Chaperone-usher fimbriae of Escherichia coli

Chaperone-usher (CU) fimbriae are adhesive surface organelles common to many Gram-negative bacteria. Escherichia coli genomes contain a large variety of characterised and putative CU fimbrial operons, however, the classification and annotation of individual loci remains problematic. Here we describe a classification model based on usher phylogeny and genomic locus position to categorise the CU fimbrial types of E. coli. Using the BLASTp algorithm, an iterative usher protein search was performed to identify CU fimbrial operons from 35 E. coli (and one Escherichia fergusonnii) genomes representing different pathogenic and phylogenic lineages, as well as 132 Escherichia spp. plasmids. A total of 458 CU fimbrial operons were identified, which represent 38 distinct fimbrial types based on genomic locus position and usher phylogeny. The majority of fimbrial operon types occupied a specific locus position on the E. coli chromosome; exceptions were associated with mobile genetic elements. A group of core-associated E. coli CU fimbriae were defined and include the Type 1, Yad, Yeh, Yfc, Mat, F9 and Ybg fimbriae. These genes were present as intact or disrupted operons at the same genetic locus in almost all genomes examined. Evaluation of the distribution and prevalence of CU fimbrial types among different pathogenic and phylogenic groups provides an overview of group specific fimbrial profiles and insight into the ancestry and evolution of CU fimbriae in E. coli.

Fine-mapping the HOXB region detects common variants tagging a rare coding allele : evidence for synthetic association in prostate cancer

The HOXB13 gene has been implicated in prostate cancer (PrCa) susceptibility. We performed a high resolution fine-mapping analysis to comprehensively evaluate the association between common genetic variation across the HOXB genetic locus at 17q21 and PrCa risk. This involved genotyping 700 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of 3195 SNPs in 20,440 PrCa cases and 21,469 controls in The PRACTICAL consortium. We identified a cluster of highly correlated common variants situated within or closely upstream of HOXB13 that were significantly associated with PrCa risk, described by rs117576373 (OR 1.30, P = 2.62×10(-14)). Additional genotyping, conditional regression and haplotype analyses indicated that the newly identified common variants tag a rare, partially correlated coding variant in the HOXB13 gene (G84E, rs138213197), which has been identified recently as a moderate penetrance PrCa susceptibility allele. The potential for GWAS associations detected through common SNPs to be driven by rare causal variants with higher relative risks has long been proposed; however, to our knowledge this is the first experimental evidence for this phenomenon of synthetic association contributing to cancer susceptibility.

A pseudo-marginal sequential Monte Carlo algorithm for random effects models in Bayesian sequential design

A computationally efficient sequential Monte Carlo algorithm is proposed for the sequential design of experiments for the collection of block data described by mixed effects models. The difficulty in applying a sequential Monte Carlo algorithm in such settings is the need to evaluate the observed data likelihood, which is typically intractable for all but linear Gaussian models. To overcome this difficulty, we propose to unbiasedly estimate the likelihood, and perform inference and make decisions based on an exact-approximate algorithm. Two estimates are proposed: using Quasi Monte Carlo methods and using the Laplace approximation with importance sampling. Both of these approaches can be computationally expensive, so we propose exploiting parallel computational architectures to ensure designs can be derived in a timely manner. We also extend our approach to allow for model uncertainty. This research is motivated by important pharmacological studies related to the treatment of critically ill patients.

Creating a common approach to safety management through structured training development

The successful management of workplace safety has many benefits for employees, employers and the community. Similar to other areas of job performance, safety performance can be enhanced through appropriate and well-designed training. The foundation of the development of effective training is a thorough training needs analysis (TNA). Currently, the application of psychometrically valid TNA practices for the management of workplace safety is an under-researched topic and limited guidance is available for implementing appropriate strategies. To address this gap in the literature, this chapter will provide an overview of TNA practices, including the purpose and benefits associated with implementing the systematic procedure. A case study will then be presented to illustrate how the TNA process was successfully applied to investigate the training needs of Australasian rail incident investigators to achieve an industry-approved national training package. Recommendations will be made to assist practitioners with implementing TNA practices with the goal of enhancing workplace safety management through targeted workforce development.

Common hazards and their mitigating measures in work zones : a qualitative study of worker perceptions

Road construction and maintenance activities present challenges for ensuring the safety of workers and the traveling public alike. Hazards in work zones are typically studied using historical crash records but the current study took a qualitative approach by interviewing 66 workers from various work zones in Queensland, Australia. This supplemented and enhanced the limited available data regarding the frequency and nature of work zone crashes in Australia, provided worker insights into contributing factors, and assessed their opinions on the likely effectiveness of current or future approaches to hazard mitigation. Workers may not be aware of objective data regarding effectiveness, but their attitudes and consequent levels of compliance can influence both the likelihood of implementation and the outcomes of safety measures. Despite the potential importance of worker perceptions, they have not been studied comprehensively to date, and thus this study fills a significant gap in the literature. Excessive vehicle speeds, driver distraction and aggression towards roadworkers, working in wet weather, at night and close to traffic stream were among the most common hazards noted by workers. The safety measures perceived to be most effective included police presence, active enforcement, and improving driver awareness and education about work zones. Worker perceptions differed according to their level of exposure to hazards.

Adaptive estimation of HMM transition probabilities

This paper presents new schemes for recursive estimation of the state transition probabilities for hidden Markov models (HMM's) via extended least squares (ELS) and recursive state prediction error (RSPE) methods. Local convergence analysis for the proposed RSPE algorithm is shown using the ordinary differential equation (ODE) approach developed for the more familiar recursive output prediction error (RPE) methods. The presented scheme converges and is relatively well conditioned compared with the ...

A Memetic Algorithm for the location-based continuously operating reference stations placement problem in Network Real-Time Kinematic

Network Real-Time Kinematic (NRTK) is a technology that can provide centimeter-level accuracy positioning services in real time, and it is enabled by a network of Continuously Operating Reference Stations (CORS). The location-oriented CORS placement problem is an important problem in the design of a NRTK as it will directly affect not only the installation and operational cost of the NRTK, but also the quality of positioning services provided by the NRTK. This paper presents a Memetic Algorithm (MA) for the location-oriented CORS placement problem, which hybridizes the powerful explorative search capacity of a genetic algorithm and the efficient and effective exploitative search capacity of a local optimization. Experimental results have shown that the MA has better performance than existing approaches. In this paper we also conduct an empirical study about the scalability of the MA, effectiveness of the hybridization technique and selection of crossover operator in the MA.

Incidence trends of keratinocytic skin cancers and melanoma in Israel 2006-2011

BACKGROUND The incidence of skin cancer, both melanoma and keratinocyte cancers (KC) is rising throughout the world, specifically squamous cell carcinomas(SCC) and basal cell carcinoma(BCC), being the most common of all cancers. OBJECTIVE To determine trends in incidence of Melanoma, BCC and SCC among 1.7 million members of Maccabi Healthcare Services from 2006 to 2011. METHODS Data on newly diagnosed Melanoma, SCC and BCC cases was collected from the MHS Cancer Registry and based on histology reports from the centralized pathology lab. Age-specific and overall age-adjusted European standardized rates were computed. Trends were estimated by calculating Average Annual Percentage Change(AAPC). RESULTS During the six year study period, a total of 16,079 subjects were diagnosed with at least one BCC, 4,767 with SCC and 1,264 with invasive melanoma. Age-standardized incidence rates were 188, 58 and 17 per 100,000 person years for BCC, SCC and melanoma, respectively. All lesions were more common among males and primarily affected the elderly. BCC rates were stable throughout the study period(AAPC -0.7%, 95%CI -4.5% to 3.2%) while SCC incidence increased significantly(AAPC 15.5%, 95%CI: 2.6% to 30.0%). In contrast, melanoma rates continuously decreased with a significant AAPC of -3.0%, 95%CI (-4.5 to -0.1). CONCLUSIONS Previously unreported, the incidence of KC in Israel is high. The disparities in incidence trends between SCC, BCC and melanoma allude to their different etiologies. These findings underscore the importance of continuous monitoring, education and prevention programs in a growing high risk population.

Delirium in advanced cancer : screening for the incidence on admission to an inpatient hospice unit

Background Delirium is a common underdiagnosed condition in advanced cancer leading to increased distress, morbidity, and mortality. Screening improves detection but there is no consensus as to the best screening tool to use with patients with advanced cancer. Objective To determine the incidence of delirium in patients with advanced cancer within 72 hours of admission to an acute inpatient hospice using clinical judgement and validated screening tools. Method One hundred consecutive patients with advanced cancer were invited to be screened for delirium within 72 hours of admission to an acute inpatient hospice unit. Two validated tools were used, the Delirium Rating Scale-Revised 98 (DRS-R-98) and the Confusion Assessment Method (CAM) shortened diagnostic algorithm. These results were compared with clinical assessment by review of medical charts. Results Of 100 consecutive admissions 51 participated and of these 22 (43.1%) screened positive for delirium with CAM and/or DRS-R-98 compared to 15 (29.4%) by clinical assessment. Eleven (21.6%) were identified as hypoactive delirium and 5 (9.8%) as subsyndromal delirium. Conclusion This study confirms that delirium is a common condition in patients with advanced cancer.While there remains a lack of consensus regarding the choice of delirium screening tool this study supports theCAMas being appropriate. Further research may determine the optimal screening tool for delirium enabling the development of best practice clinical guidelines for routinemedical practice.

BOSTER : an efficient algorithm for mining frequent unordered induced subtrees

Extracting frequent subtrees from the tree structured data has important applications in Web mining. In this paper, we introduce a novel canonical form for rooted labelled unordered trees called the balanced-optimal-search canonical form (BOCF) that can handle the isomorphism problem efficiently. Using BOCF, we define a tree structure guided scheme based enumeration approach that systematically enumerates only the valid subtrees. Finally, we present the balanced optimal search tree miner (BOSTER) algorithm based on BOCF and the proposed enumeration approach, for finding frequent induced subtrees from a database of labelled rooted unordered trees. Experiments on the real datasets compare the efficiency of BOSTER over the two state-of-the-art algorithms for mining induced unordered subtrees, HybridTreeMiner and UNI3. The results are encouraging.

BEST : an efficient algorithm for mining frequent unordered embedded subtrees

This paper presents an algorithm for mining unordered embedded subtrees using the balanced-optimal-search canonical form (BOCF). A tree structure guided scheme based enumeration approach is defined using BOCF for systematically enumerating the valid subtrees only. Based on this canonical form and enumeration technique, the balanced optimal search embedded subtree mining algorithm (BEST) is introduced for mining embedded subtrees from a database of labelled rooted unordered trees. The extensive experiments on both synthetic and real datasets demonstrate the efficiency of BEST over the two state-of-the-art algorithms for mining embedded unordered subtrees, SLEUTH and U3.

A prospective study of natural recovery from cannabis use in early psychosis

Background and Objectives: Cannabis use is common in early psychosis and has been linked to adverse outcomes. However, factors that influence and maintain change in cannabis use in this population are poorly understood. An existing prospective dataset was used to predict abstinence from cannabis use over the 6 months following inpatient admission for early psychosis. Methods: Participants were 67 inpatients with early psychosis who had used cannabis in the 6 weeks prior to admission. Current diagnoses of psychotic and substance use disorders were confirmed using a clinical checklist and structured diagnostic interview. Measures of clinical, substance use and social and occupational functioning were administered at baseline and at least fortnightly over the 6-month follow up. Results: No substance use or clinical variables were associated with 6-months’ of cannabis abstinence. Only Caucasian ethnicity, living in private accommodation and receiving an income before the admission were predictive. Only private accommodation and receiving an income were significant predictors of abstinence when these variables were entered into a multivariate analysis. Conclusions: While the observed relationships do not necessarily imply causation, they suggest that more optimal substance use outcomes could be achieved by addressing the accommodation and employment needs of patients.