Exome sequencing identifies germline variants in DIS3 in familial multiple myeloma

[Excerpt] Multiple myeloma (MM) is the third most common hematological malignancy, after Non-Hodgkin Lymphoma and Leukemia. MM is generally preceded by Monoclonal Gammopathy of Undetermined Significance (MGUS) [1], and epidemiological studies have identified older age, male gender, family history, and MGUS as risk factors for developing MM [2]. The somatic mutational landscape of sporadic MM has been increasingly investigated, aiming to identify recurrent genetic events involved in myelomagenesis. Whole exome and whole genome sequencing studies have shown that MM is a genetically heterogeneous disease that evolves through accumulation of both clonal and subclonal driver mutations [3] and identified recurrently somatically mutated genes, including KRAS, NRAS, FAM46C, TP53, DIS3, BRAF, TRAF3, CYLD, RB1 and PRDM1 [3,4,5]. Despite the fact that family-based studies have provided data consistent with an inherited genetic susceptibility to MM compatible with Mendelian transmission [6], the molecular basis of inherited MM predisposition is only partly understood. Genome-Wide Association (GWAS) studies have identified and validated 23 loci significantly associated with an increased risk of developing MM that explain ~16% of heritability [7] and only a subset of familial cases are thought to have a polygenic background [8]. Recent studies have identified rare germline variants predisposing to MM in KDM1A [9], ARID1A and USP45 [10], and the implementation of next-generation sequencing technology will allow the characterization of more such rare variants. [...]French National Cancer Institute (INCA) and the Fondation Française pour la Recherche contre le Myélome et les Gammapathies (FFMRG), the Intergroupe Francophone du Myélome (IFM), NCI R01 NCI CA167824 and a generous donation from Matthew Bell. This work was supported in part through the computational resources and staff expertise provided by Scientific Computing at the Icahn School of Medicine at Mount Sinai. Research reported in this paper was supported by the Office of Research Infrastructure of the National Institutes of Health under award number S10OD018522. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. The authors thank the Association des Malades du Myélome Multiple (AF3M) for their continued support and participation. Where authors are identified as personnel of the International Agency for Research on Cancer / World Health Organization, the authors alone are responsible for the views expressed in this article and they do not necessarily represent the decisions, policy or views of the International Agency for Research on Cancer / World Health Organizatio

Modelling human choices: MADeM and decision‑making

Research supported by FAPESP 2015/50122-0 and DFG-GRTK 1740/2. RP and AR are also part of the Research, Innovation and Dissemination Center for Neuromathematics FAPESP grant (2013/07699-0). RP is supported by a FAPESP scholarship (2013/25667-8). ACR is partially supported by a CNPq fellowship (grant 306251/2014-0)

La radio-immunothérapie associée à l'intensification thérapeutique suivie d'autogreffe dans les lymphomes malins non hodgkiniens indolents

BESANCON-BU Médecine pharmacie (250562102) / SudocSudocFranceF

Agrégation/abstraction de modèles pour l'analyse et l'organisation de réseaux de flux (application à la gestion des effluents d'élevage à La Réunion)

MONTPELLIER-SupAgro La Gaillarde (341722306) / SudocSudocFranceF

La différenciation des monocytes en macrophages et ses altérations au cours de la leucémie myélo-monocytaire chronique

BESANCON-BU Médecine pharmacie (250562102) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Environmental assessment of a biomethane production system from offshore-cultivated macroalgae

National audienc

Review on land use considerations in Life Cycle Assessment (LCA): methodological perspectives for marine ecosystems

National audienc

Using real-time model-checking tools in agricultural planning : application to livestock waste management

International audienceThis paper addresses the dynamical representation of a network made of a set of waste production units (i.e., livestock farms) needing to transfer their wastes to a set of consumption units (i.e., crops onto which wastes may be spread over). The dynamics of stocks (taken as continuous fluxes with imprecise parameters) should thus be coupled with management decisions or actions (taken as discrete events). Various temporal constraints determine the possibilities of waste transfers. These constraints, for each production or consumption unit, are modelled as a timed automaton. Possible allocation of wastes is then analysed by using model-checking techniques applied to the global timed automaton resulting from the product of all the elementary timed automata. For this, we used the Kronos software based on the Timed Computational Tree Logic (TCTL). Our approach is illustrated on the functioning of a typical farming system made of livestock and crop enterprises in the context of the Reunion Island

Abstracting continuous system behaviours into timed automata : application to diagnosis of an anaerobic digestion process

National audienceAbstracting 'continuous' system behaviours into discrete-event representations (i.e., timed automata) for diagnosis purposes is demonstrated in this paper. As complex system dynamics are often partially known, the resulting imprecision on continuous variables is represented by means of intervals partitioning the state space according to landmarks defined by expert knowledge. Based on a continuous model simulation, an algorithm assigns discrete labels to landmark crossing by continuous variables, then, generates a timed automaton that can be further analysed by a model-checker. This procedure allows one to summarize a continuous system simulation output as a set of transitions among discrete states with qualitative interpretation (e.g., high, medium, low). In order to reduce explosion in the number of states, the generated timed automaton is specifically determined according to the property of interest for the user (e.g., reachability of some unwanted states). This approach has been applied to predict possible dysfunctions of a wastewater treatment process and validated using real-life data