Localization of type 1 diabetes susceptibility to the MHC class I genes HLA-B and HLA-A

The major histocompatibility complex (MHC) on chromosome 6 is associated with susceptibility to more common diseases than any other region of the human genome, including almost all disorders classified as autoimmune. In type 1 diabetes the major genetic susceptibility determinants have been mapped to the MHC class II genes HLA-DQB1 and HLA-DRB1 (refs 1–3), but these genes cannot completely explain the association between type 1 diabetes and the MHC region4, 5, 6, 7, 8, 9, 10, 11. Owing to the region's extreme gene density, the multiplicity of disease-associated alleles, strong associations between alleles, limited genotyping capability, and inadequate statistical approaches and sample sizes, which, and how many, loci within the MHC determine susceptibility remains unclear. Here, in several large type 1 diabetes data sets, we analyse a combined total of 1,729 polymorphisms, and apply statistical methods—recursive partitioning and regression...

Model selection with misspecified spatial covariance structure

Spatial data analysis has become more and more important in the studies of ecology and economics during the last decade. One focus of spatial data analysis is how to select predictors, variance functions and correlation functions. However, in general, the true covariance function is unknown and the working covariance structure is often misspecified. In this paper, our target is to find a good strategy to identify the best model from the candidate set using model selection criteria. This paper is to evaluate the ability of some information criteria (corrected Akaike information criterion, Bayesian information criterion (BIC) and residual information criterion (RIC)) for choosing the optimal model when the working correlation function, the working variance function and the working mean function are correct or misspecified. Simulations are carried out for small to moderate sample sizes. Four candidate covariance functions (exponential, Gaussian, Matern and rational quadratic) are used in simulation studies. With the summary in simulation results, we find that the misspecified working correlation structure can still capture some spatial correlation information in model fitting. When the sample size is large enough, BIC and RIC perform well even if the the working covariance is misspecified. Moreover, the performance of these information criteria is related to the average level of model fitting which can be indicated by the average adjusted R square ( [GRAPHICS] ), and overall RIC performs well.

Weighted rank regression for clustered data analysis

We consider ranked-based regression models for clustered data analysis. A weighted Wilcoxon rank method is proposed to take account of within-cluster correlations and varying cluster sizes. The asymptotic normality of the resulting estimators is established. A method to estimate covariance of the estimators is also given, which can bypass estimation of the density function. Simulation studies are carried out to compare different estimators for a number of scenarios on the correlation structure, presence/absence of outliers and different correlation values. The proposed methods appear to perform well, in particular, the one incorporating the correlation in the weighting achieves the highest efficiency and robustness against misspecification of correlation structure and outliers. A real example is provided for illustration.

An optimal design for screening trials

Yao, Begg, and Livingston (1996, Biometrics 52, 992-1001) considered the optimal group size for testing a series of potentially therapeutic agents to identify a promising one as soon as possible for given error rates. The number of patients to be tested with each agent was fixed as the group size. We consider a sequential design that allows early acceptance and rejection, and we provide an optimal strategy to minimize the sample sizes (patients) required using Markov decision processes. The minimization is under the constraints of the two types (false positive and false negative) of error probabilities, with the Lagrangian multipliers corresponding to the cost parameters for the two types of errors. Numerical studies indicate that there can be a substantial reduction in the number of patients required.

Working correlation structure misspecification, estimation and covariate design: Implications for generalised estimating equations performance

The method of generalised estimating equations for regression modelling of clustered outcomes allows for specification of a working matrix that is intended to approximate the true correlation matrix of the observations. We investigate the asymptotic relative efficiency of the generalised estimating equation for the mean parameters when the correlation parameters are estimated by various methods. The asymptotic relative efficiency depends on three-features of the analysis, namely (i) the discrepancy between the working correlation structure and the unobservable true correlation structure, (ii) the method by which the correlation parameters are estimated and (iii) the 'design', by which we refer to both the structures of the predictor matrices within clusters and distribution of cluster sizes. Analytical and numerical studies of realistic data-analysis scenarios show that choice of working covariance model has a substantial impact on regression estimator efficiency. Protection against avoidable loss of efficiency associated with covariance misspecification is obtained when a 'Gaussian estimation' pseudolikelihood procedure is used with an AR(1) structure.

A generalized estimating equations approach for analysis of the impact of new technology on a trawl fishery

The article describes a generalized estimating equations approach that was used to investigate the impact of technology on vessel performance in a trawl fishery during 1988-96, while accounting for spatial and temporal correlations in the catch-effort data. Robust estimation of parameters in the presence of several levels of clustering depended more on the choice of cluster definition than on the choice of correlation structure within the cluster. Models with smaller cluster sizes produced stable results, while models with larger cluster sizes, that may have had complex within-cluster correlation structures and that had within-cluster covariates, produced estimates sensitive to the correlation structure. The preferred model arising from this dataset assumed that catches from a vessel were correlated in the same years and the same areas, but independent in different years and areas. The model that assumed catches from a vessel were correlated in all years and areas, equivalent to a random effects term for vessel, produced spurious results. This was an unexpected finding that highlighted the need to adopt a systematic strategy for modelling. The article proposes a modelling strategy of selecting the best cluster definition first, and the working correlation structure (within clusters) second. The article discusses the selection and interpretation of the model in the light of background knowledge of the data and utility of the model, and the potential for this modelling approach to apply in similar statistical situations.

Gittins indices and constrained allocation in clinical trials

We explore the use of Gittins indices to search for near optimality in sequential clinical trials. Some adaptive allocation rules are proposed to achieve the following two objectives as far as possible: (i) to reduce the expected successes lost, (ii) to minimize the error probability at the end. Simulation results indicate the merits of the rules based on Gittins indices for small trial sizes. The rules are generalized to the case when neither of the response densities is known. Asymptotic optimality is derived for the constrained rules. A simple allocation rule is recommended for one-stage models. The simulation results indicate that it works better than both equal allocation and Bather's randomized allocation. We conclude with a discussion of possible further developments.

Pattern visual evoked potentials in dyslexic versus normal children

Purpose: Presence of neurophysiological abnormalities in dyslexia has been a conflicting issue. This study was performed to evaluate the role of sensory visual deficits in the pathogenesis of dyslexia. Methods: Pattern visual evoked potentials (PVEP) were recorded in 72 children including 36 children with dyslexia and 36 children without dyslexia (controls) who were matched for age, sex and intelligence. Two check sizes of 15 and 60 min of arc were used with temporal frequencies of 1.5 Hz for transient and 6 Hz for steady‑state methods. Results: Mean latency and amplitude values for 15 min arc and 60 min arc check sizes using steady state and transient methods showed no significant difference between the two study groups (P values: 0.139/0.481/0.356/0.062).Furthermore, no significant difference was observed between two methods of PVEPs in dyslexic and normal children using 60min arc with high contrast(Pvalues: 0.116, 0.402, 0.343 and 0.106). Conclusion: The sensitivity of PVEP has high validity to detect visual deficits in children with dyslexic problem. However, no significant difference was found between dyslexia and normal children using high contrast stimuli.

Visual demands in modern Australian primary school classrooms

BACKGROUND The visual demands of modern classrooms are poorly understood yet are relevant in determining the levels of visual function required to perform optimally within this environment. METHODS Thirty-three Year 5 and 6 classrooms from eight south-east Queensland schools were included. Classroom activities undertaken during a full school day (9 am to 3 pm) were observed and a range of measurements recorded, including classroom environment (physical dimensions, illumination levels), text size and contrast of learning materials, habitual working distances (distance and estimated for near) and time spent performing various classroom tasks. These measures were used to calculate demand-related minimum criteria for distance and near visual acuity, contrast and sustained use of accommodation and vergence. RESULTS The visual acuity demands for distance and near were 0.33 ± 0.13 and 0.72 ± 0.09 logMAR, respectively (using habitual viewing distances and smallest target sizes) or 0.33 ± 0.09 logMAR assuming a 2.5 times acuity reserve for sustained near tasks. The mean contrast levels of learning materials at distance and near were greater than 70 per cent. Near tasks (47 per cent) dominated the academic tasks performed in the classroom followed by distance (29 per cent), distance to near (15 per cent) and computer-based (nine per cent). On average, children engaged in continuous near fixation for 23 ± 5 minutes at a time and during distance-near tasks performed fixation changes 10 ± 1 times per minute. The mean estimated habitual near working distance was 23 ± 1 cm (4.38 ± 0.24 D accommodative demand) and the vergence demand was 0.86 ± 0.07Δ at distance and 21.94 ± 1.09Δ at near assuming an average pupillary distance of 56 mm. CONCLUSIONS Relatively high levels of visual acuity, contrast demand and sustained accommodative-convergence responses are required to meet the requirements of modern classroom environments. These findings provide an evidence base to inform prescribing guidelines and develop paediatric vision screening protocols and referral criteria.

Design studio terrains: Mapping the learning landscapes of Australian architectural education

It has been nearly 25 years since the problems associated with passive learning in large undergraduate classes were first established by McDermott (1991). STEM education, for example North Carolina State University’s SCALE-UP project, has subsequently been influenced by some unique aspects of design studio education. While there are now many institutions applying SCALE-UP or similar approaches to enable lively interaction, enhanced learning, increased student engagement, and to teach many different content areas to classes of all sizes, nearly all of these have remained in the STEM fields (Beichner, 2008). Architectural education, although originally at the forefront of this field, has arguably been left behind. Architectural practice is undergoing significant change, globally. Access to new technology and the development of specialised architectural documentation software has scaffolded new building procurement methods and allowed consultant teams to work more collaboratively, efficiently and even across different time zones. Up until recently, the spatial arrangements, pedagogical approaches, and project work outcomes in the architectural design studio, have not been dissimilar to its inception. It is not possible to keep operating architectural design studios the same way that they have for the past two hundred years, with this new injection of high-end technology and personal mobile Wi-Fi enabled devices. Employing a grounded theory methodology, this study reviews the current provision of architectural design learning terrains across a range of tertiary institutions, in Australia. Some suggestions are provided for how these spaces could be modified to address the changing nature of the profession, and implications for how these changes may impact the design of future SCALE-UP type spaces outside of the discipline of architecture, are also explored.

A comparison of training methods to increase neck muscle strength

Objective To compare two neck strength training modalities. Background Neck injury in pilots flying high performance aircraft is a concern in aviation medicine. Strength training may be an effective means to strengthen the neck and decrease injury risk. Methods The cohort consisted of 32 age-height-weight matched participants, divided into two experimental groups; the Multi-Cervical Unit (MCU) and Thera-Band tubing groups (THER), and a control (CTRL) group. Ten weeks of training were undertaken and pre-and post isometric strength testing for all groups was performed on the MCU. Comparisons between the three groups were made using a Kruskal-Wallis test and effect sizes between the MCU and the THER groups and the THER and CTRL groups were also calculated. Results The MCU group displayed the greatest increase in isometric strength (flexion 64.4%, extension 62.9%, left lateral flexion 53.3%, right lateral flexion 49.1%) and differences were only statistically significant (p<0.05) when compared to the CTRL group. Increases in neck strength for the THER group were lower than that shown in the MCU group (flexion 42.0%, extension 29.9%, left lateral flexion 26.7%, right lateral flexion 24.1%). Moderate to large effect sizes were found between the MCU and THER as well as the THER and CTRL groups. Conclusions This study demonstrated that the MCU was the most effective training modality to increase isometric cervical muscle strength. Thera-Band tubing did however, produce moderate gains in isometric neck strength

Under the skin: Wearable technology futures

Artist statement – Artisan Gallery I have a confession to make… I don’t wear a FitBit, I don’t want an Apple Watch and I don’t like bling LED’s. But, what excites me is a future where ‘wearables’ are discreet, seamless and potentially one with our body. Burgeoning E-textiles research will provide the ability to inconspicuously communicate, measure and enhance human health and well-being. Alongside this, next generation wearables arguably will not be worn on the body, but rather within the body…under the skin. ‘Under the Skin’ is a polemic piece provoking debate on the future of wearables – a place where they are not overt, not auxiliary and perhaps not apparent. Indeed, a future where wearables are under the skin or one with our apparel. And, as underwear closets the skin and is the most intimate and cloaked apparel item we wear, this work unashamedly teases dialogue to explore how wearables can transcend from the overt to the unseen. Context Wearable Technology, also referred to as wearable computing or ‘wearables’, is an embryonic field that has the potential to unsettle conventional notions as to how technology can interact, enhance and augment the human body. Wearable technology is the next-generation for ubiquitous consumer electronics and ‘Wearables’ are, in essence, miniature electronic devices that are worn by a person, under clothing, embedded within clothing/textiles, on top of clothing, or as stand-alone accessories/devices. This wearables market is predicted to grow somewhere between $30-$50 billion in the next 5 years (Credit Suisse, 2013). The global ‘wearables’ market, which is emergent in phase, has forecasted predictions for vast consumer revenue with the potential to become a significant cross-disciplinary disruptive space for designers and entrepreneurs. For Fashion, the field of wearables is arguably at the intersection of the second and third generation for design innovation: the first phase being purely decorative with aspects such as LED lighting; the second phase consisting of an array of wearable devices, such as smart watches, to communicate areas such as health and fitness, the third phase involving smart electronics that are woven into the textile to perform a vast range of functions such as body cooling, fabric colour change or garment silhouette change; and the fourth phase where wearable devices are surgically implanted under the skin to augment, transform and enhance the human body. Whilst it is acknowledged the wearable phases are neither clear-cut nor discreet in progression and design innovation can still be achieved with first generation decorative approaches, the later generation of technology that is less overt and at times ‘under the skin’ provides a uniquely rich point for design innovation where the body and technology intersect as one. With this context in mind, the wearable provocation piece ‘Under the Skin’ provides a unique opportunity for the audience to question and challenge conventional notions that wearables need to be a: manifest in nature, b: worn on or next to the body, and c: purely functional. The piece ‘Under the Skin’ is informed by advances in the market place for wearable innovation, such as: the Australian based wearable design firm Catapult with their discreet textile biometric sports tracking innovation, French based Spinali Design with their UV app based textile senor to provide sunburn alerts, as well as opportunities for design technology innovation through UNICEF’s ‘Wearables for Good’ design challenge to improve the quality of life in disadvantaged communities. Exhibition As part of Artisan’s Wearnext exhibition, the work was on public display from 25 July to 7 November 2015 and received the following media coverage: WEARNEXT ONLINE LISTINGS AND MEDIA COVERAGE: http://indulgemagazine.net/wear-next/ http://www.weekendnotes.com/wear-next-exhibition-gallery-artisan/ http://concreteplayground.com/brisbane/event/wear-next_/ http://www.nationalcraftinitiative.com.au/news_and_events/event/48/wear-next http://bneart.com/whats-on/wear-next_/ http://creativelysould.tumblr.com/post/124899079611/creative-weekend-art-edition http://www.abc.net.au/radionational/programs/breakfast/smartly-dressed-the-future-of-wearable-technology/6744374 http://couriermail.newspaperdirect.com/epaper/viewer.aspx RADIO COVERAGE http://www.abc.net.au/radionational/programs/breakfast/wear-next-exhibition-whats-next-for-wearable-technology/6745986 TELEVISION COVERAGE http://www.abc.net.au/radionational/programs/breakfast/wear-next-exhibition-whats-next-for-wearable-technology/6745986 https://au.news.yahoo.com/video/watch/29439742/how-you-could-soon-be-wearing-smart-clothes/#page1

Traffic and nucleation events as main sources of ultrafine particles in high-insolation developed world cities

Road traffic emissions are often considered the main source of ultrafine particles (UFP, diameter smaller than 100 nm) in urban environments. However, recent studies worldwide have shown that - in high-insolation urban regions at least - new particle formation events can also contribute to UFP. In order to quantify such events we systematically studied three cities located in predominantly sunny environments: Barcelona (Spain), Madrid (Spain) and Brisbane (Australia). Three long term datasets (1-2 years) of fine and ultrafine particle number size distributions (measured by SMPS, Scanning Mobility Particle Sizer) were analysed. Compared to total particle number concentrations, aerosol size distributions offer far more information on the type, origin and atmospheric evolution of the particles. By applying k-Means clustering analysis, we categorized the collected aerosol size distributions in three main categories: “Traffic” (prevailing 44-63% of the time), “Nucleation” (14-19%) and “Background pollution and Specific cases” (7-22%). Measurements from Rome (Italy) and Los Angeles (California) were also included to complement the study. The daily variation of the average UFP concentrations for a typical nucleation day at each site revealed a similar pattern for all cities, with three distinct particle bursts. A morning and an evening spike reflected traffic rush hours, whereas a third one at midday showed nucleation events. The photochemically nucleated particles burst lasted 1-4 hours, reaching sizes of 30-40 nm. On average, the occurrence of particle size spectra dominated by nucleation events was 16% of the time, showing the importance of this process as a source of UFP in urban environments exposed to high solar radiation. On average, nucleation events lasting for 2 hours or more occurred on 55% of the days, this extending to >4hrs in 28% of the days, demonstrating that atmospheric conditions in urban environments are not favourable to the growth of photochemically nucleated particles. In summary, although traffic remains the main source of UFP in urban areas, in developed countries with high insolation urban nucleation events are also a main source of UFP. If traffic-related particle concentrations are reduced in the future, nucleation events will likely increase in urban areas, due to the reduced urban condensation sinks.

GWAS of 126,559 individuals identifies genetic variants associated with educational attainment

A genome-wide association study (GWAS) of educational attainment was conducted in a discovery sample of 101,069 individuals and a replication sample of 25,490. Three independent single-nucleotide polymorphisms (SNPs) are genome-wide significant (rs9320913, rs11584700, rs4851266), and all three replicate. Estimated effects sizes are small (coefficient of determination R(2) approximately 0.02%), approximately 1 month of schooling per allele. A linear polygenic score from all measured SNPs accounts for approximately 2% of the variance in both educational attainment and cognitive function. Genes in the region of the loci have previously been associated with health, cognitive, and central nervous system phenotypes, and bioinformatics analyses suggest the involvement of the anterior caudate nucleus. These findings provide promising candidate SNPs for follow-up work, and our effect size estimates can anchor power analyses in social-science genetics.

Inference of the genetic architecture underlying BMI and height with the use of 20,240 sibling pairs

Evidence that complex traits are highly polygenic has been presented by population-based genome-wide association studies (GWASs) through the identification of many significant variants, as well as by family-based de novo sequencing studies indicating that several traits have a large mutational target size. Here, using a third study design, we show results consistent with extreme polygenicity for body mass index (BMI) and height. On a sample of 20,240 siblings (from 9,570 nuclear families), we used a within-family method to obtain narrow-sense heritability estimates of 0.42 (SE = 0.17, p = 0.01) and 0.69 (SE = 0.14, p = 6 x 10(-)(7)) for BMI and height, respectively, after adjusting for covariates. The genomic inflation factors from locus-specific linkage analysis were 1.69 (SE = 0.21, p = 0.04) for BMI and 2.18 (SE = 0.21, p = 2 x 10(-10)) for height. This inflation is free of confounding and congruent with polygenicity, consistent with observations of ever-increasing genomic-inflation factors from GWASs with large sample sizes, implying that those signals are due to true genetic signals across the genome rather than population stratification. We also demonstrate that the distribution of the observed test statistics is consistent with both rare and common variants underlying a polygenic architecture and that previous reports of linkage signals in complex traits are probably a consequence of polygenic architecture rather than the segregation of variants with large effects. The convergent empirical evidence from GWASs, de novo studies, and within-family segregation implies that family-based sequencing studies for complex traits require very large sample sizes because the effects of causal variants are small on average.