Heritability and genome-wide linkage analysis of migraine in the genetic isolate of Norfolk Island

Migraine is a common neurovascular disorder with a complex envirogenomic aetiology. In an effort to identify migraine susceptibility genes, we conducted a study of the isolated population of Norfolk Island, Australia. A large portion of the permanent inhabitants of Norfolk Island are descended from 18th Century English sailors involved in the infamous mutiny on the Bounty and their Polynesian consorts. In total, 600 subjects were recruited including a large pedigree of 377 individuals with lineage to the founders. All individuals were phenotyped for migraine using International Classification of Headache Disorders-II criterion. All subjects were genotyped for a genome-wide panel of microsatellite markers. Genotype and phenotype data for the pedigree were analysed using heritability and linkage methods implemented in the programme SOLAR. Follow-up association analysis was performed using the CLUMP programme. A total of 154 migraine cases (25%) were identified indicating the Norfolk Island population is high-risk for migraine. Heritability estimation of the 377-member pedigree indicated a significant genetic component for migraine (h2 = 0.53, P = 0.016). Linkage analysis showed peaks on chromosome 13q33.1 (P = 0.003) and chromosome 9q22.32 (P = 0.008). Association analysis of the key microsatellites in the remaining 223 unrelated Norfolk Island individuals showed evidence of association, which strengthen support for the linkage findings (P ≤ 0.05). In conclusion, a genome-wide linkage analysis and follow-up association analysis of migraine in the genetic isolate of Norfolk Island provided evidence for migraine susceptibility loci on chromosomes 9q22.22 and 13q33.1.

Improving the detection of donations within the RHD negative blood donor panel which weakly express the RHD antigen

This project improved the detection and classification of very weakly expressed RhD variants in the Australian blood donor panel and contributed to the knowledge of anti-D reactivity patterns of RHD alleles that are undescribed. As such, the management of donations possessing these RHD alleles can be improved upon and the overall safety of transfusion medicine pertaining to the Rh blood group system will be increased. Future projects at ARCBS will be able to utilise the procedures developed in this project, thereby decreasing throughput time. The specificity of current testing will be improved and the need for outsourced RHD testing diminished.

Nephrotoxicity and nephrocarcinogenicity of dinitrotoluene : new aspects to be considered

Technical dinitrotoluene (DNT) is a mixture of 2,4- and 2,6-DNT. In humans, industrial or environmental exposure can occur orally, by inhalation, or by skin contact. The classification of DNT as an 'animal carcinogen' is based on the formation of malignant tumors in kidneys, liver, and mammary glands of rats and mice. Clear signs of toxic nephropathy were found in rats dosed with DNT, and the concept was derived of an interrelation between renal toxicity and carcinogenicity. Recent data point to the carcinogenicity of DNT on the urinary tract of exposed humans. Between 1984 and 1997, 6 cases of urothelial cancer and 14 cases of renal cell cancer were diagnosed in a group of 500 underground mining workers in the copper mining industry of the former GDR and having high exposures to explosives containing technical DNT. The incidences of both urothelial and renal cell tumors in this group were 4.5 and 14.3 times higher, respectively, than anticipated on the basis of the cancer registers of the GDR. The genotyping of all identified tumor patients for the polymorphic enzymes NAT2, GSTM1, and GSTT1 identified the urothelial tumor cases as exclusively 'slow acetylates'. A group of 161 miners highly exposed to DNT was investigated for signs of subclinical renal damage. The exposures were categorized semi-quantitatively into 'low', 'medium', 'high', and 'very high'. A straight dose-dependence of the excretion of urinary biomarker proteins with the ranking of exposure was seen. Biomarker excretion (alpha1-microglobulin, glutathione S-transferases alpha and pi) indicated that DNT-induced damage was directed toward the tubular system. New data on DNT-exposed humans appear consistent with the concept of cancer initiation by DNT isomers and the subsequent promotion of renal carcinogenesis by selective damage to the proximal tubule. The differential pathways of metabolic activation of DNT appear to apply to the proximal tubule of the kidney and to the urothelium of the renal pelvis and lower urinary tract as target tissues of carcinogenicity.

The contribution of major depression to the global burden of ischemic heart disease : a comparative risk assessment

Background Cardiovascular disease and mental health both hold enormous public health importance, both ranking highly in results of the recent Global Burden of Disease Study 2010 (GBD 2010). For the first time, the GBD 2010 has systematically and quantitatively assessed major depression as an independent risk factor for the development of ischemic heart disease (IHD) using comparative risk assessment methodology. Methods A pooled relative risk (RR) was calculated from studies identified through a systematic review with strict inclusion criteria designed to provide evidence of independent risk factor status. Accepted case definitions of depression include diagnosis by a clinician or by non-clinician raters adhering to Diagnostic and Statistical Manual of Mental Disorders (DSM) or International Classification of Diseases (ICD) classifications. We therefore refer to the exposure in this paper as major depression as opposed to the DSM-IV category of major depressive disorder (MDD). The population attributable fraction (PAF) was calculated using the pooled RR estimate. Attributable burden was calculated by multiplying the PAF by the underlying burden of IHD estimated as part of GBD 2010. Results The pooled relative risk of developing IHD in those with major depression was 1.56 (95% CI 1.30 to 1.87). Globally there were almost 4 million estimated IHD disability-adjusted life years (DALYs), which can be attributed to major depression in 2010; 3.5 million years of life lost and 250,000 years of life lived with a disability. These findings highlight a previously underestimated mortality component of the burden of major depression. As a proportion of overall IHD burden, 2.95% (95% CI 1.48 to 4.46%) of IHD DALYs were estimated to be attributable to MDD in 2010. Eastern Europe and North Africa/Middle East demonstrate the highest proportion with Asia Pacific, high income representing the lowest. Conclusions The present work comprises the most robust systematic review of its kind to date. The key finding that major depression may be responsible for approximately 3% of global IHD DALYs warrants assessment for depression in patients at high risk of developing IHD or at risk of a repeat IHD event.

A framework for model integration and holistic modelling of socio-technical systems

This paper presents a layered framework for the purposes of integrating different Socio-Technical Systems (STS) models and perspectives into a whole-of-systems model. Holistic modelling plays a critical role in the engineering of STS due to the interplay between social and technical elements within these systems and resulting emergent behaviour. The framework decomposes STS models into components, where each component is either a static object, dynamic object or behavioural object. Based on existing literature, a classification of the different elements that make up STS, whether it be a social, technical or a natural environment element, is developed; each object can in turn be classified according to the STS elements it represents. Using the proposed framework, it is possible to systematically decompose models to an extent such that points of interface can be identified and the contextual factors required in transforming the component of one model to interface into another is obtained. Using an airport inbound passenger facilitation process as a case study socio-technical system, three different models are analysed: a Business Process Modelling Notation (BPMN) model, Hybrid Queue-based Bayesian Network (HQBN) model and an Agent Based Model (ABM). It is found that the framework enables the modeller to identify non-trivial interface points such as between the spatial interactions of an ABM and the causal reasoning of a HQBN, and between the process activity representation of a BPMN and simulated behavioural performance in a HQBN. Such a framework is a necessary enabler in order to integrate different modelling approaches in understanding and managing STS.

Bayesian computational methods for spatial analysis of images

This thesis introduces a new way of using prior information in a spatial model and develops scalable algorithms for fitting this model to large imaging datasets. These methods are employed for image-guided radiation therapy and satellite based classification of land use and water quality. This study has utilized a pre-computation step to achieve a hundredfold improvement in the elapsed runtime for model fitting. This makes it much more feasible to apply these models to real-world problems, and enables full Bayesian inference for images with a million or more pixels.

Integration over song classification replicates: song variant analysis in the hihi

Human expert analyses are commonly used in bioacoustic studies and can potentially limit the reproducibility of these results. In this paper, a machine learning method is presented to statistically classify avian vocalizations. Automated approaches were applied to isolate bird songs from long field recordings, assess song similarities, and classify songs into distinct variants. Because no positive controls were available to assess the true classification of variants, multiple replicates of automatic classification of song variants were analyzed to investigate clustering uncertainty. The automatic classifications were more similar to the expert classifications than expected by chance. Application of these methods demonstrated the presence of discrete song variants in an island population of the New Zealand hihi (Notiomystis cincta). The geographic patterns of song variation were then revealed by integrating over classification replicates. Because this automated approach considers variation in song variant classification, it reduces potential human bias and facilitates the reproducibility of the results.

Structure matters: Adoption of structured classification Approach in the context of cognitive presence classification

Within online learning communities, receiving timely and meaningful insights into the quality of learning activities is an important part of an effective educational experience. Commonly adopted methods – such as the Community of Inquiry framework – rely on manual coding of online discussion transcripts, which is a costly and time consuming process. There are several efforts underway to enable the automated classification of online discussion messages using supervised machine learning, which would enable the real-time analysis of interactions occurring within online learning communities. This paper investigates the importance of incorporating features that utilise the structure of on-line discussions for the classification of "cognitive presence" – the central dimension of the Community of Inquiry framework focusing on the quality of students' critical thinking within online learning communities. We implemented a Conditional Random Field classification solution, which incorporates structural features that may be useful in increasing classification performance over other implementations. Our approach leads to an improvement in classification accuracy of 5.8% over current existing techniques when tested on the same dataset, with a precision and recall of 0.630 and 0.504 respectively.

Porn, censorship, classification and free speech: Global paradoxes in the governance of media content

In this presentation, I reflect upon the global landscape surrounding the governance and classification of media content, at a time of rapid change in media platforms and services for content production and distribution, and contested cultural and social norms. I discuss the tensions and contradictions arising in the relationship between national, regional and global dimensions of media content distribution, as well as the changing relationships between state and non-state actors. These issues will be explored through consideration of issues such as: recent debates over film censorship; the review of the National Classification Scheme conducted by the Australian Law Reform Commission; online controversies such as the future of the Reddit social media site; and videos posted online by the militant group ISIS.

The validity of the GENEActiv wrist-worn accelerometer for measuring adult sedentary time in free living

OBJECTIVES Based on self-reported measures, sedentary time has been associated with chronic disease and mortality. This study examined the validity of the wrist-worn GENEactiv accelerometer for measuring sedentary time (i.e. sitting and lying) by posture classification, during waking hours in free living adults. DESIGN Fifty-seven participants (age=18-55 years 52% male) were recruited using convenience sampling from a large metropolitan Australian university. METHODS Participants wore a GENEActiv accelerometer on their non-dominant wrist and an activPAL device attached to their right thigh for 24-h (00:00 to 23:59:59). Pearson's Correlation Coefficient was used to examine the convergent validity of the GENEActiv and the activPAL for estimating total sedentary time during waking hours. Agreement was illustrated using Bland and Altman plots, and intra-individual agreement for posture was assessed with the Kappa statistic. RESULTS Estimates of average total sedentary time over 24-h were 623 (SD 103) min/day from the GENEActiv, and 626 (SD 123) min/day from the activPAL, with an Intraclass Correlation Coefficient of 0.80 (95% confidence intervals 0.68-0.88). Bland and Altman plots showed slight underestimation of mean total sedentary time for GENEActiv relative to activPAL (mean difference: -3.44min/day), with moderate limits of agreement (-144 to 137min/day). Mean Kappa for posture was 0.53 (SD 0.12), indicating moderate agreement for this sample at the individual level. CONCLUSIONS The estimation of sedentary time by posture classification of the wrist-worn GENEActiv accelerometer was comparable to the activPAL. The GENEActiv may provide an alternative, easy to wear device based measure for descriptive estimates of sedentary time in population samples

Statistical analysis of spectral data: A methodology for designing an intelligent monitoring system for the diabetic foot

Early detection of (pre-)signs of ulceration on a diabetic foot is valuable for clinical practice. Hyperspectral imaging is a promising technique for detection and classification of such (pre-)signs. However, the number of the spectral bands should be limited to avoid overfitting, which is critical for pixel classification with hyperspectral image data. The goal was to design a detector/classifier based on spectral imaging (SI) with a small number of optical bandpass filters. The performance and stability of the design were also investigated. The selection of the bandpass filters boils down to a feature selection problem. A dataset was built, containing reflectance spectra of 227 skin spots from 64 patients, measured with a spectrometer. Each skin spot was annotated manually by clinicians as "healthy" or a specific (pre-)sign of ulceration. Statistical analysis on the data set showed the number of required filters is between 3 and 7, depending on additional constraints on the filter set. The stability analysis revealed that shot noise was the most critical factor affecting the classification performance. It indicated that this impact could be avoided in future SI systems with a camera sensor whose saturation level is higher than 106, or by postimage processing.