mecA locus diversity in methicillin-resistant Staphylococcus aureus isolates in Brisbane, Australia, and the development of a novel diagnostic procedure for the Western Samoan phage pattern clone

An emerging public health phenomenon is the increasing incidence of methicillin-resistant Staphylococcus aureus (MRSA) infections that are acquired outside of health care facilities. One lineage of community-acquired MRSA (CA-MRSA) is known as the Western Samoan phage pattern (WSPP) clone. The central aim of this study was to develop an efficient genotyping procedure for the identification of WSPP isolates. The approach taken was to make use of the highly variable region downstream of mecA in combination with a single nucleotide polymorphism (SNP) defined by the S. aureus multilocus sequence typing (MLST) database. The premise was that a combinatorial genotyping method that interrogated both a highly variable region and the genomic backbone would deliver a high degree of informative power relative to the number of genetic polymorphisms-interrogated. Thirty-five MRSA isolates were used for this study, and their gene contents and order downstream of mecA were determined. The CA-MRSA isolates were found to contain a truncated mecA downstream region consisting of mecA-HVR-IS431 mec-dcs-Ins117, and a PCR-based method for identifying this structure was developed. The hospital-acquired isolates were found to contain eight different mecA downstream regions, three of which were novel. The Minimum SNPs computer software program was used to mine the S. aureus MLST database, and the arcC 2726 polymorph was identified as 82% discriminatory for ST-30. A real-time PCR assay was developed to interrogate this SNP. We found that the assay for the truncated mecA downstream region in combination with the interrogation of arcC position 272 provided an unambiguous identification of WSPP isolates.

Perceived academic performance, self-esteem and locus of control as indicators of need for assessment of adolescent suicide risk: implications for teachers

Introduction: There is currently a need for research into indicators that could be used by non-clinical professionals working with young people, to inform the need for referral for further clinical assessment of those at risk of suicide. Method: Participants of this repeated measures longitudinal study, were 2603, 2485, and 2246 school students aged 13, 14, and 15, respectively, from 27 South Australian Schools. Results: Perceived academic performance, self-esteem and locus of control are significantly associated with suicidality. Further, logistic regression of longitudinal results suggests that perceived academic performance, over and above self-esteem and locus of control, in some instances, is a good long-term predictor of suicidality. (C) 2004 Published by Elsevier Ltd. on behalf of The Association for Professionals in Services for Adolescents.

On the estimation and comparison of short-rate models using the generalised method of moments

Subsequent to the influential paper of [Chan, K.C., Karolyi, G.A., Longstaff, F.A., Sanders, A.B., 1992. An empirical comparison of alternative models of the short-term interest rate. Journal of Finance 47, 1209-1227], the generalised method of moments (GMM) has been a popular technique for estimation and inference relating to continuous-time models of the short-term interest rate. GMM has been widely employed to estimate model parameters and to assess the goodness-of-fit of competing short-rate specifications. The current paper conducts a series of simulation experiments to document the bias and precision of GMM estimates of short-rate parameters, as well as the size and power of [Hansen, L.P., 1982. Large sample properties of generalised method of moments estimators. Econometrica 50, 1029-1054], J-test of over-identifying restrictions. While the J-test appears to have appropriate size and good power in sample sizes commonly encountered in the short-rate literature, GMM estimates of the speed of mean reversion are shown to be severely biased. Consequently, it is dangerous to draw strong conclusions about the strength of mean reversion using GMM. In contrast, the parameter capturing the levels effect, which is important in differentiating between competing short-rate specifications, is estimated with little bias. (c) 2006 Elsevier B.V. All rights reserved.

GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease

Background The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results We show that GPNN has high power to detect even relatively small genetic effects (2–3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

GPNN: Power studies and applications of a neural network method for detecting gene-gene interactions in studies of human disease

Background: The identification and characterization of genes that influence the risk of common, complex multifactorial disease primarily through interactions with other genes and environmental factors remains a statistical and computational challenge in genetic epidemiology. We have previously introduced a genetic programming optimized neural network (GPNN) as a method for optimizing the architecture of a neural network to improve the identification of gene combinations associated with disease risk. The goal of this study was to evaluate the power of GPNN for identifying high-order gene-gene interactions. We were also interested in applying GPNN to a real data analysis in Parkinson's disease. Results: We show that GPNN has high power to detect even relatively small genetic effects (2-3% heritability) in simulated data models involving two and three locus interactions. The limits of detection were reached under conditions with very small heritability (

Short root mutant of Lotus japonicus with a dramatically altered symbiotic phenotype

Legume plants carefully control the extent of nodulation in response to rhizobial infection. To examine the mechanism underlying this process we conducted a detailed analysis of the Lotus japonicus hypernodulating mutants, har1-1, 2 and 3 that define a new locus, HYPERNODULATION ABERRANT ROOT FORMATION (Har1), involved in root and symbiotic development. Mutations in the Har1 locus alter root architecture by inhibiting root elongation, diminishing root diameter and stimulating lateral root initiation. At the cellular level these developmental alterations are associated with changes in the position and duration of root cell growth and result in a premature differentiation of har1-1 mutant root. No significant differences between har1-1 mutant and wild-type plants were detected with respect to root growth responses to 1-aminocyclopropane1-carboxylic acid, the immediate precursor of ethylene, and auxin; however, cytokinin in the presence of AVG (aminoetoxyvinylglycine) was found to stimulate root elongation of the har1-1 mutant but not the wild-type. After inoculation with Mesorhizobium loti, the har1 mutant lines display an unusual hypernodulation (HNR) response, characterized by unrestricted nodulation (hypernodulation), and a concomitant drastic inhibition of root and shoot growth. These observations implicate a role for the Har1 locus in both symbiotic and non-symbiotic development of L. japonicus, and suggest that regulatory processes controlling nodule organogenesis and nodule number are integrated in an overall mechanism governing root growth and development.