A non-invasive, home-based EEG hypoglycaemia warning system for personal monitoring using skin surface electrodes : a single-case feasibility study

Hypoglycaemia unawareness is a common condition associated with increased risk of severe hypoglycaemia. The purpose of the authors' study was to develop a simple to use, home-based and non-invasive hypoglycaemia warning system based on electroencephalography (EEG), and to demonstrate its use in a single-case feasibility study. Methods: A participant with type 1 diabetes forms a single-person case study where blood sugar levels and EEG were recorded. EEG was recorded using skin surface electrodes placed behind the ear located within the T3 region by the participant in the home. EEG was analysed retrospectively to develop an algorithm which would trigger a warning if EEG changes associated with hypoglycaemia onset were detected. Results: All hypoglycaemia events were detected by the EEG hypoglycaemia warning algorithm. Warnings were triggered with blood glucose concentration levels at or below 4.2 mmol/l in this participant and no warnings were issued when in euglycaemia. Conclusion: The feasibility of a non-invasive EEG-based hypoglycaemia warning system for personal monitoring in the home has been demonstrated in a single case study. The results suggest that further studies are warranted to evaluate the system prospectively in a larger group of participants

The effect of beat interval on ventricular repolarisation in atrial fibrillation

© 2018 Creative Commons Attribution. Atrial fibrillation (AF) is characterised by rapid beat interval changes. The aim of the study was to investigate the effect of such changes on ECG ventricular repolarisation characteristics. In 10 AF recordings beat averaging of lead V4 was used to generate averaged T waves where the preceding beat interval (R-R) was either short (625+/-25 ms) or long (1075+/-25 ms). The amplitudes of T wave (T amp) and T wave end, defined as the TU nadir, (TUn amp), and the intervals for R wave to T wave peak (R-T) and R wave to T wave end (R-TUn) where measured from these average beats. Difference in measured T wave characteristics between short and long beat intervals were quantified. All measurements increased significantly for long preceding beat intervals compared to short: T amp (mean±SD) 0.31±0.17 mV (short) vs 0.35±0.20 mV (long) (p = 0.04); TUn amp 0.00±0.02 mV (short) vs 0.03±0.03 mV (long) (p = 0.009); R-T 251.7±13.5 ms (short) vs 264.2±12 ms (long) (p = 0.002) and R-TUn 376.5±31 ms (short) vs 392±26.5 ms (long) (p=0.027). ECG T wave characteristics are significantly affected by preceding ventricular beat interval in AF

Beta-decay properties of 25^{25}Si and 26^{26}P

The $\beta$-decay properties of the neutron-deficient nuclei $^{25}$Si and $^{26}$P have been investigated at the GANIL/LISE3 facility by means of charged-particle and $\gamma$-ray spectroscopy. The decay schemes obtained and the Gamow-Teller strength distributions are compared to shell-model calculations based on the USD interaction. B(GT) values derived from the absolute measurement of the $\beta$-decay branching ratios give rise to a quenching factor of the Gamow-Teller strength of 0.6. A precise half-life of 43.7 (6) ms was determined for $^{26}$P, the $\beta$- (2)p decay mode of which is described

Human HELB is a processive motor protein that catalyzes RPA clearance from single-stranded DNA

Human DNA helicase B (HELB) is a poorly characterized helicase suggested to play both positive and negative regulatory roles in DNA replication and recombination. In this work, we used bulk and single-molecule approaches to characterize the biochemical activities of HELB protein with a particular focus on its interactions with Replication Protein A (RPA) and RPA–single-stranded DNA (ssDNA) filaments. HELB is a monomeric protein that binds tightly to ssDNA with a site size of ∼20 nucleotides. It couples ATP hydrolysis to translocation along ssDNA in the 5′ to 3′ direction accompanied by the formation of DNA loops. HELB also displays classical helicase activity, but this is very weak in the absence of an assisting force. HELB binds specifically to human RPA, which enhances its ATPase and ssDNA translocase activities but inhibits DNA unwinding. Direct observation of HELB on RPA nucleoprotein filaments shows that translocating HELB concomitantly clears RPA from ssDNA. This activity, which can allow other proteins access to ssDNA intermediates despite their shielding by RPA, may underpin the diverse roles of HELB in cellular DNA transactions.[Significance] Single-stranded DNA (ssDNA) is a key intermediate in many cellular DNA transactions, including DNA replication, repair, and recombination. Nascent ssDNA is rapidly bound by the Replication Protein A (RPA) complex, forming a nucleoprotein filament that both stabilizes ssDNA and mediates downstream processing events. Paradoxically, however, the very high affinity of RPA for ssDNA may block the recruitment of further factors. In this work, we show that RPA–ssDNA nucleoprotein filaments are specifically targeted by the human HELB helicase. Recruitment of HELB by RPA–ssDNA activates HELB translocation activity, leading to processive removal of upstream RPA complexes. This RPA clearance activity may underpin the diverse roles of HELB in replication and recombination.Work in the laboratory of M.S.D. was supported by an Elizabeth Blackwell Early Career Fellowship from the University of Bristol (to O.J.W.) and Wellcome Trust Investigator Grant 100401/Z/12/Z (to M.S.D.). Work in the laboratory of E.A. was supported by NIH Grants GM130746 (to E.A.) and GM133967 (to E.A.). F.M.-H. acknowledges support from the European Research Council under European Union Horizon 2020 Research and Innovation Program Grant Agreement 681299. Work in the laboratory of F.M.-H. was also supported by Spanish Ministry of Science and Innovation Grants BFU2017-83794-P (AEI/FEDER, UE; to F.M.-H.) and PID2020-112998GB-100 (AEI/10.13039/501100011033; to F.M.-H.) and Comunidad de Madrid Grants Tec4-Bio–S2018/NMT-4443 (to F.M.-H.) and NanoBioCancer–Y2018/BIO-4747 (to F.M.-H.)

Predicting pharmaceutical powder flow from microscopy images using deep learning

The powder flowability of active pharmaceutical ingredients and excipients is a key parameter in the manufacturing of solid dosage forms used to inform the choice of tabletting methods. Direct compression is the favoured tabletting method; however, it is only suitable for materials that do not show cohesive behaviour. For materials that are cohesive, processing methods before tabletting, such as granulation, are required. Flowability measurements require large quantities of materials, significant time and human investments and repeat testing due to a lack of reproducible results when taking experimental measurements. This process is particularly challenging during the early-stage development of a new formulation when the amount of material is limited. To overcome these challenges, we present the use of deep learning methods to predict powder flow from images of pharmaceutical materials. We achieve 98.9% validation accuracy using images which by eye are impossible to extract meaningful particle or flowability information from. Using this approach, the need for experimental powder flow characterization is reduced as our models rely on images which are routinely captured as part of the powder size and shape characterization process. Using the imaging method recorded in this work, images can be captured with only 500 mg of material in just 1 hour. This completely removes the additional 30 g of material and extra measurement time needed to carry out repeat testing for traditional flowability measurements. This data-driven approach can be better applied to early-stage drug development which is by nature a highly iterative process. By reducing the material demand and measurement times, new pharmaceutical products can be developed faster with less material, reducing the costs, limiting material waste and hence resulting in a more efficient, sustainable manufacturing process. This work aims to improve decision-making for manufacturing route selection, achieving the key goal for digital design of being able to better predict properties while minimizing the amount of material required and time to inform process selection during early-stage development

The education effect: higher educational qualifications are robustly associated with beneficial personal and socio-political outcomes

Level of education is a predictor of a range of important outcomes, such as political interest and cynicism, social trust, health, well-being, and intergroup attitudes. We address a gap in the literature by analyzing the strength and stability of the education effect associated with this diverse range of outcomes across three surveys covering the period 1986–2011, including novel latent growth analyses of the stability of the education effect within the same individuals over time. Our analyses of the British Social Attitudes Survey, British Household Panel Survey, and International Social Survey Programme indicated that the education effect was robust across these outcomes and relatively stable over time, with higher education levels being associated with higher trust and political interest, better health and well-being, and with less political cynicism and less negative intergroup attitudes. The education effect was strongest when associated with political outcomes and attitudes towards immigrants, whereas it was weakest when associated with health and well-being. Most of the education effect appears to be due to the beneficial consequences of having a university education. Our results demonstrate that this beneficial education effect is also manifested in within-individual changes, with the education effect tending to become stronger as individuals age

Effects of antiplatelet therapy on stroke risk by brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases: subgroup analyses of the RESTART randomised, open-label trial

Background Findings from the RESTART trial suggest that starting antiplatelet therapy might reduce the risk of recurrent symptomatic intracerebral haemorrhage compared with avoiding antiplatelet therapy. Brain imaging features of intracerebral haemorrhage and cerebral small vessel diseases (such as cerebral microbleeds) are associated with greater risks of recurrent intracerebral haemorrhage. We did subgroup analyses of the RESTART trial to explore whether these brain imaging features modify the effects of antiplatelet therapy

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice