Automating Genomic Data Mining via a Sequence-based Matrix Format and Associative Rule Set

There is an enormous amount of information encoded in each genome – enough to create living, responsive and adaptive organisms. Raw sequence data alone is not enough to understand function, mechanisms or interactions. Changes in a single base pair can lead to disease, such as sickle-cell anemia, while some large megabase deletions have no apparent phenotypic effect. Genomic features are varied in their data types and annotation of these features is spread across multiple databases. Herein, we develop a method to automate exploration of genomes by iteratively exploring sequence data for correlations and building upon them. First, to integrate and compare different annotation sources, a sequence matrix (SM) is developed to contain position-dependant information. Second, a classification tree is developed for matrix row types, specifying how each data type is to be treated with respect to other data types for analysis purposes. Third, correlative analyses are developed to analyze features of each matrix row in terms of the other rows, guided by the classification tree as to which analyses are appropriate. A prototype was developed and successful in detecting coinciding genomic features among genes, exons, repetitive elements and CpG islands

The SHED-IT community trial study protocol: a randomised controlled trial of weight loss programs for overweight and obese men

<p>Abstract</p> <p>Background</p> <p>Obesity is a major cause of preventable death in Australia with prevalence increasing at an alarming rate. Of particular concern is that approximately 68% of men are overweight/obese, yet are notoriously difficult to engage in weight loss programs, despite being more susceptible than women to adverse weight-related outcomes. There is a need to develop and evaluate obesity treatment programs that target and appeal to men. The primary aim of this study is to evaluate the efficacy of two relatively low intensity weight loss programs developed specifically for men.</p> <p>Methods and Design</p> <p>The study design is an assessor blinded, parallel-group randomised controlled trial that recruited 159 overweight and obese men in Newcastle, Australia. Inclusion criteria included: BMI 25-40 (kg/m²); no participation in other weight loss programs during the study; pass a health-screening questionnaire and pre-exercise risk assessment; available for assessment sessions; access to a computer with e-mail and Internet facilities; and own a mobile phone. Men were recruited to the SHED-IT (Self-Help, Exercise and Diet using Internet Technology) study via the media and emails sent to male dominated workplaces. Men were stratified by BMI category (overweight, obese class I, obese class II) and randomised to one of three groups: (1) SHED-IT <it>Resources </it>- provision of materials (DVD, handbooks, pedometer, tape measure) with embedded behaviour change strategies to support weight loss; (2) SHED-IT <it>Online </it>- same materials as SHED-IT <it>Resources </it>plus access to and instruction on how to use the study website; (3) Wait-list Control. The intervention programs are three months long with outcome measures taken by assessors blinded to group allocation at baseline, and 3- and 6-months post baseline. Outcome measures include: weight (primary outcome), % body fat, waist circumference, blood pressure, resting heart rate, objectively measured physical activity, self-reported dietary intake, sedentary behaviour, physical activity and dietary cognitions, sleepiness, quality of life, and perceived sexual health. Generalised linear mixed models will be used to assess all outcomes for the impact of group (<it>Resources</it>, <it>Online</it>, and <it>Control</it>), time (treated as categorical with levels baseline, 3-months and 6-months) and the group-by-time interaction. These three terms will form the base model. 'Intention-to-treat' analysis will include all randomised participants.</p> <p>Discussion</p> <p>Our study will compare evidence-based and theoretically driven, low cost and easily disseminated strategies specifically targeting weight loss in men. The SHED-IT community trial will provide evidence to inform development and dissemination of sustainable strategies to reduce obesity in men.</p> <p>Trial Registration</p> <p>Australian New Zealand Clinical Trials Registry (ACTRN12610000699066)</p

A systematic review of dietary, nutritional, and physical activity interventions for the prevention of prostate cancer progression and mortality

PURPOSE: Given the long-term, although potentially fatal, nature of prostate cancer, there is increasing observational evidence for the reduction in disease progression and mortality through changes in lifestyle factors. METHODS: We systematically reviewed dietary, nutritional, and physical activity randomized interventions aimed at modifying prostate cancer progression and disease-specific mortality, including a detailed assessment of risk of bias and methodological quality. RESULTS: Forty-four randomized controlled trials of lifestyle interventions, with prostate cancer progression or mortality outcomes, were identified. Substantial heterogeneity of the data prevented a meta-analysis. The included trials involved 3,418 prostate cancer patients, median 64 men per trial, from 13 countries. A trial of a nutritional supplement of pomegranate seed, green tea, broccoli, and turmeric; a trial comparing flaxseed, low-fat diet, flaxseed, and low-fat diet versus usual diet; and a trial supplementing soy, lycopene, selenium, and coenzyme Q10, all demonstrated beneficial effects. These trials were also assessed as having low risk of bias and high methodological quality (as were seven other trials with no evidence of benefit). The remaining trials were either underpowered, at high or unclear risk of bias, inadequately reported, of short duration or measured surrogate outcomes of unproven relationship to mortality or disease progression, which precluded any benefits reported being reliable. CONCLUSION: Large, well-designed randomized trials with clinical endpoints are recommended for lifestyle modification interventions. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s10552-015-0659-4) contains supplementary material, which is available to authorized users

Refining trait resilience: identifying engineering, ecological, and adaptive facets from extant measures of resilience

The current paper presents a new measure of trait resilience derived from three common mechanisms identified in ecological theory: Engineering, Ecological and Adaptive (EEA) resilience. Exploratory and confirmatory factor analyses of five existing resilience scales suggest that the three trait resilience facets emerge, and can be reduced to a 12-item scale. The conceptualization and value of EEA resilience within the wider trait and well-being psychology is illustrated in terms of differing relationships with adaptive expressions of the traits of the five-factor personality model and the contribution to well-being after controlling for personality and coping, or over time. The current findings suggest that EEA resilience is a useful and parsimonious model and measure of trait resilience that can readily be placed within wider trait psychology and that is found to contribute to individual well-bein