ERIC recommendations on TP53 mutation analysis in chronic lymphocytic leukemia.

Recent evidence suggests that - in addition to 17p deletion - TP53 mutation is an independent prognostic factor in chronic lymphocytic leukemia (CLL). Data from retrospective analyses and prospective clinical trials show that ∼5% of untreated CLL patients with treatment indication have a TP53 mutation in the absence of 17p deletion. These patients have a poor response and reduced progression-free survival and overall survival with standard treatment approaches. These data suggest that TP53 mutation testing warrants integration into current diagnostic work up of patients with CLL. There are a number of assays to detect TP53 mutations, which have respective advantages and shortcomings. Direct Sanger sequencing of exons 4-9 can be recommended as a suitable test to identify TP53 mutations for centers with limited experience with alternative screening methods. Recommendations are provided on standard operating procedures, quality control, reporting and interpretation. Patients with treatment indications should be investigated for TP53 mutations in addition to the work-up recommended by the International workshop on CLL guidelines. Patients with TP53 mutation may be considered for allogeneic stem cell transplantation in first remission. Alemtuzumab-based regimens can yield a substantial proportion of complete responses, although of short duration. Ideally, patients should be treated within clinical trials exploring new therapeutic agents.

ERIC Educational Resources Information Center

ERIC is an information system sponsored by the National Institute of Education, Department of Education, United States acquires, selects, summarizes, indexes, processes and disseminates information that is generated and produced in the field of education.ERIC was founded in 1966 with the purpose of controlling and collecting the literature of education and research and technical reports, conferences, studies by commissions and committees, descriptions of projects and programs, lectures, speeches and the like.

The EMSO-ERIC Pan-European Consortium: Data Benefits and Lessons Learned as the Legal Entity Forms

The European Multidisciplinary Seafloor and water-column Observatory (EMSO) European Research Infrastructure Consortium (ERIC) provides power, communications, sensors, and data infrastructure for continuous, high-resolution, (near-)real-time, interactive ocean observations across a multidisciplinary and interdisciplinary range of research areas including biology, geology, chemistry, physics, engineering, and computer science, from polar to subtropical environments, through the water column down to the abyss. Eleven deep-sea and four shallow nodes span from the Arctic through the Atlantic and Mediterranean, to the Black Sea. Coordination among the consortium nodes is being strengthened through the EMSOdev project (H2020), which will produce the EMSO Generic Instrument Module (EGIM). Early installations are now being upgraded, for example, at the Ligurian, Ionian, Azores, and Porcupine Abyssal Plain (PAP) nodes. Significant findings have been flowing in over the years; for example, high-frequency surface and subsurface water-column measurements of the PAP node show an increase in seawater pCO2 (from 339 μatm in 2003 to 353 μatm in 2011) with little variability in the mean air-sea CO2 flux. In the Central Eastern Atlantic, the Oceanic Platform of the Canary Islands open-ocean canary node (aka ESTOC station) has a long-standing time series on water column physical, biogeochemical, and acidification processes that have contributed to the assessment efforts of the Intergovernmental Panel on Climate Change (IPCC). EMSO not only brings together countries and disciplines but also allows the pooling of resources and coordination to assemble harmonized data into a comprehensive regional ocean picture, which will then be made available to researchers and stakeholders worldwide on an open and interoperable access basis.

The 17th Annual Eric E. Williams Memorial Lecture

This flyer promotes an event for The 17th Annual Eric E.Williams Memorial Lecture, featuring the Honorable Dr. Ralph Everard Gonsalves, Prime Minister of Saint Vincent and the Grenadines. The event was held on October 23, 2015.

The 17th Annual Eric E. Williams Memorial Lecture- The US-Cuba Accord: How the Caribbean Paved the Way

This flyer promotes an event for The 17th Annual Eric E.Williams Memorial Lecture, featuring the Honorable Dr. Ralph Everard Gonsalves, Prime Minister of Saint Vincent and the Grenadines. The event was held on October 23, 2015 at the Wertheim Performing Arts Center, Florida International University.

Caracterização de Fusarium decemcellulare isolado de guaranazeiro (Paullinia cupana var. sorbilis) por meio de ERIC-PCR.

A presente pesquisa visa analisar a diversidade genética De F. decemcellulare isolado de mudas e plantas adultas de guaranazeiro com sintomas de superbrotamento, hipertrofia floral ou galhas por meio do marcador molecular ERIC-PCR.

On Ordinal VC-Dimension and Some Notions of Complexity

We generalize the classical notion of Vapnik–Chernovenkis (VC) dimension to ordinal VC-dimension, in the context of logical learning paradigms. Logical learning paradigms encompass the numerical learning paradigms commonly studied in Inductive Inference. A logical learning paradigm is defined as a set W of structures over some vocabulary, and a set D of first-order formulas that represent data. The sets of models of ϕ in W, where ϕ varies over D, generate a natural topology W over W. We show that if D is closed under boolean operators, then the notion of ordinal VC-dimension offers a perfect characterization for the problem of predicting the truth of the members of D in a member of W, with an ordinal bound on the number of mistakes. This shows that the notion of VC-dimension has a natural interpretation in Inductive Inference, when cast into a logical setting. We also study the relationships between predictive complexity, selective complexity—a variation on predictive complexity—and mind change complexity. The assumptions that D is closed under boolean operators and that W is compact often play a crucial role to establish connections between these concepts. We then consider a computable setting with effective versions of the complexity measures, and show that the equivalence between ordinal VC-dimension and predictive complexity fails. More precisely, we prove that the effective ordinal VC-dimension of a paradigm can be defined when all other effective notions of complexity are undefined. On a better note, when W is compact, all effective notions of complexity are defined, though they are not related as in the noncomputable version of the framework.