No description available.

Malaria afflicts about 500 million people worldwide thus causing significant global economic toll. The drugs available to treat the disease are rapidly losing their efficacy because of widespread prevalence of drug resistant parasites. Thus there is an urgent need to discover novel malaria therapeutics. This research is focused on to study the properties of a novel naturallike synthetic scaffold and analyze its selectivity, and cellular mechanism of action in Plasmodium falciparum. We have identified a novel compound, 3-amino-2-piperidinequinoline (APQ), which we termed UCF401. APQ demonstrated IC[sub50] at submicromolar concentrations against Plasmodium falciparum using the SYBR Green-I fluorescence assay measuring cellular proliferation. This compound also demonstrated low cytotoxicity against the NIH3T3 and HEPG2 cells using MTS assays, showing an IC50 of 174 [micro]M and 125 [micro]M respectively, suggesting of excellent selectivity. We evaluated the compliance of APQ with Lipinski's parameters and determined the in vitro physicochemical profiles of the compound. Our results show that APQ is a Lipinski parameter compliant and has good physicochemical properties. The cellular mechanism of action of APQ was characterized through the assessment of the effects of the compound at different stages of the parasite's intraerythrocytic life cycle. This assay was done by treating a synchronized cell line with the compound at 5X the IC50 value and then imaging the cells at 12-hour intervals. We found that APQ arrests parasite development at the trophozoite stage. In addition we determined that APQ is parasitocidal after a 96 h exposure. These results demonstrate that APQ can be considered as a validated hit and/or early lead.

In a short dialogue, philosopher Paul Feyerabend made some remarks regarding the interpretation of Plato’s theory of writing in the Phaedrus, which boil down to the suggestion that written works are didactically valuable when having the right kind of resemblance to “live exchanges”, adding that Plato in this respect resembles modern philosophies of science. In the present thesis, I flesh out and vindicate Feyerabend’s suggestions by a thematic reading of Phaedrus 274c–278b and a subsequent comparison of the interpreted theory with a few relevant modern philosophies of science.  My reading focuses on Plato’s philosophical use of the words ζῆν ‘live’, εἴδωλον ‘idol/image/representation/eidōlon’ and παιδιά ‘play’. Through them I show how Plato constructs a three-tiered value ranking of didactic processes, with live exchanges as the best, traditional monographs in the style of Lysias’ written speech as the worst, and Plato’s own original conception of “playful” writing in the middle: “a kind of eidōlon” of a live exchange that nevertheless does not pretend to be the real thing. Plato’s three tiers correspond well to the modern distinction between everyday scientific work, scientific papers and the different suggestions for in-betweens, such as the one made by Peter Medawar or the one contained in the so-called strong programme of David Bloor. I also identify four characteristics of Plato’s theory, including its emphasis on imitative learning, the necessity of the prescribed didactics, non-propositionality and reflexivity, which are found in the modern philosophies of the just-mentioned authors, as well as in that of Ludwik Fleck.

No description available.

With an ever-growing number of publications in the biomedical domain, it becomes likely that important implicit connections between individual concepts of biomedical knowledge are overlooked. Literature based discovery (LBD) is in practice for many years to identify plausible associations between previously unrelated concepts. In this paper, we present a new, completely automatic and interactive system that creates a graph-based knowledge base to capture multifaceted complex associations among biomedical concepts. For a given pair of input concepts, our system auto-generates a list of ranked subgraphs uncovering possible previously unnoticed associations based on context information. To rank these subgraphs, we implement a novel ranking method using the context information obtained by performing random walks on the graph. In addition, we enhance the system by training a Neural Network Classifier to output the likelihood of the two concepts being likely related, which provides better insights to the end user.

No description available.

The Bluetooth Scatternet Formation (BSF) problem can be defined as the problem of forming wireless networks of Bluetooth devices in an efficient manner. A number of restrictions imposed by the Bluetooth specifications make the BSF problem challenging and unique. Many interesting solution algorithms have been proposed in the literature to solve this problem. In this thesis, we investigate the BSF problem. We concentrate on problems introduced by the procedures of device discovery of the Bluetooth specifications and on the different solutions used by BSF algorithms to deal with these problems. We study also in this thesis problems introduced by the specifications of link establishment in Bluetooth due to their close interaction with the device discovery specifications. We survey and categorize the different device discovery techniques used by BSF algorithms. This categorization is then used as a basis to identify the different theoretical computational models used to study BSF algorithms. We argue, in this thesis, that the currently available models for Bluetooth wireless networks do not model adequately, in most cases, the complexities of the Bluetooth specifications and we show that these models were oversimplified in many cases. A general computational model will be useful as a starting point to design BSF algorithms and to compare the different and numerous BSF algorithms – especially in term of the execution time efficiency. In this thesis, we provide a set of suggestions that will help in the creation of such model. We survey a number of studies that examined in more depth the specifications of device discovery in Bluetooth. We survey also other studies that attempted to simplify the Bluetooth network model, either by suggesting modifications on the Bluetooth specifications or by the use of communication technologies other than Bluetooth. Finally, we present some experiments accompanied with analyzes to show the complexities of the Bluetooth specifications and their sensitivity to minor changes (whether in the specifications or in their implementation).

Missing data are ubiquitous in many domains such as healthcare. Depending on how they are missing, the (conditional) independence relations in the observed data may be different from those for the complete data generated by the underlying causal process (which are not fully observable) and, as a consequence, simply applying existing causal discovery methods to the observed data may give wrong conclusions. It is then essential to extend existing causal discovery approaches to find true underlying causal structure from such incomplete data. In this thesis, we aim at solving this problem for data that are missing completely at random (MCAR), missing at random (MAR), or missing not at random (MNAR). With missingness mechanisms represented by the Missingness Graph, we present conditions under which addition corrected to derive conditional independence/dependence relations in the complete data. Combined with the correction method that gives closed-form, consistent tests of conditional independence, the proposed causal discovery method, as an extension of the PC algorithm, is shown to give asymptotically correct results. Experiment results illustrate that with further reasonable assumptions, the proposed algorithm can correct the conditional independence for values MCAR, MAR and rather general cases of values MNAR. / Saknade data är allestädes närvarande på många områden, t.ex. sjukvård. Beroende på hur de saknas kan de (villkorliga) oberoende förhållandena i de observerade uppgifterna skilja sig från de för de fullständiga data som genereras av den underliggande orsaksprocessen (som inte är fullt observerbara) och som en följd av att helt enkelt tillämpa befintlig kausal upptäckt metoder för de observerade data kan ge felaktiga slutsatser. Det är då viktigt att förlänga befintliga metoder för kausala upptäckter för att hitta en sann underliggande kausalstruktur från sådana ofullständiga data. I denna avhandling strävar vi efter att lösa detta problem för data som saknas helt slumpmässigt (MCAR), saknas slumpmässigt (MAR) eller saknas inte slumpmässigt (MNAR). Med missmekanismer representerade av Missfallsgrafen presenterar vi förhållanden under vilka tillägg korrigerade för att härleda villkorliga oberoende/beroendeförhållanden i de fullständiga uppgifterna.Kombinerad med korrigeringsmetoden som ger sluten form, konsekventa test av villkorligt oberoende, visas att den föreslagnaorsaks-sökningsmetoden, som en förlängning av PC-algoritmen, ger asymptotiskt korrekta resultat. Experimentresultat illustrera att med ytterligare rimliga antaganden kan den föreslagna algoritmen korrigera det villkorliga oberoende för värdena MCAR, MAR och ganska generella fall av värden MNAR.

As malaria, caused by Plasmodium spp., continues to afflict millions of people worldwide, there is a dire need for the discovery of novel, inexpensive antimalarial drugs. Although there are effective drugs on the market, the consistent development of drug resistant species has decreased their efficacy, further emphasizing that novel therapeutic measures are urgently needed. Natural products provide the most diverse reservoir for the discovery of unique chemical scaffolds with the potential to effectively combat malarial infections, but, due to their complex structures, they often pose extreme challenges to medicinal chemists during pharmacokinetic optimization. In our laboratory we have performed unbiased, cell-based assays of numerous synthetic compounds from chemical libraries enriched with nature-like elements. This screening has led to the discovery of many original chemical scaffolds with promising antimalarial properties. In an attempt to further characterize these scaffolds, the most promising compounds were assayed in order to determine their cytotoxic effects on mammalian cells. In addition, the development of a drug resistant parasite line of Plasmodium falciparum to the most promising compound was done in order to determine the relative probability for parasite resistance development.

Crisis management simulation is important in training the next generation of surgeons. In this review, we highlight our experiences with the cavernous carotid injury model. We then delve into other crisis simulation models available for the neurosurgical specialty. The discussion focuses upon how these trainings can continue to evolve. Much work is yet to be done in this exciting arena and we present several avenues for future discovery. Simulation continues to be an important training tool for the surgical learner.