Multiple types of data are required to identify the mechanisms influencing the spatial expansion of melanoma cell colonies

Background The expansion of cell colonies is driven by a delicate balance of several mechanisms including cell motility, cell-to-cell adhesion and cell proliferation. New approaches that can be used to independently identify and quantify the role of each mechanism will help us understand how each mechanism contributes to the expansion process. Standard mathematical modelling approaches to describe such cell colony expansion typically neglect cell-to-cell adhesion, despite the fact that cell-to-cell adhesion is thought to play an important role. Results We use a combined experimental and mathematical modelling approach to determine the cell diffusivity, D, cell-to-cell adhesion strength, q, and cell proliferation rate, ?, in an expanding colony of MM127 melanoma cells. Using a circular barrier assay, we extract several types of experimental data and use a mathematical model to independently estimate D, q and ?. In our first set of experiments, we suppress cell proliferation and analyse three different types of data to estimate D and q. We find that standard types of data, such as the area enclosed by the leading edge of the expanding colony and more detailed cell density profiles throughout the expanding colony, does not provide sufficient information to uniquely identify D and q. We find that additional data relating to the degree of cell-to-cell clustering is required to provide independent estimates of q, and in turn D. In our second set of experiments, where proliferation is not suppressed, we use data describing temporal changes in cell density to determine the cell proliferation rate. In summary, we find that our experiments are best described using the range D = 161 - 243 ?m2 hour-1, q = 0.3 - 0.5 (low to moderate strength) and ? = 0.0305 - 0.0398 hour-1, and with these parameters we can accurately predict the temporal variations in the spatial extent and cell density profile throughout the expanding melanoma cell colony. Conclusions Our systematic approach to identify the cell diffusivity, cell-to-cell adhesion strength and cell proliferation rate highlights the importance of integrating multiple types of data to accurately quantify the factors influencing the spatial expansion of melanoma cell colonies.

Data requirements of hedonic models in determining the impact of infrastructure charges on new housing costs

The use of hedonic models to estimate the effects of various factors on house prices is well established. This paper examines a number of international hedonic house price models that seek to quantify the effect of infrastructure charges on new house prices. This work is an important factor in the housing affordability debate, with many governments in high growth areas having user-pays infrastructure charging policies operating in tandem with housing affordability objectives, with no empirical evidence on the impact of one on the other. This research finds there is little consistency between existing models and the data sets utilised. Specification appears dependent upon data availability rather than sound theoretical grounding. This may lead to a lack of external validity with model specification dependent upon data availability rather than sound theoretical grounding.

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.

Management of endocrine resistant breast cancer

Metastatic breast cancer (MBC) may present de novo but more commonly develops in women initially presenting with early breast cancer despite the widespread use of adjuvant hormonal and cytotoxic chemotherapy. MBC is incurable. Hormone sensitive MBC eventually becomes resistant to endocrine therapy in most women. Anthracyclines are the agents of choice in the treatment of endocrine resistant MBC. With the widespread use of anthracyclines in the adjuvant setting, taxanes have become the agents of choice for many patients. Recently capecitabine has become established as a standard of care for patients pretreated with anthracyclines and taxanes. However, a range of agents have activity as third line treatment. These include gemcitabine, vinorelbine and platinum analogues. The sequential use of non-cross resistant single agents rather than combination therapy is preferable in most women with MBC. Even though combination therapy can improve response rates and increase progression free interval, there is no robust evidence to indicate an advantage in terms of overall survival. Moreover, combination therapy is associated with a higher toxicity rate and poor quality of life. There is no role for dose-intense therapy, high dose therapy or maintenance chemotherapy outside the context of a clinical trial. The introduction of trastuzumab, monoclonal antibody targeting growth factor receptors, has improved the therapeutic options for women with tumours overexpressing HER2/neu. DNA micro-array profiles of tumours can potentially help to individualise therapy in future. Molecular targeted therapy has the potential to revolutionise the management of MBC.

On the role of RNA silencing in the pathogenicity and evolution of viroids and viral satellites

Viroids and most viral satellites have small, noncoding, and highly structured RNA genomes. How they cause disease symptoms without encoding proteins and why they have characteristic secondary structures are two longstanding questions. Recent studies have shown that both viroids and satellites are capable of inducing RNA silencing, suggesting a possible role of this mechanism in the pathology and evolution of these subviral RNAs. Here we show that preventing RNA silencing in tobacco, using a silencing suppressor, greatly reduces the symptoms caused by the Y satellite of cucumber mosaic virus. Furthermore, tomato plants expressing hairpin RNA, derived from potato spindle tuber viroid, developed symptoms similar to those of potato spindle tuber viroid infection. These results provide evidence suggesting that viroids and satellites cause disease symptoms by directing RNA silencing against physiologically important host genes. We also show that viroid and satellite RNAs are significantly resistant to RNA silencing-mediated degradation, suggesting that RNA silencing is an important selection pressure shaping the evolution of the secondary structures of these pathogens.

Expression patterns of vascular-specific promoters RolC and Sh in transgenic potatoes and their use in engineering PLRV-resistant plants

The expression patterns of GUS fusion constructs driven by the Agrobacterium rhizogenes RolC and the maize Sh (Shrunken: sucrose synthase-1) promoters were examined in transgenic potatoes (cv. Atlantic). RolC drove high-level gene expression in phloem tissue, bundle sheath cells and vascular parenchyma, but not in xylem or non-vascular tissues. Sh expression was exclusively confined to phloem tissue. Potato leafroll luteovirus (PLRV) replicates only in phloem tissues, and we show that when RolC is used to drive expression of the PLRV coat protein gene, virus-resistant lines can be obtained. In contrast, no significant resistance was observed when the Sh promoter was used.

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.

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.