Elm Farm Research Centre Bulletin 79 July 2005

Regular newletter from Elm Farm Research Centre (EFRC)covering research, technical and policy articles, views and comment

Interventions for behaviour change and self-management in stroke secondary prevention: protocol for an overview of reviews

Abstract Background Stroke secondary prevention guidelines recommend medication prescription and adherence, active education and behavioural counselling regarding lifestyle risk factors. To impact on recurrent vascular events, positive behaviour/s must be adopted and sustained as a lifestyle choice, requiring theoretically informed behaviour change and self-management interventions. A growing number of systematic reviews have addressed complex interventions in stroke secondary prevention. Differing terminology, inclusion criteria and overlap of studies between reviews makes the mechanism/s that affect positive change difficult to identify or replicate clinically. Adopting a two-phase approach, this overview will firstly comprehensively summarise systematic reviews in this area and secondly identify and synthesise primary studies in these reviews which provide person-centred, theoretically informed interventions for stroke secondary prevention. Methods An overview of reviews will be conducted using a systematic search strategy across the Cochrane Database of Systematic Reviews, PubMed and Epistomonikas. Inclusion criteria: systematic reviews where the population comprises individuals post-stroke or TIA and where data relating to person-centred risk reduction are synthesised for evidence of efficacy when compared to standard care or no intervention. Primary outcomes of interest include mortality, recurrent stroke and other cardiovascular events. In phase 1, two reviewers will independently (1) assess the eligibility of identified reviews for inclusion; (2) rate the quality of included reviews using the ROBIS tool; (3) identify unique primary studies and overlap between reviews; (4) summarise the published evidence supporting person-centred behavioural change and self-management interventions in stroke secondary prevention and (5) identify evidence gaps in this field. In phase 2, two independent reviewers will (1) examine person-centred, primary studies in each review using the Template for Intervention Description and Replication (TIDieR checklist), itemising, where present, theoretical frameworks underpinning interventions; (2) group studies employing theoretically informed interventions by the intervention delivered and by the outcomes reported (3) apply GRADE quality of evidence for each intervention by outcome/s identified from theoretically informed primary studies. Disagreement between reviewers at each process stage will be discussed and a third reviewer consulted. Discussion This overview will comprehensively bring together the best available evidence supporting person-centred, stroke secondary prevention strategies in an accessible format, identifying current knowledge gaps

A Rare Case of a Systemic Non-Langerhans Histiocytosis Presenting with Diabetes Insipidus and a Tentorial Mass

Introduction The histiocytoses are a group of clinically diverse diseases distinguished from one another based on the specific immunophenotype of the lesional cells, implying derivation from the same precursor cell. Langerhans cell histiocytoses (LCH) diseases stem from abnormal dendritic cell lineages, while the non-Langerhans cell histiocytoses (non-LCH) are usually derived from an abnormal monocyte/macrophage cell line.1 Non-LCH with central nervous system (CNS) involvement is predictive of poor outcome. Histopathology is used to make a diagnosis of non-LCH. Immunohistochemistry and the clinical setting are used to differentiate between the various subtypes of non-LCH.1 The non-LCH can be divided into cutaneous non-LCH, cutaneous with a major systemic component, and systemic non-LCH.1 Erdheim-Chester disease (ECD) and Rosai-Dorfman disease (RDD) are systemic non-LCH diseases. First described in 1930, ECD is characterized by xanthogranulomatous accumulations. The extent of infiltration is heterogeneous and can include skin, bones, lungs, kidneys, and the CNS. Approximately 500 cases have been reported so far.2 The majority of ECD patients harbor an activating mutation of the proto-oncogene BRAF, namely BRAF-V600E.3 Recent studies indicate CNS involvement as a predictor of highest mortality among ECD patients.4 First described in 1969, RDD is characterized by accumulation of histiocytes exhibiting emperipolesis in lymph nodes, in the head and neck or in extranodal sites. Extranodal sites include the CNS, skin, soft tissue and gastrointestinal tract. The clinical presentation is typically painless cervical lymphadenopathy with leukocytosis and a fever.5 The etiology of RDD is unknown.6 RDD with CNS involvement is rare and approximately 210 cases have been reported. CNS involvement typically lacks extracranial lymphadenopathy and resembles meningioma radiologically and clinically. 1 Select cases have demonstrated a combined presentation of ECD and RDD.2 In this report we describe a rare case presenting with headache and with clinically and pathologically overlapping features of RDD and ECD. We describe treatment and complications and review the existing literature regarding diagnosis and treatment for these rare conditions

Tissue-specific calibration of extracellular matrix material properties by transforming growth factor-beta and Runx2 in bone is required for hearing

Publisher version: http://www.nature.com/embor/journal/v11/n10/full/embor2010135.htmlDA - 20100917 IS - 1469-3178 (Electronic) IS - 1469-221X (Linking) LA - ENG PT - JOURNAL ARTICLEDA - 20100917 IS - 1469-3178 (Electronic) IS - 1469-221X (Linking) LA - ENG PT - JOURNAL ARTICLEDA - 20100917 IS - 1469-3178 (Electronic) IS - 1469-221X (Linking) LA - ENG PT - JOURNAL ARTICLEPhysical cues, such as extracellular matrix stiffness, direct cell differentiation and support tissue-specific function. Perturbation of these cues underlies diverse pathologies, including osteoarthritis, cardiovascular disease and cancer. However, the molecular mechanisms that establish tissue-specific material properties and link them to healthy tissue function are unknown. We show that Runx2, a key lineage-specific transcription factor, regulates the material properties of bone matrix through the same transforming growth factor-beta (TGFbeta)-responsive pathway that controls osteoblast differentiation. Deregulated TGFbeta or Runx2 function compromises the distinctly hard cochlear bone matrix and causes hearing loss, as seen in human cleidocranial dysplasia. In Runx2(+/-) mice, inhibition of TGFbeta signalling rescues both the material properties of the defective matrix, and hearing. This study elucidates the unknown cause of hearing loss in cleidocranial dysplasia, and demonstrates that a molecular pathway controlling cell differentiation also defines material properties of extracellular matrix. Furthermore, our results suggest that the careful regulation of these properties is essential for healthy tissue functio

Методи оцінки ризиків в інформаційній системі аналізу екологічного стану басейну малої ріки

В інформаційній системі аналізу стану басейну малої ріки запропоновано методи оцінки ризиків на основі імовірнісних та статистичних оцінок, формалізації моделі гри з природою, прогнозування процесів підтоплення земель з використанням ланцюгів Маркова, розглянуто багато критеріальні моделі ризиків.In informational and analytical system of the small rivers’ ecological condition estimation the methods of risks modelling on the basis of likelihood and statistical estimations, formalization of models of game with nature, risk modelling and forecasting processes flooded lands using Markov chains are offered, multicriteria models of risks are considered

Forecasting Player Behavioral Data and Simulating in-Game Events

Understanding player behavior is fundamental in game data science. Video games evolve as players interact with the game, so being able to foresee player experience would help to ensure a successful game development. In particular, game developers need to evaluate beforehand the impact of in-game events. Simulation optimization of these events is crucial to increase player engagement and maximize monetization. We present an experimental analysis of several methods to forecast game-related variables, with two main aims: to obtain accurate predictions of in-app purchases and playtime in an operational production environment, and to perform simulations of in-game events in order to maximize sales and playtime. Our ultimate purpose is to take a step towards the data-driven development of games. The results suggest that, even though the performance of traditional approaches such as ARIMA is still better, the outcomes of state-of-the-art techniques like deep learning are promising. Deep learning comes up as a well-suited general model that could be used to forecast a variety of time series with different dynamic behaviors