The INSIG2 rs7566605 polymorphism is not associated with body mass index and breast cancer risk

Background The single nucleotide polymorphism rs7566605, located in the promoter of the INSIG2 gene, has been the subject of a strong scientific effort aimed to elucidate its possible association with body mass index (BMI). The first report showing that rs7566605 could be associated with body fatness was a genome-wide association study (GWAS) which used BMI as the primary phenotype. Many follow-up studies sought to validate the association of rs7566605 with various markers of obesity, with several publications reporting inconsistent findings. BMI is considered to be one of the measures of choice to evaluate body fatness and there is evidence that body fatness is related with an increased risk of breast cancer (BC). Methods we tested in a large-scale association study (3,973 women, including 1,269 invasive BC cases and 2,194 controls), nested within the EPIC cohort, the involvement of rs7566605 as predictor of BMI and BC risk. Results and Conclusions In this study we were not able to find any statistically significant association between this SNP and BMI, nor did we find any significant association between the SNP and an increased risk of breast cancer overall and by subgroups of age, or menopausal status.

Assessment of Severe Apnoea through Voice Analysis, Automatic Speech, and Speaker Recognition Techniques

This study is part of an ongoing collaborative effort between the medical and the signal processing communities to promote research on applying standard Automatic Speech Recognition (ASR) techniques for the automatic diagnosis of patients with severe obstructive sleep apnoea (OSA). Early detection of severe apnoea cases is important so that patients can receive early treatment. Effective ASR-based detection could dramatically cut medical testing time. Working with a carefully designed speech database of healthy and apnoea subjects, we describe an acoustic search for distinctive apnoea voice characteristics. We also study abnormal nasalization in OSA patients by modelling vowels in nasal and nonnasal phonetic contexts using Gaussian Mixture Model (GMM) pattern recognition on speech spectra. Finally, we present experimental findings regarding the discriminative power of GMMs applied to severe apnoea detection. We have achieved an 81% correct classification rate, which is very promising and underpins the interest in this line of inquiry.

Digital inmigrants and digital natives expectation collection in the Andalusian Public Health System Virtual Library: communication with our users

The Andalusian Public Health System Virtual Library (Biblioteca Virtual del Sistema Sanitario Público de Andalucía, BV-SSPA) provides access to health information resources and services to healthcare professionals through its Website. This virtual environment demands higher users’ knowledge in order to satisfy of the need of information of our users, as digital natives as digital immigrants, improving at the same time the communication with all of them. 1. To collect clients' views and expectations according to their nature of digital natives and immigrants. 2. To know our online reputation. A Collecting User Expectation Questionnaire will be built, taking into account the segmentation of the BV-SSPA users’ professional groups of the Andalusian Public Health System. A pilot test will be run to check the survey dimensions and items about practices, attitudes and knowledge of our users. Two Quality Function Deployment (QFD) matrices will enable the BV-SSPA services to be targeted to our digital natives or digital immigrants, according to their nature, finding the best way to satisfy their information needs. We provide feedback on BV-SSPA: users can have the opportunity to post feedback about the site via the 'Contact us' section and comment about their experience. And Web 2.0 is a shop window, providing the opportunity to show the comments; and through time, our online reputation will be built, but the BV-SSPA must manage its own personal branding. Web 2.0 tools are a driver of improvement, because they provide a key source of insight into people's attitudes. Besides, the BV-SSPA digital identity will be analyzed through indicators like major search engine referrals breakdown, top referring sites (non search engines), or top search engine referral phrases, among others. Definition of digital native and digital immigrant profiles of the BV-SSPA, and their difference, will be explained by their expectations. The design of the two QFD matrices will illustrate in just one graph the requirements of both groups for tackling digital abilities and inequalities. The BV-SSPA could deliver information and services through alternative channels. On the other hand, we are developing a strategy to identify, to measure and to manage a digital identity through communication with the user and to find out our online reputation. With the use of different tools from quantitative and qualitative methodology, and the opportunities offered by Web 2.0 tools, the BV-SSPA will know the expectations of their users as a first step to satisfy their necessities. Personalization is pivotal to the success of the Site, delivering tailored content to individuals based on their recorded preferences. The valuable user research can be used during new product development and redesign. Besides positive interaction let us build trust, show authenticity, and foster loyalty: we improve with effort, communication and show.