Fossil data support a pre-Cretaceous origin of flowering plants

Data and scripts associated with the paper. Updated version of the code will be available here: https://github.com/dsilvestro/rootBB

Addressing chemical pollution in biodiversity research

Climate change, biodiversity loss, and chemical pollution are planetary-scale emergencies requiring urgent mitigation actions. As these “triple crises” are deeply interlinked, they need to be tackled in an integrative manner. However, while climate change and biodiversity are often studied together, chemical pollution as a global change factor contributing to worldwide biodiversity loss has received much less attention in biodiversity research so far. Here, we review evidence showing that the multifaceted effects of anthropogenic chemicals in the environment are posing a growing threat to biodiversity and ecosystems. Therefore, failure to account for pollution effects may significantly undermine the success of biodiversity protection efforts. We argue that progress in understanding and counteracting the negative impact of chemical pollution on biodiversity requires collective efforts of scientists from different disciplines, including but not limited to ecology, ecotoxicology, and environmental chemistry. Importantly, recent developments in these fields have now enabled comprehensive studies that could efficiently address the manifold interactions between chemicals and ecosystems. Based on their experience with intricate studies of biodiversity, ecologists are well equipped to embrace the additional challenge of chemical complexity through interdisciplinary collaborations. This offers a unique opportunity to jointly advance a seminal frontier in pollution ecology and facilitate the development of innovative solutions for environmental protection

Statistical Workflow for Feature Selection in Human Metabolomics Data.

High-throughput metabolomics investigations, when conducted in large human cohorts, represent a potentially powerful tool for elucidating the biochemical diversity underlying human health and disease. Large-scale metabolomics data sources, generated using either targeted or nontargeted platforms, are becoming more common. Appropriate statistical analysis of these complex high-dimensional data will be critical for extracting meaningful results from such large-scale human metabolomics studies. Therefore, we consider the statistical analytical approaches that have been employed in prior human metabolomics studies. Based on the lessons learned and collective experience to date in the field, we offer a step-by-step framework for pursuing statistical analyses of cohort-based human metabolomics data, with a focus on feature selection. We discuss the range of options and approaches that may be employed at each stage of data management, analysis, and interpretation and offer guidance on the analytical decisions that need to be considered over the course of implementing a data analysis workflow. Certain pervasive analytical challenges facing the field warrant ongoing focused research. Addressing these challenges, particularly those related to analyzing human metabolomics data, will allow for more standardization of as well as advances in how research in the field is practiced. In turn, such major analytical advances will lead to substantial improvements in the overall contributions of human metabolomics investigations

Estado ácido-básico de garrotes intoxicados por amônia

Although several studies on ammonia poisoning have been carried out, there is a lack of information on acid-base balance status in ammonia-poisoned cattle. Twelve crossbred steers received intraruminally 0.5 g of urea per kg of body weight in order to induce a clinical picture of ammonia poisoning. Blood samples were collected throughout the trials in order to determine the blood ammonia, lactate, and perform blood gas analysis. All cattle presented a classical clinical picture of ammonia poisoning, with a blood ammonia concentration rising progressively from the beginning until reaching higher values at 180 min (27 ± 3 to 1719 ± 101 μmol L-1), with a similar pattern occurring with blood L-lactate levels (1.7 ± 0.3 to 26.0 ± 1.7 mmol L-1). The higher the blood ammonia concentration the higher the blood L-lactate levels (r = 0.86). All animals developed metabolic acidosis, as blood pH lowered to 7.24 0.03. The steers tried to compensate the metabolic acidosis mainly through the use of blood buffers and respiratory adjustments by lowering the pCO2 levels in the blood to 32.8 ± 2.0 mm Hg.Apesar dos diversos estudos sobre a intoxicação por amônia, ainda existe uma lacuna de informação sobre o estado do equilíbrio ácido-básico em bovinos intoxicados por amônia. Doze garrotes mestiços receberam, intrarruminalmente, 0,5 g de ureia por kg de peso vivo com a finalidade de induzir quadro clínico de intoxicação por amônia. Amostras de sangue venoso foram coletadas para determinação de amônia e lactato-L e realização de hemogasometria. Todos os animais apresentaram quadro clínico clássico de intoxicação por amônia. A concentração de amônia sanguínea elevou-se progressivamente desde o início do experimento até atingir seus valores mais elevados, após 180 min da administração da ureia (27 ± 3 to 1719 ± 101 μmol.L-1), e os teores de lactato-L apresentaram padrão similar (1,7 ± 0,3 to 26,0 ± 1,7 mmol.L-1). Quanto mais elevada foi a concentração de amônia sanguínea maior foi a concentração de lactato-L no sangue (r=0,86). Todos os animais desenvolveram acidose metabólica sendo que o pH sanguíneo diminui a valores médios de 7,24 ± 0,03. Os garrotes tentaram compensar a acidose metabólica através principalmente do uso de tampões presentes no sangue e compensação respiratória por meio da diminuição dos teores de pCO2 para valores médios de 32,8 ± 2,0 mmHg

Z boson production in Pb+Pb collisions at √Snn = 5.02 TeV measured by the ATLAS experiment

The production yield of Z bosons is measured in the electron and muon decay channels in Pb+Pb collisions at √S = 5.02 TeV with the ATLAS detector. Data from the 2015 LHC run corresponding to an integrated luminosity of 0.49 nb are used for the analysis. The Z boson yield, normalised by the total number of minimum-bias events and the mean nuclear thickness function, is measured as a function of dilepton rapidity and event centrality. The measurements in Pb+Pb collisions are compared with similar measurements made in proton-proton collisions at the same centre-of-mass energy. The nuclear modification factor is found to be consistent with unity for all centrality intervals. The results are compared with theoretical predictions obtained at next-to-leading order using nucleon and nuclear parton distribution functions. The normalised Z boson yields in Pb+Pb collisions lie 1-3σ above the predictions. The nuclear modification factor measured as a function of rapidity agrees with unity and is consistent with a next-to-leading-order QCD calculation including the isospin effect. nn -

Measurement of J/ψ production in association with a W ± boson with pp data at 8 TeV

A measurement of the production of a prompt J/ψ meson in association with a W± boson with W± → μν and J/ψ → μ+μ− is presented for J/ψ transverse momenta in the range 8.5–150 GeV and rapidity |yJ/ψ| < 2.1 using ATLAS data recorded in 2012 at the LHC. The data were taken at a proton-proton centre-of-mass energy of s = 8 TeV and correspond to an integrated luminosity of 20.3 fb−1. The ratio of the prompt J/ψ plus W± cross-section to the inclusive W± cross-section is presented as a differential measurement as a function of J/ψ transverse momenta and compared with theoretical predictions using different double-parton-scattering cross-sections. [Figure not available: see fulltext.]

Search for flavour-changing neutral currents in processes with one top quark and a photon using 81 fb−1 of pp collisions at s=13TeV with the ATLAS experiment

A search for flavour-changing neutral current (FCNC) events via the coupling of a top quark, a photon, and an up or charm quark is presented using 81 fb−1 of proton–proton collision data taken at a centre-of-mass energy of 13 TeV with the ATLAS detector at the LHC. Events with a photon, an electron or muon, a b-tagged jet, and missing transverse momentum are selected. A neural network based on kinematic variables differentiates between events from signal and background processes. The data are consistent with the background-only hypothesis, and limits are set on the strength of the tqγ coupling in an effective field theory. These are also interpreted as 95% CL upper limits on the cross section for FCNC tγ production via a left-handed (right-handed) tuγ coupling of 36 fb (78 fb) and on the branching ratio for t→γu of 2.8×10−5 (6.1×10−5). In addition, they are interpreted as 95% CL upper limits on the cross section for FCNC tγ production via a left-handed (right-handed) tcγ coupling of 40 fb (33 fb) and on the branching ratio for t→γc of 22×10−5 (18×10−5)