Jagiellonian University

About: Jagiellonian University is a education organization based out in Krakow, Poland. It is known for research contribution in the topics: Population & Catalysis. The organization has 17438 authors who have published 44092 publications receiving 862633 citations. The organization is also known as: Academia Cracoviensis & Akademia Krakowska.

Broad-spectrum antiviral GS-5734 inhibits both epidemic and zoonotic coronaviruses

Abstract: Emerging viral infections are difficult to control because heterogeneous members periodically cycle in and out of humans and zoonotic hosts, complicating the development of specific antiviral therapies and vaccines. Coronaviruses (CoVs) have a proclivity to spread rapidly into new host species causing severe disease. Severe acute respiratory syndrome CoV (SARS-CoV) and Middle East respiratory syndrome CoV (MERS-CoV) successively emerged, causing severe epidemic respiratory disease in immunologically naive human populations throughout the globe. Broad-spectrum therapies capable of inhibiting CoV infections would address an immediate unmet medical need and could be invaluable in the treatment of emerging and endemic CoV infections. We show that a nucleotide prodrug, GS-5734, currently in clinical development for treatment of Ebola virus disease, can inhibit SARS-CoV and MERS-CoV replication in multiple in vitro systems, including primary human airway epithelial cell cultures with submicromolar IC50 values. GS-5734 was also effective against bat CoVs, prepandemic bat CoVs, and circulating contemporary human CoV in primary human lung cells, thus demonstrating broad-spectrum anti-CoV activity. In a mouse model of SARS-CoV pathogenesis, prophylactic and early therapeutic administration of GS-5734 significantly reduced lung viral load and improved clinical signs of disease as well as respiratory function. These data provide substantive evidence that GS-5734 may prove effective against endemic MERS-CoV in the Middle East, circulating human CoV, and, possibly most importantly, emerging CoV of the future.

Asymmetric Dimethylarginine (ADMA): A Novel Risk Factor for Endothelial Dysfunction Its Role in Hypercholesterolemia

Abstract: Background—Asymmetric dimethylarginine (ADMA) is an endogenous competitive inhibitor of nitric oxide (NO) synthase. Because endothelial NO elaboration is impaired in hypercholesterolemia, we investigated whether plasma concentrations of ADMA are elevated in young, clinically asymptomatic hypercholesterolemic adults. We further studied whether such elevation of ADMA levels was correlated with impaired endothelium-dependent, NO-mediated vasodilation and urinary nitrate excretion. In a randomized, double-blind, placebo-controlled study, we investigated whether these changes could be reversed with exogenous l-arginine. Methods and Results—We measured plasma levels of l-arginine, ADMA, and symmetrical dimethylarginine (SDMA) by high-performance liquid chromatography in 49 hypercholesterolemic (HC) and 31 normocholesterolemic (NC) humans. In 8 HC subjects, endothelium-dependent forearm vasodilation was assessed before and after an intravenous infusion of l-arginine or placebo and compared with 8 NC control subj...

Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer

Abstract: The capacity of a neural network to absorb information is limited by its number of parameters. Conditional computation, where parts of the network are active on a per-example basis, has been proposed in theory as a way of dramatically increasing model capacity without a proportional increase in computation. In practice, however, there are significant algorithmic and performance challenges. In this work, we address these challenges and finally realize the promise of conditional computation, achieving greater than 1000x improvements in model capacity with only minor losses in computational efficiency on modern GPU clusters. We introduce a Sparsely-Gated Mixture-of-Experts layer (MoE), consisting of up to thousands of feed-forward sub-networks. A trainable gating network determines a sparse combination of these experts to use for each example. We apply the MoE to the tasks of language modeling and machine translation, where model capacity is critical for absorbing the vast quantities of knowledge available in the training corpora. We present model architectures in which a MoE with up to 137 billion parameters is applied convolutionally between stacked LSTM layers. On large language modeling and machine translation benchmarks, these models achieve significantly better results than state-of-the-art at lower computational cost.

Geometry of Quantum States: An Introduction to Quantum Entanglement

Abstract: Preface 1 Convexity, colours and statistics 2 Geometry of probability distributions 3 Much ado about spheres 4 Complex projective spaces 5 Outline of quantum mechanics 6 Coherent states and group actions 7 The stellar representation 8 The space of density matrices 9 Purification of mixed quantum states 10 Quantum operations 11 Duality: maps versus states 12 Density matrices and entropies 13 Distinguishability measures 14 Monotone metrics and measures 15 Quantum entanglement Epilogue Appendices References Index