The ongoing significance of national media systems in the context of media globalization

This article argues that the concept of national media systems, and the comparative study of media systems, institutions, and practices, retains relevance in an era of media globalization and technological convergence. It considers various critiques of ‘media systems’ theories, such as those which view the concept of ‘system’ as a legacy of an outdated positivism and those which argue that the media globalization is weakening the relevance of nation-states in structuring the field of media cultures and practices. It argues for the continuing centrality of nation-states to media processes, and the ongoing significance of the national space in an age of media globalization, with reference to case studies of Internet policies in China, Brazil, and Australia. These studies indicate that nation-states remain critical actors in media governance and that domestic actors largely shape the central dynamics of media policies, even where media technologies and platforms enable global flows of media content.

Association between single-nucleotide polymorphisms in growth factor genes and quality of life in men with prostate cancer and the general population

Purpose Improved survival for men with prostate cancer has led to increased attention to factors influencing quality of life (QOL). As protein levels of vascular endothelial growth factor (VEGF) and insulin-like growth factor 1 (IGF-1) have been reported to be associated with QOL in people with cancer, we sought to identify whether single-nucleotide polymorphisms (SNPs) of these genes were associated with QOL in men with prostate cancer. Methods Multiple linear regression of two data sets (including approximately 750 men newly diagnosed with prostate cancer and 550 men from the general population) was used to investigate SNPs of VEGF and IGF-1 (10 SNPs in total) for associations with QOL (measured by the SF-36v2 health survey). Results Men with prostate cancer who carried the minor ‘T’ allele for IGF-1 SNP rs35767 had higher mean Role-Physical scale scores (≥0.3 SD) compared to non-carriers (p < 0.05). While this association was not identified in men from the general population, one IGF-1 SNP rs7965399 was associated with higher mean Bodily Pain scale scores in men from the general population that was not found in men with prostate cancer. Men from the general population who carried the rare ‘C’ allele had higher mean Bodily Pain scale scores (≥0.3 SD) than non-carriers (p < 0.05). Conclusions Through identifying SNPs that are associated with QOL in men with prostate cancer and men from the general population, this study adds to the mapping of complex interrelationships that influence QOL and suggests a role for IGF-I in physical QOL outcomes. Future research may identify biomarkers associated with increased risk of poor QOL that could assist in the provision of pre-emptive support for those identified at risk.

Parallel streaming signature EM-tree: A clustering algorithm for web scale applications

The proliferation of the web presents an unsolved problem of automatically analyzing billions of pages of natural language. We introduce a scalable algorithm that clusters hundreds of millions of web pages into hundreds of thousands of clusters. It does this on a single mid-range machine using efficient algorithms and compressed document representations. It is applied to two web-scale crawls covering tens of terabytes. ClueWeb09 and ClueWeb12 contain 500 and 733 million web pages and were clustered into 500,000 to 700,000 clusters. To the best of our knowledge, such fine grained clustering has not been previously demonstrated. Previous approaches clustered a sample that limits the maximum number of discoverable clusters. The proposed EM-tree algorithm uses the entire collection in clustering and produces several orders of magnitude more clusters than the existing algorithms. Fine grained clustering is necessary for meaningful clustering in massive collections where the number of distinct topics grows linearly with collection size. These fine-grained clusters show an improved cluster quality when assessed with two novel evaluations using ad hoc search relevance judgments and spam classifications for external validation. These evaluations solve the problem of assessing the quality of clusters where categorical labeling is unavailable and unfeasible.

Treatment of silk fibroin with poly(ethylene glycol) for the enhancement of corneal epithelial cell growth

A silk protein, fibroin, was isolated from the cocoons of the domesticated silkworm (Bombyx mori) and cast into membranes to serve as freestanding templates for tissue-engineered corneal cell constructs to be used in ocular surface reconstruction. In this study, we sought to enhance the attachment and proliferation of corneal epithelial cells by increasing the permeability of the fibroin membranes and the topographic roughness of their surface. By mixing the fibroin solution with poly(ethylene glycol) (PEG) of molecular weight 300 Da, membranes were produced with increased permeability and with topographic patterns generated on their surface. In order to enhance their mechanical stability, some PEG-treated membranes were also crosslinked with genipin. The resulting membranes were thoroughly characterized and compared to the non-treated membranes. The PEG-treated membranes were similar in tensile strength to the non-treated ones, but their elastic modulus was higher and elongation lower, indicating enhanced rigidity. The crosslinking with genipin did not induce a significant improvement in mechanical properties. In cultures of a human-derived corneal epithelial cell line (HCE-T), the PEG treatment of the substratum did not improve the attachment of cells and it enhanced only slightly the cell proliferation in the longer term. Likewise, primary cultures of human limbal epithelial cells grew equally well on both non-treated and PEG-treated membranes, and the stratification of cultures was consistently improved in the presence of an underlying culture of irradiated 3T3 feeder cells, irrespectively of PEG-treatment. Nevertheless, the cultures grown on the PEG-treated membranes in the presence of feeder cells did display a higher nuclear-to-cytoplasmic ratio suggesting a more proliferative phenotype. We concluded that while the treatment with PEG had a significant effect on some structural properties of the B. mori silk fibroin (BMSF) membranes, there were minimal gains in the performance of these materials as a substratum for corneal epithelial cell growth. The reduced mechanical stability of freestanding PEG-treated membranes makes them a less viable choice than the non-treated membranes.

Vascular endothelial growth factor is an autocrine growth factor, signaling through neuropilin-1 in non-small cell lung cancer

Background The VEGF pathway has become an important therapeutic target in lung cancer, where VEGF has long been established as a potent pro-angiogenic growth factor expressed by many types of tumors. While Bevacizumab (Avastin) has proven successful in increasing the objective tumor response rate and in prolonging progression and overall survival in patients with NSCLC, the survival benefit is however relatively short and the majority of patients eventually relapse. The current use of tyrosine kinase inhibitors alone and in combination with chemotherapy has been underwhelming, highlighting an urgent need for new targeted therapies. In this study, we examined the mechanisms of VEGF-mediated survival in NSCLC cells and the role of the Neuropilin receptors in this process. Methods NSCLC cells were screened for expression of VEGF and its receptors. The effects of recombinant VEGF and its blockade on lung tumor cell proliferation and cell cycle were examined. Phosphorylation of Akt and Erk1/2 proteins was examined by high content analysis and confocal microscopy. The effects of silencing VEGF on cell proliferation and survival signaling were also assessed. A Neuropilin-1 stable-transfected cell line was generated. Cell growth characteristics in addition to pAkt and pErk1/2 signaling were studied in response to VEGF and its blockade. Tumor growth studies were carried out in nude mice following subcutaneous injection of NP1 over-expressing cells. Results Inhibition of the VEGF pathway with anti-VEGF and anti-VEGFR-2 antibodies or siRNA to VEGF, NP1 and NP2 resulted in growth inhibition of NP1 positive tumor cell lines associated with down-regulation of PI3K and MAPK kinase signaling. Stable transfection of NP1 negative cells with NP1 induced proliferation in vitro, which was further enhanced by exogenous VEGF. In vivo, NP1 over-expressing cells significantly increased tumor growth in xenografts compared to controls. Conclusions Our data demonstrate that VEGF is an autocrine growth factor in NSCLC signaling, at least in part, through NP1. Targeting this VEGF receptor may offer potential as a novel therapeutic approach and also support the evaluation of the role of NP1 as a biomarker predicting sensitivity or resistance to VEGF and VEGFR-targeted therapies in the clinical arena.

Design intersection: The growth of community-led technology enabled companies

The sharing economy or collaborative consumption based firms have the potential to disrupt long-standing traditional industries. However, little is known on the topic, specifically the role of design in these successful community-led, technology enable firms. It is the proposition of this research that the intrinsic innovation of collaborative consumption firms is not merely a technological one. With successful firms being identified by being able to marry both technological advancement and human insight on product meaning. Therefore, the authors suggest the use of design as an effective way to capitalise and build on product meaning, not only technological advancements in order to foster the growth of a community. To explore this further, the research team decided to investigate two fast growing examples of industry disrupting, sharing economy businesses; Airbnb and Uber. Of the two cases, the use of design was found to be more evident within, Airbnb, due to wide profession of using design techniques. Each case study has been mapped on Guenther’s (2012) framework of techno-economic innovation to help illustrate this marriage of innovation agendas. This paper explored the role of design in community-led companies by presenting an argument for why they have succeeded due to an understanding of human need and key market trends, instead of only technological innovation alone. Findings and implication of these case studies suggest the future role of design as a method to achieve this success. Built on the core tenants of design thinking, these techniques rationalise technology, human needs and business viability to product innovative solutions. Upon these findings, the research team has created a new framework for understanding community-led technology enabled companies, one that builds upon the work of Guenther’s (2012) model of enterprise design innovation. This paper is the first step in a new research agenda.

Understanding the relationship between interfragmentary movement and callus growth in fracture healing: A novel computational approach

Introduction & Aims Optimising fracture treatments requires a sound understanding of relationships between stability, callus development and healing outcomes. This has been the goal of computational modelling, but discrepancies remain between simulations and experimental results. We compared healing patterns vs fixation stiffness between a novel computational callus growth model and corresponding experimental data. Hypothesis We hypothesised that callus growth is stimulated by diffusible signals, whose production is in turn regulated by mechanical conditions at the fracture site. We proposed that introducing this scheme into computational models would better replicate the observed tissue patterns and the inverse relationship between callus size and fixation stiffness. Method Finite element models of bone healing under stiff and flexible fixation were constructed, based on the parameters of a parallel rat femoral osteotomy study. An iterative procedure was implemented, to simulate the development of callus and its mechanical regulation. Tissue changes were regulated according to published mechano-biological criteria. Predictions of healing patterns were compared between standard models, with a pre-defined domain for callus development, and a novel approach, in which periosteal callus growth is driven by a diffusible signal. Production of this signal was driven by local mechanical conditions. Finally, each model’s predictions were compared to the corresponding histological data. Results Models in which healing progressed within a prescribed callus domain predicted that greater interfragmentary movements would displace early periosteal bone formation further from the fracture. This results from artificially large distortional strains predicted near the fracture edge. While experiments showed increased hard callus size under flexible fixation, this was not reflected in the standard models. Allowing the callus to grow from a thin soft tissue layer, in response to a mechanically stimulated diffusible signal, results in a callus shape and tissue distribution closer to those observed histologically. Importantly, the callus volume increased with increasing interfragmentary movement. Conclusions A novel method to incorporate callus growth into computational models of fracture healing allowed us to successfully capture the relationship between callus size and fixation stability observed in our rat experiments. This approach expands our toolkit for understanding the influence of different fixation strategies on healing outcomes.

Complete-linkage clustering for voice activity detection in audio and visual speech

We propose a novel technique for conducting robust voice activity detection (VAD) in high-noise recordings. We use Gaussian mixture modeling (GMM) to train two generic models; speech and non-speech. We then score smaller segments of a given (unseen) recording against each of these GMMs to obtain two respective likelihood scores for each segment. These scores are used to compute a dissimilarity measure between pairs of segments and to carry out complete-linkage clustering of the segments into speech and non-speech clusters. We compare the accuracy of our method against state-of-the-art and standardised VAD techniques to demonstrate an absolute improvement of 15% in half-total error rate (HTER) over the best performing baseline system and across the QUT-NOISE-TIMIT database. We then apply our approach to the Audio-Visual Database of American English (AVDBAE) to demonstrate the performance of our algorithm in using visual, audio-visual or a proposed fusion of these features.

Understanding the function and mechanisms of intestinal cell kinase in the growth and survival of prostate cancer cells

This project was a step forward in discovering the potential role of intestinal cell kinase in prostate cancer development. Intestinal cell kinase was shown to be upregulated in prostate cancer cells and altered expression led to changes in key cell survival proteins. This study used in vitro experiments to monitor changes in cell growth, protein and RNA expression.

Hierarchical clustering of the genetic connectivity matrix reveals the network topology of gene action on brain microstructure: An N=531 twin study

Genetic correlation (rg) analysis determines how much of the correlation between two measures is due to common genetic influences. In an analysis of 4 Tesla diffusion tensor images (DTI) from 531 healthy young adult twins and their siblings, we generalized the concept of genetic correlation to determine common genetic influences on white matter integrity, measured by fractional anisotropy (FA), at all points of the brain, yielding an NxN genetic correlation matrix rg(x,y) between FA values at all pairs of voxels in the brain. With hierarchical clustering, we identified brain regions with relatively homogeneous genetic determinants, to boost the power to identify causal single nucleotide polymorphisms (SNP). We applied genome-wide association (GWA) to assess associations between 529,497 SNPs and FA in clusters defined by hubs of the clustered genetic correlation matrix. We identified a network of genes, with a scale-free topology, that influences white matter integrity over multiple brain regions.

Genetic clustering on the hippocampal surface for genome-wide association studies

Imaging genetics aims to discover how variants in the human genome influence brain measures derived from images. Genome-wide association scans (GWAS) can screen the genome for common differences in our DNA that relate to brain measures. In small samples, GWAS has low power as individual gene effects are weak and one must also correct for multiple comparisons across the genome and the image. Here we extend recent work on genetic clustering of images, to analyze surface-based models of anatomy using GWAS. We performed spherical harmonic analysis of hippocampal surfaces, automatically extracted from brain MRI scans of 1254 subjects. We clustered hippocampal surface regions with common genetic influences by examining genetic correlations (r(g)) between the normalized deformation values at all pairs of surface points. Using genetic correlations to cluster surface measures, we were able to boost effect sizes for genetic associations, compared to clustering with traditional phenotypic correlations using Pearson's r.

Automatic clustering of white matter fibers in brain diffusion mri with an application to genetics

To understand factors that affect brain connectivity and integrity, it is beneficial to automatically cluster white matter (WM) fibers into anatomically recognizable tracts. Whole brain tractography, based on diffusion-weighted MRI, generates vast sets of fibers throughout the brain; clustering them into consistent and recognizable bundles can be difficult as there are wide individual variations in the trajectory and shape of WM pathways. Here we introduce a novel automated tract clustering algorithm based on label fusion - a concept from traditional intensity-based segmentation. Streamline tractography generates many incorrect fibers, so our top-down approach extracts tracts consistent with known anatomy, by mapping multiple hand-labeled atlases into a new dataset. We fuse clustering results from different atlases, using a mean distance fusion scheme. We reliably extracted the major tracts from 105-gradient high angular resolution diffusion images (HARDI) of 198 young normal twins. To compute population statistics, we use a pointwise correspondence method to match, compare, and average WM tracts across subjects. We illustrate our method in a genetic study of white matter tract heritability in twins.

Automatic population HARDI white matter tract clustering by label fusion of multiple tract atlases

Automatic labeling of white matter fibres in diffusion-weighted brain MRI is vital for comparing brain integrity and connectivity across populations, but is challenging. Whole brain tractography generates a vast set of fibres throughout the brain, but it is hard to cluster them into anatomically meaningful tracts, due to wide individual variations in the trajectory and shape of white matter pathways. We propose a novel automatic tract labeling algorithm that fuses information from tractography and multiple hand-labeled fibre tract atlases. As streamline tractography can generate a large number of false positive fibres, we developed a top-down approach to extract tracts consistent with known anatomy, based on a distance metric to multiple hand-labeled atlases. Clustering results from different atlases were fused, using a multi-stage fusion scheme. Our "label fusion" method reliably extracted the major tracts from 105-gradient HARDI scans of 100 young normal adults. © 2012 Springer-Verlag.