Gibbs Sampling for (Coupled) Infinite Mixture Models in the Stick Breaking Representation

Nonparametric Bayesian approaches to clustering, information retrieval, language modeling and object recognition have recently shown great promise as a new paradigm for unsupervised data analysis. Most contributions have focused on the Dirichlet process mixture models or extensions thereof for which efficient Gibbs samplers exist. In this paper we explore Gibbs samplers for infinite complexity mixture models in the stick breaking representation. The advantage of this representation is improved modeling flexibility. For instance, one can design the prior distribution over cluster sizes or couple multiple infinite mixture models (e.g. over time) at the level of their parameters (i.e. the dependent Dirichlet process model). However, Gibbs samplers for infinite mixture models (as recently introduced in the statistics literature) seem to mix poorly over cluster labels. Among others issues, this can have the adverse effect that labels for the same cluster in coupled mixture models are mixed up. We introduce additional moves in these samplers to improve mixing over cluster labels and to bring clusters into correspondence. An application to modeling of storm trajectories is used to illustrate these ideas.Comment: Appears in Proceedings of the Twenty-Second Conference on Uncertainty in Artificial Intelligence (UAI2006

Estimating the burden of minor ailment consultations in general practices and emergency departments through retrospective review of routine data in North East Scotland

Minor ailment attendances in general practices and emergency departments (EDs) place significant burden on health care resources

'Help for hay fever', a goal-focused intervention for people with intermittent allergic rhinitis, delivered in Scottish community pharmacies: study protocol for a pilot cluster randomized controlled trial

<b>Background</b> Despite the availability of evidence-based guidelines for managing allergic rhinitis in primary care, management of the condition in the United Kingdom (UK) remains sub-optimal. Its high prevalence and negative effects on quality of life, school performance, productivity and co-morbid respiratory conditions (in particular, asthma), and high health and societal costs, make this a priority for developing novel models of care. Recent Australian research demonstrated the potential of a community pharmacy-based ‘goal-focused’ intervention to help people with intermittent allergic rhinitis to self-manage their condition better, reduce symptom severity and improve quality of life. In this pilot study we will assess the transferability of the goal-focused intervention to a UK context, the suitability of the intervention materials, procedures and outcome measures and collect data to inform a future definitive UK randomized controlled trial (RCT). <p></p> <b>Methods/design</b> A pilot cluster RCT with associated preliminary economic analysis and embedded qualitative evaluation. The pilot trial will take place in two Scottish Health Board areas: Grampian and Greater Glasgow and Clyde. Twelve community pharmacies will be randomly assigned to intervention or usual care group. Each will recruit 12 customers seeking advice or treatment for intermittent allergic rhinitis. Pharmacy staff in intervention pharmacies will support recruited customers in developing strategies for setting and achieving goals that aim to avoid/minimize triggers for, and eliminate/minimize symptoms of allergic rhinitis. Customers recruited in non-intervention pharmacies will receive usual care. The co-primary outcome measures, selected to inform a sample size calculation for a future RCT, are: community pharmacy and customer recruitment and completion rates; and effect size of change in the validated mini-Rhinoconjunctivitis Quality of Life Questionnaire between baseline, one-week and six-weeks post-intervention. Secondary outcome measures relate to changes in symptom severity, productivity, medication adherence and self-efficacy. Quantitative data about accrual, retention and economic measures, and qualitative data about participants’ experiences during the trial will be collected to inform the future RCT.<P></P> <b>Discussion</b> This work will lay the foundations for a definitive RCT of a community pharmacy-based ‘goal-focused’ self-management intervention for people with intermittent allergic rhinitis. Results of the pilot trial are expected to be available in April 2013

A cohort study of influences, health outcomes and costs of patients' health-seeking behaviour for minor ailments from primary and emergency care settings

To compare health-related and cost-related outcomes of consultations for symptoms suggestive of minor ailments in emergency departments (EDs), general practices and community pharmacies

Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC

Despite having various attractive qualities such as high prediction accuracy and the ability to quantify uncertainty and avoid over-fitting, Bayesian Matrix Factorization has not been widely adopted because of the prohibitive cost of inference. In this paper, we propose a scalable distributed Bayesian matrix factorization algorithm using stochastic gradient MCMC. Our algorithm, based on Distributed Stochastic Gradient Langevin Dynamics, can not only match the prediction accuracy of standard MCMC methods like Gibbs sampling, but at the same time is as fast and simple as stochastic gradient descent. In our experiments, we show that our algorithm can achieve the same level of prediction accuracy as Gibbs sampling an order of magnitude faster. We also show that our method reduces the prediction error as fast as distributed stochastic gradient descent, achieving a 4.1% improvement in RMSE for the Netflix dataset and an 1.8% for the Yahoo music dataset

Common polygenic risk for autism spectrum disorder (ASD) is associated with cognitive ability in the general population

Acknowledgements Generation Scotland has received core funding from the Chief Scientist Office of the Scottish Government Health Directorates CZD/16/6 and the Scottish Funding Council HR03006. We are grateful to all the families who took part, the general practitioners and the Scottish School of Primary Care for their help in recruiting them and the whole Generation Scotland team, which includes interviewers, computer and laboratory technicians, clerical workers, research scientists, volunteers, managers, receptionists, health-care assistants and nurses. We acknowledge with gratitude the financial support received for this work from the Dr Mortimer and Theresa Sackler Foundation. For the Lothian Birth Cohorts (LBC1921 and LBC1936), we thank Paul Redmond for database management assistance; Alan Gow, Martha Whiteman, Alison Pattie, Michelle Taylor, Janie Corley, Caroline Brett and Caroline Cameron for data collection and data entry; nurses and staff at the Wellcome Trust Clinical Research Facility, where blood extraction and genotyping was performed; staff at the Lothian Health Board; and the staff at the SCRE Centre, University of Glasgow. The research was supported by a program grant from Age UK (Disconnected Mind) and by grants from the Biotechnology and Biological Sciences Research Council (BBSRC). The work was undertaken by The University of Edinburgh Centre for Cognitive Ageing and Cognitive Epidemiology, part of the cross council Lifelong Health and Wellbeing Initiative (MR/K026992/1). Funding from the Medical Research Council (MRC) and BBSRC is gratefully acknowledged. DJM is an NRS Career Research Fellow funded by the CSO. BATS were funded by the Australian Research Council (A79600334, A79906588, A79801419, DP0212016, DP0664638, and DP1093900) and the National Health and Medical Research Council (389875) Australia. MKL is supported by a Perpetual Foundation Wilson Fellowship. SEM is supported by a Future Fellowship (FT110100548) from the Australian Research Council. GWM is supported by a National Health and Medical Research Council (NHMRC), Australia, Fellowship (619667). We thank the twins and siblings for their participation, Marlene Grace, Ann Eldridge and Natalie Garden for cognitive assessments, Kerrie McAloney, Daniel Park, David Smyth and Harry Beeby for research support, Anjali Henders and staff in the Molecular Epidemiology Laboratory for DNA sample processing and preparation and Scott Gordon for quality control and management of the genotypes. This work is supported by a Stragetic Award from the Wellcome Trust, reference 104036/Z/14/Z.Peer reviewedPublisher PD

The DISC1 Pathway Modulates Expression of Neurodevelopmental, Synaptogenic and Sensory Perception Genes

Genetic and biological evidence supports a role for DISC1 across a spectrum of major mental illnesses, including schizophrenia and bipolar disorder. There is evidence for genetic interplay between variants in DISC1 and in biologically interacting loci in psychiatric illness. DISC1 also associates with normal variance in behavioral and brain imaging phenotypes.Here, we analyze public domain datasets and demonstrate correlations between variants in the DISC1 pathway genes and levels of gene expression. Genetic variants of DISC1, NDE1, PDE4B and PDE4D regulate the expression of cytoskeletal, synaptogenic, neurodevelopmental and sensory perception proteins. Interestingly, these regulated genes include existing targets for drug development in depression and psychosis.Our systematic analysis provides further evidence for the relevance of the DISC1 pathway to major mental illness, identifies additional potential targets for therapeutic intervention and establishes a general strategy to mine public datasets for insights into disease pathways

Using the MitoB method to assess levels of reactive oxygen species in ecological studies of oxidative stress

In recent years evolutionary ecologists have become increasingly interested in the effects of reactive oxygen species (ROS) on the life-histories of animals. ROS levels have mostly been inferred indirectly due to the limitations of estimating ROS from in vitro methods. However, measuring ROS (hydrogen peroxide, H2O2) content in vivo is now possible using the MitoB probe. Here, we extend and refine the MitoB method to make it suitable for ecological studies of oxidative stress using the brown trout Salmo trutta as model. The MitoB method allows an evaluation of H2O2 levels in living organisms over a timescale from hours to days. The method is flexible with regard to the duration of exposure and initial concentration of the MitoB probe, and there is no transfer of the MitoB probe between fish. H2O2 levels were consistent across subsamples of the same liver but differed between muscle subsamples and between tissues of the same animal. The MitoB method provides a convenient method for measuring ROS levels in living animals over a significant period of time. Given its wide range of possible applications, it opens the opportunity to study the role of ROS in mediating life history trade-offs in ecological settings