A "Candidate-Interactome" Aggregate Analysis of Genome-Wide Association Data in Multiple Sclerosis

Though difficult, the study of gene-environment interactions in multifactorial diseases is crucial for interpreting the relevance of non-heritable factors and prevents from overlooking genetic associations with small but measurable effects. We propose a "candidate interactome" (i.e. a group of genes whose products are known to physically interact with environmental factors that may be relevant for disease pathogenesis) analysis of genome-wide association data in multiple sclerosis. We looked for statistical enrichment of associations among interactomes that, at the current state of knowledge, may be representative of gene-environment interactions of potential, uncertain or unlikely relevance for multiple sclerosis pathogenesis: Epstein-Barr virus, human immunodeficiency virus, hepatitis B virus, hepatitis C virus, cytomegalovirus, HHV8-Kaposi sarcoma, H1N1-influenza, JC virus, human innate immunity interactome for type I interferon, autoimmune regulator, vitamin D receptor, aryl hydrocarbon receptor and a panel of proteins targeted by 70 innate immune-modulating viral open reading frames from 30 viral species. Interactomes were either obtained from the literature or were manually curated. The P values of all single nucleotide polymorphism mapping to a given interactome were obtained from the last genome-wide association study of the International Multiple Sclerosis Genetics Consortium & the Wellcome Trust Case Control Consortium, 2. The interaction between genotype and Epstein Barr virus emerges as relevant for multiple sclerosis etiology. However, in line with recent data on the coexistence of common and unique strategies used by viruses to perturb the human molecular system, also other viruses have a similar potential, though probably less relevant in epidemiological terms. © 2013 Mechelli et al.

Systems modelling of the socio-technical aspects of residential electricity use and network peak demand

Provision of network infrastructure to meet rising network peak demand is increasing the cost of electricity. Addressing this demand is a major imperative for Australian electricity agencies. The network peak demand model reported in this paper provides a quantified decision support tool and a means of understanding the key influences and impacts on network peak demand. An investigation of the system factors impacting residential consumers’ peak demand for electricity was undertaken in Queensland, Australia. Technical factors, such as the customers’ location, housing construction and appliances, were combined with social factors, such as household demographics, culture, trust and knowledge, and Change Management Options (CMOs) such as tariffs, price,managed supply, etc., in a conceptual ‘map’ of the system. A Bayesian network was used to quantify the model and provide insights into the major influential factors and their interactions. The model was also used to examine the reduction in network peak demand with different market-based and government interventions in various customer locations of interest and investigate the relative importance of instituting programs that build trust and knowledge through well designed customer-industry engagement activities. The Bayesian network was implemented via a spreadsheet with a tick box interface. The model combined available data from industry-specific and public sources with relevant expert opinion. The results revealed that the most effective intervention strategies involve combining particular CMOs with associated education and engagement activities. The model demonstrated the importance of designing interventions that take into account the interactions of the various elements of the socio-technical system. The options that provided the greatest impact on peak demand were Off-Peak Tariffs and Managed Supply and increases in the price of electricity. The impact in peak demand reduction differed for each of the locations and highlighted that household numbers, demographics as well as the different climates were significant factors. It presented possible network peak demand reductions which would delay any upgrade of networks, resulting in savings for Queensland utilities and ultimately for households. The use of this systems approach using Bayesian networks to assist the management of peak demand in different modelled locations in Queensland provided insights about the most important elements in the system and the intervention strategies that could be tailored to the targeted customer segments.

A new open-pit multi-stage mine production timetabling model for drilling, blasting and excavating operations

This paper proposes a new multi-resource multi-stage mine production timetabling problem for optimising the open-pit drilling, blasting and excavating operations under equipment capacity constraints. The flow process is analysed based on the real-life data from an Australian iron ore mine site. The objective of the model is to maximise the throughput and minimise the total idle times of equipment at each stage. The following comprehensive mining attributes and constraints are considered: types of equipment; operating capacities of equipment; ready times of equipment; speeds of equipment; block-sequence-dependent movement times; equipment-assignment-dependent operational times; etc. The model also provides the availability and usage of equipment units at multiple operational stages such as drilling, blasting and excavating stages. The problem is formulated by mixed integer programming and solved by ILOG-CPLEX optimiser. The proposed model is validated with extensive computational experiments to improve mine production efficiency at the operational level.

Associated schools of construction of southern Africa infrastructure design and delivery workshop - Report. CIB task group 91 infrastructure

This workshop comprised a diverse group of African construction experts, ranging far wider than RSA. Each of the attendees had attended the annual ASOCSA conference and was additionally provided with a short workshop pre-brief. The aim was to develop a view of their 15-20 year vision of construction improvement in RSA and the steps necessary to get there. These included sociological, structural, technical and process changes. Whilst some suggestions are significantly challenging, none are impossible, given sufficient collaboration between government, industry, academia and NGOs. The highest priority projects (more properly, programmes) were identified and further explored. These are: 1. Information Hub (‘Open Africa’). Aim – to utilise emerging trends in Open Data to provide a force for African unity. 2. Workforce Development. Aim – to rebuild a competent, skilled construction industry for RSA projects and for export. 3. Modular DIY Building. Aim – to accelerate the development of sustainable, cost-efficient and desirable housing for African economic immigrants and others living in makeshift and slum dwellings. Open Data is a maturing theme in different cities and governments around the world and the workshop attendees were very keen to seize such a possibility to assist in developing an environment where Africans can share information and foster collaboration. It is likely that NGOs might be keen to follow up such an initiative. There are significant developments taking place around the world in the construction sector currently, with comparatively large savings being made for taxpayers (20% plus in the UK). Not all of these changes would be easy to transplant to RSA (even more so to much of the rest of Africa). Workforce development was a keen plea amongst the attendees, who seemed concerned that expertise has leaked away and is not being replaced with sufficient intensity. It is possible today to develop modular buildings in such a way that even unskilled residents can assist in their construction, and even their appropriate design. These buildings can be sited nearly autonomously from infrastructures, thus relieving the tensions on cities and townships, whilst providing humane accommodation for the economically disadvantaged. Development of suitable solutions could either be conducted with other similarly stressed countries or developed in-country and the expertise exported. Finally, it should be pointed out that this was very much a first step. Any opportunity to collaborate from an Australian, QUT or CIB perspective would be welcomed, whilst acknowledging that the leading roles belong to RSA, CSIR, NRF, ASOCSA and the University of KwaZulu-Natal.

A principled experimental design approach to Big Data analysis

Big Datasets are endemic, but they are often notoriously difficult to analyse because of their size, heterogeneity, history and quality. The purpose of this paper is to open a discourse on the use of modern experimental design methods to analyse Big Data in order to answer particular questions of interest. By appealing to a range of examples, it is suggested that this perspective on Big Data modelling and analysis has wide generality and advantageous inferential and computational properties. In particular, the principled experimental design approach is shown to provide a flexible framework for analysis that, for certain classes of objectives and utility functions, delivers near equivalent answers compared with analyses of the full dataset under a controlled error rate. It can also provide a formalised method for iterative parameter estimation, model checking, identification of data gaps and evaluation of data quality. Finally, it has the potential to add value to other Big Data sampling algorithms, in particular divide-and-conquer strategies, by determining efficient sub-samples.

Prevalence of retinopathy among adults with self-reported diabetes mellitus: the Sri Lanka diabetes and Cardiovascular Study

Background: At present there are no large scale nationally-representative studies from Sri Lanka on the prevalence and associations of Diabetic Retinopathy (DR). The present study aims to evaluate the prevalence and risk factors for DR in a community-based nationally-representative sample of adults with self-reported diabetes mellitus from Sri Lanka. Methods: A cross-sectional community-based national study among 5,000 adults (≥18 years) was conducted in Sri Lanka, using a multi-stage stratified cluster sampling technique. An interviewer-administered questionnaire was used to collect data. Ophthalmological evaluation of patients with ‘known’ diabetes (previously diagnosed at a government hospital or by a registered medical practitioner) was done using indirect ophthalmoscopy. A binary-logistic regression analysis was performed with ‘presence of DR’ as the dichotomous dependent variable and other independent covariates. Results: Crude prevalence of diabetes was 12.0%(n=536),of which 344 were patients with ‘known’ diabetes.Mean age was 56.4 ± 10.9 years and 37.3% were males. Prevalence of any degree of DR was 27.4% (Males-30.5%, Females-25.6%; p = 0.41). In patients with DR, majority had NPDR (93.4%), while 5.3% had maculopathy. Patients with DR had a significantly longer duration of diabetes than those without. In the binary-logistic regression analysis in all adults duration of diabetes (OR:1.07), current smoking (OR:1.67) and peripheral neuropathy (OR:1.72)all were significantly associated with DR. Conclusions: Nearly 1/3rd of Sri Lankan adults with self-reported diabetes are having retinopathy. DR was associated with diabetes duration, cigarette smoking and peripheral neuropathy. However, further prospective follow up studies are required to establish causality for identified risk factors

Archiving primary data: Solutions for long-term studies

The recent trend for journals to require open access to primary data included in publications has been embraced by many biologists, but has caused apprehension amongst researchers engaged in long-term ecological and evolutionary studies. A worldwide survey of 73 principal investigators (Pls) with long-term studies revealed positive attitudes towards sharing data with the agreement or involvement of the PI, and 93% of PIs have historically shared data. Only 8% were in favor of uncontrolled, open access to primary data while 63% expressed serious concern. We present here their viewpoint on an issue that can have non-trivial scientific consequences. We discuss potential costs of public data archiving and provide possible solutions to meet the needs of journals and researchers.

Cardiovascular diseases and vulnerable plaques: data, modeling, predictions and clinical applications PREFACE

Introduction Two symposia on “cardiovascular diseases and vulnerable plaques” Cardiovascular disease (CVD) is the leading cause of death worldwide. Huge effort has been made in many disciplines including medical imaging, computational modeling, bio- mechanics, bioengineering, medical devices, animal and clinical studies, population studies as well as genomic, molecular, cellular and organ-level studies seeking improved methods for early detection, diagnosis, prevention and treatment of these diseases [1-14]. However, the mechanisms governing the initiation, progression and the occurrence of final acute clinical CVD events are still poorly understood. A large number of victims of these dis- eases who are apparently healthy die suddenly without prior symptoms. Available screening and diagnostic methods are insufficient to identify the victims before the event occurs [8,9]. Most cardiovascular diseases are associated with vulnerable plaques. A grand challenge here is to develop new imaging techniques, predictive methods and patient screening tools to identify vulnerable plaques and patients who are more vulnerable to plaque rupture and associated clinical events such as stroke and heart attack, and recommend proper treatment plans to prevent those clinical events from happening. Articles in this special issue came from two symposia held recently focusing on “Cardio-vascular Diseases and Vulnerable Plaques: Data, Modeling, Predictions and Clinical Applications.” One was held at Worcester Polytechnic Institute (WPI), Worcester, MA, USA, July 13-14, 2014, right after the 7th World Congress of Biomechanics. This symposium was endorsed by the World Council of Biomechanics, and partially supported by a grant from NIH-National Institute of Biomedical Image and Bioengineering. The other was held at Southeast University (SEU), Nanjing, China, April 18-20, 2014.

An integrated model of an open-pit coal mine: Improving energy efficiency decisions

This article contributes an original integrated model of an open-pit coal mine for supporting energy-efficient decisions. Mixed integer linear programming is used to formulate a general integrated model of the operational energy consumption of four common open-pit coal mining subsystems: excavation and haulage, stockpiles, processing plants and belt conveyors. Mines are represented as connected instances of the four subsystems, in a flow sheet manner, which are then fitted to data provided by the mine operators. Solving the integrated model ensures the subsystems’ operations are synchronised and whole-of-mine energy efficiency is encouraged. An investigation on a case study of an open-pit coal mine is conducted to validate the proposed methodology. Opportunities are presented for using the model to aid energy-efficient decision-making at various levels of a mine, and future work to improve the approach is described.

Effect of an interactive therapeutic robotic animal on engagement, mood states, agitation and psychotropic drug use in people with dementia: A cluster-randomised controlled trial protocol

Introduction: Apathy, agitated behaviours, loneliness and depression are common consequences of dementia. This trial aims to evaluate the effect of a robotic animal on behavioural and psychological symptoms of dementia in people with dementia living in long-term aged care. Methods and analysis: A cluster-randomised controlled trial with three treatment groups: PARO (robotic animal), Plush-Toy (non-robotic PARO) or Usual Care (Control). The nursing home sites are Australian Government approved and accredited facilities of 60 or more beds. The sites are located in South-East Queensland, Australia. A sample of 380 adults with a diagnosis of dementia, aged 60 years or older living in one of the participating facilities will be recruited. The intervention consists of three individual 15 min non-facilitated sessions with PARO or Plush- Toy per week, for a period of 10 weeks. The primary outcomes of interest are improvement in agitation, mood states and engagement. Secondary outcomes include sleep duration, step count, change in psychotropic medication use, change in treatment costs, and staff and family perceptions of PARO or Plush-Toy. Video data will be analysed using Noldus XT Pocket Observer; descriptive statistics will be used for participants’ demographics and outcome measures; cluster and individual level analyses to test all hypotheses and Generalised Linear Models for cluster level and Generalised Estimation Equations and/or Multi-level Modeling for individual level data. Ethics and dissemination: The study participants or their proxy will provide written informed consent. The Griffith University Human Research Ethics Committee has approved the study (NRS/03/14/HREC). The results of the study will provide evidence of the efficacy of a robotic animal as a psychosocial treatment for the behavioural and psychological symptoms of dementia. Findings will be presented at local and international conference meetings and published in peer-reviewed journals.

Specialisation versus special interest: The Australian podiatry experience

Background Ensuring efficient and effective delivery of health care to an ageing population has been a major driver for a review of the health workforce in Australia. As part of this process a National Registration and Accreditation Scheme (NRAS) has evolved with one goal being to improve workforce flexibility within a nationally consistent model of governance. In addition to increased flexibility, there have been discussions about maintaining standards and the role of specialisation. This study aims to explore the association between practitioners’ self-perceptions about their special interest in musculoskeletal, diabetes related and podopaediatric foot care and the actual podiatry services they deliver in Australia. Methods A cross sectional on-line survey was administered on behalf of the Australasian Podiatry Council and its’ state based member associations. Self-reported data were collected over a 3-week interval and captured information about the practitioners by gender, years of clinical experience, area of work by state, work setting, and location. For those participants that identified with an area of special interest or specialty, further questions were asked regarding support for the area of special interest through education, and activities performed in treating patients in the week prior to survey completion. Queensland University of Technology Human Research Ethics approval was sought and confirmed exemption from review. Results 218 podiatrists participated in the survey. Participants were predominately female and worked in private practices. The largest area of personal interest by the podiatrists was related to the field of musculoskeletal podiatry (n = 65), followed closely by diabetes foot care (n = 61), and a third area identified was in the management of podopaediatric conditions (n = 26). Conclusions Health workforce reform in Australia is in part being managed by the federal government with a goal to meet the health care needs of Australians into the future. The recognition of a specialty registration of podiatric surgery and endorsement for scheduled medicines was established with this workforce reform in mind. Addition of new subspecialties may be indicated based on professional development, to maintain high standards and meet community expectations.

"Re-thinking" the influence of regulatory capture in the development of government regulation

On 30 March 2015 the Australian Federal Government launched its "Re-Think" initiative with the objective of achieving a better tax system which delivers taxes that are lower, simpler and fairer. The discussion paper released as part of the "Re:think" initiative is designed to start a national conversation on tax reform. However, inquiries into Australia's future tax system, subsequent reforms and the introduction of new taxes are nothing new. Unfortunately, recent history also demonstrates that reform initiatives arising from reviews of the Australian tax system are often deemed a failure. The most prominent of these failures in recent times is the Minerals Resource Rent Tax (MRRT), which lasted a mere 16 months before its announced repeal. Using the established theoretic framework of regulatory capture to interpret publically observable data, the purpose of this article is to explain the failure of this arguably sound tax. It concludes that the MRRT legislation itself, through the capture by the mining companies, provided internal subsidization in the form of reduced tax and minimal or no rents. In doing so, it offers an opportunity to understand and learn from past experiences to ensure that recommendations coming out of the Re:think initiative do not suffer the same fate.

Estimating cell diffusivity and cell proliferation rate by interpreting IncuCyte ZOOM™ assay data using the Fisher-Kolmogorov model

Background: Standard methods for quantifying IncuCyte ZOOM™ assays involve measurements that quantify how rapidly the initially-vacant area becomes re-colonised with cells as a function of time. Unfortunately, these measurements give no insight into the details of the cellular-level mechanisms acting to close the initially-vacant area. We provide an alternative method enabling us to quantify the role of cell motility and cell proliferation separately. To achieve this we calibrate standard data available from IncuCyte ZOOM™ images to the solution of the Fisher-Kolmogorov model. Results: The Fisher-Kolmogorov model is a reaction-diffusion equation that has been used to describe collective cell spreading driven by cell migration, characterised by a cell diffusivity, D, and carrying capacity limited proliferation with proliferation rate, λ, and carrying capacity density, K. By analysing temporal changes in cell density in several subregions located well-behind the initial position of the leading edge we estimate λ and K. Given these estimates, we then apply automatic leading edge detection algorithms to the images produced by the IncuCyte ZOOM™ assay and match this data with a numerical solution of the Fisher-Kolmogorov equation to provide an estimate of D. We demonstrate this method by applying it to interpret a suite of IncuCyte ZOOM™ assays using PC-3 prostate cancer cells and obtain estimates of D, λ and K. Comparing estimates of D, λ and K for a control assay with estimates of D, λ and K for assays where epidermal growth factor (EGF) is applied in varying concentrations confirms that EGF enhances the rate of scratch closure and that this stimulation is driven by an increase in D and λ, whereas K is relatively unaffected by EGF. Conclusions: Our approach for estimating D, λ and K from an IncuCyte ZOOM™ assay provides more detail about cellular-level behaviour than standard methods for analysing these assays. In particular, our approach can be used to quantify the balance of cell migration and cell proliferation and, as we demonstrate, allow us to quantify how the addition of growth factors affects these processes individually.

The Victorian 260 cc Legislation. Evaluation Report Using Accident Data to December, 1982.

Learner and first year probationary motorcyclists are over-represented in traffic accidents, being involved about four times as often as full motorcycle licence holders in relation to their numbers. In an attempt to reduce this over-involvement, the Victorian Government amended the law in 1979 to restrict learner and first year probationary motorcyclists to motorcycles with engine capacities of less than 260 cc. This paper reports an evaluation which showed that casualty rates for learner and first year probationers began to decrease from mid 1979 and continued to do so until the end of 1980. A further analysis indicated that compared to full licence holder casualties, learner permit casualties were about 40% less than expected while first year probationary casualties were about 39% lower.

Solutions for archiving data in long-term studies: A reply to Whitlock et al.

In our recent paper [1], we discussed some potential undesirable consequences of public data archiving (PDA) with specific reference to long-term studies and proposed solutions to manage these issues. We reaffirm our commitment to data sharing and collaboration, both of which have been common and fruitful practices supported for many decades by researchers involved in long-term studies. We acknowledge the potential benefits of PDA (e.g., [2]), but believe that several potential negative consequences for science have been underestimated [1] (see also 3 and 4). The objective of our recent paper [1] was to define practices to simultaneously maximize the benefits and minimize the potential unwanted consequences of PDA.