Multi-messenger observations of a binary neutron star merger

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

All-sky visible and near infrared space astrometry

The era of all-sky space astrometry began with the Hipparcos mission in 1989 and provided the first very accurate catalogue of apparent magnitudes, positions, parallaxes and proper motions of 120 000 bright stars at the milliarcsec (or milliarcsec per year) accuracy level. Hipparcos has now been superseded by the results of the Gaia mission. The second Gaia data release contained astrometric data for almost 1.7 billion sources with tens of microarcsec (or microarcsec per year) accuracy in a vast volume of the Milky Way and future data releases will further improve on this. Gaia has just completed its nominal 5-year mission (July 2019), but is expected to continue in operations for an extended period of an additional 5 years through to mid 2024. Its final catalogue to be released ∼ 2027, will provide astrometry for ∼ 2 billion sources, with astrometric precisions reaching 10 microarcsec. Why is accurate astrometry so important? The answer is that it provides fundamental data which underpin much of modern observational astronomy as will be detailed in this White Paper. All-sky visible and Near-InfraRed (NIR) astrometry with a wavelength cutoff in the K-band is not just focused on a single or small number of key science cases. Instead, it is extremely broad, answering key science questions in nearly every branch of astronomy while also providing a dense and accurate visible-NIR reference frame needed for future astronomy facilities

Semi-automatic algorithm for construction of the left ventricular area variation curve over a complete cardiac cycle

<p>Abstract</p> <p>Background</p> <p>Two-dimensional echocardiography (2D-echo) allows the evaluation of cardiac structures and their movements. A wide range of clinical diagnoses are based on the performance of the left ventricle. The evaluation of myocardial function is typically performed by manual segmentation of the ventricular cavity in a series of dynamic images. This process is laborious and operator dependent. The automatic segmentation of the left ventricle in 4-chamber long-axis images during diastole is troublesome, because of the opening of the mitral valve.</p> <p>Methods</p> <p>This work presents a method for segmentation of the left ventricle in dynamic 2D-echo 4-chamber long-axis images over the complete cardiac cycle. The proposed algorithm is based on classic image processing techniques, including time-averaging and wavelet-based denoising, edge enhancement filtering, morphological operations, homotopy modification, and watershed segmentation. The proposed method is semi-automatic, requiring a single user intervention for identification of the position of the mitral valve in the first temporal frame of the video sequence. Image segmentation is performed on a set of dynamic 2D-echo images collected from an examination covering two consecutive cardiac cycles.</p> <p>Results</p> <p>The proposed method is demonstrated and evaluated on twelve healthy volunteers. The results are quantitatively evaluated using four different metrics, in a comparison with contours manually segmented by a specialist, and with four alternative methods from the literature. The method's intra- and inter-operator variabilities are also evaluated.</p> <p>Conclusions</p> <p>The proposed method allows the automatic construction of the area variation curve of the left ventricle corresponding to a complete cardiac cycle. This may potentially be used for the identification of several clinical parameters, including the area variation fraction. This parameter could potentially be used for evaluating the global systolic function of the left ventricle.</p

A Catalytic Mechanism for Cysteine N-Terminal Nucleophile Hydrolases, as Revealed by Free Energy Simulations

The N-terminal nucleophile (Ntn) hydrolases are a superfamily of enzymes specialized in the hydrolytic cleavage of amide bonds. Even though several members of this family are emerging as innovative drug targets for cancer, inflammation, and pain, the processes through which they catalyze amide hydrolysis remains poorly understood. In particular, the catalytic reactions of cysteine Ntn-hydrolases have never been investigated from a mechanistic point of view. In the present study, we used free energy simulations in the quantum mechanics/molecular mechanics framework to determine the reaction mechanism of amide hydrolysis catalyzed by the prototypical cysteine Ntn-hydrolase, conjugated bile acid hydrolase (CBAH). The computational analyses, which were confirmed in water and using different CBAH mutants, revealed the existence of a chair-like transition state, which might be one of the specific features of the catalytic cycle of Ntn-hydrolases. Our results offer new insights on Ntn-mediated hydrolysis and suggest possible strategies for the creation of therapeutically useful inhibitors

Intratumoral CRH modulates immuno-escape of ovarian cancer cells through FasL regulation

Although corticotropin-releasing hormone (CRH) and Fas ligand (FasL) have been documented in ovarian carcinoma, a clear association with tumour progression and immuno-escape has not been established. FasL plays an important role in promoting tumour cells' ability to counterattack immune cells. Here, we examined immunohistochemically the expression of CRH, CRHR1, CRHR2 and FasL in 47 human ovarian cancer cases. The ovarian cancer cell lines OvCa3 and A2780 were further used to test the hypothesis that CRH might contribute to the immune privilege of ovarian tumours, by modulating FasL expression on the cancer cells. We found that CRH, CRHR1, CRHR2 and FasL were expressed in 68.1, 70.2, 63.8 and 63.8% of the cases respectively. Positivity for CRH or FasL expression was associated with higher tumour stage. Finally, CRH increased the expression of FasL in OvCa3 and A2780 cells through CRHR1 thereby potentiated their ability to induce apoptosis of activated peripheral blood lymphocytes. Corticotropin-releasing hormone produced by human ovarian cancer might favour survival and progression of the tumour by promoting its immune privilege. These findings support the hypothesis that CRHR1 antagonists could potentially be used against ovarian cancer

All-sky visible and near infrared space astrometry

AbstractThe era of all-sky space astrometry began with the Hipparcos mission in 1989 and provided the first very accurate catalogue of apparent magnitudes, positions, parallaxes and proper motions of 120 000 bright stars at the milliarcsec (or milliarcsec per year) accuracy level. Hipparcos has now been superseded by the results of the Gaia mission. The second Gaia data release contained astrometric data for almost 1.7 billion sources with tens of microarcsec (or microarcsec per year) accuracy in a vast volume of the Milky Way and future data releases will further improve on this. Gaia has just completed its nominal 5-year mission (July 2019), but is expected to continue in operations for an extended period of an additional 5 years through to mid 2024. Its final catalogue to be released $\sim$ ∼ 2027, will provide astrometry for $\sim$ ∼ 2 billion sources, with astrometric precisions reaching 10 microarcsec. Why is accurate astrometry so important? The answer is that it provides fundamental data which underpin much of modern observational astronomy as will be detailed in this White Paper. All-sky visible and Near-InfraRed (NIR) astrometry with a wavelength cutoff in the K-band is not just focused on a single or small number of key science cases. Instead, it is extremely broad, answering key science questions in nearly every branch of astronomy while also providing a dense and accurate visible-NIR reference frame needed for future astronomy facilities.</jats:p

Adopting Learning Analytics to Inform Postgraduate Curriculum Design

Part 4: Diffusion and Adoption TechnologyInternational audienceUnderstanding students’ sentiment is valuable to understanding the changes that could or should be made in curriculum design at third level. Learning analytics has shown potential for improving student learning experiences and supporting teacher inquiry. Yet, there is limited research that reports on the adoption and actual use of learning analytics to support teacher inquiry. This study captures sentiment of postgraduate students by integrating learning analytics with the steps of teacher inquiry. This study makes two important contributions to teaching and learning literature. First, it reports on the use of learning analytics to support teacher inquiry over three iterations of a business analytics programme between 2016 and 2019. Second, evidence-based recommendations on how to optimise learning analytics to support teacher inquiry are provided