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Acute Coronavirus Disease 2019 (COVID-19) has been associated with new-onset cardiovascular disease (CVD) and diabetes mellitus (DM), but it is not known whether COVID-19 has long-term impacts on cardiometabolic outcomes. This study aimed to determine whether the incidence of new DM and CVDs are increased over 12 months after COVID-19 compared with matched controls. We conducted a cohort study from 2020 to 2021 analysing electronic records for 1,356 United Kingdom family practices with a population of 13.4 million. Participants were 428,650 COVID-19 patients without DM or CVD who were individually matched with 428,650 control patients on age, sex, and family practice and followed up to January 2022. Outcomes were incidence of DM and CVD. A difference-in-difference analysis estimated the net effect of COVID-19 allowing for baseline differences, age, ethnicity, smoking, body mass index (BMI), systolic blood pressure, Charlson score, index month, and matched set. Follow-up time was divided into 4 weeks from index date (\"acute COVID-19\"), 5 to 12 weeks from index date (\"post-acute COVID-19\"), and 13 to 52 weeks from index date (\"long COVID-19\"). Net incidence of DM increased in the first 4 weeks after COVID-19 (adjusted rate ratio, RR 1.81, 95% confidence interval (CI) 1.51 to 2.19) and remained elevated from 5 to 12 weeks (RR 1.27, 1.11 to 1.46) but not from 13 to 52 weeks overall (1.07, 0.99 to 1.16). Acute COVID-19 was associated with net increased CVD incidence (5.82, 4.82 to 7.03) including pulmonary embolism (RR 11.51, 7.07 to 18.73), atrial arrythmias (6.44, 4.17 to 9.96), and venous thromboses (5.43, 3.27 to 9.01). CVD incidence declined from 5 to 12 weeks (RR 1.49, 1.28 to 1.73) and showed a net decrease from 13 to 52 weeks (0.80, 0.73 to 0.88). The analyses were based on health records data and participants' exposure and outcome status might have been misclassified. In this study, we found that CVD was increased early after COVID-19 mainly from pulmonary embolism, atrial arrhythmias, and venous thromboses. DM incidence remained elevated for at least 12 weeks following COVID-19 before declining. People without preexisting CVD or DM who suffer from COVID-19 do not appear to have a long-term increase in incidence of these conditions.

COVID-19 is a disease with unique characteristics that include lung thrombosis 1 , frequent diarrhoea 2 , abnormal activation of the inflammatory response 3 and rapid deterioration of lung function consistent with alveolar oedema 4 . The pathological substrate for these findings remains unknown. Here we show that the lungs of patients with COVID-19 contain infected pneumocytes with abnormal morphology and frequent multinucleation. The generation of these syncytia results from activation of the SARS-CoV-2 spike protein at the cell plasma membrane level. On the basis of these observations, we performed two high-content microscopy-based screenings with more than 3,000 approved drugs to search for inhibitors of spike-driven syncytia. We converged on the identification of 83 drugs that inhibited spike-mediated cell fusion, several of which belonged to defined pharmacological classes. We focused our attention on effective drugs that also protected against virus replication and associated cytopathicity. One of the most effective molecules was the antihelminthic drug niclosamide, which markedly blunted calcium oscillations and membrane conductance in spike-expressing cells by suppressing the activity of TMEM16F (also known as anoctamin 6), a calcium-activated ion channel and scramblase that is responsible for exposure of phosphatidylserine on the cell surface. These findings suggest a potential mechanism for COVID-19 disease pathogenesis and support the repurposing of niclosamide for therapy. Lungs from patients who died from COVID-19 show atypical fused cells, the formation of which is mediated by the SARS-CoV-2 spike protein, and drugs that inhibit TMEM16F can prevent spike-induced syncytia formation.

Chronic heart failure continues to impose a substantial health-care burden, despite recent treatment advances. The key pathophysiological process that ultimately leads to chronic heart failure is cardiac remodelling in response to chronic disease stresses. Here, we review recent advances in our understanding of molecular and cellular mechanisms that play a part in the complex remodelling process, with a focus on key molecules and pathways that might be suitable targets for therapeutic manipulation. Such pathways include those that regulate cardiac myocyte hypertrophy, calcium homoeostasis, energetics, and cell survival, and processes that take place outside the cardiac myocyte—eg, in the myocardial vasculature and extracellular matrix. We also discuss major gaps in our current understanding, take a critical look at conventional approaches to target discovery that have been used to date, and consider new investigational avenues that might accelerate clinically relevant discovery.

Machine learning (ML) is a powerful tool for identifying and structuring several informative variables for predictive tasks. Here, we investigated how ML algorithms may assist in echocardiographic pulmonary hypertension (PH) prediction, where current guidelines recommend integrating several echocardiographic parameters. In our database of 90 patients with invasively determined pulmonary artery pressure (PAP) with corresponding echocardiographic estimations of PAP obtained within 24 hours, we trained and applied five ML algorithms (random forest of classification trees, random forest of regression trees, lasso penalized logistic regression, boosted classification trees, support vector machines) using a 10 times 3-fold cross-validation (CV) scheme. ML algorithms achieved high prediction accuracies: support vector machines (AUC 0.83; 95% CI 0.73-0.93), boosted classification trees (AUC 0.80; 95% CI 0.68-0.92), lasso penalized logistic regression (AUC 0.78; 95% CI 0.67-0.89), random forest of classification trees (AUC 0.85; 95% CI 0.75-0.95), random forest of regression trees (AUC 0.87; 95% CI 0.78-0.96). In contrast to the best of several conventional formulae (by Aduen et al.), this ML algorithm is based on several echocardiographic signs and feature selection, with estimated right atrial pressure (RAP) being of minor importance. Using ML, we were able to predict pulmonary hypertension based on a broader set of echocardiographic data with little reliance on estimated RAP compared to an existing formula with non-inferior performance. With the conceptual advantages of a broader and unbiased selection and weighting of data our ML approach is suited for high level assistance in PH prediction.

A pathway triggered by chronic severe hypoxia boosts regeneration of injured hearts in adult mice. Hypoxia pathway linked to heart regeneration Hesham Sadek and colleagues show that a pathway triggered by chronic severe hypoxia boosts the regeneration of injured hearts in adult mice. Mice subjected to myocardial infarction that are placed in a hypoxic environment for a prolonged period make new cardiomyocytes, and recover heart function through a mechanism involving a reduction of reactive oxygen species concentration and cardiomyocyte cell cycle re-entry. Prolonged severe hypoxia is not a viable therapeutic strategy for use in humans, but targeting this pathway can induce myocardial regeneration. The adult mammalian heart is incapable of regeneration following cardiomyocyte loss, which underpins the lasting and severe effects of cardiomyopathy. Recently, it has become clear that the mammalian heart is not a post-mitotic organ. For example, the neonatal heart is capable of regenerating lost myocardium 1 , and the adult heart is capable of modest self-renewal 2 , 3 . In both of these scenarios, cardiomyocyte renewal occurs via the proliferation of pre-existing cardiomyocytes, and is regulated by aerobic-respiration-mediated oxidative DNA damage 4 , 5 . Therefore, we reasoned that inhibiting aerobic respiration by inducing systemic hypoxaemia would alleviate oxidative DNA damage, thereby inducing cardiomyocyte proliferation in adult mammals. Here we report that, in mice, gradual exposure to severe systemic hypoxaemia, in which inspired oxygen is gradually decreased by 1% and maintained at 7% for 2 weeks, results in inhibition of oxidative metabolism, decreased reactive oxygen species production and oxidative DNA damage, and reactivation of cardiomyocyte mitosis. Notably, we find that exposure to hypoxaemia 1 week after induction of myocardial infarction induces a robust regenerative response with decreased myocardial fibrosis and improvement of left ventricular systolic function. Genetic fate-mapping analysis confirms that the newly formed myocardium is derived from pre-existing cardiomyocytes. These results demonstrate that the endogenous regenerative properties of the adult mammalian heart can be reactivated by exposure to gradual systemic hypoxaemia, and highlight the potential therapeutic role of hypoxia in regenerative medicine.

Prognostic characteristics inform risk stratification in intensive care unit (ICU) patients with coronavirus disease 2019 (COVID-19). We obtained blood samples ( n  = 474) from hospitalized COVID-19 patients ( n  = 123), non-COVID-19 ICU sepsis patients ( n  = 25) and healthy controls ( n  = 30). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was detected in plasma or serum (RNAemia) of COVID-19 ICU patients when neutralizing antibody response was low. RNAemia is associated with higher 28-day ICU mortality (hazard ratio [HR], 1.84 [95% CI, 1.22–2.77] adjusted for age and sex). RNAemia is comparable in performance to the best protein predictors. Mannose binding lectin 2 and pentraxin-3 (PTX3), two activators of the complement pathway of the innate immune system, are positively associated with mortality. Machine learning identified ‘Age, RNAemia’ and ‘Age, PTX3’ as the best binary signatures associated with 28-day ICU mortality. In longitudinal comparisons, COVID-19 ICU patients have a distinct proteomic trajectory associated with mortality, with recovery of many liver-derived proteins indicating survival. Finally, proteins of the complement system and galectin-3-binding protein (LGALS3BP) are identified as interaction partners of SARS-CoV-2 spike glycoprotein. LGALS3BP overexpression inhibits spike-pseudoparticle uptake and spike-induced cell-cell fusion in vitro. Here the authors use RT-qPCR and mass spectrometry to analyze longitudinal blood samples from intensive care unit (ICU) COVID-19 patients and controls. They find that viral RNA and pentraxin-3 predict 28-day ICU mortality and that galectin-3-binding protein is an interaction partner of SARS-CoV-2 spike glycoprotein with antiviral properties.

Epithelial-mesenchymal transition (EMT) of adherent epithelial cells to a migratory mesenchymal state has been implicated in tumor metastasis in preclinical models. To investigate its role in human cancer, we characterized EMT in circulating tumor cells (CTCs) from breast cancer patients. Rare primary tumor cells simultaneously expressed mesenchymal and epithelial markers, but mesenchymal cells were highly enriched in CTCs. Serial CTC monitoring in 11 patients suggested an association of mesenchymal CTCs with disease progression. In an index patient, reversible shifts between these cell fates accompanied each cycle of response to therapy and disease progression. Mesenchymal CTCs occurred as both single cells and multicellular clusters, expressing known EMT regulators, including transforming growth factor (TGF)—β pathway components and the FOXC1 transcription factor. These data support a role for EMT in the blood-borne dissemination of human breast cancer.

Heart failure is a major public health problem, and abnormal iron metabolism is common in patients with heart failure. Although iron is necessary for metabolic homeostasis, it induces a programmed necrosis. Iron release from ferritin storage is through nuclear receptor coactivator 4 (NCOA4)-mediated autophagic degradation, known as ferritinophagy. However, the role of ferritinophagy in the stressed heart remains unclear. Deletion of Ncoa4 in mouse hearts reduced left ventricular chamber size and improved cardiac function along with the attenuation of the upregulation of ferritinophagy-mediated ferritin degradation 4 weeks after pressure overload. Free ferrous iron overload and increased lipid peroxidation were suppressed in NCOA4-deficient hearts. A potent inhibitor of lipid peroxidation, ferrostatin-1, significantly mitigated the development of pressure overload-induced dilated cardiomyopathy in wild-type mice. Thus, the activation of ferritinophagy results in the development of heart failure, whereas inhibition of this process protects the heart against hemodynamic stress.

Background The National Early Warning Score (NEWS2) is currently recommended in the UK for the risk stratification of COVID-19 patients, but little is known about its ability to detect severe cases. We aimed to evaluate NEWS2 for the prediction of severe COVID-19 outcome and identify and validate a set of blood and physiological parameters routinely collected at hospital admission to improve upon the use of NEWS2 alone for medium-term risk stratification. Methods Training cohorts comprised 1276 patients admitted to King’s College Hospital National Health Service (NHS) Foundation Trust with COVID-19 disease from 1 March to 30 April 2020. External validation cohorts included 6237 patients from five UK NHS Trusts (Guy’s and St Thomas’ Hospitals, University Hospitals Southampton, University Hospitals Bristol and Weston NHS Foundation Trust, University College London Hospitals, University Hospitals Birmingham), one hospital in Norway (Oslo University Hospital), and two hospitals in Wuhan, China (Wuhan Sixth Hospital and Taikang Tongji Hospital). The outcome was severe COVID-19 disease (transfer to intensive care unit (ICU) or death) at 14 days after hospital admission. Age, physiological measures, blood biomarkers, sex, ethnicity, and comorbidities (hypertension, diabetes, cardiovascular, respiratory and kidney diseases) measured at hospital admission were considered in the models. Results A baseline model of ‘NEWS2 + age’ had poor-to-moderate discrimination for severe COVID-19 infection at 14 days (area under receiver operating characteristic curve (AUC) in training cohort = 0.700, 95% confidence interval (CI) 0.680, 0.722; Brier score = 0.192, 95% CI 0.186, 0.197). A supplemented model adding eight routinely collected blood and physiological parameters (supplemental oxygen flow rate, urea, age, oxygen saturation, C-reactive protein, estimated glomerular filtration rate, neutrophil count, neutrophil/lymphocyte ratio) improved discrimination (AUC = 0.735; 95% CI 0.715, 0.757), and these improvements were replicated across seven UK and non-UK sites. However, there was evidence of miscalibration with the model tending to underestimate risks in most sites. Conclusions NEWS2 score had poor-to-moderate discrimination for medium-term COVID-19 outcome which raises questions about its use as a screening tool at hospital admission. Risk stratification was improved by including readily available blood and physiological parameters measured at hospital admission, but there was evidence of miscalibration in external sites. This highlights the need for a better understanding of the use of early warning scores for COVID.

Sepsis must be diagnosed quickly to avoid morbidity and mortality. However, the clinical manifestations of sepsis are highly variable and emergency department (ED) clinicians often must make rapid, impactful decisions before laboratory results are known. We previously developed a technique that allows the measurement of the biophysical properties of white blood cells as they are stretched through a microfluidic channel. In this study we describe and validate the resultant output as a model and score—the IntelliSep Index (ISI)—that aids in the diagnosis of sepsis in patients with suspected or confirmed infection from a single blood draw performed at the time of ED presentation. By applying this technique to a high acuity cohort with a 23.5% sepsis incidence ( n = 307), we defined specific metrics—the aspect ratio and visco-elastic inertial response—that are more sensitive than cell size or cell count in predicting disease severity. The final model was trained and cross-validated on the high acuity cohort, and the performance and generalizability of the model was evaluated on a separate low acuity cohort with a 6.4% sepsis incidence ( n = 94) and healthy donors ( n = 72). For easier clinical interpretation, the ISI is divided into three interpretation bands of Green, Yellow, and Red that correspond to increasing disease severity. The ISI agreed with the diagnosis established by retrospective physician adjudication, and accurately identified subjects with severe illness as measured by SOFA, APACHE-II, hospital-free days, and intensive care unit admission. Measured using routinely collected blood samples, with a short run-time and no requirement for patient or laboratory information, the ISI is well suited to aid ED clinicians in rapidly diagnosing sepsis.