The geography of the UK’s creative and high–tech economies

This report is the first systematic analysis of employment in the UK’s creative and high-tech economies. It analyses their size, growth and distribution across the country. Key Findings • The UK’s creative economy had 2.6 million jobs in 2013, consisting of 1.7 million jobs in the creative industries (890,000 in creative occupations and 818,000 working in other roles) and 907,000 jobs in creative occupations outside of the creative industries. • The UK’s high–tech economy had 3.2 million jobs in 2013, 2.4 million of which were jobs in high–tech industries (825,000 in Science Technology Engineering and Mathematics (STEM) occupations and 1.6 million in other roles) and 806,000 jobs in STEM occupations outside of the high–tech industries. • Employment in the creative economy grew on average over three times faster than the workforce as a whole (4.3 per cent per annum (p.a.) vs 1.2 per cent p.a.) between 2011 and 2013. • Employment in the high–tech economy also grew faster than the workforce over this period (2.1 per cent p.a. vs 1.2 per cent p.a.). • The creative economy is particularly concentrated in London and the South East which together account for 43 per cent of the UK’s creative economy workforce. By contrast, 31 per cent of high-tech economy employment and 28 per cent of the UK’s workforce is located in this area.

Changes in anatomical brain connectivity between ages 12 and 30: A HARDI study of 467 adolescents and adults

Graph theory can be applied to matrices that represent the brain's anatomical connections, to better understand global properties of anatomical networks, such as their clustering, efficiency and "small-world" topology. Network analysis is popular in adult studies of connectivity, but only one study - in just 30 subjects - has examined how network measures change as the brain develops over this period. Here we assessed the developmental trajectory of graph theory metrics of structural brain connectivity in a cross-sectional study of 467 subjects, aged 12 to 30. We computed network measures from 70×70 connectivity matrices of fiber density generated using whole-brain tractography in 4-Tesla 105-gradient high angular resolution diffusion images (HARDI). We assessed global efficiency and modularity, and both age and age 2 effects were identified. HARDI-based connectivity maps are sensitive to the remodeling and refinement of structural brain connections as the human brain develops.

Australian patients using a cardiac-diabetes web-based intervention program: Contributions to person-centered clinical practice

Rationale, aims and objectives: Patients with both cardiac disease and diabetes have poorer health outcomes than patients with only one chronic condition. While evidence indicates that internet based interventions may improve health outcomes for patients with a chronic disease, there is no literature on internet programs specific to cardiac patients with comorbid diabetes. Therefore this study aimed to develop a specific web-based program, then to explore patients’ perspectives on the usefulness of a new program. Methods: The interpretive approach using semi-structured interviews on a purposive sample of eligible patients with type 2 diabetes and a cardiac condition in a metropolitan hospital in Brisbane, Australia. Thematic analysis was undertaken to describe the perceived usefulness of a newly developed Heart2heart webpage. Results: Themes identified included confidence in hospital health professionals and reliance on doctors to manage conditions. Patients found the webpage useful for managing their conditions at home. Conclusions: The new Heart2heart webpage provided a positive and useful resource. Further research on to determine the potential influence of this resource on patients’ self-management behaviours is paramount. Implications for practice include using multimedia strategies for providing information to patients’ comorbidities of cardiac disease and type 2 diabetes, and further development on enhancement of such strategies

Meta-analysis of genome-wide association for migraine in six population-based European cohorts

Migraine is a common neurological disorder with a genetically complex background. This paper describes a meta-analysis of genome-wide association (GWA) studies on migraine, performed by the Dutch-Icelandic migraine genetics (DICE) consortium, which brings together six population-based European migraine cohorts with a total sample size of 10,980 individuals (2446 cases and 8534 controls). A total of 32 SNPs showed marginal evidence for association at a P-value<10(-5). The best result was obtained for SNP rs9908234, which had a P-value of 8.00 x 10(-8). This top SNP is located in the nerve growth factor receptor (NGFR) gene. However, this SNP did not replicate in three cohorts from the Netherlands and Australia. Of the other 31 SNPs, 18 SNPs were tested in two replication cohorts, but none replicated. In addition, we explored previously identified candidate genes in the meta-analysis data set. This revealed a modest gene-based significant association between migraine and the metadherin (MTDH) gene, previously identified in the first clinic-based GWA study (GWAS) for migraine (Bonferroni-corrected gene-based P-value=0.026). This finding is consistent with the involvement of the glutamate pathway in migraine. Additional research is necessary to further confirm the involvement of glutamate.