A close-packed sphere model for characterising porous networks in atomistic simulations and its application in energy storage and conversion

Hierarchical (micro, meso & macro) porosity in materials plays a crucial role in influencing the movement of ions which governs the energy and power density during energy storage and conversion. The extant available methods to characterise porosity across scales (nano to meso to macro) lacks rigour and accuracy. Having accurate assessment of the porosity in materials can unlock new designs of electrodes for energy efficient energy storage and conversion devices such as batteries, supercapacitors and fuel cells. Through this work, we report the systematic development of a method to fully characterise the carbon porous networks using a molecular dynamics simulation testbed. Our work entails modelling and simulation of porous carbon structures using quenched molecular dynamics (QMD) simulations using Gaussian Approximation potential (GAP) and benchmarking the results with prior literature. This modelling technique can reliably be used for quantitative characterisation of the interconnectivity in porous structures to study ionic movements and charge transfer mechanisms. A new parameter, namely nearest neighbour search (NNS) coefficient was introduced to quantify homogeneity and networking in the porous structures. NNS coefficient increased from 1.62 to 1.92 with decrease of the annealing temperature from 8000 K to 4000 K in carbon. The procedure outlined was although tested on porous carbon networks, but adaptable to study any other material system at multi-length scales

Sleeve gastrectomy and the risk of leak: a systematic analysis of 4,888 patients

Abstract Introduction Sleeve gastrectomy has become a popular stand-alone bariatric procedure with comparable weight loss and resolution of comorbidities to that of laparoscopic gastric bypass. The simplicity of the procedure and the decreased long-term risk profile make this surgery more appealing. Nonetheless, the ever present risk of a staple-line leak is still of great concern and needs further investigation. Methods An electronic literature search of MEDLINE database plus manual reference checks of articles published on laparoscopic sleeve gastrectomy for morbid obesity and its complications was completed. Keywords used in the search were ''sleeve gastrectomy'' OR ''gastric sleeve'' AND ''leak.'' We analyzed 29 publications, including 4,888 patients. We analyzed the frequency of leak after sleeve gastrectomy and its associated risks of causation. Results The risk of leak after sleeve gastrectomy in all comers was 2.4%. This risk was 2.9% in the super-obese [body mass index (BMI) [ 50 kg/m 2 ] and 2.2% for BMI \ 50 kg/m 2 . Staple height and use of buttressing material did not affect leak rate. The use of a size 40-Fr or greater bougie was associated with a leak rate of 0.6% compared with those who used smaller sizes whose leak rate was 2.8%. Leaks were found at the proximal third of the stomach in 89% of cases. Most leaks were diagnosed after discharge. Endoscopic management is a viable option for leaks and was documented in 11% of cases as successful. Conclusions Sleeve gastrectomy has become an important surgical option for the treatment of the ever growing morbidly obese population. The risk of leak is low at 2.4%. Attention to detail specifically at the esophagogastric junction cannot be stressed enough. Careful patient selection (BMI \ 50 kg/m 2 ) and adopting the use of a 40-Fr or larger bougie may decrease the risk of leak. Vigilant followup during the first 30 days is critical to avoid catastrophe, because most leaks will happen after patient discharge

Role of KCNMA1 gene in breast cancer invasion and metastasis to brain

International audienceBACKGROUND: The prognosis for patients with breast tumor metastases to brain is extremely poor. Identification of prognostic molecular markers of the metastatic process is critical for designing therapeutic modalities for reducing the occurrence of metastasis. Although ubiquitously present in most human organs, large-conductance calcium- and voltage-activated potassium channel (BKCa) channels are significantly upregulated in breast cancer cells. In this study we investigated the role of KCNMA1 gene that encodes for the pore-forming alpha-subunit of BKCa channels in breast cancer metastasis and invasion. METHODS: We performed Global exon array to study the expression of KCNMA1 in metastatic breast cancer to brain, compared its expression in primary breast cancer and breast cancers metastatic to other organs, and validated the findings by RT-PCR. Immunohistochemistry was performed to study the expression and localization of BKCa channel protein in primary and metastatic breast cancer tissues and breast cancer cell lines. We performed matrigel invasion, transendothelial migration and membrane potential assays in established lines of normal breast cells (MCF-10A), non-metastatic breast cancer (MCF-7), non-brain metastatic breast cancer cells (MDA-MB-231), and brain-specific metastatic breast cancer cells (MDA-MB-361) to study whether BKCa channel inhibition attenuates breast tumor invasion and metastasis using KCNMA1 knockdown with siRNA and biochemical inhibition with Iberiotoxin (IBTX). RESULTS: The Global exon array and RT-PCR showed higher KCNMA1 expression in metastatic breast cancer in brain compared to metastatic breast cancers in other organs. Our results clearly show that metastatic breast cancer cells exhibit increased BKCa channel activity, leading to greater invasiveness and transendothelial migration, both of which could be attenuated by blocking KCNMA1. CONCLUSION: Determining the relative abundance of BKCa channel expression in breast cancer metastatic to brain and the mechanism of its action in brain metastasis will provide a unique opportunity to identify and differentiate between low grade breast tumors that are at high risk for metastasis from those at low risk for metastasis. This distinction would in turn allow for the appropriate and efficient application of effective treatments while sparing patients with low risk for metastasis from the toxic side effects of chemotherapy

Clinical Features of Critical Coronavirus Disease 2019 in Children

This article is made available for unrestricted research re-use and secondary analysis in any form or be any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic.Objectives: We sought to describe the presentation, course, and outcomes of hospitalized pediatric coronavirus disease 2019 patients, with detailed description of those requiring mechanical ventilation, and comparisons between critically ill and noncritical hospitalized pediatric patients. Design: Observational cohort study. Setting: Riley Hospital for Children at Indiana University Health in Indianapolis in the early weeks of the coronavirus disease 2019 pandemic. Patients: All hospitalized pediatric patients with confirmed coronavirus disease 2019 as of May 4, 2020, were included. Interventions: Patients received therapies including hydroxychloroquine, remdesivir, tocilizumab, and convalescent serum and were managed according to an institutional algorithm based on evidence available at the time of presentation. Measurements and Main Results: Of 407 children tested for severe acute respiratory syndrome-coronavirus 2 at our hospital, 24 were positive, and 19 required hospitalization. Seven (36.8%) were critically ill in ICU, and four (21%) required mechanical ventilation. Hospitalized children were predominantly male (14, 74%) and African-American or Hispanic (14, 74%), with a bimodal distribution of ages among young children less than or equal to 2 years old (8, 42%) and older adolescents ages 15–18 (6, 32%). Five of seven (71.4%) of critically ill patients were African-American (n = 3) or Hispanic (n = 2). Critical illness was associated with older age (p = 0.017), longer duration of symptoms (p = 0.036), and lower oxygen saturation on presentation (p = 0.016); with more thrombocytopenia (p = 0.015); higher C-reactive protein (p = 0.031); and lower WBC count (p = 0.039). Duration of mechanical ventilation averaged 14.1 days. One patient died. Conclusions: Severe, protracted coronavirus disease 2019 is seen in pediatric patients, including those without significant comorbidities. We observed a greater proportion of hospitalized children requiring mechanical ventilation than has been reported to date. Older children, African-American or Hispanic children, and males may be at risk for severe coronavirus disease 2019 requiring hospitalization. Hypoxia, thrombocytopenia, and elevated C-reactive protein may be useful markers of critical illness. Data regarding optimal management and therapies for pediatric coronavirus disease 2019 are urgently needed.This work was supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development at the National Institutes of Health (grant numbers K23 HD095778, T32 HD069047); and by the National Institute of Allergy and Infectious at the National Institutes of Health Diseases (grant number T32 AI07637). Drs. Bhumbra, Malin, Khaitan, John, Rowan, and Enane disclosed off-label use of remdesivir, convalescent plasma, hydroxychloroquine, and tocilizumab. Drs. Kirkpatrick and Enane are supported by the Eunice Kennedy Shriver National Institute of Child Health and Human Development at the National Institutes of Health (grant numbers K23 HD095778, T32 HD069047). Dr. Bhumbra is supported by the National Institute of Allergy and Infectious at the National Institutes of Health Diseases (grant number T32 AI07637)

Towards learning and verifying invariants of cyber-physical systems by code mutation

Cyber-physical systems (CPS), which integrate algorithmic control with physical processes, often consist of physically distributed components communicating over a network. A malfunctioning or compromised component in such a CPS can lead to costly consequences, especially in the context of public infrastructure. In this short paper, we argue for the importance of constructing invariants (or models) of the physical behaviour exhibited by CPS, motivated by their applications to the control, monitoring, and attestation of components. To achieve this despite the inherent complexity of CPS, we propose a new technique for learning invariants that combines machine learning with ideas from mutation testing. We present a preliminary study on a water treatment system that suggests the efficacy of this approach, propose strategies for establishing confidence in the correctness of invariants, then summarise some research questions and the steps we are taking to investigate them.Comment: Short paper accepted by the 21st International Symposium on Formal Methods (FM 2016

Simulations of events for the LUX-ZEPLIN (LZ) dark matter experiment

The LUX-ZEPLIN dark matter search aims to achieve a sensitivity to the WIMP-nucleon spin-independent cross-section down to (1–2)×10−12 pb at a WIMP mass of 40 GeV/c2. This paper describes the simulations framework that, along with radioactivity measurements, was used to support this projection, and also to provide mock data for validating reconstruction and analysis software. Of particular note are the event generators, which allow us to model the background radiation, and the detector response physics used in the production of raw signals, which can be converted into digitized waveforms similar to data from the operational detector. Inclusion of the detector response allows us to process simulated data using the same analysis routines as developed to process the experimental data

Emergent Properties of Tumor Microenvironment in a Real-life Model of Multicell Tumor Spheroids

Multicellular tumor spheroids are an important {\it in vitro} model of the pre-vascular phase of solid tumors, for sizes well below the diagnostic limit: therefore a biophysical model of spheroids has the ability to shed light on the internal workings and organization of tumors at a critical phase of their development. To this end, we have developed a computer program that integrates the behavior of individual cells and their interactions with other cells and the surrounding environment. It is based on a quantitative description of metabolism, growth, proliferation and death of single tumor cells, and on equations that model biochemical and mechanical cell-cell and cell-environment interactions. The program reproduces existing experimental data on spheroids, and yields unique views of their microenvironment. Simulations show complex internal flows and motions of nutrients, metabolites and cells, that are otherwise unobservable with current experimental techniques, and give novel clues on tumor development and strong hints for future therapies.Comment: 20 pages, 10 figures. Accepted for publication in PLOS One. The published version contains links to a supplementary text and three video file

Projected sensitivity of the LUX-ZEPLIN experiment to the 0νββ decay of Xe 136

The LUX-ZEPLIN (LZ) experiment will enable a neutrinoless double β decay search in parallel to the main science goal of discovering dark matter particle interactions. We report the expected LZ sensitivity to Xe136 neutrinoless double β decay, taking advantage of the significant (>600 kg) Xe136 mass contained within the active volume of LZ without isotopic enrichment. After 1000 live-days, the median exclusion sensitivity to the half-life of Xe136 is projected to be 1.06×1026 years (90% confidence level), similar to existing constraints. We also report the expected sensitivity of a possible subsequent dedicated exposure using 90% enrichment with Xe136 at 1.06×1027 years