24 research outputs found

    Piezo buffers mechanical stress via modulation of intracellular Ca 2+ handling in the Drosophila heart

    Get PDF
    Throughout its lifetime the heart is buffeted continuously by dynamic mechanical forces resulting from contraction of the heart muscle itself and fluctuations in haemodynamic load and pressure. These forces are in flux on a beat-by-beat basis, resulting from changes in posture, physical activity or emotional state, and over longer timescales due to altered physiology (e.g. pregnancy) or as a consequence of ageing or disease (e.g. hypertension). It has been known for over a century of the heart’s ability to sense differences in haemodynamic load and adjust contractile force accordingly[1-4]. These adaptive behaviours are important for cardiovascular homeostasis, but the mechanism(s) underpinning them are incompletely understood. Here we present evidence that the mechanically-activated ion channel, Piezo, is an important component of the Drosophila heart’s ability to adapt to mechanical force. We find Piezo is a sarcoplasmic reticulum (SR)-resident channel and is part of a mechanism that regulates Ca2+ handling in cardiomyocytes in response to mechanical stress. Our data support a simple model in which Drosophila Piezo transduces mechanical force such as stretch into a Ca2+ signal, originating from the SR, that modulates cardiomyocyte contraction. We show that Piezo mutant hearts fail to buffer mechanical stress, have altered Ca2+ handling, become prone to arrhythmias and undergo pathological remodelling

    COVID-19 trajectories among 57 million adults in England: a cohort study using electronic health records

    Get PDF
    BACKGROUND: Updatable estimates of COVID-19 onset, progression, and trajectories underpin pandemic mitigation efforts. To identify and characterise disease trajectories, we aimed to define and validate ten COVID-19 phenotypes from nationwide linked electronic health records (EHR) using an extensible framework. METHODS: In this cohort study, we used eight linked National Health Service (NHS) datasets for people in England alive on Jan 23, 2020. Data on COVID-19 testing, vaccination, primary and secondary care records, and death registrations were collected until Nov 30, 2021. We defined ten COVID-19 phenotypes reflecting clinically relevant stages of disease severity and encompassing five categories: positive SARS-CoV-2 test, primary care diagnosis, hospital admission, ventilation modality (four phenotypes), and death (three phenotypes). We constructed patient trajectories illustrating transition frequency and duration between phenotypes. Analyses were stratified by pandemic waves and vaccination status. FINDINGS: Among 57 032 174 individuals included in the cohort, 13 990 423 COVID-19 events were identified in 7 244 925 individuals, equating to an infection rate of 12·7% during the study period. Of 7 244 925 individuals, 460 737 (6·4%) were admitted to hospital and 158 020 (2·2%) died. Of 460 737 individuals who were admitted to hospital, 48 847 (10·6%) were admitted to the intensive care unit (ICU), 69 090 (15·0%) received non-invasive ventilation, and 25 928 (5·6%) received invasive ventilation. Among 384 135 patients who were admitted to hospital but did not require ventilation, mortality was higher in wave 1 (23 485 [30·4%] of 77 202 patients) than wave 2 (44 220 [23·1%] of 191 528 patients), but remained unchanged for patients admitted to the ICU. Mortality was highest among patients who received ventilatory support outside of the ICU in wave 1 (2569 [50·7%] of 5063 patients). 15 486 (9·8%) of 158 020 COVID-19-related deaths occurred within 28 days of the first COVID-19 event without a COVID-19 diagnoses on the death certificate. 10 884 (6·9%) of 158 020 deaths were identified exclusively from mortality data with no previous COVID-19 phenotype recorded. We observed longer patient trajectories in wave 2 than wave 1. INTERPRETATION: Our analyses illustrate the wide spectrum of disease trajectories as shown by differences in incidence, survival, and clinical pathways. We have provided a modular analytical framework that can be used to monitor the impact of the pandemic and generate evidence of clinical and policy relevance using multiple EHR sources. FUNDING: British Heart Foundation Data Science Centre, led by Health Data Research UK

    Alien Registration- Denholm, Mary (Rumford, Oxford County)

    Get PDF
    https://digitalmaine.com/alien_docs/12677/thumbnail.jp
    corecore