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

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

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

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

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

A Vast Thin Plane of Co-rotating Dwarf Galaxies Orbiting the Andromeda Galaxy

Dwarf satellite galaxies are thought to be the remnants of the population of primordial structures that coalesced to form giant galaxies like the Milky Way. An early analysis noted that dwarf galaxies may not be isotropically distributed around our Galaxy, as several are correlated with streams of HI emission, and possibly form co-planar groups. These suspicions are supported by recent analyses, and it has been claimed that the apparently planar distribution of satellites is not predicted within standard cosmology, and cannot simply represent a memory of past coherent accretion. However, other studies dispute this conclusion. Here we report the existence (99.998% significance) of a planar sub-group of satellites in the Andromeda galaxy, comprising approximately 50% of the population. The structure is vast: at least 400 kpc in diameter, but also extremely thin, with a perpendicular scatter <14.1 kpc (99% confidence). Radial velocity measurements reveal that the satellites in this structure have the same sense of rotation about their host. This finding shows conclusively that substantial numbers of dwarf satellite galaxies share the same dynamical orbital properties and direction of angular momentum, a new insight for our understanding of the origin of these most dark matter dominated of galaxies. Intriguingly, the plane we identify is approximately aligned with the pole of the Milky Way's disk and is co-planar with the Milky Way to Andromeda position vector. The existence of such extensive coherent kinematic structures within the halos of massive galaxies is a fact that must be explained within the framework of galaxy formation and cosmology.Comment: Published in the 3rd Jan 2013 issue of Nature. 19 pages, 4 figures, 1 three-dimensional interactive figure. To view and manipulate the 3-D figure, an Adobe Reader browser plug-in is required; alternatively save to disk and view with Adobe Reade

Characterizing genomic alterations in cancer by complementary functional associations.

Systematic efforts to sequence the cancer genome have identified large numbers of mutations and copy number alterations in human cancers. However, elucidating the functional consequences of these variants, and their interactions to drive or maintain oncogenic states, remains a challenge in cancer research. We developed REVEALER, a computational method that identifies combinations of mutually exclusive genomic alterations correlated with functional phenotypes, such as the activation or gene dependency of oncogenic pathways or sensitivity to a drug treatment. We used REVEALER to uncover complementary genomic alterations associated with the transcriptional activation of β-catenin and NRF2, MEK-inhibitor sensitivity, and KRAS dependency. REVEALER successfully identified both known and new associations, demonstrating the power of combining functional profiles with extensive characterization of genomic alterations in cancer genomes

High Energy Neutrinos from Quasars

We review and clarify the assumptions of our basic model for neutrino production in the cores of quasars, as well as those modifications to the model subsequently made by other workers. We also present a revised estimate of the neutrino background flux and spectrum obtained using more recent empirical studies of quasars and their evolution. We compare our results with other thoeretical calculations and experimental upper limits on the AGN neutrino background flux. We also estimate possible neutrino fluxes from the jets of blazars detected recently by the EGRET experiment on the Compton Gamma Ray Observatory. We discuss the theoretical implications of these estimates.Comment: 14 pg., ps file (includes figures), To be published in Space Science Review

Discovery and saturation analysis of cancer genes across 21 tumour types

Although a few cancer genes are mutated in a high proportion of tumours of a given type (>20%), most are mutated at intermediate frequencies (2–20%). To explore the feasibility of creating a comprehensive catalogue of cancer genes, we analysed somatic point mutations in exome sequences from 4,742 human cancers and their matched normal-tissue samples across 21 cancer types. We found that large-scale genomic analysis can identify nearly all known cancer genes in these tumour types. Our analysis also identified 33 genes that were not previously known to be significantly mutated in cancer, including genes related to proliferation, apoptosis, genome stability, chromatin regulation, immune evasion, RNA processing and protein homeostasis. Down-sampling analysis indicates that larger sample sizes will reveal many more genes mutated at clinically important frequencies. We estimate that near-saturation may be achieved with 600–5,000 samples per tumour type, depending on background mutation frequency. The results may help to guide the next stage of cancer genomics