Covalently Labeled Fluorescent Exosomes for In Vitro and In Vivo Applications.

The vertiginous increase in the use of extracellular vesicles and especially exosomes for therapeutic applications highlights the necessity of advanced techniques for gaining a deeper knowledge of their pharmacological properties. Herein, we report a novel chemical approach for the robust attachment of commercial fluorescent dyes to the exosome surface with covalent binding. The applicability of the methodology was tested on milk and cancer cell-derived exosomes (from U87 and B16F10 cancer cells). We demonstrated that fluorescent labeling did not modify the original physicochemical properties of exosomes. We tested this nanoprobe in cell cultures and healthy mice to validate its use for in vitro and in vivo applications. We confirmed that these fluorescently labeled exosomes could be successfully visualized with optical imaging.This study was supported by the Comunidad de Madrid, projects: “Y2018/NMT-4949 (NanoLiver-CM)” and “S2017/BMD-3867 (RENIM-CM)”; it was also co-funded by the European Structural and Investment Fund. The CNIC is supported by the Instituto de Salud Carlos III (ISCIII), the Ministerio de Ciencia e Innovación (MCIN), and the Pro CNIC Foundation, and it is a Severo Ochoa Center of Excellence (SEV-2015-0505). JV was supported by grants from Instituto de Salud Carlos III (PI18/01833), co-funded by European Regional Development Fund (ERDF) and from Comunidad de Madrid, project “S2017/BMD2737 (ExoHep-CM)”, co-funded by European Structural and Investment Fund. A. Santos-Coquillat is grateful for the financial support from Ministerio de Ciencia e Innovación, Instituto de Salud Carlos III Sara Borrell Fellowship grant CD19/00136.S

Four-month incidence of suicidal thoughts and behaviors among healthcare workers after the first wave of the Spain COVID-19 pandemic

[EN] Healthcare workers (HCW) are at high risk for suicide, yet little is known about the onset of suicidal thoughts and behaviors (STB) in this important segment of the population in conjunction with the COVID-19 pandemic. We conducted a multicenter, prospective cohort study of Spanish HCW active during the COVID-9 pandemic. A total of n = 4809 HCW participated at baseline (May–September 2020; i.e., just after the first wave of the pandemic) and at a four-month follow-up assessment (October–December 2020) using web-based surveys. Logistic regression assessed the individual- and population-level associations of separate proximal (pandemic) risk factors with four-month STB incidence (i.e., 30-day STB among HCW negative for 30-day STB at baseline), each time adjusting for distal (pre-pandemic) factors. STB incidence was estimated at 4.2% (SE = 0.5; n = 1 suicide attempt). Adjusted for distal factors, proximal risk factors most strongly associated with STB incidence were various sources of interpersonal stress (scaled 0–4; odds ratio [OR] range = 1.23–1.57) followed by personal health-related stress and stress related to the health of loved ones (scaled 0–4; OR range 1.30–1.32), and the perceived lack of healthcare center preparedness (scaled 0–4; OR = 1.34). Population-attributable risk proportions for these proximal risk factors were in the range 45.3–57.6%. Other significant risk factors were financial stressors (OR range 1.26–1.81), isolation/quarantine due to COVID-19 (OR = 1.53) and having changed to a specific COVID-19 related work location (OR = 1.72). Among other interventions, our findings call for healthcare systems to implement adequate conflict communication and resolution strategies and to improve family-work balance embedded in organizational justice strategies.S

Comparison of seven prognostic tools to identify low-risk pulmonary embolism in patients aged <50 years

publishersversionPeer reviewe

Ciencias Sociales: Economía y Humanidades HANDBOOK T-I

Se presenta un breve examen de la producción y comercialización de rosa en México; un estudio en México sobre el ingreso mínimo de las familias que identifica la línea de pobreza alimentaria en el área rural del sur de México, 2012; un pequeño estudio donde hablará sobre el análisis comparado del Sector Gubernamental y la Economía Mexicana desde la perspectiva de los eslabonamientos productivos Hirshman-Rasmuss; un estudio sobre los canales de comercialización de limón persa en el municipio de Martínez de la Torre, Veracruz; una análisis del comercio estratégico en el TLCAN: El Estado en la política agrícola de biocombustibles; también se expresan acerca de la importancia de la comercialización del café en México; un diagnóstico, retos del comercio electrónico en el Sector Agroindustrial Mexicano; trabajo nos muestra y habla sobre la inversión extranjera directa y su impacto en crecimiento de México, un análisis en prospectiva: 1999-2010; un estudio acerca sobre la importancia de la Banca en México; un trabajo acerca de la competitividad de la producción agrícola en México, un análisis regional; se analizan todo acerca de el SIAL productor de quesos en Poxtla, competividad y territorio; se habla acerca de la intermediación financiera al servicio de la comunidad indígena: el fondo regional indígena Tarhiata Keri; ademas un estudio acerca de la demanda de Importaciones de durazno (Prunus pérsica L. Batsch) en México procedentes de Estados Unidos de América (1982-2011); Loera y Sepúlveda analizan los parámetros de la productividad forestal en la producción de madera en rollo; un análisis de factores sociales, ambientales y económicos del territorio rural cercano a la ciudad de México; un estudio acerca de la crisis económica mundial y su efecto sobre los flujos migratorios de América Latina; Magadán, Hernández y Escalona presentan la tipología de los sujetos sociales que intervienen en el mercado campesino de Ocotlán Oaxaca; la normalización del proceso de compostaje: una opción para desarrollar el mercado de la composta; acerca de la reestructuración del capitalismo y crisis política en México; la rentabilidad de la producción de miel en el municipio de León, Guanjuato; la economía del maíz en la región metropolitana, Chiapas, 2014; análisis de los centros de educación y cultura ambiental, necesidad de profesionalización Pedagógica de facilitadores ambientales; los Costos y competitividad de la producción del limón persa en el municipio de Martínez de la Torre, Veracruz

Ciencias Sociales: Economía y Humanidades

Este volumen I contiene 29 capítulos arbitrados que se ocupan de estos asuntos en Tópicos Selectos de Ciencias Sociales: Economía y Humanidades, elegidos de entre las contribuciones, reunimos algunos investigadores y estudiantes.Gómez, presenta un breve examen de la producción y comercialización de rosa en México; Arpi y Portillo realiza un estudio en México sobre el ingreso mínimo de las familias que identifica la línea de pobreza alimentaria en el área rural del sur de México, 2012; Bravo realiza un pequeño estudio donde hablará sobre el análisis comparado del Sector Gubernamental y la Economía Mexicana desde la perspectiva de los eslabonamientos productivos Hirshman-Rasmuss; Caamal, Pat, Jerónimo y Romero realizan un estudio sobre los canales de comercialización de limón persa en el municipio de Martínez de la Torre, Veracruz; Macías y Perales nos hablarán sobre una análisis del comercio estratégico en el TLCAN: El Estado en la política agrícola de biocombustibles; Figueroa, Pérez y Godínez se expresan acerca de la importancia de la comercialización del café en México; Sepúlveda, Sepúlveda y Pérez realizan un diagnóstico, retos del comercio electrónico en el Sector Agroindustrial Mexicano; Duana mediante su trabajo nos muestra y habla sobre la inversión extranjera directa y su impacto en crecimiento de México, un análisis en prospectiva: 1999-2010; Figueroa, Pérez y Ramírez hacen un estudio acerca sobre la importancia de la Banca en México; Pérez, Figueroa, Godínez y Pérez presenta un trabajo acerca de la competitividad de la producción agrícola en México, un análisis regional; Rodríguez, Espinosa y Márquez analizan todo acerca de el SIAL productor de quesos en Poxtla, competividad y territorio; Garza nos habla acerca de la intermediación financiera al servicio de la comunidad indígena: el fondo regional indígena Tarhiata Keri; Arroyo, Aguilar, Santoyo y Muñoz realizan un estudio acerca de la demanda de Importaciones de durazno (Prunus pérsica L. Batsch) en México procedentes de Estados Unidos de América (1982-2011); Loera y Sepúlveda analizan los parámetros de la productividad forestal en la producción de madera en rollo; Pérez, Morett y Tecpan realizan un análisis de factores sociales, ambientales y económicos del territorio rural cercano a la ciudad de México; Godínez, Figueroa y Pérez realizan un estudio acerca de la crisis económica mundial y su efecto sobre los flujos migratorios de América Latina; Magadán, Hernández y Escalona presentan la tipología de los sujetos sociales que intervienen en el mercado campesino de Ocotlán Oaxaca; Tavera y Cobos nos hablan de la normalización del proceso de compostaje: una opción para desarrollar el mercado de la composta; Piña y Pérez hablan acerca de la reestructuración del capitalismo y crisis política en México; Gonzáles, Rucoba y Ramírez realizan un estudio de la rentabilidad de la producción de miel en el municipio de León, Guanjuato; Ramírez, Gutiérrez y Figueroa realizan un estudio acerca de la economía del maíz en la región metropolitana, Chiapas, 2014; Bueno, Méndez y Cruz realizan un estudio y análisis de los centros de educación y cultura ambiental, necesidad de profesionalización Pedagógica de facilitadores ambientales; Pat, Caamal, Jerónimo y Mendoza presentan un estudio acerca de los Costos y competitividad de la producción del limón persa en el municipio de Martínez de la Torre, Veracruz. Vizuet presenta un trabajo de la construcción polisémica e histórica del concepto de la pobreza; Navarrete, Ríos y Arévalo presentan un estudio acerca de la producción ejidal de tomate rojo (Lycopersicum esculentum) en el DR-017, y su huella hídrica; Pérez y Piña hablan acerca de la productividad e inversión extranjera: La industria de Alimentos; Pérez, Figueroa, Godínez y Gómez presentan el trabajo sobre el sector primario en México; Pérez, Figueroa, Godínez y Gómez presentan acerca de los subsidios al campo como instrumento de política económica en México; Venegas, Perales y Del Valle realizan un estudio de rentabilidad de biodigestores y motogeneradores para diferentes tamaños de granjas porcinas en Michoacán

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

Development of an advanced SiPM camera for the Large Size Telescope of the Cherenkov TelescopeArray Observatory

Silicon photomultipliers (SiPMs) have become the baseline choice for cameras of the small-sized telescopes (SSTs) of the Cherenkov Telescope Array (CTA). On the other hand, SiPMs are relatively new to the field and covering large surfaces and operating at high data rates still are challenges to outperform photomultipliers (PMTs). The higher sensitivity in the near infra-red and longer signals compared to PMTs result in higher night sky background rate for SiPMs. However, the robustness of the SiPMs represents a unique opportunity to ensure long-term operation with low maintenance and better duty cycle than PMTs. The proposed camera for large size telescopes will feature 0.05 degree pixels, low power and fast front-end electronics and a fully digital readout. In this work, we present the status of dedicated simulations and data analysis for the performance estimation. The design features and the different strategies identified, so far, to tackle the demanding requirements and the improved performance are described

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

First follow-up of transient events with the CTA Large Size Telescope prototype

When very-high-energy gamma rays interact high in the Earth’s atmosphere, they produce cascades of particles that induce flashes of Cherenkov light. Imaging Atmospheric Cherenkov Telescopes (IACTs) detect these flashes and convert them into shower images that can be analyzed to extract the properties of the primary gamma ray. The dominant background for IACTs is comprised of air shower images produced by cosmic hadrons, with typical noise-to-signal ratios of several orders of magnitude. The standard technique adopted to differentiate between images initiated by gamma rays and those initiated by hadrons is based on classical machine learning algorithms, such as Random Forests, that operate on a set of handcrafted parameters extracted from the images. Likewise, the inference of the energy and the arrival direction of the primary gamma ray is performed using those parameters. State-of-the-art deep learning techniques based on convolutional neural networks (CNNs) have the potential to enhance the event reconstruction performance, since they are able to autonomously extract features from raw images, exploiting the pixel-wise information washed out during the parametrization process. Here we present the results obtained by applying deep learning techniques to the reconstruction of Monte Carlo simulated events from a single, next-generation IACT, the Large-Sized Telescope (LST) of the Cherenkov Telescope Array (CTA). We use CNNs to separate the gamma-ray-induced events from hadronic events and to reconstruct the properties of the former, comparing their performance to the standard reconstruction technique. Three independent implementations of CNN-based event reconstruction models have been utilized in this work, producing consistent results