Cavity-mediated coherent coupling of magnetic moments

We demonstrate the long range strong coupling of magnetostatic modes in spatially separated ferromagnets mediated by a microwave frequency cavity. Two spheres of yttrium iron garnet are embedded in the cavity and their magnetostatic modes probed using a dispersive measurement technique. We find they are strongly coupled to each other even when detuned from the cavity modes, and investigate the dependence of the magnet-magnet coupling on the cavity detuning. Dark states of the coupled magnetostatic modes of the system are observed, and ascribed to mismatches between the symmetries of the modes and the drive field.We would like to acknowledge support from Hitachi Cambridge Laboratory, EPSRC Grant No. EP/K027018/1 and ERC Grant No. 648613. A.J.F. is supported by a Hitachi Research Fellowship. A.C.D. is supported by the ARC via the Centre of Excellence in Engineered Quantum Systems (EQuS), Project No. CE110001013.This is the author accepted manuscript. The final version is available from the American Physical Society via http://dx.doi.org/10.1103/PhysRevA.93.02180

Serious Games Application for Memory Training Using Egocentric Images

Mild cognitive impairment is the early stage of several neurodegenerative diseases, such as Alzheimer's. In this work, we address the use of lifelogging as a tool to obtain pictures from a patient's daily life from an egocentric point of view. We propose to use them in combination with serious games as a way to provide a non-pharmacological treatment to improve their quality of life. To do so, we introduce a novel computer vision technique that classifies rich and non rich egocentric images and uses them in serious games. We present results over a dataset composed by 10,997 images, recorded by 7 different users, achieving 79% of F1-score. Our model presents the first method used for automatic egocentric images selection applicable to serious games.Comment: 11 page

Exploring the context of sedentary behaviour in older adults (what, where, why, when and with whom)

BACKGROUND: Older adults are the most sedentary segment of the population. Little information is available about the context of sedentary behaviour to inform guidelines and intervention. There is a dearth of information about when, where to intervene and which specific behaviours intervention should target. The aim of this exploratory study was to obtain objective information about what older adults do when sedentary, where and when they are sedentary and in what social context. METHODS: The study was a cross-sectional data collection. Older adults (Mean age = 73.25, SD ± 5.48, median = 72, IQR = 11) volunteers wore activPAL monitors and a Vicon Revue timelapse camera between 1 and 7 days. Periods of sedentary behaviour were identified using the activPAL and the context extracted from the pictures taken during these periods. Analysis of context was conducted using the Sedentary Behaviour International Taxonomy classification system. RESULTS: In total, 52 days from 36 participants were available for analysis. Participants spent 70.1 % of sedentary time at home, 56.9 % of sedentary time on their own and 46.8 % occurred in the afternoon. Seated social activities were infrequent (6.9 % of sedentary bouts) but prolonged (18 % of sedentary time). Participants appeared to frequently have vacant sitting time (41 % of non-screen sedentary time) and screen sitting was prevalent (36 % of total sedentary time). CONCLUSIONS: This study provides valuable information to inform future interventions to reduce sedentary behaviour. Interventions should consider targeting the home environment and focus on the afternoon sitting time, though this needs confirmation in a larger study. Tackling social isolation may also be a target to reduce sedentary time

Artificial intelligence for dementia drug discovery and trials optimization

Drug discovery and clinical trial design for dementia have historically been challenging. In part these challenges have arisen from patient heterogeneity, length of disease course, and the tractability of a target for the brain. Applying big data analytics and machine learning tools for drug discovery and utilizing them to inform successful clinical trial design has the potential to accelerate progress. Opportunities arise at multiple stages in the therapy pipeline and the growing availability of large medical data sets opens possibilities for big data analyses to answer key questions in clinical and therapeutic challenges. However, before this goal is reached, several challenges need to be overcome and only a multi-disciplinary approach can promote data-driven decision-making to its full potential. Herein we review the current state of machine learning applications to clinical trial design and drug discovery, while presenting opportunities and recommendations that can break down the barriers to implementation

Hepatocellular Carcinoma with Immature T-Cell (T-lymphoblastic) Proliferation

Indolent T-lymphoblastic proliferation has been rarely reported in the upper aerodigestive tract. The lymphoid cells associated with this condition have the morphological and phenotypical features of immature thymocytes. However, their pathogenesis and biology are unknown. We present an unusual type of tumor infiltrating lymphocytes in a case with hepatocellular carcinoma, presumed to be a T-lymphoblastic proliferation. A 58-yr-old female patient presented with indigestion and a palpable epigastric mass. The abdominal computed tomography revealed a mass in the S6 region of the liver. A hepatic segmentectomy was performed. Microscopic examination showed dense isolated nests of monomorphic lymphoid cells within the tumor. Immunohistochemically, the lymphoid cells were positive for CD3, terminal deoxymucleotide transferase (TdT) and CD1a. In addition, they showed dual expression of CD4 and CD8. The polymerase chain reaction used to examine the T-cell antigen receptor gamma gene rearrangement showed polyclonal T-cell proliferation. This is the second case of hepatocellular carcinoma combined with indolent T-lymphoblastic proliferation identified by an unusual tumor infiltrating lymphocytes

Use of Twitter in Neurology: Boon or Bane?

Twitter is a free, open access social media platform that is widely used in medicine by physicians, scientists, and patients. It provides an opportunity for advocacy, education, and collaboration. However, it is likely not utilized to its full advantage by many disciplines in medicine, and pitfalls exist in its use. In particular, there has not been a review of Twitter use and its applications in the field of neurology. This review seeks to provide an understanding of the current use of Twitter in the field of neurology to assist neurologists in engaging with this potentially powerful application to support their work

A systematic review on health resilience to economic crises

Background The health effects of recent economic crises differ markedly by population group. The objective of this systematic review is to examine evidence from longitudinal studies on factors influencing resilience for any health outcome or health behaviour among the general population living in countries exposed to financial crises. Methods We systematically reviewed studies from six electronic databases (EMBASE, Global Health, MEDLINE, PsycINFO, Scopus, Web of Science) which used quantitative longitudinal study designs and included: (i) exposure to an economic crisis; (ii) changes in health outcomes/behaviours over time; (iii) statistical tests of associations of health risk and/or protective factors with health outcomes/behaviours. The quality of the selected studies was appraised using the Quality Assessment Tool for Quantitative Studies. PRISMA reporting guidelines were followed. Results From 14,584 retrieved records, 22 studies met the eligibility criteria. These studies were conducted across 10 countries in Asia, Europe and North America over the past two decades. Ten socio-demographic factors that increased or protected against health risk were identified: gender, age, education, marital status, household size, employment/occupation, income/ financial constraints, personal beliefs, health status, area of residence, and social relations. These studies addressed physical health, mortality, suicide and suicide attempts, mental health, and health behaviours. Women’s mental health appeared more susceptible to crises than men’s. Lower income levels were associated with greater increases in cardiovascular disease, mortality and worse mental health. Employment status was associated with changes in mental health. Associations with age, marital status, and education were less consistent, although higher education was associated with healthier behaviours. Conclusions Despite widespread rhetoric about the importance of resilience, there was a dearth of studies which operationalised resilience factors. Future conceptual and empirical research is needed to develop the epidemiology of resilience

The effectiveness of modern cardiac rehabilitation : A systematic review of recent observational studies in non-attenders versus attenders

BACKGROUND: The beneficial effects of cardiac rehabilitation (CR) have been challenged in recent years and there is now a need to investigate whether current CR programmes, delivered in the context of modern cardiology, still benefit patients. METHODS: A systematic review of non-randomised controlled studies was conducted. Electronic searches of Medline, Embase, CINAHL, science citation index (web of science), CIRRIE and Open Grey were undertaken. Non-randomised studies investigating the effects of CR were included when recruitment occurred from the year 2000 onwards in accordance with significant CR guidance changes from the late 1990's. Adult patients diagnosed with acute myocardial infarction (AMI) were included. Non-English articles were considered. Two reviewers independently screened articles according to pre-defined selection criteria as reported in the PROSPERO database (CRD42015024021). RESULTS: Out of 2,656 articles, 8 studies involving 9,836 AMI patients were included. Studies were conducted in 6 countries. CR was found to reduce the risk of all-cause and cardiac-related mortality and improve Health-Related Quality of Life (HRQOL) significantly in at least one domain. The benefits of CR in terms of recurrent MI were inconsistent and no significant effects were found regarding re-vascularisation or re-hospitalisation following AMI. CONCLUSION: Recent observational evidence draws different conclusions to the most current reviews of trial data with respect to total mortality and re-hospitalisation, questioning the representativeness of historic data in the modern cardiological era. Future work should seek to clarify which patient and service level factors determine the likelihood of achieving improved all-cause and cardiac mortality and reduced hospital re-admissions

Sparse canonical correlation analysis for identifying, connecting and completing gene-expression networks

<p>Abstract</p> <p>Background</p> <p>We generalized penalized canonical correlation analysis for analyzing microarray gene-expression measurements for checking completeness of known metabolic pathways and identifying candidate genes for incorporation in the pathway. We used Wold's method for calculation of the canonical variates, and we applied ridge penalization to the regression of pathway genes on canonical variates of the non-pathway genes, and the elastic net to the regression of non-pathway genes on the canonical variates of the pathway genes.</p> <p>Results</p> <p>We performed a small simulation to illustrate the model's capability to identify new candidate genes to incorporate in the pathway: in our simulations it appeared that a gene was correctly identified if the correlation with the pathway genes was 0.3 or more. We applied the methods to a gene-expression microarray data set of 12, 209 genes measured in 45 patients with glioblastoma, and we considered genes to incorporate in the glioma-pathway: we identified more than 25 genes that correlated > 0.9 with canonical variates of the pathway genes.</p> <p>Conclusion</p> <p>We concluded that penalized canonical correlation analysis is a powerful tool to identify candidate genes in pathway analysis.</p