Sex differences in natural history of cardiovascular magnetic resonance- and biopsy-proven lymphocytic myocarditis

Aims: the role of sex in determining the profile and the outcomes of patients with myocarditis is largely unexplored. We evaluated the impact of sex as a modifier factor in the clinical characterization and natural history of patients with definite diagnosis of myocarditis. Methods and results: we retrospectively analysed a single-centre cohort of consecutive patients with definite diagnosis of myocarditis (i.e. endomyocardial biopsy or cardiac magnetic resonance proven). Specific sub-analyses were performed in cohorts of patients with chest pain, ventricular arrhythmias, and heart failure as different main symptoms at presentation. The primary outcome measure was a composite of all-cause mortality or heart transplantation (HTx). We included 312 patients, of which 211, 68% of the whole population, were males. Despite no clinically relevant differences found at baseline presentation, males had a higher indexed left ventricular end-diastolic volume (62 ± 23 mL/m2 vs. 52 ± 20 mL/m2, P = 0.011 in males vs. females, respectively) at follow-up evaluation. At a median follow-up of 72 months, 36 (17%) males vs. 8 (8%) females experienced death or HTx (P = 0.033). Male sex emerged as predictors of all-cause mortality or HTx in every combination of covariates (HR 2.600; 1.163–5.809; P = 0.020). Results were agreeable regardless of the main symptom of presentation. Conclusions: in a large cohort of patients with definite diagnosis of myocarditis, females experienced a more favourable long-term prognosis than males, despite a similar clinical profile at presentation

Inhibition of the RNA-dependent RNA-polymerase from SARS-CoV-2 by 6-chloropurine isoxazoline-carbocyclic monophosphate nucleotides

Isoxazoline-carbocyclic monophosphate nucleotides were designed and synthesized through the chemistry of nitrosocarbonyl intermediates and stable anthracenenitrile oxide. Docking and molecular dynamics studies were first conducted for determining the best candidate for polymerase SARS-CoV-2 inhibition. The setup phosphorylation protocol afforded the nucleotides available for the biological tests. Preliminary inhibition and cytotoxicity assays were then performed, and the results showed a moderate activity of the nucleotides accompanied by cytotoxicity

Distributed Storage for the Provision of Ancillary Services to the Main Grid: Project PRESTO

AbstractThis paper presents the three-year PRESTO research project (2013-2015). PRESTO is a self-funded project developed by the Department of Energy of Politecnico di Milano in cooperation with FIAMM Storage, Elvi Energy and MCM Energy Lab (an Italian spin-off). Within the project, experimental tests and numerical simulations were performed in order to evaluate the effectiveness of an Energy Storage System (ESS) in the provision of ancillary services to the main grid. This paper focuses specifically on the experimental and numerical analyses carried out in the project to develop an innovative control law for the primary frequency regulation, able to maximize the performances of the regulating service and effectively manage the ESS state of charge

Lymphocytic Myocarditis: A Genetically Predisposed Disease?

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Detection of subjects with ischemic heart disease by using machine learning technique based on heart rate total variability parameters

OBJECTIVE: Ischemic heart disease (IHD), in its chronic stable form, is a subtle pathology due to its silent behavior before developing in unstable angina, myocardial infarction or sudden cardiac death. The clinical assessment is based on typical symptoms and finally confirmed, invasively, by coronary angiography. Recently, heart rate variability (HRV) analysis as well as some machine learning algorithms like Artificial Neural Networks (ANNs) were used to identify cardiovascular arrhythmias and, only in few cases, to classify IHD segments in a limited number of subjects. The goal of this study was the identification of the ANN structure and the HRV parameters producing the best performance to identify IHD patients in a non-invasive way, validating the results on a large sample of subjects. Moreover, we examined the influence of a clinical non-invasive parameter, the left ventricular ejection fraction (LVEF), on the classification performance.APPROACH: To this aim, we extracted several linear and non-linear parameters from 24h RR signal, considering both normal and ectopic beats (Heart Rate Total Variability), of 251 normal and 245 IHD subjects, matched by age and gender. ANNs using several different combinations of these parameters together with age and gender were tested. For each ANN, we varied the number of hidden neurons from 2 to 7 and simulated 100 times changing randomly training and test dataset.MAIN RESULTS: The HRTV parameters showed significant greater variability in IHD than in normal subjects. The ANN applied to meanRR, LF, LF/HF, Beta exponent, SD2 together with age and gender reached a maximum accuracy of 71.8% and, by adding as input LVEF, an accuracy of 79.8%.SIGNIFICANCE: The study provides a deep insight into how a combination of some HRTV parameters and LVEF could be exploited to reliably detect the presence of subjects affected by IHD