68 research outputs found

    Superluminal motion of a relativistic jet in the neutron star merger GW170817

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    The binary neutron star merger GW170817 was accompanied by radiation across the electromagnetic spectrum and localized to the galaxy NGC 4993 at a distance of 41+/-3 Mpc. The radio and X-ray afterglows of GW170817 exhibited delayed onset, a gradual rise in the emission with time as t^0.8, a peak at about 150 days post-merger, followed by a relatively rapid decline. To date, various models have been proposed to explain the afterglow emission, including a choked-jet cocoon and a successful-jet cocoon (a.k.a. structured jet). However, the observational data have remained inconclusive as to whether GW170817 launched a successful relativistic jet. Here we show, through Very Long Baseline Interferometry, that the compact radio source associated with GW170817 exhibits superluminal motion between two epochs at 75 and 230 days post-merger. This measurement breaks the degeneracy between the models and indicates that, while the early-time radio emission was powered by a wider-angle outflow (cocoon), the late-time emission was most likely dominated by an energetic and narrowly-collimated jet, with an opening angle of <5 degrees, and observed from a viewing angle of about 20 degrees. The imaging of a collimated relativistic outflow emerging from GW170817 adds substantial weight to the growing evidence linking binary neutron star mergers and short gamma-ray bursts.Comment: 42 pages, 4 figures (main text), 2 figures (supplementary text), 2 tables. Referee and editor comments incorporate

    Assessing Recent Smoking Status by Measuring Exhaled Carbon Monoxide Levels

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    The main expectations of applying proteomics technologies to clinical questions are the discovery of disease related biomarkers. Despite technological advancement to increase proteome coverage and depth to meet these expectations the number of generated biomarkers for clinical use is small. One of the reasons is that found potential biomarkers often are false discoveries. Small sample sizes, in combination with patient sample heterogeneity increase the risk of false discoveries. To be able to extract relevant biological information from such data, high demands are put on the experimental design and the use of sensitive and quantitatively accurate technologies. The overall aim of this thesis was to apply quantitative proteomics methods for biomarker discovery in clinical samples. A method for reducing bias by controlling for individual variation in smoking habits is described in paper I. The aim of the method was objective assessment of recent smoking in clinical studies on inflammatory responses. In paper II, the proteome of alveolar macrophages obtained from smoking subjects with and without the inflammatory lung disease chronic obstructive pulmonary disease (COPD) were quantified by two-dimensional gel-electrophoresis (2-DE). A gender focused analysis showed protein level differences within the female group, with down-regulation of lysosomal pathway and up-regulation of oxidative pathway in COPD patients. Paper III, a mass spectrometry based proteomics analysis of tumour samples, contributes to the molecular understanding of vulvar squamous cell carcinoma (VSCC) and we identified a high risk patient subgroup of HPV-negative tumours based on the expression of four proteins, further suggesting that this subgroup is characterized by an altered ubiquitin-proteasome signalling pathway. Paper III describes a data analysis workflow for the extraction of biological information from quantitative mass spectrometry based proteomics data. High patient-to-patient tumour proteome variability was addressed by using pathway profiling on individual tumour data, followed by comparison of pathway association ranks in a multivariate analysis. We show that pathway data on individual tumour level can detect subpopulations of patients and identify pathways of specific importance in pre-defined clinical groups by the use of multivariate statistics. In paper IV, the potentials and limits of quantitative mass spectrometry on clinical samples was evaluated by defining the quantitative accuracy of isobaric labels and label-free quantification. Quantification by isobaric labels in combination with pI pre-fractionation showed a lower limit of quantification (LOQ) than a label-free analysis without pI pre-fractionation, and 6-plex TMT were more sensitive than 8-plex iTRAQ. Precursor mixing measured by isolation interference (MS1 interference) is more linked to the quantitative accuracy of isobaric labels than reporter ion interference (MS2 interference). Based on that we could define recommendations for how much isolation interference that can be accepted; in our data <30% isolation interference had little effect the quantitative accuracy. In conclusion, getting biological knowledge from proteomics studies requires a careful study design, control of possible confounding factors and the use of clinical data to identify disease subtypes. Further, to be able to draw conclusions from the data, the analysis requires accurate quantitative data and robust statistical tools to detect significant protein alterations. Methods around these issues are developed and discussed in this thesis

    Tracking of an electron beam through the solar corona with LOFAR

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    © ESO 2018. The Sun's activity leads to bursts of radio emission, among other phenomena. An example is type-III radio bursts. They occur frequently and appear as short-lived structures rapidly drifting from high to low frequencies in dynamic radio spectra. They are usually interpreted as signatures of beams of energetic electrons propagating along coronal magnetic field lines. Here we present novel interferometric LOFAR (LOw Frequency ARray) observations of three solar type-III radio bursts and their reverse bursts with high spectral, spatial, and temporal resolution. They are consistent with a propagation of the radio sources along the coronal magnetic field lines with nonuniform speed. Hence, the type-III radio bursts cannot be generated by a monoenergetic electron beam, but by an ensemble of energetic electrons with a spread distribution in velocity and energy. Additionally, the density profile along the propagation path is derived in the corona. It agrees well with three-fold coronal density model by (1961, ApJ, 133, 983)

    Personalized translational epilepsy research - Novel approaches and future perspectives: Part I: Clinical and network analysis approaches.

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    Despite the availability of more than 15 new "antiepileptic drugs", the proportion of patients with pharmacoresistant epilepsy has remained constant at about 20-30%. Furthermore, no disease-modifying treatments shown to prevent the development of epilepsy following an initial precipitating brain injury or to reverse established epilepsy have been identified to date. This is likely in part due to the polyetiologic nature of epilepsy, which in turn requires personalized medicine approaches. Recent advances in imaging, pathology, genetics and epigenetics have led to new pathophysiological concepts and the identification of monogenic causes of epilepsy. In the context of these advances, the First International Symposium on Personalized Translational Epilepsy Research (1st ISymPTER) was held in Frankfurt on September 8, 2016, to discuss novel approaches and future perspectives for personalized translational research. These included new developments and ideas in a range of experimental and clinical areas such as deep phenotyping, quantitative brain imaging, EEG/MEG-based analysis of network dysfunction, tissue-based translational studies, innate immunity mechanisms, microRNA as treatment targets, functional characterization of genetic variants in human cell models and rodent organotypic slice cultures, personalized treatment approaches for monogenic epilepsies, blood-brain barrier dysfunction, therapeutic focal tissue modification, computational modeling for target and biomarker identification, and cost analysis in (monogenic) disease and its treatment. This report on the meeting proceedings is aimed at stimulating much needed investments of time and resources in personalized translational epilepsy research. Part I includes the clinical phenotyping and diagnostic methods, EEG network-analysis, biomarkers, and personalized treatment approaches. In Part II, experimental and translational approaches will be discussed (Bauer et al., 2017) [1]

    Multi-messenger observations of a binary neutron star merger

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    On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

    Cell surface receptors.

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    During the past year, the database of ligand-receptor complexes has essentially doubled. These new results have immeasurably extended and expanded our view of cell surface receptor structure and function. The flood of data has revealed new models for receptor cross-linking, demonstrating the potential stringency of the extracellular requirements for the initiation of intracellular signalling and highlighting unexpected interactions suggestive of higher order clustering
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