Paracrine interactions between LNCaP prostate cancer cells and bioengineered bone in 3D in vitro culture reflect molecular changes during bone metastasis

As microenvironmental factors such as three-dimensionality and cell–matrix interactions are increasingly being acknowledged by cancer biologists, more complex 3D in vitro models are being developed to study tumorigenesis and cancer progression. To better understand the pathophysiology of bone metastasis, we have established and validated a 3D indirect co-culture model to investigate the paracrine interactions between prostate cancer (PCa) cells and human osteoblasts. Co-culture of the human PCa, LNCaP cells embedded within polyethylene glycol hydrogels with human osteoblasts in the form of a tissue engineered bone construct (TEB), resulted in reduced proliferation of LNCaP cells. LNCaP cells in both monoculture and co-culture were responsive to the androgen analog, R1881, as indicated by an increase in the expression (mRNA and/or protein induction) of androgen-regulated genes including prostate specific antigen and fatty acid synthase. Microarray gene expression analysis further revealed an up-regulation of bone markers and other genes associated with skeletal and vasculature development and a significant activation of transforming growth factor β1 downstream genes in LNCaP cells after co-culture with TEB. LNCaP cells co-cultured with TEB also unexpectedly showed similar changes in classical androgen-responsive genes under androgen-deprived conditions not seen in LNCaP monocultures. The molecular changes of LNCaP cells after co-culturing with TEBs suggest that osteoblasts exert a paracrine effect that may promote osteomimicry and modulate the expression of androgen-responsive genes in LNCaP cells. Taken together, we have presented a novel 3D in vitro model that allows the study of cellular and molecular changes occurring in PCa cells and osteoblasts that are relevant to metastatic colonization of bone. This unique in vitro model could also facilitate cancer biologists to dissect specific biological hypotheses via extensive genomic or proteomic assessments to further our understanding of the PCa-bone crosstalk.

Differential expression of NADPH-diaphorase between electrophysiologically-defined classes of pyramidal neurons in rat ventral subiculum, in vitro

The subiculum is the major output region of the hippocampal formation. We have studied pyramidal neurons in slices of rat ventral subiculum to determine if there is a correlation between nicotinamide adenine dinucleotide phosphate-diaphorase (NADPH-d) activity and electrophysiological phenotype. The majority of NADPH-d-positive pyramidal neurons were found in the superficial cell layer (i.e. nearest to the hippocampal fissure) of the subiculum and appreciable NADPH-d activity was absent from pyramidal neurons in area CA1. This distribution of NADPH-d activity was mimicked by that of immunoreactivity for the neuronal isoform of nitric oxide synthase. Subicular pyramidal neurons were classified, electrophysiologically, as intrinsically burst-firing or regular spiking. After electrophysiological characterization, neurons were filled with Neurobiotin and revealed using fluorescence immunocytochemistry. The slices containing these neurons were also processed for NADPH-d. NADPH-d activity was found in six out of eight regular spiking neurons but was not found in any of 13 intrinsically burst-firing neurons (P=0.0008, Fisher's Exact Test). We conclude that in rat ventral subiculum, NADPH-d activity is present in a proportion of pyramidal neurons and indicates the presence of the neuronal isoform of nitric oxide synthase. Furthermore, amongst pyramidal neurons, NADPH-d activity is distributed preferentially to those with the regular spiking phenotype. The distribution of regular spiking neurons suggests that they may not be present to the same extent in all subicular output pathways. Thus, the actions of nitric oxide may be relatively specific to particular hippocampal connections.

Monocyte chemoattractant protein-1 and nitric oxide promote adipogenesis in a model that mimics obesity

Objective: An increasing body of evidence is emerging linking adipogenesis and inflammation. Obesity, alone or as a part of the metabolic syndrome, is characterized by a state of chronic low-level inflammation as revealed by raised plasma levels of inflammatory cytokines and acute-phase proteins. If inflammation can, in turn, increase adipose tissue growth, this may be the basis for a positive feedback loop in obesity. We have developed a tissue engineering model for growing adipose tissue in the mouse that allows quantification of increases in adipogenesis. In this study, we evaluated the adipogenic potential of the inflammogens monocyte chemoattractant protein (MCP)-I and zymosan-A (Zy) in a murine tissue engineering model. Research Methods and Procedures: MCP-I and Zy were added to chambers filled with Matrigel and fibroblastgrowth factor 2. To analyze the role of inducible nitric oxide synthase (iNOS), the iNOS inhibitor aminoguanidine was added to the chamber. Results: Our results show that MCP-I generated proportionally large quantities of new adipose tissue. This neoadipogenesis was accompanied by an ingrowth of macrophages and could be mimicked by Zy. Aminoguanidine significantly inhibited the formation of adipose tissue. Discussion: Our findings demonstrate that low-grade inflammation and iNOS expression are important factors in adipogenesis, Because fat neoformation in obesity and the metabolic syndrome is believed to be mediated by macrophage-derived proinflammatory cytokines, this adipose tissue engineering system provides a model that could potentially be used to further unravel the pathogenesis of these two metabolic disorders.

iNOS expression and osteocyte apoptosis in idiopathic, non- traumatic osteonecrosis

Background and purpose Non-traumatic osteonecrosis is a progressive disease with multiple etiologies. It affects younger individuals more and more, often leading to total hip arthroplasty. We investigated whether there is a correlation between inducible nitric oxide synthase (iNOS) expression and osteocyte apoptosis in non-traumatic osteonecrosis. Patients and methods We collected and studied 20 human idiopathic, non-traumatic osteonecrosis femoral heads. Subchondral bone samples in the non-sclerotic region (n = 30), collected from osteoarthritis patients, were used as controls. Spontaneously hypertensive rats were used as a model for osteonecrosis in the study. We used scanning electron microscopy, TUNEL assay, and immunohistochemical staining to study osteocyte changes and apoptosis. Results The morphology of osteocytes in the areas close to the necrotic region changed and the number of apoptotic osteocytes increased in comparison with the same region in control groups. The expression of iNOS and cytochrome C in osteocytes increased while Bax expression was not detectable in osteonecrosis samples. Using spontaneously hypertensive rats, we found a positive correlation between iNOS expression and osteocyte apoptosis in the osteonecrotic region. iNOS inhibitor (aminoguanidine) added to the drinking water for 5 weeks reduced the production of iNOS and osteonecrosis compared to a control group without aminoguanidine. Interpretation Our findings show that increased iNOS expression can lead to osteocyte apopotosis in idiopathic, non-traumatic osteonecrosis and that an iNOS inhibitor may prevent the progression of the disease.

Potential pitfalls in packaged software adoption

The common reasons for those in organizations adopting large config- urable packaged software products are compelling. Problems with the existing software situation, the supposed predictability and perceived business benefits of packaged software, and various social influences, can lead to packages being preferred to custom approaches. Yet, for every reason, there is a potential associated problem that must be understood before an informed adoption decision can be made...

Acceptability-based QoE management for user-centric mobile video delivery : a field study evaluation

Effective Quality of Experience (QoE) management for mobile video delivery – to optimize overall user experience while adapting to heterogeneous use contexts – is still a big challenge to date. This paper proposes a mobile video delivery system to emphasize the use of acceptability as the main indicator of QoE to manage the end-to-end factors in delivering mobile video services. The first contribution is a novel framework for user-centric mobile video system that is based on acceptability-based QoE (A-QoE) prediction models, which were derived from comprehensive subjective studies. The second contribution is results from a field study that evaluates the user experience of the proposed system during realistic usage circumstances, addressing the impacts of perceived video quality, loading speed, interest in content, viewing locations, network bandwidth, display devices, and different video coding approaches, including region-of-interest (ROI) enhancement and center zooming

Stochastic output feedback model predictive control

This paper addresses the issue of output feedback model predictive control for linear systems with input constraints and stochastic disturbances. We show that the optimal policy uses the Kalman filter for state estimation, but the resultant state estimates are not utilized in a certainty equivalence control law

Learning-based Relevance Feedback for Web-based Relation Completion

In a pilot application based on web search engine calledWeb-based Relation Completion (WebRC), we propose to join two columns of entities linked by a predefined relation by mining knowledge from the web through a web search engine. To achieve this, a novel retrieval task Relation Query Expansion (RelQE) is modelled: given an entity (query), the task is to retrieve documents containing entities in predefined relation to the given one. Solving this problem entails expanding the query before submitting it to a web search engine to ensure that mostly documents containing the linked entity are returned in the top K search results. In this paper, we propose a novel Learning-based Relevance Feedback (LRF) approach to solve this retrieval task. Expansion terms are learned from training pairs of entities linked by the predefined relation and applied to new entity-queries to find entities linked by the same relation. After describing the approach, we present experimental results on real-world web data collections, which show that the LRF approach always improves the precision of top-ranked search results to up to 8.6 times the baseline. Using LRF, WebRC also shows performances way above the baseline.

Choosing an appropriate modelling framework for analysing multispecies co-culture cell biology experiments

In vitro cell biology assays play a crucial role in informing our understanding of the migratory, proliferative and invasive properties of many cell types in different biological contexts. While mono-culture assays involve the study of a population of cells composed of a single cell type, co-culture assays study a population of cells composed of multiple cell types (or subpopulations of cells). Such co-culture assays can provide more realistic insights into many biological processes including tissue repair, tissue regeneration and malignant spreading. Typically, system parameters, such as motility and proliferation rates, are estimated by calibrating a mathematical or computational model to the observed experimental data. However, parameter estimates can be highly sensitive to the choice of model and modelling framework. This observation motivates us to consider the fundamental question of how we can best choose a model to facilitate accurate parameter estimation for a particular assay. In this work we describe three mathematical models of mono-culture and co-culture assays that include different levels of spatial detail. We study various spatial summary statistics to explore if they can be used to distinguish between the suitability of each model over a range of parameter space. Our results for mono-culture experiments are promising, in that we suggest two spatial statistics that can be used to direct model choice. However, co-culture experiments are far more challenging: we show that these same spatial statistics which provide useful insight into mono-culture systems are insuffcient for co-culture systems. Therefore, we conclude that great care ought to be exercised when estimating the parameters of co-culture assays.

Large scale multiuser digital mind mapping tool : a study in usability

Project work can involve multiple people from varying disciplines coming together to solve problems as a group. Large scale interactive displays are presenting new opportunities to support such interactions with interactive and semantically enabled cooperative work tools such as intelligent mind maps. In this paper, we present a novel digital, touch-enabled mind-mapping tool as a first step towards achieving such a vision. This first prototype allows an evaluation of the benefits of a digital environment for a task that would otherwise be performed on paper or flat interactive surfaces. Observations and surveys of 12 participants in 3 groups allowed the formulation of several recommendations for further research into: new methods for capturing text input on touch screens; inclusion of complex structures; multi-user environments and how users make the shift from single- user applications; and how best to navigate large screen real estate in a touch-enabled, co-present multi-user setting.

Evolutionary game design : automated game design comes of age

The "Humies" awards are an annual competition held in conjunction with the Genetic and Evolutionary Computation Conference (GECCO), in which cash prizes totalling $10,000 are awarded to the most human-competitive results produced by any form of evolutionary computation published in the previous year. This article describes the gold medal-winning entry from the 2012 "Humies" competition, based on the LUDI system for playing, evaluating and creating new board games. LUDI was able to demonstrate human-competitive results in evolving novel board games that have gone on to be commercially published, one of which, Yavalath, has been ranked in the top 2.5% of abstract board games ever invented. Further evidence of human-competitiveness was demonstrated in the evolved games implicitly capturing several principles of good game design, outperforming human designers in at least one case, and going on to inspire a new sub-genre of games.

An internet of social things

The Internet of Things is a vision for a world of interconnected smart devices. We present an alternative vision based on a review of literature that emphasizes the importance and role of objects in social relations. We situate this work in relation to a conceptual understanding of objects and sociality, and note some methodological implications of a more object-centred sociality that may suggest design opportunities alongside the emerging Internet of Things.

Mobile phone use in Australian Indigenous communities : future pathways for HC14D

This paper collates recent research on mobile phone use in Indigenous communities in Australia. Its key finding is that mobile phones are heavily used in these communities, albeit in unique and unusual ways that may be difficult to comprehend beneath 'top-down' measurements. Rather than framing these uses as being compromises made in lieu of appropriate infrastructures or literacies, it is argued that HCI4D (Human-Computer Interaction for Development) would be better served by seriously plumbing into the information they reveal about how mobile phones are constructed and placed in these communities, and what these factors might reveal about local understandings of development and well-being. A consideration of these specific patterns of appropriation is necessary to push the field beyond top-down, rationalist approaches to development towards more flexible, creative solutions that build from local knowledge and competencies.

Instructional objectives to core-gameplay : a serious game design technique

This paper explores a gap within the serious game design research. That gap is the ambiguity surrounding the process of aligning the instructional objectives of serious games with their core-gameplay i.e. the moment-to-moment activity that is the core of player interaction. A core-gameplay focused design framework is proposed that can work alongside existing, more broadly focused serious games design frameworks. The framework utilises an inquiry-based approach that allows the serious game designer to use key questions as a means to clearly outline instructional objectives with the core-gameplay. The use of this design framework is considered in the context of a small section of gameplay from an educational game currently in development. This demonstration of the framework brings shows how instructional objectives can be embedded into a serious games core-gameplay.

Refining user and item profiles based on multidimensional data for top-n item recommendation

In recommender systems based on multidimensional data, additional metadata provides algorithms with more information for better understanding the interaction between users and items. However, most of the profiling approaches in neighbourhood-based recommendation approaches for multidimensional data merely split or project the dimensional data and lack the consideration of latent interaction between the dimensions of the data. In this paper, we propose a novel user/item profiling approach for Collaborative Filtering (CF) item recommendation on multidimensional data. We further present incremental profiling method for updating the profiles. For item recommendation, we seek to delve into different types of relations in data to understand the interaction between users and items more fully, and propose three multidimensional CF recommendation approaches for top-N item recommendations based on the proposed user/item profiles. The proposed multidimensional CF approaches are capable of incorporating not only localized relations of user-user and/or item-item neighbourhoods but also latent interaction between all dimensions of the data. Experimental results show significant improvements in terms of recommendation accuracy.