University of Luxembourg

About: University of Luxembourg is a education organization based out in Luxembourg, Luxembourg. It is known for research contribution in the topics: Context (language use) & Computer science. The organization has 4744 authors who have published 22175 publications receiving 381824 citations.

Estimating worldwide effects of non-pharmaceutical interventions on COVID-19 incidence and population mobility patterns using a multiple-event study.

Abstract: Various non-pharmaceutical interventions were adopted by countries worldwide in the fight against the COVID-19 pandemic with adverse socioeconomic side effects, which raises the question about their differential effectiveness. We estimate the average dynamic effect of each intervention on the incidence of COVID-19 and on people's whereabouts by developing a statistical model that accounts for the contemporaneous adoption of multiple interventions. Using daily data from 175 countries, we show that, even after controlling for other concurrent lockdown policies, cancelling public events, imposing restrictions on private gatherings and closing schools and workplaces had significant effects on reducing COVID-19 infections. Restrictions on internal movement and public transport had no effects because the aforementioned policies, imposed earlier on average, had already de facto reduced human mobility. International travel restrictions, although imposed early, had a short-lived effect failing to prevent the epidemic from turning into a pandemic because they were less stringent. We interpret the impact of each intervention on containing the pandemic using a conceptual framework which relies on their effects on human mobility behaviors in a manner consistent with time-use and epidemiological factors.

Automated workflows for accurate mass-based putative metabolite identification in LC/MS-derived metabolomic datasets

Abstract: Motivation: The study of metabolites (metabolomics) is increasingly being applied to investigate microbial, plant, environmental and mammalian systems. One of the limiting factors is that of chemically identifying metabolites from mass spectrometric signals present in complex datasets. Results: Three workflows have been developed to allow for the rapid, automated and high-throughput annotation and putative metabolite identification of electrospray LC-MS-derived metabolomic datasets. The collection of workflows are defined as PUTMEDID_LCMS and perform feature annotation, matching of accurate m/z to the accurate mass of neutral molecules and associated molecular formula and matching of the molecular formulae to a reference file of metabolites. The software is independent of the instrument and data pre-processing applied. The number of false positives is reduced by eliminating the inaccurate matching of many artifact, isotope, multiply charged and complex adduct peaks through complex interrogation of experimental data. Availability: The workflows, standard operating procedure and further information are publicly available at http://www.mcisb.org/resources/putmedid.html. Contact: warwick.dunn@manchester.ac.uk

Neurodegeneration by Activation of the Microglial Complement–Phagosome Pathway

Abstract: Systemic inflammatory reactions have been postulated to exacerbate neurodegenerative diseases via microglial activation. We now demonstrate in vivo that repeated systemic challenge of mice over four consecutive days with bacterial LPS maintained an elevated microglial inflammatory phenotype and induced loss of dopaminergic neurons in the substantia nigra. The same total cumulative LPS dose given within a single application did not induce neurodegeneration. Whole-genome transcriptome analysis of the brain demonstrated that repeated systemic LPS application induced an activation pattern involving the classical complement system and its associated phagosome pathway. Loss of dopaminergic neurons induced by repeated systemic LPS application was rescued in complement C3-deficient mice, confirming the involvement of the complement system in neurodegeneration. Our data demonstrate that a phagosomal inflammatory response of microglia is leading to complement-mediated loss of dopaminergic neurons.