32 research outputs found

    Sequential inverse dysregulation of the RNA helicases DDX3X and DDX3Y facilitates MYC-driven lymphomagenesis

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    Summary DDX3X is a ubiquitously expressed RNA helicase involved in multiple stages of RNA biogenesis. DDX3X is frequently mutated in Burkitt lymphoma, but the functional basis for this is unknown. Here, we show that loss-of-function DDX3X mutations are also enriched in MYC-translocated diffuse large B cell lymphoma and reveal functional cooperation between mutant DDX3X and MYC. DDX3X promotes the translation of mRNA encoding components of the core translational machinery, thereby driving global protein synthesis. Loss-of-function DDX3X mutations moderate MYC-driven global protein synthesis, thereby buffering MYC-induced proteotoxic stress during early lymphomagenesis. Established lymphoma cells restore full protein synthetic capacity by aberrant expression of DDX3Y, a Y chromosome homolog, the expression of which is normally restricted to the testis. These findings show that DDX3X loss of function can buffer MYC-driven proteotoxic stress and highlight the capacity of male B cell lymphomas to then compensate for this loss by ectopic DDX3Y expression

    Past, present and future mathematical models for buildings (i)

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    This is the first of two articles presenting a detailed review of the historical evolution of mathematical models applied in the development of building technology, including conventional buildings and intelligent buildings. After presenting the technical differences between conventional and intelligent buildings, this article reviews the existing mathematical models, the abstract levels of these models, and their links to the literature for intelligent buildings. The advantages and limitations of the applied mathematical models are identified and the models are classified in terms of their application range and goal. We then describe how the early mathematical models, mainly physical models applied to conventional buildings, have faced new challenges for the design and management of intelligent buildings and led to the use of models which offer more flexibility to better cope with various uncertainties. In contrast with the early modelling techniques, model approaches adopted in neural networks, expert systems, fuzzy logic and genetic models provide a promising method to accommodate these complications as intelligent buildings now need integrated technologies which involve solving complex, multi-objective and integrated decision problems

    Past, present and future mathematical models for buildings (ii)

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    This article is the second part of a review of the historical evolution of mathematical models applied in the development of building technology. The first part described the current state of the art and contrasted various models with regard to the applications to conventional buildings and intelligent buildings. It concluded that mathematical techniques adopted in neural networks, expert systems, fuzzy logic and genetic models, that can be used to address model uncertainty, are well suited for modelling intelligent buildings. Despite the progress, the possible future development of intelligent buildings based on the current trends implies some potential limitations of these models. This paper attempts to uncover the fundamental limitations inherent in these models and provides some insights into future modelling directions, with special focus on the techniques of semiotics and chaos. Finally, by demonstrating an example of an intelligent building system with the mathematical models that have been developed for such a system, this review addresses the influences of mathematical models as a potential aid in developing intelligent buildings and perhaps even more advanced buildings for the future

    Interleukin 15 Levels in Serum May Predict a Severe Disease Course in Patients with Early Arthritis

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    Background: Interleukin-15 (IL-15) is thought to be involved in the physiopathological mechanisms of RA and it can be detected in the serum and the synovial fluid of inflamed joints in patients with RA but not in patients with osteoarthritis or other inflammatory joint diseases. Therefore, the objective of this work is to analyse whether serum IL-15 (sIL-15) levels serve as a biomarker of disease severity in patients with early arthritis (EA). Methodology and Results: Data from 190 patients in an EA register were analysed (77.2% female; median age 53 years; 6-month median disease duration at entry). Clinical and treatment information was recorded systematically, especially the prescription of disease modifying anti-rheumatic drugs. Two multivariate longitudinal analyses were performed with different dependent variables: 1) DAS28 and 2) a variable reflecting intensive treatment. Both included sIL-15 as predictive variable and other variables associated with disease severity, including rheumatoid factor (RF) and anti-cyclic citrullinated peptide antibodies (ACPA). Of the 171 patients (638 visits analysed) completing the follow-up, 71% suffered rheumatoid arthritis and 29% were considered as undifferentiated arthritis. Elevated sIL-15 was detected in 29% of this population and this biomarker did not overlap extensively with RF or ACPA. High sIL-15 levels (β Coefficient [95% confidence interval]: 0.12 [0.06-0.18]; p&0.001) or ACPA (0.34 [0.01-0.67]; p = 0.044) were significantly and independently associated with a higher DAS28 during follow-up, after adjusting for confounding variables such as gender, age and treatment. In addition, those patients with elevated sIL-15 had a significantly higher risk of receiving intensive treatment (RR 1.78, 95% confidence interval 1.18-2.7; p = 0.007). Conclusions: Patients with EA displaying high baseline sIL-15 suffered a more severe disease and received more intensive treatment. Thus, sIL-15 may be a biomarker for patients that are candidates for early and more intensive treatmentThe work of Belen Díaz-Sánchez was supported by the RETICS Programme (Programa de Redes Temáticas de Investigación Colaborativa [Colaborative Research Thematic Network Programme]; RD08/0075 - RIER [Red de Inflamación y Enfermedades Reumáticas; Inflammation and Rheumatic Diseases Network]) from the Instituto de Salud Carlos III, Spain (URL: www.isciii.es) within the VI National Plan for I+D+I 2008–2011 (FEDER). The work of Isidoro González-Álvaro was in part supported by a grant for the Intensification of the Research Tasks in the National Health Care System from Instituto de Salud Carlos III, Spain. The consumables for measurements and data analysis were supported by a Fondo de Investigación Sanitaria grant (08/0754) from the Instituto de Salud Carlos II
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