University of Paris

About: University of Paris is a education organization based out in Paris, France. It is known for research contribution in the topics: Population & Transplantation. The organization has 102426 authors who have published 174180 publications receiving 5041753 citations. The organization is also known as: Sorbonne.

New class of consistent scalar-tensor theories.

Abstract: We introduce a new class of scalar-tensor theories of gravity that extend Horndeski, or " generalized galileon " , models. Despite possessing equations of motion of higher order in derivatives, we show that the true propagating degrees of freedom obey well-behaved second-order equations and are thus free from Ostrogradski instabilities, in contrast to standard lore. Remarkably, the covariant versions of the original galileon Lagrangians—obtained by direct replacement of derivatives with covariant derivatives—belong to this class of theories. These extensions of Horndeski theories exhibit an uncommon, interesting phenomenology: The scalar degree of freedom affects the speed of sound of matter, even when the latter is minimally coupled to gravity. The discovery of the present cosmological acceleration has spurred the exploration of gravitational theories that could account for this effect. Many extensions of general relativity (GR) are based on the inclusion of a scalar degree of freedom (DOF) in addition to the two ten-sor propagating modes of GR (see e.g. [1] for a review). In this context, a recent important proposal is the so-called galileon models [2], with Lagrangians that involve second-order derivatives of the scalar field and lead, nevertheless , to equations of motions of second order. Such a property guarantees the avoidance of Ostrogradski in-stabilities, i.e. of the ghost-like DOF that are usually associated with higher time derivatives (see e.g. [3]). Initially introduced in Minkowski spacetime, galileons have then been generalized to curved spacetimes [4–6], where they turn out to be equivalent to a class of theories originally constructed by Horndeski forty years ago [7]. Today, Horndeski theories, which include quintessence, k-essence and f (R) models, constitute the main theoretical framework for scalar-tensor theories, in which cosmologi-cal observations are interpreted. The purpose of this Letter is to show that this framework is not as exhaustive as generally believed, and can in fact be extended to include new Lagrangians. Indeed, having equations of motion of second order in derivatives—while indeed sufficient—is not necessary to avoid Ostrogradski instabilities, as already pointed out in e.g. [8, 9]. The theories beyond Horndeski that we propose lead to distinct observational effects and are thus fully relevant for an extensive comparison of scalar-tensor theories with observations.

Role of mutator alleles in adaptive evolution

Abstract: that the mutation rate has evolved to be as low as possible, limited only by the cost of error-avoidance and error-correction mechanisms. But up to one per cent of natural bacterial isolates are 'mutator' clones that have high mutation rates 4-6 . We consider here whether high mutation rates might play an important role in adaptive evolution. Models of large, asexual, clonal populations adapting to a new environment show that strong mutator genes (such as those that increase mutation rates by 1,000-fold) can accelerate adaptation, even if the mutator gene remains at a very low frequency (for example, 10 2 5 ). Less potent mutators (10 to 100-fold increase) can become fixed in a fraction of finite populations. The parameters of the model have been set to values typical for Escherichia coli cultures, which behave in a manner similar to the model in long-term adaptation experiments 7 . Early models of the evolution of the mutation rate were based on group selection for an optimal compromise between adaptability and adaptedness 2,3 . However, later models, incorporating mutators and antimutators (modifiers of the mutation rate) showed that a mutator can reduce individual fitness while increasing the prob- ability for an adaptive mutation to appear in the population. The prediction of these models was that a minimal mutation rate would be selected in a stable environment (reduction principle 8 ), whereas in an oscillating environment, infinite populations at equilibrium

EULAR Sjögren's syndrome disease activity index: development of a consensus systemic disease activity index for primary Sjögren's syndrome

Abstract: Objective To develop a disease activity index for patients with primary Sjogren9s syndrome (SS): the European League Against Rheumatism (EULAR) Sjogren9s syndrome disease activity index (ESSDAI). Methods Thirty-nine SS experts participated in an international collaboration, promoted by EULAR, to develop the ESSDAI. Experts identified 12 organ-specific ‘domains’ contributing to disease activity. For each domain, features of disease activity were classified in three or four levels according to their severity. Data abstracted from 96 patients with systemic complications of primary SS were used to generate 702 realistic vignettes for which all possible systemic complications were represented. Using the 0–10 physician global assessment (PhGA) scale, each expert scored the disease activity of five patient profiles and 20 realistic vignettes. Multiple regression modelling, with PhGA used as the dependent variable, was used to estimate the weight of each domain. Results All 12 domains were significantly associated with disease activity in the multivariate model, domain weights ranged from 1 to 6. The ESSDAI scores varied from 2 to 47 and were significantly correlated with PhGA for both real patient profiles and realistic vignettes (r=0.61 and r=0.58, respectively, p Conclusions The ESSDAI is a clinical index designed to measure disease activity in patients with primary SS. Once validated, such a standardised evaluation of primary SS should facilitate clinical research and be helpful as an outcome measure in clinical trials.

Cancer classification using the Immunoscore: a worldwide task force

Abstract: Prediction of clinical outcome in cancer is usually achieved by histopathological evaluation of tissue samples obtained during surgical resection of the primary tumor. Traditional tumor staging (AJCC/UICC-TNM classification) summarizes data on tumor burden (T), presence of cancer cells in draining and regional lymph nodes (N) and evidence for metastases (M). However, it is now recognized that clinical outcome can significantly vary among patients within the same stage. The current classification provides limited prognostic information, and does not predict response to therapy. Recent literature has alluded to the importance of the host immune system in controlling tumor progression. Thus, evidence supports the notion to include immunological biomarkers, implemented as a tool for the prediction of prognosis and response to therapy. Accumulating data, collected from large cohorts of human cancers, has demonstrated the impact of immune-classification, which has a prognostic value that may add to the significance of the AJCC/UICC TNM-classification. It is therefore imperative to begin to incorporate the 'Immunoscore' into traditional classification, thus providing an essential prognostic and potentially predictive tool. Introduction of this parameter as a biomarker to classify cancers, as part of routine diagnostic and prognostic assessment of tumors, will facilitate clinical decision-making including rational stratification of patient treatment. Equally, the inherent complexity of quantitative immunohistochemistry, in conjunction with protocol variation across laboratories, analysis of different immune cell types, inconsistent region selection criteria, and variable ways to quantify immune infiltration, all underline the urgent requirement to reach assay harmonization. In an effort to promote the Immunoscore in routine clinical settings, an international task force was initiated. This review represents a follow-up of the announcement of this initiative, and of the J Transl Med. editorial from January 2012. Immunophenotyping of tumors may provide crucial novel prognostic information. The results of this international validation may result in the implementation of the Immunoscore as a new component for the classification of cancer, designated TNM-I (TNM-Immune).