87 research outputs found

    Implications of bleaching on cnidarian venom ecology

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    Cnidarian bleaching research often focuses on the effects on a cnidarian's physiological health and fitness, whilst little focus has been towards the impacts of these events on their venom ecology. Given the importance of a cnidarian's venom to their survival and the increasing threat of bleaching events, it is important to understand the effects that this threat may have on this important aspect of their ecology as it may have unforeseen impacts on their ability to catch prey and defend themselves. This review aims to explore evidence that suggests that bleaching may impact on each of the key aspects of a cnidarians' venom ecology: cnidae, venom composition, and venom toxicity. Additionally, the resulting energy deficit, compensatory heterotrophic feeding, and increased defensive measures have been highlighted as possible ecological factors driving these changes. Suggestions are also made to guide the success of research in this field into the future, specifically in regards to selecting a study organism, the importance of accurate symbiont and cnidae identification, use of appropriate bleaching methods, determination of bleaching, and animal handling. Ultimately, this review highlights a significant and important gap in our knowledge into how cnidarians are, and will, continue to be impacted by bleaching stress

    Definition and recommendations for advance care planning: an international consensus supported by the European Association for Palliative Care

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    Advance care planning (ACP) is increasingly implemented in oncology and beyond, but a definition of ACP and recommendations concerning its use are lacking. We used a formal Delphi consensus process to help develop a definition of ACP and provide recommendations for its application. Of the 109 experts (82 from Europe, 16 from North America, and 11 from Australia) who rated the ACP definitions and its 41 recommendations, agreement for each definition or recommendation was between 68–100%. ACP was defined as the ability to enable individuals to define goals and preferences for future medical treatment and care, to discuss these goals and preferences with family and health-care providers, and to record and review these preferences if appropriate. Recommendations included the adaptation of ACP based on the readiness of the individual; targeting ACP content as the individual's health condition worsens; and, using trained non-physician facilitators to support the ACP process. We present a list of outcome measures to enable the pooling and comparison of results of ACP studies. We believe that our recommendations can provide guidance for clinical practice, ACP policy, and research

    Definition and Calculation of Bottom Quark Cross-Sections in Deep-inelastic Scattering at HERA and Determination of their Uncertainties

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    The uncertainties involved in the calculation of bottom quark cross-sections in deep-inelastic scattering at HERA are studied in different phase space regions. Besides the inclusive bottom quark cross-section, definitions closer to the detector acceptance requiring at least one high energetic muon from the semi-leptonic \bquark decay or a jet with high transverse energy are investigated. For each case the uncertainties due to the choice of the renormalisation and factorisation scale as well as the \bquark mass are estimated in the perturbative NLO QCD calculation and furthermore uncertainties in the fragmenation of the bottom quark to a B-meson and in its semi-leptonic decay are discussed

    D* Production in Deep Inelastic Scattering at HERA

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    This paper presents measurements of D^{*\pm} production in deep inelastic scattering from collisions between 27.5 GeV positrons and 820 GeV protons. The data have been taken with the ZEUS detector at HERA. The decay channel D∗+→(D0→K−π+)π+D^{*+}\to (D^0 \to K^- \pi^+) \pi^+ (+ c.c.) has been used in the study. The e+pe^+p cross section for inclusive D^{*\pm} production with 5<Q2<100GeV25<Q^2<100 GeV^2 and y<0.7y<0.7 is 5.3 \pms 1.0 \pms 0.8 nb in the kinematic region {1.3<pT(D∗±)<9.01.3<p_T(D^{*\pm})<9.0 GeV and ∣η(D∗±)∣<1.5| \eta(D^{*\pm}) |<1.5}. Differential cross sections as functions of p_T(D^{*\pm}), η(D∗±),W\eta(D^{*\pm}), W and Q2Q^2 are compared with next-to-leading order QCD calculations based on the photon-gluon fusion production mechanism. After an extrapolation of the cross section to the full kinematic region in p_T(D^{*\pm}) and η\eta(D^{*\pm}), the charm contribution F2ccˉ(x,Q2)F_2^{c\bar{c}}(x,Q^2) to the proton structure function is determined for Bjorken xx between 2 ⋅\cdot 10−4^{-4} and 5 ⋅\cdot 10−3^{-3}.Comment: 17 pages including 4 figure

    Interleukin-6 Receptor Antagonists in Critically Ill Patients with Covid-19.

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    BACKGROUND: The efficacy of interleukin-6 receptor antagonists in critically ill patients with coronavirus disease 2019 (Covid-19) is unclear. METHODS: We evaluated tocilizumab and sarilumab in an ongoing international, multifactorial, adaptive platform trial. Adult patients with Covid-19, within 24 hours after starting organ support in the intensive care unit (ICU), were randomly assigned to receive tocilizumab (8 mg per kilogram of body weight), sarilumab (400 mg), or standard care (control). The primary outcome was respiratory and cardiovascular organ support-free days, on an ordinal scale combining in-hospital death (assigned a value of -1) and days free of organ support to day 21. The trial uses a Bayesian statistical model with predefined criteria for superiority, efficacy, equivalence, or futility. An odds ratio greater than 1 represented improved survival, more organ support-free days, or both. RESULTS: Both tocilizumab and sarilumab met the predefined criteria for efficacy. At that time, 353 patients had been assigned to tocilizumab, 48 to sarilumab, and 402 to control. The median number of organ support-free days was 10 (interquartile range, -1 to 16) in the tocilizumab group, 11 (interquartile range, 0 to 16) in the sarilumab group, and 0 (interquartile range, -1 to 15) in the control group. The median adjusted cumulative odds ratios were 1.64 (95% credible interval, 1.25 to 2.14) for tocilizumab and 1.76 (95% credible interval, 1.17 to 2.91) for sarilumab as compared with control, yielding posterior probabilities of superiority to control of more than 99.9% and of 99.5%, respectively. An analysis of 90-day survival showed improved survival in the pooled interleukin-6 receptor antagonist groups, yielding a hazard ratio for the comparison with the control group of 1.61 (95% credible interval, 1.25 to 2.08) and a posterior probability of superiority of more than 99.9%. All secondary analyses supported efficacy of these interleukin-6 receptor antagonists. CONCLUSIONS: In critically ill patients with Covid-19 receiving organ support in ICUs, treatment with the interleukin-6 receptor antagonists tocilizumab and sarilumab improved outcomes, including survival. (REMAP-CAP ClinicalTrials.gov number, NCT02735707.)

    Transformer-based biomarker prediction from colorectal cancer histology: A large-scale multicentric study.

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    Deep learning (DL) can accelerate the prediction of prognostic biomarkers from routine pathology slides in colorectal cancer (CRC). However, current approaches rely on convolutional neural networks (CNNs) and have mostly been validated on small patient cohorts. Here, we develop a new transformer-based pipeline for end-to-end biomarker prediction from pathology slides by combining a pre-trained transformer encoder with a transformer network for patch aggregation. Our transformer-based approach substantially improves the performance, generalizability, data efficiency, and interpretability as compared with current state-of-the-art algorithms. After training and evaluating on a large multicenter cohort of over 13,000 patients from 16 colorectal cancer cohorts, we achieve a sensitivity of 0.99 with a negative predictive value of over 0.99 for prediction of microsatellite instability (MSI) on surgical resection specimens. We demonstrate that resection specimen-only training reaches clinical-grade performance on endoscopic biopsy tissue, solving a long-standing diagnostic problem

    Galaxy bulges and their massive black holes: a review

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    With references to both key and oft-forgotten pioneering works, this article starts by presenting a review into how we came to believe in the existence of massive black holes at the centres of galaxies. It then presents the historical development of the near-linear (black hole)-(host spheroid) mass relation, before explaining why this has recently been dramatically revised. Past disagreement over the slope of the (black hole)-(velocity dispersion) relation is also explained, and the discovery of sub-structure within the (black hole)-(velocity dispersion) diagram is discussed. As the search for the fundamental connection between massive black holes and their host galaxies continues, the competing array of additional black hole mass scaling relations for samples of predominantly inactive galaxies are presented.Comment: Invited (15 Feb. 2014) review article (submitted 16 Nov. 2014). 590 references, 9 figures, 25 pages in emulateApJ format. To appear in "Galactic Bulges", E. Laurikainen, R.F. Peletier, and D.A. Gadotti (eds.), Springer Publishin

    TRY plant trait database – enhanced coverage and open access

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    Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait‐based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives
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