STAT4 deficiency reduces obesity-induced insulin resistance and adipose tissue inflammation

Signal transducer and activator of transcription (STAT) 4 is one of the seven members of the STAT family. STAT4 has a prominent role in mediating interleukin-12-induced T-helper cell type 1 lineage differentiation. T cells are key players in the maintenance of adipose tissue (AT) inflammation. The role of STAT4 in obesity and AT inflammation is unknown. We sought to determine the role of STAT4 in AT inflammation in obesity-induced insulin resistance. We studied STAT4-null mice on the C57Bl6/J background. We have found that STAT4(-/-)C57Bl6/J mice develop high-fat diet-induced obesity (DIO) similar to wild-type controls, but that they have significantly improved insulin sensitivity and better glucose tolerance. Using flow cytometry and real-time PCR, we show that STAT4(-/-) mice with DIO produce significantly reduced numbers of inflammatory cytokines and chemokines in adipocytes, have reduced numbers of CD8(+) cells, and display increased alternative (M2) macrophage polarization. CD8(+) cells, but not CD4(+) cells, from STAT4(-/-) mice displayed reduced in vitro migration. Also, we found that adipocyte inflammation is reduced and insulin signaling is improved in STAT4(-/-) mice with DIO. We have identified STAT4 as a key contributor to insulin resistance and AT inflammation in DIO. Targeting STAT4 activation could be a novel approach to reducing AT inflammation and insulin resistance in obesity

Improving Photoelectron Counting and Particle Identification in Scintillation Detectors with Bayesian Techniques

Many current and future dark matter and neutrino detectors are designed to measure scintillation light with a large array of photomultiplier tubes (PMTs). The energy resolution and particle identification capabilities of these detectors depend in part on the ability to accurately identify individual photoelectrons in PMT waveforms despite large variability in pulse amplitudes and pulse pileup. We describe a Bayesian technique that can identify the times of individual photoelectrons in a sampled PMT waveform without deconvolution, even when pileup is present. To demonstrate the technique, we apply it to the general problem of particle identification in single-phase liquid argon dark matter detectors. Using the output of the Bayesian photoelectron counting algorithm described in this paper, we construct several test statistics for rejection of backgrounds for dark matter searches in argon. Compared to simpler methods based on either observed charge or peak finding, the photoelectron counting technique improves both energy resolution and particle identification of low energy events in calibration data from the DEAP-1 detector and simulation of the larger MiniCLEAN dark matter detector.Comment: 16 pages, 16 figure

In-situ characterization of the Hamamatsu R5912-HQE photomultiplier tubes used in the DEAP-3600 experiment

The Hamamatsu R5912-HQE photomultiplier-tube (PMT) is a novel high-quantum efficiency PMT. It is currently used in the DEAP-3600 dark matter detector and is of significant interest for future dark matter and neutrino experiments where high signal yields are needed. We report on the methods developed for in-situ characterization and monitoring of DEAP's 255 R5912-HQE PMTs. This includes a detailed discussion of typical measured single-photoelectron charge distributions, correlated noise (afterpulsing), dark noise, double, and late pulsing characteristics. The characterization is performed during the detector commissioning phase using laser light injected through a light diffusing sphere and during normal detector operation using LED light injected through optical fibres

Measurement of the scintillation time spectra and pulse-shape discrimination of low-energy beta and nuclear recoils in liquid argon with DEAP-1

The DEAP-1 low-background liquid argon detector was used to measure scintillation pulse shapes of electron and nuclear recoil events and to demonstrate the feasibility of pulse-shape discrimination (PSD) down to an electron-equivalent energy of 20 keV. In the surface dataset using a triple-coincidence tag we found the fraction of beta events that are misidentified as nuclear recoils to be $<1.4\times 10^{-7}$ (90% C.L.) for energies between 43-86 keVee and for a nuclear recoil acceptance of at least 90%, with 4% systematic uncertainty on the absolute energy scale. The discrimination measurement on surface was limited by nuclear recoils induced by cosmic-ray generated neutrons. This was improved by moving the detector to the SNOLAB underground laboratory, where the reduced background rate allowed the same measurement with only a double-coincidence tag. The combined data set contains $1.23\times10^8$ events. One of those, in the underground data set, is in the nuclear-recoil region of interest. Taking into account the expected background of 0.48 events coming from random pileup, the resulting upper limit on the electronic recoil contamination is $<2.7\times10^{-8}$ (90% C.L.) between 44-89 keVee and for a nuclear recoil acceptance of at least 90%, with 6% systematic uncertainty on the absolute energy scale. We developed a general mathematical framework to describe PSD parameter distributions and used it to build an analytical model of the distributions observed in DEAP-1. Using this model, we project a misidentification fraction of approx. $10^{-10}$ for an electron-equivalent energy threshold of 15 keV for a detector with 8 PE/keVee light yield. This reduction enables a search for spin-independent scattering of WIMPs from 1000 kg of liquid argon with a WIMP-nucleon cross-section sensitivity of $10^{-46}$ cm$^2$, assuming negligible contribution from nuclear recoil backgrounds.Comment: Accepted for publication in Astroparticle Physic

Design and construction of the DEAP-3600 dark matter detector

The Dark matter Experiment using Argon Pulse-shape discrimination (DEAP) has been designed for a direct detection search for particle dark matter using a single-phase liquid argon target. The projected cross section sensitivity for DEAP-3600 to the spin-independent scattering of Weakly Interacting Massive Particles (WIMPs) on nucleons is 10−46cm2 for a 100 GeV/c2 WIMP mass with a fiducial exposure of 3 tonne-years. This paper describes the physical properties and construction of the DEAP-3600 detector

First results from the DEAP-3600 dark matter search with argon at SNOLAB

This paper reports the first results of a direct dark matter search with the DEAP-3600 single-phase liquid argon (LAr) detector. The experiment was performed 2 km underground at SNOLAB (Sudbury, Canada) utilizing a large target mass, with the LAr target contained in a spherical acrylic vessel of 3600 kg capacity. The LAr is viewed by an array of PMTs, which would register scintillation light produced by rare nuclear recoil signals induced by dark matter particle scattering. An analysis of 4.44 live days (fidicial exposure of 9.87 tonne days) of data taken during the initial filling phase demonstrates the best electronic recoil rejection using pulse-shape discrimination in argon, with leakage <1.2X107 (90% C.L.) between 15 and 31 keVee. No candidate signal events are observed, which results in the leading limit on WIMP-nucleon spin-independent cross section on argon, <1.21044 cm2 for a 100 GeV/c2 WIMP mass (90% C.L.)

Design and construction of the DEAP-3600 dark matter detector

The Dark matter Experiment using Argon Pulse-shape discrimination (DEAP) has been designed for a direct detection search for particle dark matter using a single-phase liquid argon target. The projected cross section sensitivity for DEAP-3600 to the spin-independent scattering of Weakly Interacting Massive Particles (WIMPs) on nucleons is 10 cm for a 100 GeV/c WIMP mass with a fiducial exposure of 3 tonne-years. This paper describes the physical properties and construction of the DEAP-3600 detector. −46 2

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

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 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

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

International genome-wide meta-analysis identifies new primary biliary cirrhosis risk loci and targetable pathogenic pathways.

Primary biliary cirrhosis (PBC) is a classical autoimmune liver disease for which effective immunomodulatory therapy is lacking. Here we perform meta-analyses of discovery data sets from genome-wide association studies of European subjects (n=2,764 cases and 10,475 controls) followed by validation genotyping in an independent cohort (n=3,716 cases and 4,261 controls). We discover and validate six previously unknown risk loci for PBC (Pcombined<5 × 10(-8)) and used pathway analysis to identify JAK-STAT/IL12/IL27 signalling and cytokine-cytokine pathways, for which relevant therapies exist