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The landscape of selection in 551 esophageal adenocarcinomas defines genomic biomarkers for the clinic
Esophageal adenocarcinoma (EAC) is a poor-prognosis cancer type with rapidly rising incidence. Understanding of the genetic events driving EAC development is limited, and there are few molecularExpand
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High‐throughput screening techniques for rapid PEG‐based precipitation of IgG4 mAb from clarified cell culture supernatant
Locating optimal protein precipitation conditions for complex biological feed materials is problematic. This article describes the application of a series of high‐throughput platforms for the rapidExpand
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Predicting the Risk of Inpatient Hypoglycemia With Machine Learning Using Electronic Health Records
OBJECTIVE We analyzed data from inpatients with diabetes admitted to a large university hospital to predict the risk of hypoglycemia through the use of machine learning algorithms. RESEARCH DESIGNExpand
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Authentication and characterisation of a new oesophageal adenocarcinoma cell line: MFD-1
New biological tools are required to understand the functional significance of genetic events revealed by whole genome sequencing (WGS) studies in oesophageal adenocarcinoma (OAC). The MFD-1 cellExpand
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Invasive versus non-invasive management of older patients with non-ST elevation myocardial infarction (SENIOR-NSTEMI): a cohort study based on routine clinical data
Summary Background Previous trials suggest lower long-term risk of mortality after invasive rather than non-invasive management of patients with non-ST elevation myocardial infarction (NSTEMI), butExpand
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Azithromycin in patients admitted to hospital with COVID-19 (RECOVERY): a randomised, controlled, open-label, platform trial
Background Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatory actions. We aimed to evaluate the safety and efficacy of azithromycin in patientsExpand
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Community Climate System Model (CCSM)
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Cluster File Systems
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Inpatient hypoglycaemia: understanding who is at risk
We analysed data obtained from the electronic patient records of inpatients with diabetes admitted to a large university hospital to understand the prevalence and distribution of inpatientExpand
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A spiking neural network model of spatial and visual mental imagery
TLDR
We built a spiking neural model that can perform mental rotation and mental map scanning using strategies informed by the psychology and neuroscience literature. Expand
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