Systemic Inflammation in Preclinical Ulcerative Colitis

Background & Aims: Preclinical ulcerative colitis is poorly defined. We aimed to characterize the preclinical systemic inflammation in ulcerative colitis, using a comprehensive set of proteins. Methods: We obtained plasma samples biobanked from individuals who developed ulcerative colitis later in life (n = 72) and matched healthy controls (n = 140) within a population-based screening cohort. We measured 92 proteins related to inflammation using a proximity extension assay. The biologic relevance of these findings was validated in an inception cohort of patients with ulcerative colitis (n = 101) and healthy controls (n = 50). To examine the influence of genetic and environmental factors on these markers, a cohort of healthy twin siblings of patients with ulcerative colitis (n = 41) and matched healthy controls (n = 37) were explored. Results: Six proteins (MMP10, CXCL9, CCL11, SLAMF1, CXCL11 and MCP-1) were up-regulated (P < .05) in preclinical ulcerative colitis compared with controls based on both univariate and multivariable models. Ingenuity Pathway Analyses identified several potential key regulators, including interleukin-1ß, tumor necrosis factor, interferon-gamma, oncostatin M, nuclear factor-¿B, interleukin-6, and interleukin-4. For validation, we built a multivariable model to predict disease in the inception cohort. The model discriminated treatment-naïve patients with ulcerative colitis from controls with leave-one-out cross-validation (area under the curve = 0.92). Consistently, MMP10, CXCL9, CXCL11, and MCP-1, but not CCL11 and SLAMF1, were significantly up-regulated among the healthy twin siblings, even though their relative abundances seemed higher in incident ulcerative colitis. Conclusions: A set of inflammatory proteins are up-regulated several years before a diagnosis of ulcerative colitis. These proteins were highly predictive of an ulcerative colitis diagnosis, and some seemed to be up-regulated already at exposure to genetic and environmental risk factors. © 2021 The Author

Interaction of inflammatory cytokines and erythropoeitin in iron metabolism and erythropoiesis in anaemia of chronic disease

In chronic inflammatory conditions increased endogenous release of specific cytokines (TNFα, IL-1, IL-6, IFNγ and others) is presumed. It has been shown that those of monocyte lineage play a key role in cytokine expression and synthesis. This may be associated with changes in iron metabolism and impaired erythropoiesis and may lead to development of anaemia in patients with rheumatoid arthritis. Firstly, increased synthesis of acute phase proteins, like ferritin, during chronic inflammation is proposed as the way by which the toxic effect of iron and thereby the synthesis of free oxy-radicals causing the damage on the affected joints, may be reduced. This is associated with a shift of iron towards the mononuclear phagocyte system which may participate in the development of anaemia of chronic disease. Secondly, an inhibitory action of inflammatory cytokines (TNFα, IL-1), on proliferation and differentiation of erythroid progenitors as well as on synthesis of erythropoietin has been shown, thereby also contributing to anaemia. Finally, chronic inflammation causes multiple, complex disturbances in the delicate physiologic equilibrium of interaction between cytokines and cells (erythroid progenitors, cells of mononuclear phagocyte system and erythropoietin producing cells) leading to development of anaemia of chronic disease (Fig. 1)

The prevalence and transcriptional activity of the mucosal microbiota of ulcerative colitis patients

Active microbes likely have larger impact on gut health status compared to inactive or dormant microbes. We investigate the composition of active and total mucosal microbiota of treatment-naïve ulcerative colitis (UC) patients to determine the microbial picture at the start-up phase of disease, using both a 16S rRNA transcript and gene amplicon sequencing. DNA and RNA were isolated from the same mucosal colonic biopsies. Our aim was to identify active microbial members of the microbiota in early stages of disease and reveal which members are present, but do not act as major players. We demonstrated differences in active and total microbiota of UC patients when comparing inflamed to non-inflamed tissue. Several taxa, among them the Proteobacteria phyla and families therein, revealed lower transcriptional activity despite a high presence. The Bifidobacteriaceae family of the Actinobacteria phylum showed lower abundance in the active microbiota, although no difference in presence was detected. The most abundant microbiota members of the inflamed tissue in UC patients were not the most active. Knowledge of active members of microbiota in UC patients could enhance our understanding of disease etiology. The active microbial community composition did not deviate from the total when comparing UC patients to non-IBD controls

Study of Z → llγ decays at √s = 8 TeV with the ATLAS detector

This paper presents a study of Z → llγ decays with the ATLAS detector at the Large Hadron Collider. The analysis uses a proton–proton data sample corresponding to an integrated luminosity of 20.2 fb−1 collected at a centre-ofmass energy √s = 8 TeV. Integrated fiducial cross-sections together with normalised differential fiducial cross-sections, sensitive to the kinematics of final-state QED radiation, are obtained. The results are found to be in agreement with stateof-the-art predictions for final-state QED radiation. First measurements of Z → llγ γ decays are also reported

Software performance of the ATLAS track reconstruction for LHC run 3

Charged particle reconstruction in the presence of many simultaneous proton–proton (pp) collisions in the LHC is a challenging task for the ATLAS experiment’s reconstruction software due to the combinatorial complexity. This paper describes the major changes made to adapt the software to reconstruct high-activity collisions with an average of 50 or more simultaneous pp interactions per bunch crossing (pileup) promptly using the available computing resources. The performance of the key components of the track reconstruction chain and its dependence on pile-up are evaluated, and the improvement achieved compared to the previous software version is quantified. For events with an average of 60 pp collisions per bunch crossing, the updated track reconstruction is twice as fast as the previous version, without significant reduction in reconstruction efficiency and while reducing the rate of combinatorial fake tracks by more than a factor two

Search for heavy Majorana or Dirac neutrinos and right-handed W gauge bosons in final states with charged leptons and jets in pp collisions at √s = 13 TeV with the ATLAS detector

A search for heavy right-handed Majorana or Dirac neutrinos NR and heavy right-handed gauge bosons WR is performed in events with energetic electrons or muons, with the same or opposite electric charge, and energetic jets. The search is carried out separately for topologies of clearly separated final-state products (“resolved” channel) and topologies with boosted final states with hadronic and/or leptonic products partially overlapping and reconstructed as a large-radius jet (“boosted” channel). The events are selected from pp collision data at the LHC with an integrated luminosity of 139 fb−1 collected by the ATLAS detector at √s = 13 TeV. No significant deviations from the Standard Model predictions are observed. The results are interpreted within the theoretical framework of a left-right symmetric model, and lower limits are set on masses in the heavy righthanded WR boson and NR plane. The excluded region extends to about m(WR) = 6.4 TeV for both Majorana and Dirac NR neutrinos at m(NR) < 1 TeV. NR with masses of less than 3.5 (3.6) TeV are excluded in the electron (muon) channel at m(WR) = 4.8 TeV for the Majorana neutrinos, and limits of m(NR) up to 3.6 TeV for m(WR) = 5.2 (5.0) TeV in the electron (muon) channel are set for the Dirac neutrinos. These constitute the most stringent exclusion limits to date for the model considered

Deep generative models for fast photon shower simulation in ATLAS

The need for large-scale production of highly accurate simulated event samples for the extensive physics programme of the ATLAS experiment at the Large Hadron Collider motivates the development of new simulation techniques. Building on the recent success of deep learning algorithms, variational autoencoders and generative adversarial networks are investigated for modelling the response of the central region of the ATLAS electromagnetic calorimeter to photons of various energies. The properties of synthesised showers are compared with showers from a full detector simulation using geant4. Both variational autoencoders and generative adversarial networks are capable of quickly simulating electromagnetic showers with correct total energies and stochasticity, though the modelling of some shower shape distributions requires more refinement. This feasibility study demonstrates the potential of using such algorithms for ATLAS fast calorimeter simulation in the future and shows a possible way to complement current simulation techniques

Search for doubly charged Higgs boson production in multi-lepton final states using 139 fb−1 of proton–proton collisions at s√ = 13 TeV with the ATLAS detector

A search for pair production of doubly charged Higgs bosons (H±± ), each decaying into a pair of prompt, isolated, and highly energetic leptons with the same electric charge, is presented. The search uses a proton–proton collision data sample at a centre-of-mass energy of 13 TeV corresponding to an integrated luminosity of 139 fb−1 recorded by the ATLAS detector during Run 2 of the Large Hadron Collider (LHC). This analysis focuses on same-charge leptonic decays, H±±→ℓ±ℓ′± where ℓ,ℓ′=e,μ,τ, in two-, three-, and four-lepton channels, but only considers final states which include electrons or muons. No evidence of a signal is observed. Corresponding upper limits on the production cross-section of a doubly charged Higgs boson are derived, as a function of its mass m(H±±), at 95% confidence level. Assuming that the branching ratios to each of the possible leptonic final states are equal, B(H±±→e±e±)=B(H±±→e±μ±)=B(H±±→μ±μ±)=B(H±±→e±τ±)=B(H±±→μ±τ±)=B(H±±→τ±τ±)=1/6, the observed (expected) lower limit on the mass of a doubly charged Higgs boson is 1080 GeV (1065 GeV) within the left-right symmetric type-II seesaw model, which is the strongest limit to date produced by the ATLAS Collaboration. Additionally, this paper provides the first direct test of the Zee–Babu neutrino mass model at the LHC, yielding an observed (expected) lower limit of m(H±±) = 900 GeV (880 GeV)

Observation of four-top-quark production in the multilepton final state with the ATLAS detector

This paper presents the observation of four-top-quark (tt¯tt¯) production in proton-proton collisions at the LHC. The analysis is performed using an integrated luminosity of 140 fb−1 at a centre-of-mass energy of 13 TeV collected using the ATLAS detector. Events containing two leptons with the same electric charge or at least three leptons (electrons or muons) are selected. Event kinematics are used to separate signal from background through a multivariate discriminant, and dedicated control regions are used to constrain the dominant backgrounds. The observed (expected) significance of the measured tt¯tt¯ signal with respect to the standard model (SM) background-only hypothesis is 6.1 (4.3) standard deviations. The tt¯tt¯ production cross section is measured to be 22.5+6.6−5.5 fb, consistent with the SM prediction of 12.0±2.4 fb within 1.8 standard deviations. Data are also used to set limits on the three-top-quark production cross section, being an irreducible background not measured previously, and to constrain the top-Higgs Yukawa coupling and effective field theory operator coefficients that affect tt¯tt¯ production