Multi-site study of additive genetic effects on fractional anisotropy of cerebral white matter: Comparing meta and megaanalytical approaches for data pooling

Combining datasets across independent studies can boost statistical power by increasing the numbers of observations and can achieve more accurate estimates of effect sizes. This is especially important for genetic studies where a large number of observations are required to obtain sufficient power to detect and replicate genetic effects. There is a need to develop and evaluate methods for joint-analytical analyses of rich datasets collected in imaging genetics studies. The ENIGMA-DTI consortium is developing and evaluating approaches for obtaining pooled estimates of heritability through meta-and mega-genetic analytical approaches, to estimate the general additive genetic contributions to the intersubject variance in fractional anisotropy (FA) measured from diffusion tensor imaging (DTI). We used the ENIGMA-DTI data harmonization protocol for uniform processing of DTI data from multiple sites. We evaluated this protocol in five family-based cohorts providing data from a total of 2248 children and adults (ages: 9-85) collected with various imaging protocols. We used the imaging genetics analysis tool, SOLAR-Eclipse, to combine twin and family data from Dutch, Australian and Mexican-American cohorts into one large "mega-family". We showed that heritability estimates may vary from one cohort to another. We used two meta-analytical (the sample-size and standard-error weighted) approaches and a mega-genetic analysis to calculate heritability estimates across-population. We performed leave-one-out analysis of the joint estimates of heritability, removing a different cohort each time to understand the estimate variability. Overall, meta- and mega-genetic analyses of heritability produced robust estimates of heritability.

A pilot RCT of a multi-component nutrition intervention for nursing home residents with dementia

Background Malnutrition and unintentional weight loss are major clinical issues in people with dementia living in residential aged care facilities (RACFs) and are associated with serious adverse outcomes. However, evidence regarding effective interventions is limited and strategies to improve the nutritional status of this population are required. This presentation describes the implementation and results of a pilot randomised controlled trial of a multi-component intervention for improving the nutritional status of RACF residents with dementia. Method Fifteen residents with moderate-severe dementia living in a secure long-term RACF participated in a five week pilot study. Participants were randomly allocated to either an Intervention (n=8) or Control group (n=7). The intervention comprised four elements delivered in a separate dining room at lunch and dinner: the systematic reinforcement of residents’ eating behaviors using a specific communication protocol; family-style dining; high ambiance table presentation; and routine Dietary-Nutrition Champion supervision. Control group participants ate their meals according to the facility’s standard practice. Baseline and follow-up assessments of nutritional status, food consumption, and body mass index were obtained by qualified nutritionists. Additional assessments included measures of cognitive functioning, mealtime agitation, depression, wandering status and multiple measures of intervention fidelity. Results No participant was malnourished at study commencement and participants in both groups gained weight from follow-up to baseline which was not significantly different between groups (t=0.43; p=0.67). A high degree of treatment fidelity was evident throughout the intervention. Qualitative data from staff indicate the intervention was perceived to be beneficial for residents. Conclusions This multi-component nutritional intervention was well received and was feasible in the RACF setting. Participants’ sound nutritional status at baseline likely accounts for the lack of an intervention effect. Further research using this protocol in malnourished residents is recommended. For success, a collaborative approach between researchers and facility staff, particularly dietary staff, is essential.

Measuring cost and affordability of healthy and less healthy diet globally

The INFORMAS food prices module proposes a step-wise framework to measure the cost and affordability of population diets. The price differential and the tax component of healthy and less healthy foods, food groups, meals and diets will be benchmarked and monitored over time. Results can be used to model or assess the impact of fiscal policies, such as ‘fat taxes’ or subsidies. Key methodological challenges include: defining healthy and less healthy foods, meals, diets and commonly consumed items; including costs of alcohol, takeaways, convenience foods and time; selecting the price metric; sampling frameworks; and standardizing collection and analysis protocols. The minimal approach uses three complementary methods to measure the price differential between pairs of healthy and less healthy foods. Specific challenges include choosing policy relevant pairs and defining an anchor for the lists. The expanded approach measures the cost of a healthy diet compared to the current (less healthy) diet for a reference household. It requires dietary principles to guide the development of the healthy diet pricing instrument and sufficient information about the population’s current intake to inform the current (less healthy) diet tool. The optimal approach includes measures of affordability and requires a standardised measure of household income that can be used for different countries. The feasibility of implementing the protocol in different countries is being tested in New Zealand, Australia and Fiji. The impact of different decision points to address challenges will be investigated in a systematic manner. We will present early insights and results from this work.

Treadmill adaptation and verification of self-selected walking speed : a protocol for children

The term self-selected (i.e., individual or comfortable walking pace or speed) is commonly used in the literature (Frost, Dowling, Bar-Or, & Dyson, 1997; Jeng, Liao, Lai, & Hou, 1997; Wergel-Kolmert & Wohlfart, 1999; Maltais, Bar-Or, Pienynowski, & Galea, 2003; Browning & Kram, 2005; Browning, Baker, Herron, & Kram, 2006; Hills, Byrne, Wearing, & Armstrong, 2006) and is identified as the most efficient walking speed, with increased efficiency defined by lower oxygen uptake (VO^sub 2^) per unit mechanical work (Hoyt & Taylor, 1981; Taylor, Heglund, & Maloiy, 1982; Hreljac, 1993). [...] assessing individual and group differences in metabolic energy expenditure using oxygen uptake requires individuals to be comfortable with, and able to accommodate to, the equipment.

A stepped-wedge cluster randomised controlled trial for evaluating rates of falls among inpatients in aged care rehabilitation units receiving tailored multimedia education in addition to usual care : a trial protocol

Introduction Falls are the most frequent adverse event reported in hospitals. Approximately 30% of in-hospital falls lead to an injury and up to 2% result in a fracture. A large randomised trial found that a trained health professional providing individualised falls prevention education to older inpatients reduced falls in a cognitively intact subgroup. This study aims to investigate whether this efficacious intervention can reduce falls and be clinically useful and cost-effective when delivered in the real-life clinical environment. Methods A stepped-wedge cluster randomised trial will be used across eight subacute units (clusters) which will be randomised to one of four dates to start the intervention. Usual care on these units includes patient's screening, assessment and implementation of individualised falls prevention strategies, ongoing staff training and environmental strategies. Patients with better levels of cognition (Mini-Mental State Examination >23/30) will receive the individualised education from a trained health professional in addition to usual care while patient's feedback received during education sessions will be provided to unit staff. Unit staff will receive training to assist in intervention delivery and to enhance uptake of strategies by patients. Falls data will be collected by two methods: case note audit by research assistants and the hospital falls reporting system. Cluster-level data including patient's admissions, length of stay and diagnosis will be collected from hospital systems. Data will be analysed allowing for correlation of outcomes (clustering) within units. An economic analysis will be undertaken which includes an incremental cost-effectiveness analysis. Ethics and dissemination The study was approved by The University of Notre Dame Australia Human Research Ethics Committee and local hospital ethics committees. Results The results will be disseminated through local site networks, and future funding and delivery of falls prevention programmes within WA Health will be informed. Results will also be disseminated through peer-reviewed publications and medical conferences.

Researching effective approaches to cleaning in hospitals: Protocol of the REACH study, a multi-site stepped-wedge randomised trial

Background The Researching Effective Approaches to Cleaning in Hospitals (REACH) study will generate evidence about the effectiveness and cost-effectiveness of a novel cleaning initiative that aims to improve the environmental cleanliness of hospitals. The initiative is an environmental cleaning bundle, with five interdependent, evidence-based components (training, technique, product, audit and communication) implemented with environmental services staff to enhance hospital cleaning practices. Methods/design The REACH study will use a stepped-wedge randomised controlled design to test the study intervention, an environmental cleaning bundle, in 11 Australian hospitals. All trial hospitals will receive the intervention and act as their own control, with analysis undertaken of the change within each hospital based on data collected in the control and intervention periods. Each site will be randomised to one of the 11 intervention timings with staggered commencement dates in 2016 and an intervention period between 20 and 50 weeks. All sites complete the trial at the same time in 2017. The inclusion criteria allow for a purposive sample of both public and private hospitals that have higher-risk patient populations for healthcare-associated infections (HAIs). The primary outcome (objective one) is the monthly number of Staphylococcus aureus bacteraemias (SABs), Clostridium difficile infections (CDIs) and vancomycin resistant enterococci (VRE) infections, per 10,000 bed days. Secondary outcomes for objective one include the thoroughness of hospital cleaning assessed using fluorescent marker technology, the bio-burden of frequent touch surfaces post cleaning and changes in staff knowledge and attitudes about environmental cleaning. A cost-effectiveness analysis will determine the second key outcome (objective two): the incremental cost-effectiveness ratio from implementation of the cleaning bundle. The study uses the integrated Promoting Action on Research Implementation in Health Services (iPARIHS) framework to support the tailored implementation of the environmental cleaning bundle in each hospital. Discussion Evidence from the REACH trial will contribute to future policy and practice guidelines about hospital environmental cleaning. It will be used by healthcare leaders and clinicians to inform decision-making and implementation of best-practice infection prevention strategies to reduce HAIs in hospitals. Trial registration Australia New Zealand Clinical Trial Registry ACTRN12615000325​505

IMPOSE (IMProving Outcomes after Sepsis)—the effect of a multidisciplinary follow-up service on health-related quality of life in patients postsepsis syndromes—a double-blinded randomised controlled trial: protocol

Introduction Patients post sepsis syndromes have a poor quality of life and a high rate of recurring illness or mortality. Follow-up clinics have been instituted for patients postgeneral intensive care but evidence is sparse, and there has been no clinic specifically for survivors of sepsis. The aim of this trial is to investigate if targeted screening and appropriate intervention to these patients can result in an improved quality of life (Short Form 36 health survey (SF36V.2)), decreased mortality in the first 12 months, decreased readmission to hospital and/or decreased use of health resources. Methods and analysis 204 patients postsepsis syndromes will be randomised to one of the two groups. The intervention group will attend an outpatient clinic two monthly for 6 months and receive screening and targeted intervention. The usual care group will remain under the care of their physician. To analyse the results, a baseline comparison will be carried out between each group. Generalised estimating equations will compare the SF36 domain scores between groups and across time points. Mortality will be compared between groups using a Cox proportional hazards (time until death) analysis. Time to first readmission will be compared between groups by a survival analysis. Healthcare costs will be compared between groups using a generalised linear model. Economic (health resource) evaluation will be a within-trial incremental cost utility analysis with a societal perspective. Ethics and dissemination Ethical approval has been granted by the Royal Brisbane and Women’s Hospital Human Research Ethics Committee (HREC; HREC/13/QRBW/17), The University of Queensland HREC (2013000543), Griffith University (RHS/08/14/HREC) and the Australian Government Department of Health (26/2013). The results of this study will be submitted to peer-reviewed intensive care journals and presented at national and international intensive care and/or rehabilitation conferences.

Within- and between-day repeatability and variability in children's physiological responses during submaximal treadmill exercise

The purpose of this study was to verify within- and between-day repeatability and variability in children's oxygen uptake (VO^sub 2^), gross economy (GE; VO^sub 2^ divided by speed) and heart rate (HR) during treadmill walking based on self-selected speed (SS). Fourteen children (10.1 ± 1.4 years) undertook three testing sessions over 2 days in which four walking speeds, including SS were tested. Within- and between-day repeatability were assessed using the Bland and Altman method, and coefficients of variability (CV) were determined for each child across exercise bouts and averaged to obtain a mean group CV value for VO^sub 2^, GE, and HR per speed. Repeated measures analysis of variance showed no statistically significant differences in within- or between-day CV for VO^sub 2^, GE, or HR at any speed. Repeatability within- and between-day for VO^sub 2^, GE, and HR for all speeds was verified. These results suggest that submaximal VO^sub 2^ during treadmill walking is stable and reproducible at a range of speeds based on children's SS.

Interventions for preventing and managing radiation-induced skin reactions in cancer patients (Protocol)

To assess the effects of any interventions which aim to prevent or manage radiation-induced skin reactions in people with cancer.

ERTP : Energy-efficient and reliable transport protocol for data streaming in wireless sensor networks

Emerging data streaming applications in Wireless Sensor Networks require reliable and energy-efficient Transport Protocols. Our recent Wireless Sensor Network deployment in the Burdekin delta, Australia, for water monitoring [T. Le Dinh, W. Hu, P. Sikka, P. Corke, L. Overs, S. Brosnan, Design and deployment of a remote robust sensor network: experiences from an outdoor water quality monitoring network, in: Second IEEE Workshop on Practical Issues in Building Sensor Network Applications (SenseApp 2007), Dublin, Ireland, 2007] is one such example. This application involves streaming sensed data such as pressure, water flow rate, and salinity periodically from many scattered sensors to the sink node which in turn relays them via an IP network to a remote site for archiving, processing, and presentation. While latency is not a primary concern in this class of application (the sampling rate is usually in terms of minutes or hours), energy-efficiency is. Continuous long-term operation and reliable delivery of the sensed data to the sink are also desirable. This paper proposes ERTP, an Energy-efficient and Reliable Transport Protocol for Wireless Sensor Networks. ERTP is designed for data streaming applications, in which sensor readings are transmitted from one or more sensor sources to a base station (or sink). ERTP uses a statistical reliability metric which ensures the number of data packets delivered to the sink exceeds the defined threshold. Our extensive discrete event simulations and experimental evaluations show that ERTP is significantly more energyefficient than current approaches and can reduce energy consumption by more than 45% when compared to current approaches. Consequently, sensor nodes are more energy-efficient and the lifespan of the unattended WSN is increased.

The effect of graded levels of exercise on energy intake and balance in free-living men, consuming their normal diet

Objective: To assess the effect of graded increases in exercised-induced energy expenditure (EE) on appetite, energy intake (EI), total daily EE and body weight in men living in their normal environment and consuming their usual diets. Design: Within-subject, repeated measures design. Six men (mean (s.d.) age 31.0 (5.0) y; weight 75.1 (15.96) kg; height 1.79 (0.10) m; body mass index (BMI) 23.3(2.4) kg/m2), were each studied three times during a 9 day protocol, corresponding to prescriptions of no exercise, (control) (Nex; 0 MJ/day), medium exercise level (Mex; ~1.6 MJ/day) and high exercise level (Hex; ~3.2 MJ/day). On days 1-2 subjects were given a medium fat (MF) maintenance diet (1.6 ´ resting metabolic rate (RMR)). Measurements: On days 3-9 subjects self-recorded dietary intake using a food diary and self-weighed intake. EE was assessed by continual heart rate monitoring, using the modified FLEX method. Subjects' HR (heart rate) was individually calibrated against submaximal VO2 during incremental exercise tests at the beginning and end of each 9 day study period. Respiratory exchange was measured by indirect calorimetry. Subjects completed hourly hunger ratings during waking hours to record subjective sensations of hunger and appetite. Body weight was measured daily. Results: EE amounted to 11.7, 12.9 and 16.8 MJ/day (F(2,10)=48.26; P<0.001 (s.e.d=0.55)) on the Nex, Mex and Hex treatments, respectively. The corresponding values for EI were 11.6, 11.8 and 11.8 MJ/day (F(2,10)=0.10; P=0.910 (s.e.d.=0.10)), respectively. There were no treatment effects on hunger, appetite or body weight, but there was evidence of weight loss on the Hex treatment. Conclusion: Increasing EE did not lead to compensation of EI over 7 days. However, total daily EE tended to decrease over time on the two exercise treatments. Lean men appear able to tolerate a considerable negative energy balance, induced by exercise, over 7 days without invoking compensatory increases in EI.

Nitrogen fertilizer management for nitrous oxide (N2O) mitigation in intensive corn (Maize) production: an emissions reduction protocol for US Midwest agriculture

Nitrous oxide (N2O) is a major greenhouse gas (GHG) product of intensive agriculture. Fertilizer nitrogen (N) rate is the best single predictor of N2O emissions in row-crop agriculture in the US Midwest. We use this relationship to propose a transparent, scientifically robust protocol that can be utilized by developers of agricultural offset projects for generating fungible GHG emission reduction credits for the emerging US carbon cap and trade market. By coupling predicted N2O flux with the recently developed maximum return to N (MRTN) approach for determining economically profitable N input rates for optimized crop yield, we provide the basis for incentivizing N2O reductions without affecting yields. The protocol, if widely adopted, could reduce N2O from fertilized row-crop agriculture by more than 50%. Although other management and environmental factors can influence N2O emissions, fertilizer N rate can be viewed as a single unambiguous proxy—a transparent, tangible, and readily manageable commodity. Our protocol addresses baseline establishment, additionality, permanence, variability, and leakage, and provides for producers and other stakeholders the economic and environmental incentives necessary for adoption of agricultural N2O reduction offset projects.

VO2max in overweight and obese adults

Purpose: The purpose of this study was to determine whether adiposity affects the attainment of VO2max. Methods: Sixty-seven male and 68 female overweight (body mass index (BMI) = 25-29.9 kg·m-2) and obese (BMI >= 30 kg·m-2) participants undertook a graded treadmill test to volitional exhaustion (phase 1) followed by a verification test (phase 2) to determine the proportion who could achieve a plateau in VO2 and other "maximal" markers (RER, lactate, HR, RPE). Results: At the end of phase 1, 46% of the participants reached a plateau in VO2, 83% increased HR to within 11 beats of age-predicted maximum, 89% reached an RER of >=1.15, 70% reached a blood lactate concentration of >=8 mmol·L-1, and 74% reached an RPE of >=18. No significant differences between genders and between BMI groups were found with the exception of blood lactate concentration (males = 84% vs females = 56%, P < 0.05). Neither gender nor fatness predicted the number of other markers attained, and attainment of other markers did not differentiate whether a VO2 plateau was achieved. The verification test (phase 2) revealed that an additional 52 individuals (39%) who did not exhibit a plateau in V·O2 in phase 1 had no further increase in VO2 in phase 2 despite an increase in workload. Conclusions: These findings indicate that the absence of a plateau in VO2 alone is not indicative of a failure to reach a true maximal VO2 and that individuals with excessive body fat are no less likely than "normal-weight" individuals to exhibit a plateau in VO2 provided that the protocol is appropriate and encouragement to exercise to maximal exertion is provided.

A distributed protocol for object tracking in wireless multimedia sensor networks

We consider the problem of object tracking in a wireless multimedia sensor network (we mainly focus on the camera component in this work). The vast majority of current object tracking techniques, either centralised or distributed, assume unlimited energy, meaning these techniques don't translate well when applied within the constraints of low-power distributed systems. In this paper we develop and analyse a highly-scalable, distributed strategy to object tracking in wireless camera networks with limited resources. In the proposed system, cameras transmit descriptions of objects to a subset of neighbours, determined using a predictive forwarding strategy. The received descriptions are then matched at the next camera on the objects path using a probability maximisation process with locally generated descriptions. We show, via simulation, that our predictive forwarding and probabilistic matching strategy can significantly reduce the number of object-misses, ID-switches and ID-losses; it can also reduce the number of required transmissions over a simple broadcast scenario by up to 67%. We show that our system performs well under realistic assumptions about matching objects appearance using colour.

Applying incremental EM to Bayesian classifiers in the learning of hyperspectral remote sensing data

In this paper, we apply the incremental EM method to Bayesian Network Classifiers to learn and interpret hyperspectral sensor data in robotic planetary missions. Hyperspectral image spectroscopy is an emerging technique for geological investigations from airborne or orbital sensors. Many spacecraft carry spectroscopic equipment as wavelengths outside the visible light in the electromagnetic spectrum give much greater information about an object. The algorithm used is an extension to the standard Expectation Maximisation (EM). The incremental method allows us to learn and interpret the data as they become available. Two Bayesian network classifiers were tested: the Naive Bayes, and the Tree-Augmented-Naive Bayes structures. Our preliminary experiments show that incremental learning with unlabelled data can improve the accuracy of the classifier.