University of Lausanne

About: University of Lausanne is a education organization based out in Lausanne, Switzerland. It is known for research contribution in the topics: Population & Poison control. The organization has 20508 authors who have published 46458 publications receiving 1996655 citations. The organization is also known as: Université de Lausanne & UNIL.

The role of biotic interactions in shaping distributions and realised assemblages of species: implications for species distribution modelling

Abstract: Predicting which species will occur together in the future, and where, remains one of the greatest challenges in ecology, and requires a sound understanding of how the abiotic and biotic environments interact with dispersal processes and history across scales. Biotic interactions and their dynamics influence species' relationships to climate, and this also has important implications for predicting future distributions of species. It is already well accepted that biotic interactions shape species' spatial distributions at local spatial extents, but the role of these interactions beyond local extents (e.g. 10 km2 to global extents) are usually dismissed as unimportant. In this review we consolidate evidence for how biotic interactions shape species distributions beyond local extents and review methods for integrating biotic interactions into species distribution modelling tools. Drawing upon evidence from contemporary and palaeoecological studies of individual species ranges, functional groups, and species richness patterns, we show that biotic interactions have clearly left their mark on species distributions and realised assemblages of species across all spatial extents. We demonstrate this with examples from within and across trophic groups. A range of species distribution modelling tools is available to quantify species environmental relationships and predict species occurrence, such as: (i) integrating pairwise dependencies, (ii) using integrative predictors, and (iii) hybridising species distribution models (SDMs) with dynamic models. These methods have typically only been applied to interacting pairs of species at a single time, require a priori ecological knowledge about which species interact, and due to data paucity must assume that biotic interactions are constant in space and time. To better inform the future development of these models across spatial scales, we call for accelerated collection of spatially and temporally explicit species data. Ideally, these data should be sampled to reflect variation in the underlying environment across large spatial extents, and at fine spatial resolution. Simplified ecosystems where there are relatively few interacting species and sometimes a wealth of existing ecosystem monitoring data (e.g. arctic, alpine or island habitats) offer settings where the development of modelling tools that account for biotic interactions may be less difficult than elsewhere.

Activation of the NALP3 inflammasome is triggered by low intracellular potassium concentration.

Abstract: Inflammasomes are Nod-like receptor(NLR)- and caspase-1-containing cytoplasmic multiprotein complexes, which upon their assembly, process and activate the proinflammatory cytokines interleukin (IL)-1beta and IL-18. The inflammasomes harboring the NLR members NALP1, NALP3 and IPAF have been best characterized. While the IPAF inflammasome is activated by bacterial flagellin, activation of the NALP3 inflammasome is triggered not only by several microbial components, but also by a plethora of danger-associated host molecules such as uric acid. How NALP3 senses these chemically unrelated activators is not known. Here, we provide evidence that activation of NALP3, but not of the IPAF inflammasome, is blocked by inhibiting K(+) efflux from cells. Low intracellular K(+) is also a requirement for NALP1 inflammasome activation by lethal toxin of Bacillus anthracis. In vitro, NALP inflammasome assembly and caspase-1 recruitment occurs spontaneously at K(+) concentrations below 90 mM, but is prevented at higher concentrations. Thus, low intracellular K(+) may be the least common trigger of NALP-inflammasome activation.

Observation of a Narrow Charmoniumlike State in Exclusive B±→K±π+π-J/ψ Decays

Abstract: We report the observation of a narrow charmoniumlike state produced in the exclusive decay process B+/--->K+/-pi(+)pi(-)J/psi. This state, which decays into pi(+)pi(-)J/psi, has a mass of 3872.0+/-0.6(stat)+/-0.5(syst) MeV, a value that is very near the M(D0)+M(D(*0)) mass threshold. The results are based on an analysis of 152M B-Bmacr; events collected at the Upsilon(4S) resonance in the Belle detector at the KEKB collider. The signal has a statistical significance that is in excess of 10sigma.

Testing differentiation in diploid populations

Abstract: We examine the power of different exact tests of differentiation for diploid populations. Since there is not necessarily random mating within populations, the appropriate hypothesis to construct exact tests is that of independent sampling of genotypes. There are two categories of tests, Fsrestimator tests and goodness of fit tests. In this latter category, we distinguish “allelic statistics”, which account for the nature of alleles within genotypes, from “genotypic statistics” that do not. We show that the power of Fs+stimator tests and of allelic goodness of fit tests are similar when sampling is balanced, and higher than the power of genotypic goodness of fit tests. When sampling is unbalanced, the most powerful tests are shown to belong to the allelic goodness of fit group.

70-Gene Signature as an Aid to Treatment Decisions in Early-Stage Breast Cancer

Abstract: BackgroundThe 70-gene signature test (MammaPrint) has been shown to improve prediction of clinical outcome in women with early-stage breast cancer. We sought to provide prospective evidence of the clinical utility of the addition of the 70-gene signature to standard clinical–pathological criteria in selecting patients for adjuvant chemotherapy. MethodsIn this randomized, phase 3 study, we enrolled 6693 women with early-stage breast cancer and determined their genomic risk (using the 70-gene signature) and their clinical risk (using a modified version of Adjuvant! Online). Women at low clinical and genomic risk did not receive chemotherapy, whereas those at high clinical and genomic risk did receive such therapy. In patients with discordant risk results, either the genomic risk or the clinical risk was used to determine the use of chemotherapy. The primary goal was to assess whether, among patients with high-risk clinical features and a low-risk gene-expression profile who did not receive chemotherapy, the...