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Risk factor associations for severe COVID-19, influenza and pneumonia in people with diabetes to inform future pandemic preparations : UK population-based cohort study
Get PDFObjective: This study aimed to compare clinical and sociodemographic risk factors for severe COVID-19, influenza and pneumonia, in people with diabetes.
Design: Population-based cohort study.
Setting: UK primary care records (Clinical Practice Research Datalink) linked to mortality and hospital records.
Participants: Individuals with type 1 and type 2 diabetes (COVID-19 cohort: n=43 033 type 1 diabetes and n=584 854 type 2 diabetes, influenza and pneumonia cohort: n=42 488 type 1 diabetes and n=585 289 type 2 diabetes).
Primary and secondary outcome measures: COVID-19 hospitalisation from 1 February 2020 to 31 October 2020 (pre-COVID-19 vaccination roll-out), and influenza and pneumonia hospitalisation from 1 September 2016 to 31 May 2019 (pre-COVID-19 pandemic). Secondary outcomes were COVID-19 and pneumonia mortality. Associations between clinical and sociodemographic risk factors and each outcome were assessed using multivariable Cox proportional hazards models. In people with type 2 diabetes, we explored modifying effects of glycated haemoglobin (HbA1c) and body mass index (BMI) by age, sex and ethnicity.
Results: In type 2 diabetes, poor glycaemic control and severe obesity were consistently associated with increased risk of hospitalisation for COVID-19, influenza and pneumonia. The highest HbA1c and BMI-associated relative risks were observed in people aged under 70 years. Sociodemographic-associated risk differed markedly by respiratory infection, particularly for ethnicity. Compared with people of white ethnicity, black and south Asian groups had a greater risk of COVID-19 hospitalisation, but a lesser risk of pneumonia hospitalisation. Risk factor associations for type 1 diabetes and for type 2 diabetes mortality were broadly consistent with the primary analysis.
Conclusions: Clinical risk factors of high HbA1c and severe obesity are consistently associated with severe outcomes from COVID-19, influenza and pneumonia, especially in younger people. In contrast, associations with sociodemographic risk factors differed by type of respiratory infection. This emphasises that risk stratification should be specific to individual respiratory infections
LEVA : Using large language models to enhance visual analytics
Get PDFVisual analytics supports data analysis tasks within complex domain problems. However, due to the richness of data types, visual designs, and interaction designs, users need to recall and process a significant amount of information when they visually analyze data. These challenges emphasize the need for more intelligent visual analytics methods. Large language models have demonstrated the ability to interpret various forms of textual data, offering the potential to facilitate intelligent support for visual analytics. We propose LEVA, a framework that uses large language models to enhance users' VA workflows at multiple stages: onboarding, exploration, and summarization. To support onboarding, we use large language models to interpret visualization designs and view relationships based on system specifications. For exploration, we use large language models to recommend insights based on the analysis of system status and data to facilitate mixed-initiative exploration. For summarization, we present a selective reporting strategy to retrace analysis history through a stream visualization and generate insight reports with the help of large language models. We demonstrate how LEVA can be integrated into existing visual analytics systems. Two usage scenarios and a user study suggest that LEVA effectively aids users in conducting visual analytics
Singular thought without temporal representation?
Get PDFWhat is required for an individual to entertain a singular thought about an object they have encountered before but that is currently no longer within their perceptual range? More specifically, does the individual have to think about the object as having been encountered in the past? I consider this question against the background of the assumption that non-human animals are cognitively ‘stuck in the present’. Does this mean that, for them, ‘out of sight is out of mind’, as, e.g., Schopenhauer seems to have thought? I suggest an alternative answer, also drawing on some empirical work on animal cognition
Purification and characterisation of the platelet-activating GPVI/FcRγ complex in SMALPs
Get PDFThe collagen/fibrin(ogen) receptor, glycoprotein VI (GPVI), is a platelet activating receptor and a promising anti-thrombotic drug target. However, while agonist-induced GPVI clustering on platelet membranes has been shown to be essential for its activation, it is unknown if GPVI dimerisation represents a unique conformation for ligand binding. Current GPVI structures all contain only the two immunoglobulin superfamily (IgSF) domains in the GPVI extracellular region, so lacking the mucin-like stalk, transmembrane, cytoplasmic tail of GPVI and its associated Fc receptor γ (FcRγ) homodimer signalling chain, and provide contradictory insights into the mechanisms of GPVI dimerisation. Here, we utilised styrene maleic-acid lipid particles (SMALPs) to extract GPVI in complex with its two associated FcRγ chains from transfected HEK-293T cells, together with the adjacent lipid bilayer, then purified and characterised the GPVI/FcRγ-containing SMALPs, to enable structural insights into the full-length GPVI/FcRγ complex. Using size exclusion chromatography followed by a native polyacrylamide gel electrophoresis (PAGE) method, SMA-PAGE, we revealed multiple sizes of the purified GPVI/FcRγ SMALPs, suggesting the potential existence of GPVI oligomers. Importantly, GPVI/FcRγ SMALPs were functional as they could bind collagen. Mono-dispersed GPVI/FcRγ SMALPs could be observed under negative stain electron microscopy. These results pave the way for the future investigation of GPVI stoichiometry and structure, while also validating SMALPs as a promising tool for the investigation of human membrane protein interactions, stoichiometry and structure. [Abstract copyright: Copyright © 2024 The Authors. Published by Elsevier Inc. All rights reserved.
Operation Soteria : improving CPS responses to rape complaints and complainants : summary briefing
Get PDFA case for animal reference : beyond functional reference and meaning attribution
Get PDFReference is a basic feature of human language. A much debated question in the scholarship on animal communication and language evolution is whether traces of the human capacity for reference can be found in animals too. Do animals refer to things with their signals in the manner that humans do? Or is reference something that is unique to human communication? Answers to these questions have shifted significantly over the years and remain contentious. In this paper, I start by reconstructing and critically analysing three influential discussions of the ways in which animal signals refer: the theory of functional reference (Marler, Evans and Hauser, 1992), Wheeler and Fischer (2012)’s meaning attribution framework, and Scarantino (2013)’s revised definition of functional reference. I show that functional reference, both in its traditional and revised version, as well as the meaning attribution framework, fail to adequately characterise animal reference as an evolutionary precursor of linguistic reference. This is because they all overlook at least some aspects of the psychology of signal production. Nonetheless, drawing on Crockford et al. (2012, 2017), I show that we can plausibly interpret chimpanzees’ alert hoos as a case of intentional, human-like animal reference
Metro Station functional clustering and dual-view recurrent graph convolutional network for metro passenger flow prediction
No full textMaDDOSY (Mass Determination Diffusion Ordered Spectroscopy) using an 80 MHz bench top NMR for the rapid determination of polymer and macromolecular molecular weight
Get PDFMeasurement of molecular weight is an integral part of macromolecular and polymer characterization which usually has limitations. Herein, this article presents the use of a bench-top 80 MHz Nuclear Magnetic Resonance (NMR) spectrometer for diffusion-ordered spectroscopy as a practical and rapid approach for the determination of molecular weight/size using a novel solvent and polymer-independent universal calibration
Bismuth nanoparticles anchored on N-doped graphite felts to give stable and efficient iron-chromium redox flow batteries
No full textIron-chromium redox flow batteries (ICRFBs) use abundant and inexpensive chromium and iron as the active substances in the electrolyte and have great potential as a cost-effective and large-scale energy storage system. However, they are still plagued by several issues, such as the low electrochemical activity of Cr3+/Cr2+ and the occurrence of the undesired hydrogen evolution reaction (HER). We report the synthesis of amorphous bismuth (Bi) nanoparticles (NPs) immobilized on N-doped graphite felts (GFs) by a combined self-polymerization and wet-chemistry reduction strategy followed by annealing, which are used as the negative electrodes for ICRFBs. The resulting Bi NPs react with H+ to form intermediates and greatly inhibit the parasitic HER. In addition, the combined effect of Bi and N dopants on the surface of GF dramatically increases the electrochemical activity of Fe2+/Fe3+ and Cr3+/Cr2+, reduces the charge transfer resistance, and increases the mass transfer rate compared to plain GF. At the optimum Bi/N ratio of 2, a high coulombic efficiency of up to 97.7% is maintained even for 25 cycles at different current densities, the energy efficiency reaches 85.8% at 60.0 mA cm−2, exceeding many other reported materials, and the capacity reaches 862.7 mAh L−1 after 100 cycles, which is about 5.3 times that of bare GF