Large variety in a panel of human colon cancer organoids in response to EZH2 inhibition

EZH2 inhibitors have gained great interest for their use as anti-cancer therapeutics. However, most research has focused on EZH2 mutant cancers and recently adverse effects of EZH2 inactivation have come to light. To determine whether colorectal cancer cells respond to EZH2 inhibition and to explore which factors influence the degree of response, we treated a panel of 20 organoid lines derived from human colon tumors with different concentrations of the EZH2 inhibitor GSK126. The resulting responses were associated with mutation status, gene expression and responses to other drugs. We found that the response to GSK126 treatment greatly varied between organoid lines. Response associated with the mutation status of ATRX and PAX2, and correlated with BIK expression. It also correlated well with response to Nutlin-3a which inhibits MDM2-p53 interaction thereby activating p53 signaling. Sensitivity to EZH2 ablation depended on the presence of wild type p53, as tumor organoids became resistant when p53 was mutated or knocked down. Our exploratory study provides insight into which genetic factors predict sensitivity to EZH2 inhibition. In addition, we show that the response to EZH2 inhibition requires wild type p53. We conclude that a subset of colorectal cancer patients may benefit from EZH2-targeting therapies

The plant traits that drive ecosystems: Evidence from three continents.

Question: A set of easily‐measured (‘soft’) plant traits has been identified as potentially useful predictors of ecosystem functioning in previous studies. Here we aimed to discover whether the screening techniques remain operational in widely contrasted circumstances, to test for the existence of axes of variation in the particular sets of traits, and to test for their links with ‘harder’ traits of proven importance to ecosystem functioning. Location: central‐western Argentina, central England, northern upland Iran, and north‐eastern Spain. Recurrent patterns of ecological specialization: Through ordination of a matrix of 640 vascular plant taxa by 12 standardized traits, we detected similar patterns of specialization in the four floras. The first PCA axis was identified as an axis of resource capture, usage and release. PCA axis 2 appeared to be a size‐related axis. Individual PCA for each country showed that the same traits remained valuable as predictors of resource capture and utilization in all of them, despite their major differences in climate, biogeography and land‐use. The results were not significantly driven by particular taxa: the main traits determining PCA axis 1 were very similar in eudicotyledons and monocotyledons and Asteraceae, Fabaceae and Poaceae. Links between recurrent suites of ‘soft’ traits and ‘hard’ traits: The validity of PCA axis 1 as a key predictor of resource capture and utilization was tested by comparisons between this axis and values of more rigorously established predictors (‘hard’ traits) for the floras of Argentina and England. PCA axis 1 was correlated with variation in relative growth rate, leaf nitrogen content, and litter decomposition rate. It also coincided with palatability to model generalist herbivores. Therefore, location on PCA axis 1 can be linked to major ecosystem processes in those habitats where the plants are dominant. Conclusion: We confirm the existence at the global scale of a major axis of evolutionary specialization, previously recognised in several local floras. This axis reflects a fundamental trade‐off between rapid acquisition of resources and conservation of resources within well‐protected tissues. These major trends of specialization were maintained across different environmental situations (including differences in the proximate causes of low productivity, i.e. drought or mineral nutrient deficiency). The trends were also consistent across floras and major phylogenetic groups, and were linked with traits directly relevant to ecosystem processes.Fil: Díaz, Sandra Myrna. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Hodgson, J.G.. The University. Department of Animal and Plant Sciences. Unit of Comparative Plant Ecology; Reino UnidoFil: Thompson, K.. The University. Department of Animal and Plant Sciences. Unit of Comparative Plant Ecology; Reino UnidoFil: Cabido, Marcelo Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Cornelissen, Johannes H. C.. Free University. Faculty Earth and Life Sciences. Department of Systems Ecology; Países BajosFil: Funes, Guillermo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Pérez Harguindeguy, Natalia. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Vendramini, Fernanda. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Falczuk, Valeria. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Zak, Marcelo Román. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Khoshnevi, M.. Research Institute of Forests and Rangelands; IránFil: Pérez Rontomé, M. C.. Instituto Pirenaico de Ecología; EspañaFil: Shirvani, F. A.. Research Institute of Forests and Rangelands; IránFil: Yazdani, S.. Research Institute of Forests and Rangelands; IránFil: Abbas Azimi, R. Research Institute of Forests and Rangelands; IránFil: Bogaard, A. The University. Department of Archaeology and Prehistory; Reino UnidoFil: Boustani, S.. Research Institute of Forests and Rangelands; IránFil: Charles, M.. The University. Department of Archaeology and Prehistory; Reino UnidoFil: Dehghan, M.. Research Institute of Forests and Rangelands; IránFil: de Torres Espuny, L.. Instituto Pirenaico de Ecología; EspañaFil: Guerrero Campo, J.. Instituto Pirenaico de Ecología; EspañaFil: Hynd, A.. The University. Department of Archaeology and Prehistory; Reino UnidoFil: Jones, G.. The University. Department of Archaeology and Prehistory; Reino UnidoFil: Kowsary, E.. Research Institute of Forests and Rangelands; Irán. Instituto Pirenaico de Ecología; EspañaFil: Kazemi Saeed, F.. Research Institute of Forests and Rangelands; IránFil: Maestro Martínez, M.. Instituto Pirenaico de Ecología; EspañaFil: Romo Diez, A.. Instituto Botanico de Barcelona; EspañaFil: Shaw, S.. Research Institute of Forests and Rangelands; Irán. The University. Department of Animal and Plant Sciences; Reino UnidoFil: Siavash, B.. Research Institute of Forests and Rangelands; IránFil: Villar Salvador, P.. Instituto Pirenaico de Ecología; Españ

Stem traits, compartments and tree species affect fungal communities on decaying wood

Dead wood quantity and quality is important for forest biodiversity, by determining wood-inhabiting fungal assemblages. We therefore evaluated how fungal communities were regulated by stem traits and compartments (i.e. bark, outer- and inner wood) of 14 common temperate tree species. Fresh logs were incubated in a common garden experiment in a forest site in the Netherlands. After 1 and 4 years of decay, the fungal composition of different compartments was assessed using Internal Transcribed Spacer amplicon sequencing. We found that fungal alpha diversity differed significantly across tree species and stem compartments, with bark showing significantly higher fungal diversity than wood. Gymnosperms and Angiosperms hold different fungal communities, and distinct fungi were found between inner wood and other compartments. Stem traits showed significant afterlife effects on fungal communities; traits associated with accessibility (e.g. conduit diameter), stem chemistry (e.g. C, N, lignin) and physical defence (e.g. density) were important factors shaping fungal community structure in decaying stems. Overall, stem traits vary substantially across stem compartments and tree species, thus regulating fungal communities and the long-term carbon dynamics of dead trees

Search for direct production of charginos and neutralinos in events with three leptons and missing transverse momentum in √s = 7 TeV pp collisions with the ATLAS detector

A search for the direct production of charginos and neutralinos in final states with three electrons or muons and missing transverse momentum is presented. The analysis is based on 4.7 fb−1 of proton–proton collision data delivered by the Large Hadron Collider and recorded with the ATLAS detector. Observations are consistent with Standard Model expectations in three signal regions that are either depleted or enriched in Z-boson decays. Upper limits at 95% confidence level are set in R-parity conserving phenomenological minimal supersymmetric models and in simplified models, significantly extending previous results

Charged-particle distributions in √s=13 TeV pp interactions measured with the ATLAS detector at the LHC

Charged-particle distributions are measured in proton–proton collisions at a centre-of-mass energy of 13 TeV, using a data sample of nearly 9 million events, corresponding to an integrated luminosity of 170 μb−1170 μb−1, recorded by the ATLAS detector during a special Large Hadron Collider fill. The charged-particle multiplicity, its dependence on transverse momentum and pseudorapidity and the dependence of the mean transverse momentum on the charged-particle multiplicity are presented. The measurements are performed with charged particles with transverse momentum greater than 500 MeV and absolute pseudorapidity less than 2.5, in events with at least one charged particle satisfying these kinematic requirements. Additional measurements in a reduced phase space with absolute pseudorapidity less than 0.8 are also presented, in order to compare with other experiments. The results are corrected for detector effects, presented as particle-level distributions and are compared to the predictions of various Monte Carlo event generators

Measurement of the View the tt production cross-section using eμ events with b-tagged jets in pp collisions at √s = 13 TeV with the ATLAS detector

This paper describes a measurement of the inclusive top quark pair production cross-section (σtt¯) with a data sample of 3.2 fb−1 of proton–proton collisions at a centre-of-mass energy of √s = 13 TeV, collected in 2015 by the ATLAS detector at the LHC. This measurement uses events with an opposite-charge electron–muon pair in the final state. Jets containing b-quarks are tagged using an algorithm based on track impact parameters and reconstructed secondary vertices. The numbers of events with exactly one and exactly two b-tagged jets are counted and used to determine simultaneously σtt¯ and the efficiency to reconstruct and b-tag a jet from a top quark decay, thereby minimising the associated systematic uncertainties. The cross-section is measured to be: σtt¯ = 818 ± 8 (stat) ± 27 (syst) ± 19 (lumi) ± 12 (beam) pb, where the four uncertainties arise from data statistics, experimental and theoretical systematic effects, the integrated luminosity and the LHC beam energy, giving a total relative uncertainty of 4.4%. The result is consistent with theoretical QCD calculations at next-to-next-to-leading order. A fiducial measurement corresponding to the experimental acceptance of the leptons is also presented

Search for strong gravity in multijet final states produced in pp collisions at √s=13 TeV using the ATLAS detector at the LHC

A search is conducted for new physics in multijet final states using 3.6 inverse femtobarns of data from proton-proton collisions at √s = 13TeV taken at the CERN Large Hadron Collider with the ATLAS detector. Events are selected containing at least three jets with scalar sum of jet transverse momenta (HT) greater than 1TeV. No excess is seen at large HT and limits are presented on new physics: models which produce final states containing at least three jets and having cross sections larger than 1.6 fb with HT > 5.8 TeV are excluded. Limits are also given in terms of new physics models of strong gravity that hypothesize additional space-time dimensions

Search for TeV-scale gravity signatures in high-mass final states with leptons and jets with the ATLAS detector at sqrt [ s ] = 13TeV

A search for physics beyond the Standard Model, in final states with at least one high transverse momentum charged lepton (electron or muon) and two additional high transverse momentum leptons or jets, is performed using 3.2 fb−1 of proton–proton collision data recorded by the ATLAS detector at the Large Hadron Collider in 2015 at √s = 13 TeV. The upper end of the distribution of the scalar sum of the transverse momenta of leptons and jets is sensitive to the production of high-mass objects. No excess of events beyond Standard Model predictions is observed. Exclusion limits are set for models of microscopic black holes with two to six extra dimensions

The performance of the jet trigger for the ATLAS detector during 2011 data taking

The performance of the jet trigger for the ATLAS detector at the LHC during the 2011 data taking period is described. During 2011 the LHC provided proton–proton collisions with a centre-of-mass energy of 7 TeV and heavy ion collisions with a 2.76 TeV per nucleon–nucleon collision energy. The ATLAS trigger is a three level system designed to reduce the rate of events from the 40 MHz nominal maximum bunch crossing rate to the approximate 400 Hz which can be written to offline storage. The ATLAS jet trigger is the primary means for the online selection of events containing jets. Events are accepted by the trigger if they contain one or more jets above some transverse energy threshold. During 2011 data taking the jet trigger was fully efficient for jets with transverse energy above 25 GeV for triggers seeded randomly at Level 1. For triggers which require a jet to be identified at each of the three trigger levels, full efficiency is reached for offline jets with transverse energy above 60 GeV. Jets reconstructed in the final trigger level and corresponding to offline jets with transverse energy greater than 60 GeV, are reconstructed with a resolution in transverse energy with respect to offline jets, of better than 4 % in the central region and better than 2.5 % in the forward direction