Improved sub-cellular resolution via simultaneous analysis of organelle proteomics data across varied experimental conditions

Spatial organisation of proteins according to their function plays an important role in the specificity of their molecular interactions. Emerging proteomics methods seek to assign proteins to sub-cellular locations by partial separation of organelles and computational analysis of protein abundance distributions among partially separated fractions. Such methods permit simultaneous analysis of unpurified organelles and promise proteome-wide localisation in scenarios wherein perturbation may prompt dynamic re-distribution. Resolving organelles that display similar behavior during a protocol designed to provide partial enrichment represents a possible shortcoming. We employ the Localisation of Organelle Proteins by Isotope Tagging (LOPIT) organelle proteomics platform to demonstrate that combining information from distinct separations of the same material can improve organelle resolution and assignment of proteins to sub-cellular locations. Two previously published experiments, whose distinct gradients are alone unable to fully resolve six known protein-organelle groupings, are subjected to a rigorous analysis to assess protein-organelle association via a contemporary pattern recognition algorithm. Upon straightforward combination of single-gradient data, we observe significant improvement in protein-organelle association via both a non-linear support vector machine algorithm and partial least-squares discriminant analysis. The outcome yields suggestions for further improvements to present organelle proteomics platforms, and a robust analytical methodology via which to associate proteins with sub-cellular organelles.

A data mining approach to improve the automated quality of data

This thesis describes the development of a robust and novel prototype to address the data quality problems that relate to the dimension of outlier data. It thoroughly investigates the associated problems with regards to detecting, assessing and determining the severity of the problem of outlier data; and proposes granule-mining based alternative techniques to significantly improve the effectiveness of mining and assessing outlier data.

Rapid scanning of spectrograms for efficient identification of bioacoustic events in big data

Acoustic sensing is a promising approach to scaling faunal biodiversity monitoring. Scaling the analysis of audio collected by acoustic sensors is a big data problem. Standard approaches for dealing with big acoustic data include automated recognition and crowd based analysis. Automatic methods are fast at processing but hard to rigorously design, whilst manual methods are accurate but slow at processing. In particular, manual methods of acoustic data analysis are constrained by a 1:1 time relationship between the data and its analysts. This constraint is the inherent need to listen to the audio data. This paper demonstrates how the efficiency of crowd sourced sound analysis can be increased by an order of magnitude through the visual inspection of audio visualized as spectrograms. Experimental data suggests that an analysis speedup of 12× is obtainable for suitable types of acoustic analysis, given that only spectrograms are shown.

An extracellular signal-regulated kinase 2 survival pathway mediates resistance of human mesothelioma cells to asbestos-induced injury

We hypothesized that normal human mesothelial cells acquire resistance to asbestos-induced toxicity via induction of one or more epidermal growth factor receptor (EGFR) - linked survival pathways (phosphoinositol-3-kinase/AKT/ mammalian target of rapamycin and extracellular signal - regulated kinase [ERK] 1/2) during simian virus 40 (SV40) transformation and carcinogenesis. Both isolated HKNM-2 mesothelial cells and a telomerase-immortalized mesothelial line (LP9/TERT-1) were more sensitive to crocidolite asbestos toxicity than an SV40 Tag-immortalized mesothelial line (MET5A) and malignant mesothelioma cell lines (HMESO and PPM Mill). Whereas increases in phosphorylation of AKT (pAKT) were observed in MET5A cells in response to asbestos, LP9/TERT-1 cells exhibited dose-related decreases in pAKT levels. Pretreatment with an EGFR phosphorylation or mitogen-activated protein kinase kinase 1/2 inhibitor abrogated asbestos-induced phosphorylated ERK (pERK) 1/2 levels in both LP9/TERT-1 and MET5A cells as well as increases in pAKT levels in MET5A cells. Transient transfection of small interfering RNAs targeting ERK1, ERK2, or AKT revealed that ERK1/2 pathways were involved in cell death by asbestos in both cell lines. Asbestos-resistant HMESO or PPM Mill cells with high endogenous levels of ERKs or AKT did not show dose-responsive increases in pERK1/ERK1, pERK2/ERK2, or pAKT/AKT levels by asbestos. However, small hairpin ERK2 stable cell lines created from both malignant mesothelioma lines were more sensitive to asbestos toxicity than shERK1 and shControl lines, and exhibited unique, tumor-specific changes in endogenous cell death - related gene expression. Our results suggest that EGFR phosphorylation is causally linkedto pERK and pAKT activation by asbestos in normal and SV40 Tag - immortalized human mesothelial cells. They also indicate that ERK2 plays a role in modulating asbestos toxicity by regulating genes critical to cell injury and survival that are differentially expressed in human mesotheliomas.

Technical efficiency of mainstream airlines and low-cost carriers : New evidence using bootstrap data envelopment analysis truncated regression

Between 2001 and 2005, the US airline industry faced financial turmoil while the European airline industry entered a period of substantive deregulation. Consequently, this opened up opportunities for low-cost carriers to become more competitive in the market. To assess airline performance and identify the sources of efficiency in the immediate aftermath of these events, we employ a bootstrap data envelopment analysis truncated regression approach. The results suggest that at the time the mainstream airlines needed to significantly reorganize and rescale their operations to remain competitive. In the second-stage analysis, the results indicate that private ownership, status as a low-cost carrier, and improvements in weight load contributed to better organizational efficiency.

Physical activity and health-related quality of life among physiotherapists : a cross sectional survey in an Australian hospital and health service

Background Physiotherapists are a professional group with a high rate of attrition and at high risk of musculoskeletal disorders. The purpose of this investigation was to examine the physical activity levels and health-related quality of life of physiotherapists working in metropolitan clinical settings in an Australian hospital and health service. It was hypothesized that practicing physiotherapists would report excellent health-related quality of life and would already be physically active. Such a finding would add weight to a claim that general physical activity conditioning strategies may not be useful for preventing musculoskeletal disorders among active healthy physiotherapists, but rather, future investigations should focus on the development and evaluation of role specific conditioning strategies. Methods A questionnaire was completed by 44 physiotherapists from three inpatient units and three ambulatory clinics (63.7% response rate). Physical activity levels were reported using the Active Australia Survey. Health-related quality of life was examined using the EQ-5D instrument. Physical activity and EQ-5D data were examined using conventional descriptive statistics; with domain responses for the EQ-5D presented in a frequency histogram. Results The majority of physiotherapists in this sample were younger than 30 years of age (n = 25, 56.8%) consistent with the presence of a high attrition rate. Almost all respondents exceeded minimum recommended physical activity guidelines (n = 40, 90.9%). Overall the respondents engaged in more vigorous physical activity (median = 180 minutes) and walking (median = 135 minutes) than moderate exercise (median = 35 minutes) each week. Thirty-seven (84.1%) participants reported no pain or discomfort impacting their health-related quality of life, with most (n = 35,79.5%) being in full health. Conclusions Physical-conditioning based interventions for the prevention of musculoskeletal disorders among practicing physiotherapists may be better targeted to role or task specific conditioning rather than general physical conditioning among this physically active population. It is plausible that an inherent attrition of physiotherapists may occur among those not as active or healthy as therapists who cope with the physical demands of clinical practice. Extrapolation of findings from this study may be limited due to the sample characteristics. However, this investigation addressed the study objectives and has provided a foundation for larger scale longitudinal investigations in this field.

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.

Development of an evidence-based framework to guide injury prevention interventions for off-road motorcyclists

There is little research on off-road motorcycle and all-terrain vehicle riders though injury levels are high. This thesis identified formal responsibility for monitoring injuries, targeting young male and recreational riders, promotion of family members as models, and controlled and accessible riding locations as ways to increase safety. These recommendations were based on analysis of Queensland hospitalisation records, rider personal reports and survey responses.

Exchanging data between Digital Human Modelling systems : a review of data formats

Digital human modeling (DHM) systems underwent significant development within the last years. They achieved constantly growing importance in the field of ergonomic workplace design, product development, product usability, ergonomic research, ergonomic education, audiovisual marketing and the entertainment industry. They help to design ergonomic products as well as healthy and safe socio-technical work systems. In the domain of scientific DHM systems, no industry specific standard interfaces are defined which could facilitate the exchange of 3D solid body data, anthropometric data or motion data. The focus of this article is to provide an overview of requirements for a reliable data exchange between different DHM systems in order to identify suitable file formats. Examples from the literature are discussed in detail. Methods: As a first step a literature review is conducted on existing studies and file formats for exchanging data between different DHM systems. The found file formats can be structured into different categories: static 3D solid body data exchange, anthropometric data exchange, motion data exchange and comprehensive data exchange. Each file format is discussed and advantages as well as disadvantages for the DHM context are pointed out. Case studies are furthermore presented, which show first approaches to exchange data between DHM systems. Lessons learnt are shortly summarized. Results: A selection of suitable file formats for data exchange between DHM systems is determined from the literature review.

A methodology for estimating exposure-controlled crash risk using traffic Police crash data

Exposure control or case-control methodologies are common techniques for estimating crash risks, however they require either observational data on control cases or exogenous exposure data, such as vehicle-kilometres travelled. This study proposes an alternative methodology for estimating crash risk of road user groups, whilst controlling for exposure under a variety of roadway, traffic and environmental factors by using readily available police-reported crash data. In particular, the proposed method employs a combination of a log-linear model and quasi-induced exposure technique to identify significant interactions among a range of roadway, environmental and traffic conditions to estimate associated crash risks. The proposed methodology is illustrated using a set of police-reported crash data from January 2004 to June 2009 on roadways in Queensland, Australia. Exposure-controlled crash risks of motorcyclists—involved in multi-vehicle crashes at intersections—were estimated under various combinations of variables like posted speed limit, intersection control type, intersection configuration, and lighting condition. Results show that the crash risk of motorcycles at three-legged intersections is high if the posted speed limits along the approaches are greater than 60 km/h. The crash risk at three-legged intersections is also high when they are unsignalized. Dark lighting conditions appear to increase the crash risk of motorcycles at signalized intersections, but the problem of night time conspicuity of motorcyclists at intersections is lessened on approaches with lower speed limits. This study demonstrates that this combined methodology is a promising tool for gaining new insights into the crash risks of road user groups, and is transferrable to other road users.

Implementing open licensing in government open data initiatives : a review of Australian government practice

As support grows for greater access to information and data held by governments, so does awareness of the need for appropriate policy, technical and legal frameworks to achieve the desired economic and societal outcomes. Since the late 2000s numerous international organizations, inter-governmental bodies and governments have issued open government data policies, which set out key principles underpinning access to, and the release and reuse of data. These policies reiterate the value of government data and establish the default position that it should be openly accessible to the public under transparent and non-discriminatory conditions, which are conducive to innovative reuse of the data. A key principle stated in open government data policies is that legal rights in government information must be exercised in a manner that is consistent with and supports the open accessibility and reusability of the data. In particular, where government information and data is protected by copyright, access should be provided under licensing terms which clearly permit its reuse and dissemination. This principle has been further developed in the policies issued by Australian Governments into a specific requirement that Government agencies are to apply the Creative Commons Attribution licence (CC BY) as the default licensing position when releasing government information and data. A wide-ranging survey of the practices of Australian Government agencies in managing their information and data, commissioned by the Office of the Australian Information Commissioner in 2012, provides valuable insights into progress towards the achievement of open government policy objectives and the adoption of open licensing practices. The survey results indicate that Australian Government agencies are embracing open access and a proactive disclosure culture and that open licensing under Creative Commons licences is increasingly prevalent. However, the finding that ‘[t]he default position of open access licensing is not clearly or robustly stated, nor properly reflected in the practice of Government agencies’ points to the need to further develop the policy framework and the principles governing information access and reuse, and to provide practical guidance tools on open licensing if the broadest range of government information and data is to be made available for innovative reuse.

Modelling survival data to account for model uncertainty: a single model or model averaging?

This study considered the problem of predicting survival, based on three alternative models: a single Weibull, a mixture of Weibulls and a cure model. Instead of the common procedure of choosing a single “best” model, where “best” is defined in terms of goodness of fit to the data, a Bayesian model averaging (BMA) approach was adopted to account for model uncertainty. This was illustrated using a case study in which the aim was the description of lymphoma cancer survival with covariates given by phenotypes and gene expression. The results of this study indicate that if the sample size is sufficiently large, one of the three models emerge as having highest probability given the data, as indicated by the goodness of fit measure; the Bayesian information criterion (BIC). However, when the sample size was reduced, no single model was revealed as “best”, suggesting that a BMA approach would be appropriate. Although a BMA approach can compromise on goodness of fit to the data (when compared to the true model), it can provide robust predictions and facilitate more detailed investigation of the relationships between gene expression and patient survival. Keywords: Bayesian modelling; Bayesian model averaging; Cure model; Markov Chain Monte Carlo; Mixture model; Survival analysis; Weibull distribution

Retrieving dynamic origin-destination matrices from Bluetooth data

The Bluetooth technology is being increasingly used, among the Automated Vehicle Identification Systems, to retrieve important information about urban networks. Because the movement of Bluetooth-equipped vehicles can be monitored, throughout the network of Bluetooth sensors, this technology represents an effective means to acquire accurate time dependant Origin Destination information. In order to obtain reliable estimations, however, a number of issues need to be addressed, through data filtering and correction techniques. Some of the main challenges inherent to Bluetooth data are, first, that Bluetooth sensors may fail to detect all of the nearby Bluetooth-enabled vehicles. As a consequence, the exact journey for some vehicles may become a latent pattern that will need to be estimated. Second, sensors that are in close proximity to each other may have overlapping detection areas, thus making the task of retrieving the correct travelled path even more challenging. The aim of this paper is twofold: to give an overview of the issues inherent to the Bluetooth technology, through the analysis of the data available from the Bluetooth sensors in Brisbane; and to propose a method for retrieving the itineraries of the individual Bluetooth vehicles. We argue that estimating these latent itineraries, accurately, is a crucial step toward the retrieval of accurate dynamic Origin Destination Matrices.

Transit passenger segmentation using travel regularity mined from Smart Card transactions data

Transit passenger market segmentation enables transit operators to target different classes of transit users to provide customized information and services. The Smart Card (SC) data, from Automated Fare Collection system, facilitates the understanding of multiday travel regularity of transit passengers, and can be used to segment them into identifiable classes of similar behaviors and needs. However, the use of SC data for market segmentation has attracted very limited attention in the literature. This paper proposes a novel methodology for mining spatial and temporal travel regularity from each individual passenger’s historical SC transactions and segments them into four segments of transit users. After reconstructing the travel itineraries from historical SC transactions, the paper adopts the Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm to mine travel regularity of each SC user. The travel regularity is then used to segment SC users by an a priori market segmentation approach. The methodology proposed in this paper assists transit operators to understand their passengers and provide them oriented information and services.