ADJUSTED PEDAGOGY FOR TEACHING STATISTICS

Traditional styles of teaching used to dominate the classroom for teaching statistics courses at tertiary level. It is proposed that knowledge will more likely be effectively learnt if traditional styles of teaching are supplemented with strategies from the more recent constructivist learning theory. It has the potential to result in increased collaboration in the classroom. When combined with the teacher’s role being more of a facilitator, and use of real-world applications, it is proposed that this will result in a more effective setting to encourage motivation and interest in learning. In turn, this will potentially provide a greater opportunity for improved learning outcomes

Discovery of a quinoline-4-carboxamide derivative with a novel mechanism of action, multistage antimalarial activity, and potent in vivo efficacy

The antiplasmodial activity, DMPK properties, and efficacy of a series of quinoline-4-carboxamides are described. This series was identified from a phenotypic screen against the blood stage of Plasmodium falciparum (3D7) and displayed moderate potency but with suboptimal physicochemical properties and poor microsomal stability. The screening hit (1, EC50 = 120 nM) was optimized to lead molecules with low nanomolar in vitro potency. Improvement of the pharmacokinetic profile led to several compounds showing excellent oral efficacy in the P. berghei malaria mouse model with ED90 values below 1 mg/kg when dosed orally for 4 days. The favorable potency, selectivity, DMPK properties, and efficacy coupled with a novel mechanism of action, inhibition of translation elongation factor 2 (PfEF2), led to progression of 2 (DDD107498) to preclinical development

Trisubstituted Pyrimidines as Efficacious and Fast-acting Antimalarials

In this paper we describe the optimization of a phenotypic hit against Plasmodium falciparum, based on a trisubstituted pyrimidine scaffold. This led to compounds with good pharmacokinetics and oral activity in a P. berghei mouse model of malaria. The most promising compound (13) showed a reduction in parasitemia of 96% when dosed at 30 mg/kg orally once a day for 4 days in the P. berghei mouse model of malaria. It also demonstrated a rapid rate of clearance of the erythrocytic stage of P. falciparum in the SCID mouse model with an ED90 of 11.7 mg/kg when dosed orally. Unfortunately, the compound is a potent inhibitor of cytochrome P450 enzymes, probably due to a 4-pyridyl substituent. Nevertheless, this is a lead molecule with a potentially useful antimalarial profile, which could either be further optimized or be used for target hunting

Lysyl-tRNA synthetase as a drug target in malaria and cryptosporidiosis

Malaria and cryptosporidiosis, caused by apicomplexan parasites, remain major drivers of global child mortality. New drugs for the treatment of malaria and cryptosporidiosis, in particular, are of high priority; however, there are few chemically validated targets. The natural product cladosporin is active against blood- and liver-stage; Plasmodium falciparum; and; Cryptosporidium parvum; in cell-culture studies. Target deconvolution in; P. falciparum; has shown that cladosporin inhibits lysyl-tRNA synthetase (; Pf; KRS1). Here, we report the identification of a series of selective inhibitors of apicomplexan KRSs. Following a biochemical screen, a small-molecule hit was identified and then optimized by using a structure-based approach, supported by structures of both; Pf; KRS1 and; C. parvum; KRS (; Cp; KRS). In vivo proof of concept was established in an SCID mouse model of malaria, after oral administration (ED; 90; = 1.5 mg/kg, once a day for 4 d). Furthermore, we successfully identified an opportunity for pathogen hopping based on the structural homology between; Pf; KRS1 and; Cp; KRS. This series of compounds inhibit; Cp; KRS and; C. parvum; and; Cryptosporidium hominis; in culture, and our lead compound shows oral efficacy in two cryptosporidiosis mouse models. X-ray crystallography and molecular dynamics simulations have provided a model to rationalize the selectivity of our compounds for; Pf; KRS1 and; Cp; KRS vs. (human); Hs; KRS. Our work validates apicomplexan KRSs as promising targets for the development of drugs for malaria and cryptosporidiosis

Bayesian Meta-Analysis to Account for Heterogeneity in Studies Relating Life Events to Disease

Associations between life events and various forms of cancers have been identified. The purpose of a recent random-effects meta-analysis was to identify studies that examined the association between adverse events associated with changes to financial status including decreased income and breast cancer risk. The same association was studied in four separate studies which displayed traits that were not consistent between studies such as the study design, location, and time frame. It was of interest to pool information from various studies to help identify characteristics that differentiated study results. Two random-effects Bayesian meta-analysis models are proposed to combine the reported estimates of the described studies. The proposed models allow major sources of variation to be taken into account, including study level characteristics, between study variance and within study variance, and illustrate the ease with which uncertainty can be incorporated using a hierarchical Bayesian modelling approach

Bayesian Methods in Meta-Analysis

Meta-analysis refers to the collection and subsequent statistical analysis of results from numerous studies. The purpose of a meta-analysis is to arrive at an overall conclusion about an issue of interest based on the available data. Meta-analysis has a long history, but it has enjoyed a surge of interest and corresponding rapid methodological development in the past two decades. Philosophical and practical problems surround the combination of studies with discrepancies in aims, study designs and quality, sampling frames, populations, and reported information. Other concerns include dealing with studies of small sample size or with peculiar results, inclusion of predictors at study level, methods by which results are updated as new information is available, and accounting for the impact of other biases because of publication, selection, and so on. A Bayesian approach to meta-analysis has been advocated as a way to address many of these issues. A Bayesian model describes the structural relationship between data and unknown parameters, whereby both data and parameters are considered random variables with uncertainty. The full posterior distributions of parameters borrow strength from all studies and enable direct inference regarding probabilities about expectations and, perhaps more notably in a pharmacology context, comparisons such as the probability with which subjects receiving a particular medication are better on average recovery, symptom level, or survival, than those on an alternative medication. Moreover, by their construction, these distributions are not confined to "usual" (normal) representations or based on asymptotic assumptions, and give substantially more information than single point estimates. The article begins with a description of some applications of Bayesian approaches in meta-analysis. The steps involved in a meta-analysis are discussed next, followed by a description of Bayesian models for meta-analysis and selection of prior distributions. Computer implementation of Bayesian models for meta-analysis next, followed by extensions to the simple Bayesian model and dealing with publication bias in the Bayesian framework.2nd ed

Multivariate Meta-Analysis

Meta-analysis is the joint statistical analysis of results from a number of related studies to obtain an overall perspective on an effect or outcome of interest. There are often multiple dimensions to the same outcome and so it is common for outcomes to be determined by at least two measures. Studies typically report multiple estimates of the same effect. Moreover, the trend toward exhaustive decision analysis to assess health technology demands examination of multiple outcomes. There are numerous forms of multivariate effect size data, which can arise in several ways, including as a comparison of one or more treatments or interventions with a control group on at least one outcome, as multiple outcomes per study, or as the measurement of an outcome at several time points. Multivariate methods in meta-analysis account for the dependence between related outcomes and are generally preferred to univariate methods that assess each outcome separately as they typically provide more information about outcomes of interest, by borrowing strength across effects both within and across studies. The chapter begins with a discussion of different sources of multivariate data. The steps involved in any meta-analysis are discussed, followed by a description of common univariate approaches for analysis of multivariate data in meta-analysis. Models in the multivariate meta-analysis framework are then reviewed.2nd ed

Spatial assessment of crime

The misuse of alcohol is associated with considerable harm to individuals and the community. Alcohol-related harm is an economic concern in Australia and has social and health implications (Chikritzhs et al., 2000). A reduction in the consumption of unsafe alcohol amounts is estimated to reduce associated harms, and to consequently reduce resources required to treat such harm. It is also predicted that the costs of investments in the prevention of alcohol-related harm would be outweighed by the costs of treating such harm, which would permit a more efficient reallocation of community resources. The more common acute type of alcohol related injury is linked with criminal activity. Criminal activity can entail personal crime which is the illegal acquiring of resources, and/or personal crime which is the asserting of control over others through violence. Research has shown a range of factors that are associated with criminal activity (Loeber and Farrington, 1998). Individual risk factors include substance abuse, among others. Many factors that predict criminal behaviour also predict substance abuse (Loeber and Farrington, 1998). Individual factors that have been linked with alcohol-related crime include age and gender (Fingerhut et al., 1992). Community factors have also been linked to alcohol-related harm. Ireland and Thommeny (1993) found that 60% of alcohol-related assaults occurred on, or near licensed premises. While entertainment areas such as restaurants and clubs are often viewed as positive economic investments, a growing body of research supports a relationship between alcohol outlet density, alcohol consumption levels and associated harm. Studies based in the US linked density of outlets to particular measures of alcohol-related harm such as drink-driving. A suggestion from this research is that drinking norms may be affected, to some degree, by environment. The purpose of the present study is to assess the relationship between various factors and crime based on certain communities in South Wales (NSW), Australia, and to explore methodology to enable the spatial assessment given the geographical auto-correlational nature of these data