Oral mucosal melanoma: a malignant trap

Oral mucosal melanomas are highly malignant tumors. The 'chameleonic' presentation of a mainly asymptomatic condition, the rarity of these lesions, the poor prognosis and the necessity of a highly specialized treatment are factors that should be seriously considered by the involved health provider. We present the case of a 75-year-old man who was referred to the Ear, Nose and Throat department. His symptoms were voice alteration and saliva drooling, progressively worsening during the last few weeks. The absence of pain was the reason for the delay of seeking medical care. The diagnosis was an oversized oral melanoma. This is an example of how the time of diagnosis and the evolution of a disease could be seriously influenced by patient's behavior. Melanomas arising from oral mucosa have poor prognosis unless they are discovered and treated early. The vigilance of the physicians is necessary to have success in this difficult task

PHOENI2X -- A European Cyber Resilience Framework With Artificial-Intelligence-Assisted Orchestration, Automation and Response Capabilities for Business Continuity and Recovery, Incident Response, and Information Exchange

As digital technologies become more pervasive in society and the economy, cybersecurity incidents become more frequent and impactful. According to the NIS and NIS2 Directives, EU Member States and their Operators of Essential Services must establish a minimum baseline set of cybersecurity capabilities and engage in cross-border coordination and cooperation. However, this is only a small step towards European cyber resilience. In this landscape, preparedness, shared situational awareness, and coordinated incident response are essential for effective cyber crisis management and resilience. Motivated by the above, this paper presents PHOENI2X, an EU-funded project aiming to design, develop, and deliver a Cyber Resilience Framework providing Artificial-Intelligence-assisted orchestration, automation and response capabilities for business continuity and recovery, incident response, and information exchange, tailored to the needs of Operators of Essential Services and the EU Member State authorities entrusted with cybersecurity

Measurement of substructure-dependent jet suppression in Pb+Pb collisions at 5.02 TeV with the ATLAS detector

The ATLAS detector at the Large Hadron Collider has been used to measure jet substructure modification and suppression in Pb+Pb collisions at a nucleon–nucleon center-of-mass energy √sNN = 5.02 TeV in comparison with proton–proton (pp) collisions at √s = 5.02 TeV. The Pb+Pb data, collected in 2018, have an integrated luminosity of 1.72 nb−1, while the ppdata, collected in 2017, have an integrated luminosity of 260 pb−1. Jets used in this analysis are clustered using the anti-kt algorithm with a radius parameter R = 0.4. The jet constituents, defined by both tracking and calorimeter information, are used to determine the angular scale rg of the first hard splitting inside the jet by reclustering them using the Cambridge–Aachen algorithm and employing the soft-drop grooming technique. The nuclear modification factor, RAA, used to characterize jet suppression in Pb+Pb collisions, is presented differentially in rg, jet transverse momentum, and in intervals of collision centrality. The RAA value is observed to depend significantly on jet rg. Jets produced with the largest measured rg are found to be twice as suppressed as those with the smallest rg in central Pb+Pb collisions. The RAA values do not exhibit a strong variation with jet pT in any of the rg intervals. The rg and pT dependence of jet RAA is qualitatively consistent with a picture of jet quenching arising from coherence and provides the most direct evidence in support of this approach

Anomaly detection search for new resonances decaying into a Higgs boson and a generic new particle X in hadronic final states using Formula Presented pp collisions with the ATLAS detector

A search is presented for a heavy resonance Formula Presented decaying into a Standard Model Higgs boson Formula Presented and a new particle Formula Presented in a fully hadronic final state. The full Large Hadron Collider run 2 dataset of proton-proton collisions at Formula Presented collected by the ATLAS detector from 2015 to 2018 is used and corresponds to an integrated luminosity of Formula Presented. The search targets the high Formula Presented-mass region, where the Formula Presented and Formula Presented have a significant Lorentz boost in the laboratory frame. A novel application of anomaly detection is used to define a general signal region, where events are selected solely because of their incompatibility with a learned background-only model. It is constructed using a jet-level tagger for signal-model-independent selection of the boosted Formula Presented particle, representing the first application of fully unsupervised machine learning to an ATLAS analysis. Two additional signal regions are implemented to target a benchmark Formula Presented decay into two quarks, covering topologies where the Formula Presented is reconstructed as either a single large-radius jet or two small-radius jets. The analysis selects Higgs boson decays into Formula Presented, and a dedicated neural-network-based tagger provides sensitivity to the boosted heavy-flavor topology. No significant excess of data over the expected background is observed, and the results are presented as upper limits on the production cross section Formula Presented) for signals with Formula Presented between 1.5 and 6 TeV and Formula Presented between 65 and 3000 GeV. A search is presented for a heavy resonance Y decaying into a Standard Model Higgs boson H and a new particle X in a fully hadronic final state. The full Large Hadron Collider run 2 dataset of proton-proton collisions at √ s = 13     TeV collected by the ATLAS detector from 2015 to 2018 is used and corresponds to an integrated luminosity of 139     fb − 1 . The search targets the high Y -mass region, where the H and X have a significant Lorentz boost in the laboratory frame. A novel application of anomaly detection is used to define a general signal region, where events are selected solely because of their incompatibility with a learned background-only model. It is constructed using a jet-level tagger for signal-model-independent selection of the boosted X particle, representing the first application of fully unsupervised machine learning to an ATLAS analysis. Two additional signal regions are implemented to target a benchmark X decay into two quarks, covering topologies where the X is reconstructed as either a single large-radius jet or two small-radius jets. The analysis selects Higgs boson decays into b ¯ b , and a dedicated neural-network-based tagger provides sensitivity to the boosted heavy-flavor topology. No significant excess of data over the expected background is observed, and the results are presented as upper limits on the production cross section σ ( p p → Y → X H → q ¯ q b ¯ b ) for signals with m Y between 1.5 and 6 TeV and m X between 65 and 3000 GeV

Exome-wide association study to identify rare variants influencing COVID-19 outcomes : Results from the Host Genetics Initiative

Publisher Copyright: Copyright: © 2022 Butler-Laporte et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.Host genetics is a key determinant of COVID-19 outcomes. Previously, the COVID-19 Host Genetics Initiative genome-wide association study used common variants to identify multiple loci associated with COVID-19 outcomes. However, variants with the largest impact on COVID-19 outcomes are expected to be rare in the population. Hence, studying rare variants may provide additional insights into disease susceptibility and pathogenesis, thereby informing therapeutics development. Here, we combined whole-exome and whole-genome sequencing from 21 cohorts across 12 countries and performed rare variant exome-wide burden analyses for COVID-19 outcomes. In an analysis of 5,085 severe disease cases and 571,737 controls, we observed that carrying a rare deleterious variant in the SARS-CoV-2 sensor toll-like receptor TLR7 (on chromosome X) was associated with a 5.3-fold increase in severe disease (95% CI: 2.75–10.05, p = 5.41x10-7). This association was consistent across sexes. These results further support TLR7 as a genetic determinant of severe disease and suggest that larger studies on rare variants influencing COVID-19 outcomes could provide additional insights.Peer reviewe

Searches for lepton-flavour-violating decays of the Higgs boson into eτ and μτ in \sqrt{s} = 13 TeV pp collisions with the ATLAS detector

Abstract This paper presents direct searches for lepton flavour violation in Higgs boson decays, H → eτ and H → μτ, performed using data collected with the ATLAS detector at the LHC. The searches are based on a data sample of proton-proton collisions at a centre-of-mass energy s $$\sqrt{s}$$ = 13 TeV, corresponding to an integrated luminosity of 138 fb−1. Leptonic (τ → ℓνℓντ) and hadronic (τ → hadrons ντ) decays of the τ-lepton are considered. Two background estimation techniques are employed: the MC-template method, based on data-corrected simulation samples, and the Symmetry method, based on exploiting the symmetry between electrons and muons in the Standard Model backgrounds. No significant excess of events is observed and the results are interpreted as upper limits on lepton-flavour-violating branching ratios of the Higgs boson. The observed (expected) upper limits set on the branching ratios at 95% confidence level, B $$\mathcal{B}$$ (H → eτ) < 0.20% (0.12%) and B $$\mathcal{B}$$ (H → μτ ) < 0.18% (0.09%), are obtained with the MC-template method from a simultaneous measurement of potential H → eτ and H → μτ signals. The best-fit branching ratio difference, B $$\mathcal{B}$$ (H → μτ) → B $$\mathcal{B}$$ (H → eτ), measured with the Symmetry method in the channel where the τ-lepton decays to leptons, is (0.25 ± 0.10)%, compatible with a value of zero within 2.5σ

Studies of new Higgs boson interactions through nonresonant HH production in the b¯bγγ fnal state in pp collisions at √s = 13 TeV with the ATLAS detector

A search for nonresonant Higgs boson pair production in the b ¯bγγ fnal state is performed using 140 fb−1 of proton-proton collisions at a centre-of-mass energy of 13 TeV recorded by the ATLAS detector at the CERN Large Hadron Collider. This analysis supersedes and expands upon the previous nonresonant ATLAS results in this fnal state based on the same data sample. The analysis strategy is optimised to probe anomalous values not only of the Higgs (H) boson self-coupling modifer κλ but also of the quartic HHV V (V = W, Z) coupling modifer κ2V . No signifcant excess above the expected background from Standard Model processes is observed. An observed upper limit µHH &lt; 4.0 is set at 95% confdence level on the Higgs boson pair production cross-section normalised to its Standard Model prediction. The 95% confdence intervals for the coupling modifers are −1.4 &lt; κλ &lt; 6.9 and −0.5 &lt; κ2V &lt; 2.7, assuming all other Higgs boson couplings except the one under study are fxed to the Standard Model predictions. The results are interpreted in the Standard Model efective feld theory and Higgs efective feld theory frameworks in terms of constraints on the couplings of anomalous Higgs boson (self-)interactions