Capped acyclic permutants of the circular protein kalata B1

The cyclotides are a family of head-to-tail cyclized peptides that display exceptionally high stability and a range of biological activities. Acyclic permutants that contain a break in the circular backbone have been reported to be devoid of the haemolytic activity of the prototypic cyclotide kalata B1, but the potential role of the charges at the introduced termini in this loss of membraneolytic activity has not been fully determined. In this study, acyclic permutants of kalata B1 with capped N- and G termini were synthesized and found to adopt a native fold. These variants were observed to cause no measurable lysis of erythrocytes, strengthening the connection between backbone cyclization and haemolytic activity. (C) 2004 Published by Elsevier B.V. on behalf of the Federation of European Biochemical Societies.

Cyclic and acyclic modifications of 5-aminoimidazole-4-carboxamide

The Introduction gives a brief resume' of the biologically important aspects of 5 -aminoimidazole -4 -carbozamide (1) and explores., in-depth, the synthetic routes to this imidazole. All documented reactions of 5 -aninoimidanole-4 -carboxamide are reviewed in detail, with particular emphasis on the preparation and subsequent coupling reactions of 5 –diazo-imidazole-4 -carboxamide (6). A series of thirteen novel amide 5-amino-2-arylazoimidazole-4-carboxamide derivatives (117-129) were prepared by the coupling of aryldiazonium salts with 5-aminoimidazole-4-carboxamide. Chemical modification of these azo-dyes resulted in the preparation of eight previously unknown acyl derivatives (136-143) Interaction of 5-amino-2-arylazoimidazole-4-carboxides with ethyl formate in sodium ethoxide effected pyrimidine ring closure to the novel 8-arylazohypoxanthines (144 and 145). Several reductive techniques were employed in an effort to obtain the elusive 2,5-diaminoimidazole-4-carboxamide (71),a candidate chemotherapeutic agent, from the arylazoiridazoles. No success can be reported although 5-amino-2-(3-aminoindazol-2-yl) imidazole-4-carboxamide (151) was isolated due to a partial reduction and intramolecular cyclisation of 5-amino72-(2-cyanaphenylazo)imidazole-4-carboxamide (122) .Further possible synthetic approaches to the diaminoimidazole are discussed in Chapter 4. An interesting degradation of a known unstable nitrohydrazone is described in Chapter 5.This resulted in formation of 1, 1-bis(pyrazol--3-ylazo)-1-nitroethane (164) instead of the expected cyclisation to a bicyclic tetrazine N-oxide. An improved preparation of 5-diazoinidazole-4-carboxamide has been achieved, and the diazo-azole formed cycloadducts with isocyanates to yield the hitherto unknown imidazo[5,1-d][1,2,3,5]tetrazin-7(6H)-ones. Eleven derivatives (167-177) of this new ring-system were prepared and characterised. Chemical and spectroscopic investigation showed this ring-system to be unstable under certain conditions, and a comparative study of stability within the group has been made. "Retro-cycloaddition" under protic and photolytic conditions was an unexpected property of 6-substituted imidazo[5,1-d][1,2,3,5]tetrazin--7(0)-ones.Selected examples of the imidazotetrazinone ring-system were tested for antitumour activity. The results of biological evaluation are given in Chapter 7, and have culminated in a Patent application by the collaborating body, May and Baker Ltd. One compound,3-carbamoyl-6-(2-chloro-ethyl)imidazo[5,1-d][1,2,3,5jtetrazin-7(6H)-one (175),shows striking anti-tumour activity in rodent test systems.

Acyclic stereocontrol and chemical diversity & application to the total synthesis of Bafilomycin A₁

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Acyclic stereocontrol and chemical diversity & application to the total synthesis of Bafilomycin A₁

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

(Figure 4) Stable carbon isotopic values and relative contents of biphytanes and sugars from sediment sample from the Peru margin and from the Pakistan margin

Glycolipids are prominent constituents in the membranes of cells from all domains of life. For example, diglycosyl-glycerol dibiphytanyl glycerol tetraethers (2Gly-GDGTs) are associated with methanotrophic ANME-1 archaea and heterotrophic benthic archaea, two archaeal groups of global biogeochemical importance. The hydrophobic biphytane moieties of 2Gly-GDGTs from these two uncultivated archaeal groups exhibit distinct carbon isotopic compositions. To explore whether the isotopic compositions of the sugar headgroups provide additional information on the metabolism of their producers, we developed a procedure to analyze the d13C values of glycosidic headgroups. Successful determination was achieved by (1) monitoring the contamination from free sugars during lipid extraction and preparation, (2) optimizing the hydrolytic conditions for glycolipids, and (3) derivatizing the resulting sugars into aldononitrile acetate derivatives, which are stable enough to withstand a subsequent column purification step. First results of d13C values of sugars cleaved from 2Gly-GDGTs in two marine sediment samples, one containing predominantly ANME-1 archaea and the other benthic archaea, were obtained and compared with the d13C values of the corresponding biphytanes. In both samples the dominant sugar headgroups were enriched in 13C relative to the corresponding major biphytane. This 13C enrichment was significantly larger in the putative major glycolipids from ANME-1 archaea (~15 per mil) than in those from benthic archaea (<7 per mil). This method opens a new analytical window for the examination of carbon isotopic relationships between sugars and lipids in uncultivated organisms.

Influence of Two Acyclic Homoterpenes (Tetranorterpenes) on the foraging behavior of Anthonomus grandis Boh.

2016

A role mining inspired approach to representing user behaviour in ERP systems

Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the most predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.

Transaction mining for fraud detection in ERP Systems

Despite all attempts to prevent fraud, it continues to be a major threat to industry and government. Traditionally, organizations have focused on fraud prevention rather than detection, to combat fraud. In this paper we present a role mining inspired approach to represent user behaviour in Enterprise Resource Planning (ERP) systems, primarily aimed at detecting opportunities to commit fraud or potentially suspicious activities. We have adapted an approach which uses set theory to create transaction profiles based on analysis of user activity records. Based on these transaction profiles, we propose a set of (1) anomaly types to detect potentially suspicious user behaviour, and (2) scenarios to identify inadequate segregation of duties in an ERP environment. In addition, we present two algorithms to construct a directed acyclic graph to represent relationships between transaction profiles. Experiments were conducted using a real dataset obtained from a teaching environment and a demonstration dataset, both using SAP R/3, presently the predominant ERP system. The results of this empirical research demonstrate the effectiveness of the proposed approach.

Exploiting the 1,2,3-triazolium motif in anion-templated formation of a bromide-selective rotaxane host assembly

Stimulated by the efficacy of copper (I) catalysed Huisgen-type 1,3-dipolar cycloaddition of terminal alkynes and organic azides to generate 1,4-disubstituted 1,2,3-triazole derivatives, the importance of ‘click’ chemistry in the synthesis of organic and biological molecular systems is ever increasing.[1] The mild reaction conditions have also led to this reaction gaining favour in the construction of interlocked molecular architectures.[2-4] In the majority of cases however, the triazole group simply serves as a covalent linkage with no function in the resulting organic molecular framework. More recently a renewed interest has been shown in the transition metal coordination chemistry of triazole ligands.[3, 5, 6] In addition novel aryl macrocyclic and acyclic triazole based oligomers have been shown to recognise halide anions via cooperative triazole C5-H….anion hydrogen bonds.[7] In light of this it is surprising the potential anion binding affinity of the positively charged triazolium motif has not, with one notable exception,[8] been investigated. With the objective of manipulating the unique topological cavities of mechanically bonded molecules for anion recognition purposes, we have developed general methods of using anions to template the formation of interpenetrated and interlocked structures.[9-13] Herein we report the first examples of exploiting the 1,2,3-triazolium group in the anion templated formation of pseudorotaxane and rotaxane assemblies. In an unprecedented discovery the bromide anion is shown to be a superior templating reagent to chloride in the synthesis of a novel triazolium axle containing [2]rotaxane. Furthermore the resulting rotaxane interlocked host system exhibits the rare selectivity preference for bromide over chloride...

Using Bayesian methods for the estimation of uncertainty in complex statistical models

The research objectives of this thesis were to contribute to Bayesian statistical methodology by contributing to risk assessment statistical methodology, and to spatial and spatio-temporal methodology, by modelling error structures using complex hierarchical models. Specifically, I hoped to consider two applied areas, and use these applications as a springboard for developing new statistical methods as well as undertaking analyses which might give answers to particular applied questions. Thus, this thesis considers a series of models, firstly in the context of risk assessments for recycled water, and secondly in the context of water usage by crops. The research objective was to model error structures using hierarchical models in two problems, namely risk assessment analyses for wastewater, and secondly, in a four dimensional dataset, assessing differences between cropping systems over time and over three spatial dimensions. The aim was to use the simplicity and insight afforded by Bayesian networks to develop appropriate models for risk scenarios, and again to use Bayesian hierarchical models to explore the necessarily complex modelling of four dimensional agricultural data. The specific objectives of the research were to develop a method for the calculation of credible intervals for the point estimates of Bayesian networks; to develop a model structure to incorporate all the experimental uncertainty associated with various constants thereby allowing the calculation of more credible credible intervals for a risk assessment; to model a single day’s data from the agricultural dataset which satisfactorily captured the complexities of the data; to build a model for several days’ data, in order to consider how the full data might be modelled; and finally to build a model for the full four dimensional dataset and to consider the timevarying nature of the contrast of interest, having satisfactorily accounted for possible spatial and temporal autocorrelations. This work forms five papers, two of which have been published, with two submitted, and the final paper still in draft. The first two objectives were met by recasting the risk assessments as directed, acyclic graphs (DAGs). In the first case, we elicited uncertainty for the conditional probabilities needed by the Bayesian net, incorporated these into a corresponding DAG, and used Markov chain Monte Carlo (MCMC) to find credible intervals, for all the scenarios and outcomes of interest. In the second case, we incorporated the experimental data underlying the risk assessment constants into the DAG, and also treated some of that data as needing to be modelled as an ‘errors-invariables’ problem [Fuller, 1987]. This illustrated a simple method for the incorporation of experimental error into risk assessments. In considering one day of the three-dimensional agricultural data, it became clear that geostatistical models or conditional autoregressive (CAR) models over the three dimensions were not the best way to approach the data. Instead CAR models are used with neighbours only in the same depth layer. This gave flexibility to the model, allowing both the spatially structured and non-structured variances to differ at all depths. We call this model the CAR layered model. Given the experimental design, the fixed part of the model could have been modelled as a set of means by treatment and by depth, but doing so allows little insight into how the treatment effects vary with depth. Hence, a number of essentially non-parametric approaches were taken to see the effects of depth on treatment, with the model of choice incorporating an errors-in-variables approach for depth in addition to a non-parametric smooth. The statistical contribution here was the introduction of the CAR layered model, the applied contribution the analysis of moisture over depth and estimation of the contrast of interest together with its credible intervals. These models were fitted using WinBUGS [Lunn et al., 2000]. The work in the fifth paper deals with the fact that with large datasets, the use of WinBUGS becomes more problematic because of its highly correlated term by term updating. In this work, we introduce a Gibbs sampler with block updating for the CAR layered model. The Gibbs sampler was implemented by Chris Strickland using pyMCMC [Strickland, 2010]. This framework is then used to consider five days data, and we show that moisture in the soil for all the various treatments reaches levels particular to each treatment at a depth of 200 cm and thereafter stays constant, albeit with increasing variances with depth. In an analysis across three spatial dimensions and across time, there are many interactions of time and the spatial dimensions to be considered. Hence, we chose to use a daily model and to repeat the analysis at all time points, effectively creating an interaction model of time by the daily model. Such an approach allows great flexibility. However, this approach does not allow insight into the way in which the parameter of interest varies over time. Hence, a two-stage approach was also used, with estimates from the first-stage being analysed as a set of time series. We see this spatio-temporal interaction model as being a useful approach to data measured across three spatial dimensions and time, since it does not assume additivity of the random spatial or temporal effects.

Using a Bayesian network to model colonisation with Vancomycin Resistant Enterococcus (VRE)

Objective: Effective management of multi-resistant organisms is an important issue for hospitals both in Australia and overseas. This study investigates the utility of using Bayesian Network (BN) analysis to examine relationships between risk factors and colonization with Vancomycin Resistant Enterococcus (VRE). Design: Bayesian Network Analysis was performed using infection control data collected over a period of 36 months (2008-2010). Setting: Princess Alexandra Hospital (PAH), Brisbane. Outcome of interest: Number of new VRE Isolates Methods: A BN is a probabilistic graphical model that represents a set of random variables and their conditional dependencies via a directed acyclic graph (DAG). BN enables multiple interacting agents to be studied simultaneously. The initial BN model was constructed based on the infectious disease physician‟s expert knowledge and current literature. Continuous variables were dichotomised by using third quartile values of year 2008 data. BN was used to examine the probabilistic relationships between VRE isolates and risk factors; and to establish which factors were associated with an increased probability of a high number of VRE isolates. Software: Netica (version 4.16). Results: Preliminary analysis revealed that VRE transmission and VRE prevalence were the most influential factors in predicting a high number of VRE isolates. Interestingly, several factors (hand hygiene and cleaning) known through literature to be associated with VRE prevalence, did not appear to be as influential as expected in this BN model. Conclusions: This preliminary work has shown that Bayesian Network Analysis is a useful tool in examining clinical infection prevention issues, where there is often a web of factors that influence outcomes. This BN model can be restructured easily enabling various combinations of agents to be studied.

Parallel ABM for electricity distribution grids : a case study

This paper introduces a parallel implementation of an agent-based model applied to electricity distribution grids. A fine-grained shared memory parallel implementation is presented, detailing the way the agents are grouped and executed on a multi-threaded machine, as well as the way the model is built (in a composable manner) which is an aid to the parallelisation. Current results show a medium level speedup of 2.6, but improvements are expected by incor-porating newer distributed or parallel ABM schedulers into this implementa-tion. While domain-specific, this parallel algorithm can be applied to similarly structured ABMs (directed acyclic graphs).

Constructing a clinical decision-making framework for image-guided radiotherapy using a Bayesian Network

A decision-making framework for image-guided radiotherapy (IGRT) is being developed using a Bayesian Network (BN) to graphically describe, and probabilistically quantify, the many interacting factors that are involved in this complex clinical process. Outputs of the BN will provide decision-support for radiation therapists to assist them to make correct inferences relating to the likelihood of treatment delivery accuracy for a given image-guided set-up correction. The framework is being developed as a dynamic object-oriented BN, allowing for complex modelling with specific sub-regions, as well as representation of the sequential decision-making and belief updating associated with IGRT. A prototype graphic structure for the BN was developed by analysing IGRT practices at a local radiotherapy department and incorporating results obtained from a literature review. Clinical stakeholders reviewed the BN to validate its structure. The BN consists of a sub-network for evaluating the accuracy of IGRT practices and technology. The directed acyclic graph (DAG) contains nodes and directional arcs representing the causal relationship between the many interacting factors such as tumour site and its associated critical organs, technology and technique, and inter-user variability. The BN was extended to support on-line and off-line decision-making with respect to treatment plan compliance. Following conceptualisation of the framework, the BN will be quantified. It is anticipated that the finalised decision-making framework will provide a foundation to develop better decision-support strategies and automated correction algorithms for IGRT.

Causal behavioural profiles : efficient computation, applications, and evaluation

Analysis of behavioural consistency is an important aspect of software engineering. In process and service management, consistency verification of behavioural models has manifold applications. For instance, a business process model used as system specification and a corresponding workflow model used as implementation have to be consistent. Another example would be the analysis to what degree a process log of executed business operations is consistent with the corresponding normative process model. Typically, existing notions of behaviour equivalence, such as bisimulation and trace equivalence, are applied as consistency notions. Still, these notions are exponential in computation and yield a Boolean result. In many cases, however, a quantification of behavioural deviation is needed along with concepts to isolate the source of deviation. In this article, we propose causal behavioural profiles as the basis for a consistency notion. These profiles capture essential behavioural information, such as order, exclusiveness, and causality between pairs of activities of a process model. Consistency based on these profiles is weaker than trace equivalence, but can be computed efficiently for a broad class of models. In this article, we introduce techniques for the computation of causal behavioural profiles using structural decomposition techniques for sound free-choice workflow systems if unstructured net fragments are acyclic or can be traced back to S- or T-nets. We also elaborate on the findings of applying our technique to three industry model collections.

Efficient computation of causal behavioural profiles using structural decomposition

Identification of behavioural contradictions is an important aspect of software engineering, in particular for checking the consistency between a business process model used as system specification and a corresponding workflow model used as implementation. In this paper, we propose causal behavioural profiles as the basis for a consistency notion, which capture essential behavioural information, such as order, exclusiveness, and causality between pairs of activities. Existing notions of behavioural equivalence, such as bisimulation and trace equivalence, might also be applied as consistency notions. Still, they are exponential in computation. Our novel concept of causal behavioural profiles provides a weaker behavioural consistency notion that can be computed efficiently using structural decomposition techniques for sound free-choice workflow systems if unstructured net fragments are acyclic or can be traced back to S- or T-nets.