University of Tübingen

About: University of Tübingen is a education organization based out in Tübingen, Germany. It is known for research contribution in the topics: Population & Transplantation. The organization has 40555 authors who have published 84108 publications receiving 3015320 citations. The organization is also known as: Eberhard Karls University & Eberhard-Karls-Universität Tübingen.

Phylogenetic Networks: Concepts, Algorithms and Applications

Abstract: The evolutionary history of species is traditionally represented using a rooted phylogenetic tree. However, when reticulate events such as hybridization, horizontal gene transfer or recombination are believed to be involved, phylogenetic networks that can accommodate non-treelike evolution have an important role to play. This book provides the first interdisciplinary overview of phylogenetic networks. Beginning with a concise introduction to both phylogenetic trees and phylogenetic networks, the fundamental concepts and results are then presented for both rooted and unrooted phylogenetic networks. Current approaches and algorithms available for computing phylogenetic networks from different types of datasets are then discussed, accompanied by examples of their application to real biological datasets. The book also summarises the algorithms used for drawing phylogenetic networks, along with the existing software for their computation and evaluation. All datasets, examples and other additional information and links are available from the book's companion website at www.phylogenetic-networks.org.

Nomograms for predicting survival of patients with newly diagnosed glioblastoma: prognostic factor analysis of EORTC and NCIC trial 26981-22981/CE.3

Abstract: Summary Background A randomised trial published by the European Organisation for Research and Treatment of Cancer (EORTC) and the National Cancer Institute of Canada (NCIC) Clinical Trials Group (trial 26981-22981/CE.3) showed that addition of temozolomide to radiotherapy in the treatment of patients with newly diagnosed glioblastoma significantly improved survival. We aimed to undertake an exploratory subanalysis of the EORTC and NCIC data to confirm or identify new prognostic factors for survival in adult patients with glioblastoma, derive nomograms that predict an individual patient's prognosis, and suggest stratification factors for future trials. Methods Data from 573 patients with newly diagnosed glioblastoma who were randomly assigned to radiotherapy alone or to the same radiotherapy plus temozolomide in the EORTC and NCIC trial were included in this subanalysis. Survival modelling was done in three patient populations: intention-to-treat population of all randomised patients (population 1); patients assigned temozolomide and radiotherapy (population 2, n=287); and patients assigned temozolomide and radiotherapy who had assessment of MGMT promoter methylation status and who had undergone tumour resection (population 3, n=103). Cox proportional hazards models were fitted with and without O6-methylguanine-DNA methyltransferase ( MGMT ) promoter methylation status. Nomograms were developed to predict an individual patient's median and 2-year survival probabilities. No nomogram was developed in the radiotherapy-alone group because combined treatment is now the new standard of care. Findings Independent of the MGMT promoter methylation status, analysis in all randomised patients (population 1) identified combined treatment with temozolomide, more extensive tumour resection, younger age, Mini-Mental State Examination (MMSE) score of 27 or higher, and no corticosteroid treatment at baseline as independent prognostic factors correlated with improved survival outcome. In patients assigned temozolomide and radiotherapy (population 2), younger age, better performance status, more extensive tumour resection, and MMSE score of 27 or higher were associated with better survival. In patients who had tumours resected, who were assigned temozolomide and radiotherapy, and who had available MGMT promoter methylation status (population 3), methylated MGMT , better performance status, and MMSE score of 27 or higher were associated with improved survival. Nomograms were developed and are available at http://www.eortc.be/tools/gbmcalculator. Interpretation MGMT promoter methylation status, age, performance status, extent of resection, and MMSE are suggested as eligibility or stratification factors for future trials in patients with newly diagnosed glioblastoma. Stratifying by MGMT promoter methylation status should be mandatory in all glioblastoma trials that use alkylating chemotherapy. Nomograms can be used to predict an individual patient's prognosis, and they integrate pertinent molecular information that is consistent with a paradigm shift towards individualised patient management.

Biodiversity at multiple trophic levels is needed for ecosystem multifunctionality

Abstract: Many experiments have shown that loss of biodiversity reduces the capacity of ecosystems to provide the multiple services on which humans depend. However, experiments necessarily simplify the complexity of natural ecosystems and will normally control for other important drivers of ecosystem functioning, such as the environment or land use. In addition, existing studies typically focus on the diversity of single trophic groups, neglecting the fact that biodiversity loss occurs across many taxa and that the functional effects of any trophic group may depend on the abundance and diversity of others. Here we report analysis of the relationships between the species richness and abundance of nine trophic groups, including 4,600 above- and below-ground taxa, and 14 ecosystem services and functions and with their simultaneous provision (or multifunctionality) in 150 grasslands. We show that high species richness in multiple trophic groups (multitrophic richness) had stronger positive effects on ecosystem services than richness in any individual trophic group; this includes plant species richness, the most widely used measure of biodiversity. On average, three trophic groups influenced each ecosystem service, with each trophic group influencing at least one service. Multitrophic richness was particularly beneficial for 'regulating' and 'cultural' services, and for multifunctionality, whereas a change in the total abundance of species or biomass in multiple trophic groups (the multitrophic abundance) positively affected supporting services. Multitrophic richness and abundance drove ecosystem functioning as strongly as abiotic conditions and land-use intensity, extending previous experimental results to real-world ecosystems. Primary producers, herbivorous insects and microbial decomposers seem to be particularly important drivers of ecosystem functioning, as shown by the strong and frequent positive associations of their richness or abundance with multiple ecosystem services. Our results show that multitrophic richness and abundance support ecosystem functioning, and demonstrate that a focus on single groups has led to researchers to greatly underestimate the functional importance of biodiversity.

Centrality dependence of pi, K, and p production in Pb-Pb collisions at root s(NN)=2.76 TeV

Abstract: In this paper measurements are presented of pi(+/-), K-+/-, p, and (p) over bar production at midrapidity (vertical bar y vertical bar < 0.5), in Pb-Pb collisions at root s(NN) = 2.76 TeV as a function of centrality. The measurement covers the transverse-momentum (p(T)) range from 100, 200, and 300 MeV/c up to 3, 3, and 4.6 GeV/c for pi, K, and p, respectively. The measured p(T) distributions and yields are compared to expectations based on hydrodynamic, thermal and recombination models. The spectral shapes of central collisions show a stronger radial flow than measured at lower energies, which can be described in hydrodynamic models. In peripheral collisions, the p(T) distributions are not well reproduced by hydrodynamic models. Ratios of integrated particle yields are found to be nearly independent of centrality. The yield of protons normalized to pions is a factor similar to 1.5 lower than the expectation from thermal models.