151 research outputs found

    Electronic properties of metal induced gap states at insulator/metal interfaces -- dependence on the alkali halide and the possibility of excitonic mechanism of superconductivity

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    Motivated from the experimental observation of metal induced gap states (MIGS) at insulator/metal interfaces by Kiguchi {\it et al.} [Phys. Rev. Lett. {\bf 90}, 196803 (2003)], we have theoretically investigated the electronic properties of MIGS at interfaces between various alkali halides and a metal represented by a jellium with the first-principles density functional method. We have found that, on top of the usual evanescent state, MIGS generally have a long tail on halogen sites with a pzp_z-like character, whose penetration depth (λ\lambda) is as large as half the lattice constant of bulk alkali halides. This implies that λ\lambda, while little dependent on the carrier density in the jellium, is dominated by the lattice constant (hence by energy gap) of the alkali halide, where λLiF<λLiCl<λLiI\lambda_{\rm LiF} < \lambda_{\rm LiCl} < \lambda_{\rm LiI}. We also propose a possibility of the MIGS working favorably for the exciton-mediated superconductivity.Comment: 7 pages, 9 figure

    A scoping review establishes need for consensus guidance on reporting health equity in observational studies.

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    To evaluate the support from the available guidance on reporting of health equity in research for our candidate items and to identify additional items for the Strengthening Reporting of Observational studies in Epidemiology-Equity extension. We conducted a scoping review by searching Embase, MEDLINE, CINAHL, Cochrane Methodology Register, LILACS, and Caribbean Center on Health Sciences Information up to January 2022. We also searched reference lists and gray literature for additional resources. We included guidance and assessments (hereafter termed "resources") related to conduct and/or reporting for any type of health research with or about people experiencing health inequity. We included 34 resources, which supported one or more candidate items or contributed to new items about health equity reporting in observational research. Each candidate item was supported by a median of six (range: 1-15) resources. In addition, 12 resources suggested 13 new items, such as "report the background of investigators". Existing resources for reporting health equity in observational studies aligned with our interim checklist of candidate items. We also identified additional items that will be considered in the development of a consensus-based and evidence-based guideline for reporting health equity in observational studies

    Modelling thirty-day mortality in the acute respiratory distress syndrome (ARDS) in an adult ICU

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    Publisher's copy made available with the permission of the publisher © Australian Society of AnaesthetistsVariables predicting thirty-day outcome from Acute Respiratory Distress Syndrome (ARDS) were analysed using Cox regression structured for time-varying covariates. Over a three-year period, 1996-1998, consecutive patients with ARDS (bilateral chest X-ray opacities, PaO₂/FiO₂ ratio of <200 and an acute precipitating event) were identified using a prospective computerized data base in a university teaching hospital ICU. The cohort, 106 mechanically ventilated patients, was of mean (SD) age 63.5 (15.5) years and 37% were female. Primary lung injury occurred in 45% and 24% were postoperative. ICU-admission day APACHE II score was 25 (8); ARDS onset time from ICU admission was 1 day (median: range 0-16) and 30 day mortality was 41% (95% CI: 33%-51%). At ARDS onset, PaO₂/FiO₂ ratio was 92 (31), 81% had four-quadrant chest X-ray opacification and lung injury score was 2.75 (0.45). Average mechanical ventilator tidal volume was 10.3 ml/ predicted kg weight. Cox model mortality predictors (hazard ratio, 95% CI) were: APACHE II score, 1.15 (1.09-1.21); ARDS lag time (days), 0.72 (0.58-0.89); direct versus indirect injury, 2.89 (1.45-5.76); PaO₂/FiO₂ ratio, 0.98 (0.97-0.99); operative versus non-operative category, 0.24 (0.09-0.63). Time-varying effects were evident for PaO₂/FiO₂ ratio, operative versus non-operative category and ventilator tidal volume assessed as a categorical predictor with a cut-point of 8 ml/kg predicted weight (mean tidal volumes, 7.1 (1.9) vs 10.7 (1.6) ml/kg predicted weight). Thirty-day survival was improved for patients ventilated with lower tidal volumes. Survival predictors in ARDS were multifactorial and related to patient-injury-time interaction and level of mechanical ventilator tidal volume.J. L. Moran, P. J. Solomon, V. Fox, M. Salagaras, P. J. Williams, K. Quinlan, A. D. Berstenhttp://www.aaic.net.au/Article.asp?D=200332

    Risk profiles and one-year outcomes of patients with newly diagnosed atrial fibrillation in India: Insights from the GARFIELD-AF Registry.

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    BACKGROUND: The Global Anticoagulant Registry in the FIELD-Atrial Fibrillation (GARFIELD-AF) is an ongoing prospective noninterventional registry, which is providing important information on the baseline characteristics, treatment patterns, and 1-year outcomes in patients with newly diagnosed non-valvular atrial fibrillation (NVAF). This report describes data from Indian patients recruited in this registry. METHODS AND RESULTS: A total of 52,014 patients with newly diagnosed AF were enrolled globally; of these, 1388 patients were recruited from 26 sites within India (2012-2016). In India, the mean age was 65.8 years at diagnosis of NVAF. Hypertension was the most prevalent risk factor for AF, present in 68.5% of patients from India and in 76.3% of patients globally (P < 0.001). Diabetes and coronary artery disease (CAD) were prevalent in 36.2% and 28.1% of patients as compared with global prevalence of 22.2% and 21.6%, respectively (P < 0.001 for both). Antiplatelet therapy was the most common antithrombotic treatment in India. With increasing stroke risk, however, patients were more likely to receive oral anticoagulant therapy [mainly vitamin K antagonist (VKA)], but average international normalized ratio (INR) was lower among Indian patients [median INR value 1.6 (interquartile range {IQR}: 1.3-2.3) versus 2.3 (IQR 1.8-2.8) (P < 0.001)]. Compared with other countries, patients from India had markedly higher rates of all-cause mortality [7.68 per 100 person-years (95% confidence interval 6.32-9.35) vs 4.34 (4.16-4.53), P < 0.0001], while rates of stroke/systemic embolism and major bleeding were lower after 1 year of follow-up. CONCLUSION: Compared to previously published registries from India, the GARFIELD-AF registry describes clinical profiles and outcomes in Indian patients with AF of a different etiology. The registry data show that compared to the rest of the world, Indian AF patients are younger in age and have more diabetes and CAD. Patients with a higher stroke risk are more likely to receive anticoagulation therapy with VKA but are underdosed compared with the global average in the GARFIELD-AF. CLINICAL TRIAL REGISTRATION-URL: http://www.clinicaltrials.gov. Unique identifier: NCT01090362

    Universal DNA methylation age across mammalian tissues

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    DATA AVAILABILITY STATEMENT : The individual-level data from the Mammalian Methylation Consortium can be accessed from several online locations. All data from the Mammalian Methylation Consortium are posted on Gene Expression Omnibus (complete dataset, GSE223748). Subsets of the datasets can also be downloaded from accession numbers GSE174758, GSE184211, GSE184213, GSE184215, GSE184216, GSE184218, GSE184220, GSE184221, GSE184224, GSE190660, GSE190661, GSE190662, GSE190663, GSE190664, GSE174544, GSE190665, GSE174767, GSE184222, GSE184223, GSE174777, GSE174778, GSE173330, GSE164127, GSE147002, GSE147003, GSE147004, GSE223943 and GSE223944. Additional details can be found in Supplementary Note 2. The mammalian data can also be downloaded from the Clock Foundation webpage: https://clockfoundation.org/MammalianMethylationConsortium. The mammalian methylation array is available through the non-profit Epigenetic Clock Development Foundation (https://clockfoundation.org/). The manifest file of the mammalian array and genome annotations of CpG sites can be found on Zenodo (10.5281/zenodo.7574747). All other data supporting the findings of this study are available from the corresponding author upon reasonable request. The chip manifest files, genome annotations of CpG sites and the software code for universal pan-mammalian clocks can be found on GitHub95 at https://github.com/shorvath/MammalianMethylationConsortium/tree/v2.0.0. The individual R code for the universal pan-mammalian clocks, EWAS analysis and functional enrichment studies can be also found in the Supplementary Code.SUPPLEMENTARY MATERIAL 1 : Supplementary Tables 1–3 and Notes 1–6.SUPPLEMENTARY MATERIAL 2 : Reporting SummarySUPPLEMENTARY MATERIAL 3 : Supplementary Data 1–14.SUPPLEMENTARY MATERIAL 4 : Supplementary Code.Aging, often considered a result of random cellular damage, can be accurately estimated using DNA methylation profiles, the foundation of pan-tissue epigenetic clocks. Here, we demonstrate the development of universal pan-mammalian clocks, using 11,754 methylation arrays from our Mammalian Methylation Consortium, which encompass 59 tissue types across 185 mammalian species. These predictive models estimate mammalian tissue age with high accuracy (r > 0.96). Age deviations correlate with human mortality risk, mouse somatotropic axis mutations and caloric restriction. We identified specific cytosines with methylation levels that change with age across numerous species. These sites, highly enriched in polycomb repressive complex 2-binding locations, are near genes implicated in mammalian development, cancer, obesity and longevity. Our findings offer new evidence suggesting that aging is evolutionarily conserved and intertwined with developmental processes across all mammals.https://www.nature.com/nataginghj2024Zoology and EntomologySDG-15:Life on lan

    Molecular biology of baculovirus and its use in biological control in Brazil

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

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    Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2,3,4 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

    Software performance of the ATLAS track reconstruction for LHC run 3

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    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
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