8 research outputs found

    Energy and Flux Measurements of Ultra-High Energy Cosmic Rays Observed During the First ANITA Flight

    Get PDF
    The first flight of the Antarctic Impulsive Transient Antenna (ANITA) experiment recorded 16 radio signals that were emitted by cosmic-ray induced air showers. For 14 of these events, this radiation was reflected from the ice. The dominant contribution to the radiation from the deflection of positrons and electrons in the geomagnetic field, which is beamed in the direction of motion of the air shower. This radiation is reflected from the ice and subsequently detected by the ANITA experiment at a flight altitude of 36km. In this paper, we estimate the energy of the 14 individual events and find that the mean energy of the cosmic-ray sample is 2.9 EeV. By simulating the ANITA flight, we calculate its exposure for ultra-high energy cosmic rays. We estimate for the first time the cosmic-ray flux derived only from radio observations. In addition, we find that the Monte Carlo simulation of the ANITA data set is in agreement with the total number of observed events and with the properties of those events.Comment: Added more explanation of the experimental setup and textual improvement

    Whole-genome sequencing reveals host factors underlying critical COVID-19

    Get PDF
    Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

    Nanoparticles from Actinobacteria: A Potential Target to Antimicrobial Therapy

    No full text
    corecore