoperate. As a synthesis of existing technologiesand protocols, we formulate an automated process for the bootstrapping of newlydeployed forwarding devices. Furthermore, we review solutions for programmingthe forwarding devices and for performing topology discovery. The functionalcorrectness of the proposed bootstrapping process is evaluated in an emulatedenvironment.

Candida albicans is a fungus found in the normal biota of humans, but in immuno-compromised individuals, C. albicans forms complex biofilms on the surface of medical prosthetics, skin, oral cavities, the urinary tract, and other epithelial cell layers. Biofilms and the development of drug resistance has limited treatment options. Antimicrobial peptides (AMPs) are increasingly becoming attractive therapeutic agents for the treatment of these infections due to their multifunctional properties, multiple cellular targets, and the lower incidence of resistance development. Previous studies have shown that Os, an AMP derived from the tick defensin OsDef2, has antifungal activity against C. albicans. Preliminary antifungal mode of action studies indicated that Os induces the formation of reactive oxygen species although not a primary mode of killing. Os causes membrane permeabilization, which is inhibited by an excess of free laminarin and mannan. Furthermore, Os was shown to bind plasmid DNA but was inactive in high salt conditions. The aim of this study was to further explore the mode of action of Os in planktonic C. albicans (ATCC 90028) cells. A modified microbroth dilution assay was developed to allow rapid screening of salt sensitive AMPs such as Os. With this method the IC50 of the positive control, amphotericin B (AmpB), and Os were determined as 0.547 ± 0.056 μM and 1.163 ± 0.116 μM, respectively. The effects of AmpB and Os on cellular morphology were evaluated using scanning electron microscopy and transmission electron microscopy at their respective IC25, IC50 and IC75 values. When comparing the effects of Os with AmpB on the cell wall and membrane, Os had more severe and nonspecific effects. Os induced the formation of pits on the cell surface and pores in the cell membrane, as well as increased budding scars. Using isothermal titration calorimetry, no interaction between Os and the fungal cell wall components, mannan and laminarin, could be detected. Factors such as the lack of tryptophan and aspartate residues as well as β-sheet secondary structures may account for the lack of interaction. However, with the modified microbroth dilution assay in the presence of excess of mannan or laminarin (20 mg/mL), reduced activity from Os was observed. The formation of soluble macro-complexes between Os and the cell wall components at high concentrations may account for reduced activity. The ability of Os to cause membrane depolarization was evaluated with bis-(1,3-dibutylbarbituric acid) trimethine oxonol. The control, melittin, caused a linear increase in depolarization with a significant increase at 0.63 μM, while Os caused a sigmoidal increase in depolarization with a significant increase at 2.5 μM. Therefore, membrane depolarization occurs following membrane permeabilization which occurs at 2 μM. Finally, the localisation of 0.5 μM and 6.4 μM (IC25, IC75) 5-FAM-Os, and concurrently the effect on vacuoles loaded with CellTracker Blue-CMAC, was determined with flow cytometry and confocal laser scanning microscopy (CLSM). Findings were that Os, at a concentration below its IC50, binds to the cell membrane, then translocates and binds DNA. At a concentration above its IC50, Os accumulates in the cytoplasm and causes destruction of membranes, including that of vacuoles, leading to cell death. In conclusion, this study shows that Os is a membrane acting AMP that can be further developed for clinical application as an antifungal drug. / Dissertation (MSc (Biochemistry))--University of Pretoria, 2020 / NRF / Biochemistry / MSc (Biochemistry) / Unrestricted

The main focus of our work is to develop, apply and assess cheminformatics tools and methods. In particular, we focus on the following three areas: Integration of open source tools with application to drug discovery, usability studies to assess the efficacy of these software tools and finally, developing novel techniques for database query. Rapid globalization in the present time has sparked a need in the scientific community to interact with each other at an economic and a fast pace. This is achieved by developing and sharing open source databases using World Wide Web. A web based open source database application has been developed to incorporate freeware from varied sources. The deployment of developed database and user interface in a university lab setting is discussed. To aid in connecting the end user and the software tools, usability studies are necessary. These studies communicate the end users’ needs and desires, resulting in a user-friendly and more powerful interactive software packages. Usability studies were conducted on developed database student application and on different drawing packages to determine their effectiveness. Developing new and interactive search engines to query publicly available databases helps researchers work more efficiently. The huge volume of data available and its heterogeneous nature presents issues related to querying, integration and presentation. In aiding the retrieval process, an innovative multi faceted classification system, called ChemFacets, is developed. This system provides dynamic categorization of large result sets retrieved from multiple databases.

京都大学 / 0048 / 新制・課程博士 / 博士(工学) / 甲第20002号 / 工博第4246号 / 新制||工||1657(附属図書館) / 33098 / 京都大学大学院工学研究科合成・生物化学専攻 / (主査)教授 濵地 格, 教授 森 泰生, 教授 跡見 晴幸 / 学位規則第4条第1項該当 / Doctor of Philosophy (Engineering) / Kyoto University / DFAM