The Most Common Comorbidities in Dandy-Walker Syndrome Patients: A Systematic Review of Case Reports.

OBJECTIVE: Dandy-Walker syndrome (DWS) is a rare neurologic multi-entity malformation. This review aimed at reporting its main nonneurologic comorbidities. METHODS: Following PRISMA guidelines, search in Medline was conducted (2000-2014, keyword: dandy-walker). Age, sex, country, DWS type, consanguinity or siblings with DWS, and recorded coexistent conditions (by ICD10 category) were extracted for 187 patients (46.5% male, 43% from Asia) from 168 case reports. RESULTS: Diagnosis was most often set in 12 years old (27.8%). One-third of cases had a chromosomal abnormality or syndrome (n = 8 PHACE), 27% had a cardiovascular condition (n = 7 Patent Ductus Arteriosus), 24% had a disease of eye and ear (n = 9 cataract); most common malignancy was nephroblastoma (n = 8, all Asian). Almost one-fifth had a mental illness diagnosis; only 6.4% had mild or severe intellectual disability. CONCLUSION: The spread of comorbidities calls for early diagnosis and multidisciplinary research and practice, especially as many cases remain clinically asymptomatic for years

Activation of Estrogen Receptor-α by E2 or EGF Induces Temporally Distinct Patterns of Large-Scale Chromatin Modification and mRNA Transcription

Estrogen receptor-α (ER) transcription function is regulated in a ligand-dependent (e.g., estradiol, E2) or ligand-independent (e.g., growth factors) manner. Our laboratory seeks to understand these two modes of action. Using a cell line that contains a visible prolactin enhancer/promoter array (PRL-HeLa) regulated by ER, we analyzed ER response to E2 and EGF by quantifying image-based results. Data show differential recruitment of GFP-ER to the array, with the AF1 domain playing a vital role in EGF-mediated responsiveness. Temporal analyses of large-scale chromatin dynamics, and accumulation of array-localized reporter mRNA over 24 hours showed that the EGF response consists of a single pulse of reporter mRNA accumulation concomitant with transient increase in array decondensation. Estradiol induced a novel cyclical pattern of mRNA accumulation with a sustained increase in array decondensation. Collectively, our work shows that there is a stimuli-specific pattern of large-scale chromatin modification and transcript levels by ER

The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC

Measurements of differential cross-sections in top-quark pair events with a high transverse momentum top quark and limits on beyond the Standard Model contributions to top-quark pair production with the ATLAS detector at √s = 13 TeV

Cross-section measurements of top-quark pair production where the hadronically decaying top quark has transverse momentum greater than 355 GeV and the other top quark decays into ℓνb are presented using 139 fb−1 of data collected by the ATLAS experiment during proton-proton collisions at the LHC. The fiducial cross-section at s = 13 TeV is measured to be σ = 1.267 ± 0.005 ± 0.053 pb, where the uncertainties reflect the limited number of data events and the systematic uncertainties, giving a total uncertainty of 4.2%. The cross-section is measured differentially as a function of variables characterising the tt¯ system and additional radiation in the events. The results are compared with various Monte Carlo generators, including comparisons where the generators are reweighted to match a parton-level calculation at next-to-next-to-leading order. The reweighting improves the agreement between data and theory. The measured distribution of the top-quark transverse momentum is used to search for new physics in the context of the effective field theory framework. No significant deviation from the Standard Model is observed and limits are set on the Wilson coefficients of the dimension-six operators OtG and Otq(8), where the limits on the latter are the most stringent to date. [Figure not available: see fulltext.]

Co-infections, secondary infections, and antimicrobial use in patients hospitalised with COVID-19 during the first pandemic wave from the ISARIC WHO CCP-UK study : a multicentre, prospective cohort study

Background Microbiological characterisation of co-infections and secondary infections in patients with COVID-19 is lacking, and antimicrobial use is high. We aimed to describe microbiologically confirmed co-infections and secondary infections, and antimicrobial use, in patients admitted to hospital with COVID-19. Methods The International Severe Acute Respiratory and Emerging Infections Consortium (ISARIC) WHO Clinical Characterisation Protocol UK (CCP-UK) study is an ongoing, prospective cohort study recruiting inpatients from 260 hospitals in England, Scotland, and Wales, conducted by the ISARIC Coronavirus Clinical Characterisation Consortium. Patients with a confirmed or clinician-defined high likelihood of SARS-CoV-2 infection were eligible for inclusion in the ISARIC WHO CCP-UK study. For this specific study, we excluded patients with a recorded negative SARS-CoV-2 test result and those without a recorded outcome at 28 days after admission. Demographic, clinical, laboratory, therapeutic, and outcome data were collected using a prespecified case report form. Organisms considered clinically insignificant were excluded. Findings We analysed data from 48 902 patients admitted to hospital between Feb 6 and June 8, 2020. The median patient age was 74 years (IQR 59–84) and 20 786 (42·6%) of 48 765 patients were female. Microbiological investigations were recorded for 8649 (17·7%) of 48 902 patients, with clinically significant COVID-19-related respiratory or bloodstream culture results recorded for 1107 patients. 762 (70·6%) of 1080 infections were secondary, occurring more than 2 days after hospital admission. Staphylococcus aureus and Haemophilus influenzae were the most common pathogens causing respiratory co-infections (diagnosed ≤2 days after admission), with Enterobacteriaceae and S aureus most common in secondary respiratory infections. Bloodstream infections were most frequently caused by Escherichia coli and S aureus. Among patients with available data, 13 390 (37·0%) of 36 145 had received antimicrobials in the community for this illness episode before hospital admission and 39 258 (85·2%) of 46 061 patients with inpatient antimicrobial data received one or more antimicrobials at some point during their admission (highest for patients in critical care). We identified frequent use of broad-spectrum agents and use of carbapenems rather than carbapenem-sparing alternatives. Interpretation In patients admitted to hospital with COVID-19, microbiologically confirmed bacterial infections are rare, and more likely to be secondary infections. Gram-negative organisms and S aureus are the predominant pathogens. The frequency and nature of antimicrobial use are concerning, but tractable targets for stewardship interventions exist

Procalcitonin is not a reliable biomarker of bacterial coinfection in people with coronavirus disease 2019 undergoing microbiological investigation at the time of hospital admission

Admission procalcitonin measurements and microbiology results were available for 1040 hospitalized adults with coronavirus disease 2019 (from 48 902 included in the International Severe Acute Respiratory and Emerging Infections Consortium World Health Organization Clinical Characterisation Protocol UK study). Although procalcitonin was higher in bacterial coinfection, this was neither clinically significant (median [IQR], 0.33 [0.11–1.70] ng/mL vs 0.24 [0.10–0.90] ng/mL) nor diagnostically useful (area under the receiver operating characteristic curve, 0.56 [95% confidence interval, .51–.60])

Direct constraint on the Higgs–charm coupling from a search for Higgs boson decays into charm quarks with the ATLAS detector

A search for the Higgs boson decaying into a pair of charm quarks is presented. The analysis uses proton–proton collisions to target the production of a Higgs boson in association with a leptonically decaying W or Z boson. The dataset delivered by the LHC at a centre-of-mass energy of and recorded by the ATLAS detector corresponds to an integrated luminosity of 139 fb−1. Flavour-tagging algorithms are used to identify jets originating from the hadronisation of charm quarks. The analysis method is validated with the simultaneous measurement of WW, WZ and ZZ production, with observed (expected) significances of 2.6 (2.2) standard deviations above the background-only prediction for the (W/Z)Z(→cc¯) process and 3.8 (4.6) standard deviations for the (W/Z)W(→cq) process. The (W/Z)H(→cc¯) search yields an observed (expected) upper limit of 26 (31) times the predicted Standard Model cross-section times branching fraction for a Higgs boson with a mass of , corresponding to an observed (expected) constraint on the charm Yukawa coupling modifier |κc|<8.5 (12.4), at the 95% confidence level. A combination with the ATLAS (W/Z)H,H→bb¯ analysis is performed, allowing the ratio κc/κb to be constrained to less than 4.5 at the 95% confidence level, smaller than the ratio of the b- and c-quark masses, and therefore determines the Higgs-charm coupling to be weaker than the Higgs-bottom coupling at the 95% confidence level

Accuracy versus precision in boosted top tagging with the ATLAS detector

Abstract The identification of top quark decays where the top quark has a large momentum transverse to the beam axis, known as top tagging, is a crucial component in many measurements of Standard Model processes and searches for beyond the Standard Model physics at the Large Hadron Collider. Machine learning techniques have improved the performance of top tagging algorithms, but the size of the systematic uncertainties for all proposed algorithms has not been systematically studied. This paper presents the performance of several machine learning based top tagging algorithms on a dataset constructed from simulated proton-proton collision events measured with the ATLAS detector at √ s = 13 TeV. The systematic uncertainties associated with these algorithms are estimated through an approximate procedure that is not meant to be used in a physics analysis, but is appropriate for the level of precision required for this study. The most performant algorithms are found to have the largest uncertainties, motivating the development of methods to reduce these uncertainties without compromising performance. To enable such efforts in the wider scientific community, the datasets used in this paper are made publicly available.</jats:p