New approaches to measuring anthelminthic drug efficacy: parasitological responses of childhood schistosome infections to treatment with praziquantel

By 2020, the global health community aims to control and eliminate human helminthiases, including schistosomiasis in selected African countries, principally by preventive chemotherapy (PCT) through mass drug administration (MDA) of anthelminthics. Quantitative monitoring of anthelminthic responses is crucial for promptly detecting changes in efficacy, potentially indicative of emerging drug resistance. Statistical models offer a powerful means to delineate and compare efficacy among individuals, among groups of individuals and among populations.; We illustrate a variety of statistical frameworks that offer different levels of inference by analysing data from nine previous studies on egg counts collected from African children before and after administration of praziquantel.; We quantify responses to praziquantel as egg reduction rates (ERRs), using different frameworks to estimate ERRs among population strata, as average responses, and within strata, as individual responses. We compare our model-based average ERRs to corresponding model-free estimates, using as reference the World Health Organization (WHO) 90 % threshold of optimal efficacy. We estimate distributions of individual responses and summarize the variation among these responses as the fraction of ERRs falling below the WHO threshold.; Generic models for evaluating responses to anthelminthics deepen our understanding of variation among populations, sub-populations and individuals. We discuss the future application of statistical modelling approaches for monitoring and evaluation of PCT programmes targeting human helminthiases in the context of the WHO 2020 control and elimination goals

Search for new phenomena in final states with an energetic jet and large missing transverse momentum in pp collisions at √ s = 8 TeV with the ATLAS detector

Results of a search for new phenomena in final states with an energetic jet and large missing transverse momentum are reported. The search uses 20.3 fb−1 of √ s = 8 TeV data collected in 2012 with the ATLAS detector at the LHC. Events are required to have at least one jet with pT > 120 GeV and no leptons. Nine signal regions are considered with increasing missing transverse momentum requirements between Emiss T > 150 GeV and Emiss T > 700 GeV. Good agreement is observed between the number of events in data and Standard Model expectations. The results are translated into exclusion limits on models with either large extra spatial dimensions, pair production of weakly interacting dark matter candidates, or production of very light gravitinos in a gauge-mediated supersymmetric model. In addition, limits on the production of an invisibly decaying Higgs-like boson leading to similar topologies in the final state are presente

Multiple novel prostate cancer susceptibility signals identified by fine-mapping of known risk loci among Europeans

Genome-wide association studies (GWAS) have identified numerous common prostate cancer (PrCa) susceptibility loci. We have fine-mapped 64 GWAS regions known at the conclusion of the iCOGS study using large-scale genotyping and imputation in 25 723 PrCa cases and 26 274 controls of European ancestry. We detected evidence for multiple independent signals at 16 regions, 12 of which contained additional newly identified significant associations. A single signal comprising a spectrum of correlated variation was observed at 39 regions; 35 of which are now described by a novel more significantly associated lead SNP, while the originally reported variant remained as the lead SNP only in 4 regions. We also confirmed two association signals in Europeans that had been previously reported only in East-Asian GWAS. Based on statistical evidence and linkage disequilibrium (LD) structure, we have curated and narrowed down the list of the most likely candidate causal variants for each region. Functional annotation using data from ENCODE filtered for PrCa cell lines and eQTL analysis demonstrated significant enrichment for overlap with bio-features within this set. By incorporating the novel risk variants identified here alongside the refined data for existing association signals, we estimate that these loci now explain ∼38.9% of the familial relative risk of PrCa, an 8.9% improvement over the previously reported GWAS tag SNPs. This suggests that a significant fraction of the heritability of PrCa may have been hidden during the discovery phase of GWAS, in particular due to the presence of multiple independent signals within the same regio

Muon reconstruction and identification efficiency in ATLAS using the full Run 2 pp collision data set at \sqrt{s}=13 TeV

This article documents the muon reconstruction and identification efficiency obtained by the ATLAS experiment for 139 \hbox {fb}^{-1} of pp collision data at \sqrt{s}=13 TeV collected between 2015 and 2018 during Run 2 of the LHC. The increased instantaneous luminosity delivered by the LHC over this period required a reoptimisation of the criteria for the identification of prompt muons. Improved and newly developed algorithms were deployed to preserve high muon identification efficiency with a low misidentification rate and good momentum resolution. The availability of large samples of Z\rightarrow \mu \mu and J/\psi \rightarrow \mu \mu decays, and the minimisation of systematic uncertainties, allows the efficiencies of criteria for muon identification, primary vertex association, and isolation to be measured with an accuracy at the per-mille level in the bulk of the phase space, and up to the percent level in complex kinematic configurations. Excellent performance is achieved over a range of transverse momenta from 3 GeV to several hundred GeV, and across the full muon detector acceptance of |\eta |<2.7

Measurement of the tt¯tt¯ production cross section in pp collisions at √s=13 TeV with the ATLAS detector

A measurement of four-top-quark production using proton-proton collision data at a centre-of-mass energy of 13 TeV collected by the ATLAS detector at the Large Hadron Collider corresponding to an integrated luminosity of 139 fb−1 is presented. Events are selected if they contain a single lepton (electron or muon) or an opposite-sign lepton pair, in association with multiple jets. The events are categorised according to the number of jets and how likely these are to contain b-hadrons. A multivariate technique is then used to discriminate between signal and background events. The measured four-top-quark production cross section is found to be 26+17−15 fb, with a corresponding observed (expected) significance of 1.9 (1.0) standard deviations over the background-only hypothesis. The result is combined with the previous measurement performed by the ATLAS Collaboration in the multilepton final state. The combined four-top-quark production cross section is measured to be 24+7−6 fb, with a corresponding observed (expected) signal significance of 4.7 (2.6) standard deviations over the background-only predictions. It is consistent within 2.0 standard deviations with the Standard Model expectation of 12.0 ± 2.4 fb

Measurements of Higgs bosons decaying to bottom quarks from vector boson fusion production with the ATLAS experiment at √=13TeV

The paper presents a measurement of the Standard Model Higgs Boson decaying to b-quark pairs in the vector boson fusion (VBF) production mode. A sample corresponding to 126 fb−1 of s√=13TeV proton–proton collision data, collected with the ATLAS experiment at the Large Hadron Collider, is analyzed utilizing an adversarial neural network for event classification. The signal strength, defined as the ratio of the measured signal yield to that predicted by the Standard Model for VBF Higgs production, is measured to be 0.95+0.38−0.36 , corresponding to an observed (expected) significance of 2.6 (2.8) standard deviations from the background only hypothesis. The results are additionally combined with an analysis of Higgs bosons decaying to b-quarks, produced via VBF in association with a photon

Search for neutral long-lived particles in pp collisions at √s = 13 TeV that decay into displaced hadronic jets in the ATLAS calorimeter

A search for decays of pair-produced neutral long-lived particles (LLPs) is presented using 139 fb−1 of proton-proton collision data collected by the ATLAS detector at the LHC in 2015–2018 at a centre-of-mass energy of 13 TeV. Dedicated techniques were developed for the reconstruction of displaced jets produced by LLPs decaying hadronically in the ATLAS hadronic calorimeter. Two search regions are defined for different LLP kinematic regimes. The observed numbers of events are consistent with the expected background, and limits for several benchmark signals are determined. For a SM Higgs boson with a mass of 125 GeV, branching ratios above 10% are excluded at 95% confidence level for values of c times LLP mean proper lifetime in the range between 20 mm and 10 m depending on the model. Upper limits are also set on the cross-section times branching ratio for scalars with a mass of 60 GeV and for masses between 200 GeV and 1 TeV. [Figure not available: see fulltext.

Performance of the upgraded PreProcessor of the ATLAS Level-1 Calorimeter Trigger

The PreProcessor of the ATLAS Level-1 Calorimeter Trigger prepares the analogue trigger signals sent from the ATLAS calorimeters by digitising, synchronising, and calibrating them to reconstruct transverse energy deposits, which are then used in further processing to identify event features. During the first long shutdown of the LHC from 2013 to 2014, the central components of the PreProcessor, the Multichip Modules, were replaced by upgraded versions that feature modern ADC and FPGA technology to ensure optimal performance in the high pile-up environment of LHC Run 2. This paper describes the features of the newMultichip Modules along with the improvements to the signal processing achieved.ANPCyTYerPhI, ArmeniaAustralian Research CouncilBMWFW, AustriaAustrian Science Fund (FWF)Azerbaijan National Academy of Sciences (ANAS)SSTC, BelarusNational Council for Scientific and Technological Development (CNPq)Fundacao de Amparo a Pesquisa do Estado de Sao Paulo (FAPESP)Natural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationNational Natural Science Foundation of China (NSFC)Departamento Administrativo de Ciencia, Tecnología e Innovación ColcienciasMinistry of Education, Youth & Sports - Czech Republic Czech Republic GovernmentCzech Republic GovernmentDNRF, DenmarkDanish Natural Science Research CouncilCentre National de la Recherche Scientifique (CNRS)CEA-DRF/IRFU, FranceFederal Ministry of Education & Research (BMBF)Max Planck SocietyGreek Ministry of Development-GSRTRGC and Hong Kong SAR, ChinaIsrael Science FoundationBenoziyo Center, IsraelIstituto Nazionale di Fisica Nucleare (INFN)Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT)Ministry of Education, Culture, Sports, Science and Technology, Japan (MEXT) Japan Society for the Promotion of ScienceCNRST, MoroccoRCN, NorwayPortuguese Foundation for Science and TechnologyMNE/IFA, RomaniaMES of RussiaMESTD, SerbiaMSSR, SlovakiaSlovenian Research Agency - SloveniaMIZS, SloveniaSpanish GovernmentSRC, SwedenWallenberg Foundation, SwedenSNSF Geneva, SwitzerlandMinistry of Science and Technology, TaiwanMinistry of Energy & Natural Resources - TurkeyScience & Technology Facilities Council (STFC)United States Department of Energy (DOE)National Science Foundation (NSF)BCKDF, CanadaCANARIE, CanadaCRC, CanadaEuropean Research Council (ERC)European Union (EU)French National Research Agency (ANR)German Research Foundation (DFG)Alexander von Humboldt FoundationGreek NSRF, GreeceBSF-NSF, IsraelGerman-Israeli Foundation for Scientific Research and DevelopmentLa Caixa Banking Foundation, SpainCERCA Programme Generalitat de Catalunya, SpainPROMETEO, SpainGenT Programmes Generalitat Valenciana, SpainGoran Gustafssons Stiftelse, SwedenRoyal Society of LondonLeverhulme TrustNRC, CanadaCERNANID, ChileChinese Academy of SciencesMinistry of Science and Technology, ChinaSRNSFG, GeorgiaHGF, GermanyNetherlands Organization for Scientific Research (NWO) Netherlands GovernmentMinistry of Science and Higher Education, PolandNCN, PolandNRCKI, Russia FederationJINRDST/NRF, South AfricaSERI, Geneva, SwitzerlandCantons of Bern and Geneva, SwitzerlandCompute Canada, CanadaHorizon 2020Marie Sklodowska-Curie ActionsEuropean Cooperation in Science and Technology (COST)EU-ESF, Greec