Cystatin C deficiency in human atherosclerosis and aortic aneurysms

The pathogenesis of atherosclerosis and abdominal aortic aneurysm involves breakdown of the elastic laminae. Elastolytic cysteine proteases, including cathepsins S and K, are overexpressed at sites of arterial elastin damage, but whether endogenous local inhibitors counterbalance these proteases is unknown. We show here that, whereas cystatin C is normally expressed in vascular wall smooth muscle cells (SMCs), this cysteine protease inhibitor is severely reduced in both atherosclerotic and aneurysmal aortic lesions. Furthermore, increased abdominal aortic diameter among 122 patients screened by ultrasonography correlated inversely with serum cystatin C levels. In vitro, cytokine-stimulated vascular SMCs secrete cathepsins, whose elastolytic activity could be blocked when cystatin C secretion was induced by treatment with TGF-β1. The findings highlight a potentially important role for imbalance between cysteine proteases and cystatin C in arterial wall remodeling and establish that cystatin C deficiency occurs in vascular disease

Ensayo cronológico de las tobas cuaternarias del río Piedra (Cordillera Ibérica)

A preliminary absolute chronology for the Quaternary calcareous tufa deposits from the Piedra River valley (Iberian Range, NE Spain) has been carried out based on U series dating, Amino Acid Racemization, Optically Stimulated Luminescence and Radiocarbon dating techniques. Although the age uncertainties of the obtained dates are substantial, four stages of tufa accumulation correlated to MIS 9, 7-6, 5 and 1 can be distinguished. The most favourable period for tufa accumulation is located around the isotopic stage

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

Uncovering Blue Diffuse Dwarf Galaxies

Extremely metal poor (XMP) galaxies are known to be very rare, despite the large numbers of low-mass galaxies predicted by the local galaxy luminosity function. This paper presents a sub-sample of galaxies that were selected via a morphology-based search on SDSS images with the aim of finding these elusive XMP galaxies. By using the recently discovered extremely metal-poor galaxy, Leo P, as a guide, we obtained a collection of faint, blue systems, each with isolated H ii regions embedded in a diffuse continuum, that have remained undetected until now. Here we show the first results from optical spectroscopic follow-up observations of 12 of ∼100 of these blue, diffuse dwarf (BDD) galaxies yielded by our search algorithm. Oxygen abundances were obtained via the direct method for eight galaxies, and found to be in the range 7.45 < 12 + log (O/H) < 8.0, with two galaxies being classified as XMPs. All BDDs were found to currently have a young star-forming population (< 10 Myr) and rela-tively high ionisation parameters of their H ii regions. Despite their low luminosities (−11. MB. −18) and low surface brightnesses ( ∼ 23–25 mag arcsec−2), the galax-ies were found to be actively star-forming, with current star-formation rates between 0.0003 and 0.078 M yr−1. From our current subsample, BDD galaxies appear to be a population of non-quiescent dwarf irregular (dIrr) galaxies, or the diffuse counterparts to blue compact galaxies (BCDs) and as such may bridge the gap between these two populations. Our search algorithm demonstrates that morphology-based searches are successful in uncovering more diffuse metal-poor star-forming galaxies, which tradi-tional emission-line based searches overlook

Status and results of the prototype LST of CTA

The Large-Sized Telescopes (LSTs) of Cherenkov Telescope Array (CTA) are designed for gamma-ray studies focusing on low energy threshold, high flux sensitivity, rapid telescope repositioning speed and a large field of view. Once the CTA array is complete, the LSTs will be dominating the CTA performance between 20 GeV and 150 GeV. During most of the CTA Observatory construction phase, however, the LSTs will be dominating the array performance until several TeVs. In this presentation we will report on the status of the LST-1 telescope inaugurated in La Palma, Canary islands, Spain in 2018. We will show the progress of the telescope commissioning, compare the expectations with the achieved performance, and give a glance of the first physics results

Reconstruction of extensive air shower images of the Large Size Telescope prototype of CTA using a novel likelihood technique

Ground-based gamma-ray astronomy aims at reconstructing the energy and direction of gamma rays from the extensive air showers they initiate in the atmosphere. Imaging Atmospheric Cherenkov Telescopes (IACT) collect the Cherenkov light induced by secondary charged particles in extensive air showers (EAS), creating an image of the shower in a camera positioned in the focal plane of optical systems. This image is used to evaluate the type, energy and arrival direction of the primary particle that initiated the shower. This contribution shows the results of a novel reconstruction method based on likelihood maximization. The novelty with respect to previous likelihood reconstruction methods lies in the definition of a likelihood per single camera pixel, accounting not only for the total measured charge, but also for its development over time. This leads to more precise reconstruction of shower images. The method is applied to observations of the Crab Nebula acquired with the Large Size Telescope prototype (LST-1) deployed at the northern site of the Cherenkov Telescope Array

Analysis of the Cherenkov Telescope Array first Large Size Telescope real data using convolutional neural networks

The Cherenkov Telescope Array (CTA) is the future ground-based gamma-ray observatory and will be composed of two arrays of imaging atmospheric Cherenkov telescopes (IACTs) located in the Northern and Southern hemispheres respectively. The first CTA prototype telescope built on-site, the Large-Sized Telescope (LST-1), is under commissioning in La Palma and has already taken data on numerous known sources. IACTs detect the faint flash of Cherenkov light indirectly produced after a very energetic gamma-ray photon has interacted with the atmosphere and generated an atmospheric shower. Reconstruction of the characteristics of the primary photons is usually done using a parameterization up to the third order of the light distribution of the images. In order to go beyond this classical method, new approaches are being developed using state-of-the-art methods based on convolutional neural networks (CNN) to reconstruct the properties of each event (incoming direction, energy and particle type) directly from the telescope images. While promising, these methods are notoriously difficult to apply to real data due to differences (such as different levels of night sky background) between Monte Carlo (MC) data used to train the network and real data. The GammaLearn project, based on these CNN approaches, has already shown an increase in sensitivity on MC simulations for LST-1 as well as a lower energy threshold. This work applies the GammaLearn network to real data acquired by LST-1 and compares the results to the classical approach that uses random forests trained on extracted image parameters. The improvements on the background rejection, event direction, and energy reconstruction are discussed in this contribution