Weighted-density approximation for general nonuniform fluid mixtures

In order to construct a general density-functional theory for nonuniform fluid mixtures, we propose an extension to multicomponent systems of the weighted-density approximation (WDA) of Curtin and Ashcroft [Phys. Rev. A 32, 2909 (1985)]. This extension corrects a deficiency in a similar extension proposed earlier by Denton and Ashcroft [Phys. Rev. A 42, 7312 (1990)], in that that functional cannot be applied to the multi-component nonuniform fluid systems with spatially varying composition, such as solid-fluid interfaces. As a test of the accuracy of our new functional, we apply it to the calculation of the freezing phase diagram of a binary hard-sphere fluid, and compare the results to simulation and the Denton-Ashcroft extension.Comment: 4 pages, 4 figures, to appear in Phys. Rev. E as Brief Repor

Predicting risk of dementia with machine learning and survival models using routine primary care records

Worldwide, it is forecasted that 131.5 million people will suffer from dementia by 2050, and the annual cost of care will increase from 818 billion USD in 2016 to 2 trillion USD by 2030, with burgeoning social consequences. Given a timely prediction of a dementia outcome in patients, appropriate mitigating interventions can be applied to reduce risk. However such prediction facilities need to be made available to wider populations, and these facilities cannot rely on specialised, costly and invasive testing (such as neuroimaging, cerebrospinal fluid collection, etc which constitute important instruments used in diagnosis), for interventions to have a meaningful quantitative impact. Hence an emerging need exists for the wider application of prognostic measures which can be deployed using lower cost data sources such as longitudinal records routinely collected by general practices. This paper proposes an efficient prediction modelling approach to the risk of dementia, using CPRD data collected from GP practices in UK, and based on machine learning in particular the Gradient Boosting Machines model combined with a survival model such as the Cox Proportional Hazard, encapsulated in a semi-supervised learning and model calibration methodology

Adjusting the melting point of a model system via Gibbs-Duhem integration: application to a model of Aluminum

Model interaction potentials for real materials are generally optimized with respect to only those experimental properties that are easily evaluated as mechanical averages (e.g., elastic constants (at T=0 K), static lattice energies and liquid structure). For such potentials, agreement with experiment for the non-mechanical properties, such as the melting point, is not guaranteed and such values can deviate significantly from experiment. We present a method for re-parameterizing any model interaction potential of a real material to adjust its melting temperature to a value that is closer to its experimental melting temperature. This is done without significantly affecting the mechanical properties for which the potential was modeled. This method is an application of Gibbs-Duhem integration [D. Kofke, Mol. Phys.78, 1331 (1993)]. As a test we apply the method to an embedded atom model of aluminum [J. Mei and J.W. Davenport, Phys. Rev. B 46, 21 (1992)] for which the melting temperature for the thermodynamic limit is 826.4 +/- 1.3K - somewhat below the experimental value of 933K. After re-parameterization, the melting temperature of the modified potential is found to be 931.5K +/- 1.5K.Comment: 9 pages, 5 figures, 4 table

Orientation dependence of heterogeneous nucleation at the Cu–Pb solid-liquid interface

In this work, we examine the effect of surface structure on the heterogeneous nucleation of Pb crystals from the melt at a Cu substrate using molecular-dynamics (MD) simulation. In a previous work [Palafox-Hernandez et al., Acta Mater. 59, 3137 (2011)] studying the Cu/Pb solid-liquid interface with MD simulation, we observed that the structure of the Cu(111) and Cu(100) interfaces was significantly different at 625 K, just above the Pb melting temperature (618 K for the model). The Cu(100) interface exhibited significant surface alloying in the crystal plane in contact with the melt. In contrast, no surface alloying was seen at the Cu(111) interface; however, a prefreezing layer of crystalline Pb, 2-3 atomic planes thick and slightly compressed relative to bulk Pb crystal, was observed to form at the interface. We observe that at the Cu(111) interface the prefreezing layer is no longer present at 750 K, but surface alloying in the Cu(100) interface persists. In a series of undercooling MD simulations, heterogeneous nucleation of fcc Pb is observed at the Cu(111) interface within the simulation time (5 ns) at 592 K—a 26 K undercooling. Nucleation and growth at Cu(111) proceeded layerwise with a nearly planar critical nucleus. Quantitative analysis yielded heterogeneous nucleation barriers that are more than two orders of magnitude smaller than the predicted homogeneous nucleation barriers from classical nucleation theory. Nucleation was considerably more difficult on the Cu(100) surface-alloyed substrate. An undercooling of approximately 170 K was necessary to observe nucleation at this interface within the simulation time. From qualitative observation, the critical nucleus showed a contact angle with the Cu(100) surface of over 90°, indicating poor wetting of the Cu(100) surface by the nucleating phase, which according to classical heterogeneous nucleation theory provides an explanation of the large undercooling necessary to nucleate on the Cu(100) surface, relative to Cu(111), whose surface is more similar to the nucleating phase due to the presence of the prefreezing layer

Risk of major cardiovascular events in patients with psoriasis receiving biologic therapies: a prospective cohort study

Background: The cardiovascular safety profile of biologic therapies used for psoriasis is unclear. Objectives: To compare the risk of major cardiovascular events (CVEs; acute coronary syndrome, unstable angina, myocardial infarction and stroke) in patients with chronic plaque psoriasis treated with adalimumab, etanercept or ustekinumab in a large prospective cohort. Methods: Prospective cohort study examining the comparative risk of major CVEs was conducted using the British Association of Dermatologists Biologics and Immunomodulators Register. The main analysis compared adults with chronic plaque psoriasis receiving ustekinumab with tumour necrosis‐α inhibitors (TNFi: etanercept and adalimumab), whilst the secondary analyses compared ustekinumab, etanercept or methotrexate against adalimumab. Hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated using overlap weights by propensity score to balance baseline covariates among comparison groups. Results: We included 5468 biologic‐naïve patients subsequently exposed (951 ustekinumab; 1313 etanercept; and 3204 adalimumab) in the main analysis. The secondary analyses also included 2189 patients receiving methotrexate. The median (p25–p75) follow‐up times for patients using ustekinumab, TNFi, adalimumab, etanercept and methotrexate were as follows: 2.01 (1.16–3.21), 1.93 (1.05–3.34), 1.94 (1.09–3.32), 1.92 (0.93–3.45) and 1.43 (0.84–2.53) years, respectively. Ustekinumab, TNFi, adalimumab, etanercept and methotrexate groups had 7, 29, 23, 6 and 9 patients experiencing major CVEs, respectively. No differences in the risk of major CVEs were observed between biologic therapies [adjusted HR for ustekinumab vs. TNFi: 0.96 (95% CI 0.41–2.22); ustekinumab vs. adalimumab: 0.81 (0.30–2.17); etanercept vs. adalimumab: 0.81 (0.28–2.30)] and methotrexate against adalimumab [1.05 (0.34–3.28)]. Conclusions: In this large prospective cohort study, we found no significant differences in the risk of major CVEs between three different biologic therapies and methotrexate. Additional studies, with longer term follow‐up, are needed to investigate the potential effects of biologic therapies on incidence of major CVEs

Development and validation of a multivariable risk prediction model for serious infection in patients with psoriasis receiving systemic therapy

BACKGROUND: Patients with psoriasis are often concerned about the risk of serious infection associated with systemic psoriasis treatments. OBJECTIVES: To develop and externally validate a prediction model for serious infection in patients with psoriasis within 1 year of starting systemic therapies. METHODS: The risk prediction model was developed using the British Association of Dermatologists Biologic Interventions Register (BADBIR), and the German Psoriasis Registry PsoBest was used as the validation dataset. Model discrimination and calibration were assessed internally and externally using the C-statistic, the calibration slope and the calibration in the large. RESULTS: Overall 175 (1·7%) out of 10 033 participants from BADBIR and 41 (1·7%) out of 2423 participants from PsoBest developed a serious infection within 1 year of therapy initiation. Selected predictors in a multiple logistic regression model included nine baseline covariates, and starting infliximab was the strongest predictor. Evaluation of model performance showed a bootstrap optimism-corrected C-statistic of 0·64 [95% confidence interval (CI) 0·60-0·69], calibration in the large of 0·02 (95% CI -0·14 to 0·17) and a calibration slope of 0·88 (95% CI 0·70-1·07), while external validation performance was poor, with C-statistic 0·52 (95% CI 0·42-0·62), calibration in the large 0·06 (95% CI -0·25 to 0·37) and calibration slope 0·36 (95% CI -0·24 to 0·97). CONCLUSIONS: We present the first results of the development of a multivariable prediction model. This model may help patients and dermatologists in the U.K. and the Republic of Ireland to identify modifiable risk factors and inform therapy choice in a shared decision-making process

Genomic epidemiology reveals geographical clustering of multidrug-resistant Escherichia coli ST131 associated with bacteraemia in Wales

Antibiotic resistance is a significant global public health concern. Uropathogenic Escherichia coli sequence type (ST)131, a widely prevalent multidrug-resistant clone, is frequently associated with bacteraemia. This study investigates third-generation cephalosporin resistance in bloodstream infections caused by E. coli ST131. From 2013-2014 blood culture surveillance in Wales, 142 E. coli ST131 genomes were studied alongside global data. All three major ST131 clades were represented across Wales, with clade C/H30 predominant (n = 102/142, 71.8%). Consistent with global findings, Welsh strains of clade C/H30 contain β-lactamase genes from the blaCTX-M-1 group (n = 65/102, 63.7%), which confer resistance to third-generation cephalosporins. Most Welsh clade C/H30 genomes belonged to sub-clade C2/H30Rx (58.3%). A Wales-specific sub-lineage, named GB-WLS.C2, diverged around 1996-2000. An introduction to North Wales around 2002 led to a localised cluster by 2009, depicting limited genomic diversity within North Wales. This investigation emphasises the value of genomic epidemiology, allowing the detection of genetically similar strains in local areas, enabling targeted and timely public health interventions

Elective Cancer Surgery in COVID-19-Free Surgical Pathways During the SARS-CoV-2 Pandemic: An International, Multicenter, Comparative Cohort Study.

PURPOSE: As cancer surgery restarts after the first COVID-19 wave, health care providers urgently require data to determine where elective surgery is best performed. This study aimed to determine whether COVID-19-free surgical pathways were associated with lower postoperative pulmonary complication rates compared with hospitals with no defined pathway. PATIENTS AND METHODS: This international, multicenter cohort study included patients who underwent elective surgery for 10 solid cancer types without preoperative suspicion of SARS-CoV-2. Participating hospitals included patients from local emergence of SARS-CoV-2 until April 19, 2020. At the time of surgery, hospitals were defined as having a COVID-19-free surgical pathway (complete segregation of the operating theater, critical care, and inpatient ward areas) or no defined pathway (incomplete or no segregation, areas shared with patients with COVID-19). The primary outcome was 30-day postoperative pulmonary complications (pneumonia, acute respiratory distress syndrome, unexpected ventilation). RESULTS: Of 9,171 patients from 447 hospitals in 55 countries, 2,481 were operated on in COVID-19-free surgical pathways. Patients who underwent surgery within COVID-19-free surgical pathways were younger with fewer comorbidities than those in hospitals with no defined pathway but with similar proportions of major surgery. After adjustment, pulmonary complication rates were lower with COVID-19-free surgical pathways (2.2% v 4.9%; adjusted odds ratio [aOR], 0.62; 95% CI, 0.44 to 0.86). This was consistent in sensitivity analyses for low-risk patients (American Society of Anesthesiologists grade 1/2), propensity score-matched models, and patients with negative SARS-CoV-2 preoperative tests. The postoperative SARS-CoV-2 infection rate was also lower in COVID-19-free surgical pathways (2.1% v 3.6%; aOR, 0.53; 95% CI, 0.36 to 0.76). CONCLUSION: Within available resources, dedicated COVID-19-free surgical pathways should be established to provide safe elective cancer surgery during current and before future SARS-CoV-2 outbreaks