A novel sequential endocardial mapping strategy for locating atrial fibrillation sources based on repetitive conduction patterns: An in-silico study.

Background: In persistent atrial fibrillation (AF), localized extra-pulmonary vein sources may contribute to arrhythmia recurrences after pulmonary vein isolation. This in-silico study proposes a high-density sequential mapping strategy to localize such sources.

Method: Catheter repositioning was guided by repetitive conduction patterns, moving against the prevailing conduction direction (upstream) toward the sources.

Synthetic ECG signals generation: A scoping review.

The scientific community has recently shown increasing interest in generating synthetic ECG data. In particular, synthetic ECG signals can be beneficial for understanding cardiac electrical activity, developing large and heterogeneous unbiased datasets, and anonymizing data to favour knowledge sharing and open science. In the present scoping review, various methodologies to generate synthetic ECG data have been thoroughly analysed, highlighting their limitations and possibilities.

Multi-year enzyme expression in patients with mucopolysaccharidosis type VI after liver-directed gene therapy.

Background: Mucopolysaccharidosis type VI (MPS VI) is due to a deficiency of the lysosomal enzyme arylsulfatase B (ARSB) that results in multi-organ accumulation of glycosaminoglycans (GAGs). Limitations of current treatments prompted the development of a liver-directed gene therapy clinical trial for MPS VI.

Methods: We report the long-term follow-up of patients with MPS VI who discontinued enzyme replacement therapy (ERT) and received a single intravenous infusion of high-dose (6 × 10 genome copies/kg) recombinant adeno-associated virus serotype 8 (AAV8) vector expressing ARSB under the control of a liver-specific promoter (ClinicalTrials.

Spatio-temporal distribution, prediction and relationship of three major acute cardiovascular events: Out-of-hospital cardiac arrest, ST-elevation myocardial infarction and stroke.

Background: Predicting the incidence of time-sensitive cardiovascular diseases like out-of-hospital cardiac arrest (OHCA), ST-elevation myocardial infarction (STEMI), and stroke can reduce time to treatment and improve outcomes. This study analysed the spatio-temporal distribution of OHCAs, STEMIs, and strokes, their spatio-temporal correlation, and the performance of different prediction algorithms.

Methods: Adults who experienced an OHCA, STEMI, or stroke in Canton Ticino, Switzerland from 2005 to 2022 were included.