Training machine learning models with synthetic data improves the prediction of ventricular origin in outflow tract ventricular arrhythmias

In order to determine the site of origin (SOO) in outflow tract ventricular arrhythmias (OTVAs) before an ablation procedure, several algorithms based on manual identification of electrocardiogram (ECG) features, have been developed. However, the reported accuracy decreases when tested with different datasets. Machine learning algorithms can automatize the process and improve generalization, but their performance is hampered by the lack of large enough OTVA databases. We propose the use of detailed electrophysiological simulations of OTVAs to train a machine learning classification model to predict the ventricular origin of the SOO of ectopic beats. We generated a synthetic database of 12-lead ECGs (2,496 signals) by running multiple simulations from the most typical OTVA SOO in 16 patient-specific geometries. Two types of input data were considered in the classification, raw and feature ECG signals. From the simulated raw 12-lead ECG, we analyzed the contribution of each lead in the predictions, keeping the best ones for the training process. For feature-based analysis, we used entropy-based methods to rank the obtained features. A cross-validation process was included to evaluate the machine learning model. Following, two clinical OTVA databases from different hospitals, including ECGs from 365 patients, were used as test-sets to assess the generalization of the proposed approach. The results show that V2 was the best lead for classification. Prediction of the SOO in OTVA, using both raw signals or features for classification, presented high accuracy values (>0.96). Generalization of the network trained on simulated data was good for both patient datasets (accuracy of 0.86 and 0.84, respectively) and presented better values than using exclusively real ECGs for classification (accuracy of 0.84 and 0.76 for each dataset). The use of simulated ECG data for training machine learning-based classification algorithms is critical to obtain good SOO predictions in OTVA compared to real data alone. The fast implementation and generalization of the proposed methodology may contribute towards its application to a clinical routine.Copyright © 2022 Doste, Lozano, Jimenez-Perez, Mont, Berruezo, Penela, Camara and Sebastian

Amelioration of systemic inflammation via the display of two different decoy protein receptors on extracellular vesicles

Extracellular vesicles (EVs) can be functionalized to display specific protein receptors on their surface. However, surface-display technology typically labels only a small fraction of the EV population. Here, we show that the joint display of two different therapeutically relevant protein receptors on EVs can be optimized by systematically screening EV-loading protein moieties. We used cytokine-binding domains derived from tumour necrosis factor receptor 1 (TNFR1) and interleukin-6 signal transducer (IL-6ST), which can act as decoy receptors for the pro-inflammatory cytokines tumour necrosis factor alpha (TNF-α) and IL-6, respectively. We found that the genetic engineering of EV-producing cells to express oligomerized exosomal sorting domains and the N-terminal fragment of syntenin (a cytosolic adaptor of the single transmembrane domain protein syndecan) increased the display efficiency and inhibitory activity of TNFR1 and IL-6ST and facilitated their joint display on EVs. In mouse models of systemic inflammation, neuroinflammation and intestinal inflammation, EVs displaying the cytokine decoys ameliorated the disease phenotypes with higher efficacy as compared with clinically approved biopharmaceutical agents targeting the TNF-α and IL-6 pathways.International Society for Advancement of Cytometry Marylou Ingram Scholar 2019-2023H2020 EXPERTSwedish foundation of Strategic Research (SSF-IRC; FormulaEx)ERC CoG (DELIVER)Swedish Medical Research CouncilAccepte

Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches

Extracellular vesicles (EVs), through their complex cargo, can reflect the state of their cell of origin and change the functions and phenotypes of other cells. These features indicate strong biomarker and therapeutic potential and have generated broad interest, as evidenced by the steady year-on-year increase in the numbers of scientific publications about EVs. Important advances have been made in EV metrology and in understanding and applying EV biology. However, hurdles remain to realising the potential of EVs in domains ranging from basic biology to clinical applications due to challenges in EV nomenclature, separation from non-vesicular extracellular particles, characterisation and functional studies. To address the challenges and opportunities in this rapidly evolving field, the International Society for Extracellular Vesicles (ISEV) updates its 'Minimal Information for Studies of Extracellular Vesicles', which was first published in 2014 and then in 2018 as MISEV2014 and MISEV2018, respectively. The goal of the current document, MISEV2023, is to provide researchers with an updated snapshot of available approaches and their advantages and limitations for production, separation and characterisation of EVs from multiple sources, including cell culture, body fluids and solid tissues. In addition to presenting the latest state of the art in basic principles of EV research, this document also covers advanced techniques and approaches that are currently expanding the boundaries of the field. MISEV2023 also includes new sections on EV release and uptake and a brief discussion of in vivo approaches to study EVs. Compiling feedback from ISEV expert task forces and more than 1000 researchers, this document conveys the current state of EV research to facilitate robust scientific discoveries and move the field forward even more rapidly

Multiscale modelling of β-adrenergic stimulation in cardiac electromechanical function

β-adrenergic receptor stimulation (β-ARS) is a physiological mechanism that regulates cardiovascular function under stress conditions or physical exercise. Triggered during the so-called “fight-or-flight” response, the activation of the β-adrenergic receptors located on the cardiomyocyte membrane initiates a phosphorylation cascade of multiple ion channel targets that regulate both cellular excitability and recovery and of different proteins involved in intracellular calcium handling. As a result, β-ARS impacts both the electrophysiological and the mechanical response of the cardiomyocyte. β-ARS also plays a crucial role in several cardiac pathologies, greatly modifying cardiac output and potentially causing arrhythmogenic events. Mathematical patient-specific models are nowadays envisioned as an important tool for the personalised study of cardiac disease, the design of tailored treatments, or to inform risk assessment. Despite that, only a reduced number of computational studies of heart disease have incorporated β-ARS modelling. In this review, we describe the main existing multiscale frameworks to equip cellular models of cardiac electrophysiology with a β-ARS response. We also outline various applications of these multiscale frameworks in the study of cardiac pathology. We end with a discussion of the main current limitations and the future steps that need to be taken to adapt these models to a clinical environment and to incorporate them in organ-level simulations

Remodelling of potassium currents underlies arrhythmic action potential prolongation under beta-adrenergic stimulation in hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) patients often present an enhanced arrhythmogenicity that can lead to lethal arrhythmias, especially during exercise. Recent studies have indicated an abnormal response of HCM cardiomyocytes to β-adrenergic receptor stimulation (β-ARS), with prolongation of their action potential rather than shortening. The mechanisms underlying this aberrant response to sympathetic stimulation and its possible proarrhythmic role remain unknown. The aims of this study are to investigate the key ionic mechanisms underlying the HCM abnormal response to β-ARS and the resultant repolarisation abnormalities using human-based experimental and computational methodologies. We integrated and calibrated the latest models of human ventricular electrophysiology and β-ARS using experimental measurements of human adult cardiomyocytes from control and HCM patients. Our major findings include: (1) the developed in silico models of β-ARS capture the behaviour observed in the experimental data, including the aberrant response of HCM cardiomyocytes to β-ARS; (2) the reduced increase of potassium currents under β-ARS was identified as the main mechanism of action potential prolongation in HCM, rather than a more sustained inward calcium current; (3) action potential duration differences between healthy and HCM cardiomyocytes were increased upon β-ARS, while endocardial to epicardial differences in HCM cardiomyocytes were reduced; (4) models presenting repolarisation abnormalities were characterised by downregulation of the rapid delayed rectifier potassium current and the sodium‑potassium pump, while inward currents were upregulated. In conclusion, our results identify causal relationships between the HCM phenotype and its arrhythmogenic response to β-ARS through the downregulation of potassium currents

Pharmacological management of hypertrophic cardiomyopathy: From bench to bedside

Hypertrophic cardiomyopathy (HCM), the most common inherited heart disease, is still orphan of a specific drug treatment. The erroneous consideration of HCM as a rare disease has hampered the design and conduct of large, randomized trials in the last 50 years, and most of the indications in the current guidelines are derived from small non-randomized studies, case series, or simply from the consensus of experts. Guideline-directed therapy of HCM includes non-selective drugs such as disopyramide, non-dihydropyridine calcium channel blockers, or β-adrenergic receptor blockers, mainly used in patients with symptomatic obstruction of the outflow tract. Following promising preclinical studies, several drugs acting on potential HCM-specific targets were tested in patients. Despite the huge efforts, none of these studies was able to change clinical practice for HCM patients, because tested drugs were proven to be scarcely effective or hardly tolerated in patients. However, novel compounds have been developed in recent years specifically for HCM, addressing myocardial hypercontractility and altered energetics in a direct manner, through allosteric inhibition of myosin. In this paper, we will critically review the use of different classes of drugs in HCM patients, starting from “old” established agents up to novel selective drugs that have been recently trialed in patients

Optimised Electroporation for Loading of Extracellular Vesicles with Doxorubicin

The clinical use of chemotherapeutics is limited by several factors, including low cellular uptake, short circulation time, and severe adverse effects. Extracellular vesicles (EVs) have been suggested as a drug delivery platform with the potential to overcome these limitations. EVs are cell-derived, lipid bilayer nanoparticles, important for intercellular communication. They can transport bioactive cargo throughout the body, surmount biological barriers, and target a variety of tissues. Several small molecule drugs have been successfully incorporated into the lumen of EVs, permitting efficient transport to tumour tissue, increasing therapeutic potency, and reducing adverse effects. However, the cargo loading is often inadequate and refined methods are a prerequisite for successful utilisation of the platform. By systematically evaluating the effect of altered loading parameters for electroporation, such as total number of EVs, drug to EV ratio, buffers, pulse capacitance, and field strength, we were able to distinguish tendencies and correlations. This allowed us to design an optimised electroporation protocol for loading EVs with the chemotherapeutic drug doxorubicin. The loading technique demonstrated improved cargo loading and EV recovery, as well as drug potency, with a 190-fold increased response compared to naked doxorubicin

Insights into cellular behavior and micromolecular communication in urothelial micrografts

Abstract Autologous micrografting is a technique currently applied within skin wound healing, however, the potential use for surgical correction of other organs with epithelial lining, including the urinary bladder, remains largely unexplored. Currently, little is known about the micrograft expansion potential and the micromolecular events that occur in micrografted urothelial cells. In this study, we aimed to evaluate the proliferative potential of different porcine urothelial micrograft sizes in vitro, and, furthermore, to explore how urothelial micrografts communicate and which microcellular events are triggered. We demonstrated that increased tissue fragmentation subsequently potentiated the yield of proliferative cells and the cellular expansion potential, which confirms, that the micrografting principles of skin epithelium also apply to uroepithelium. Furthermore, we targeted the expression of the extracellular signal-regulated kinase (ERK) pathway and demonstrated that ERK activation occurred predominately at the micrograft borders and that ERK inhibition led to decreased urothelial migration and proliferation. Finally, we successfully isolated extracellular vesicles from the micrograft culture medium and evaluated their contents and relevance within various enriched biological processes. Our findings substantiate the potential of applying urothelial micrografting in future tissue-engineering models for reconstructive urological surgery, and, furthermore, highlights certain mechanisms as potential targets for future wound healing treatments

Prediction of CRT Activation Sequence by Personalization of Biventricular Models from Electroanatomical Maps

[EN] Optimization of lead placement and interventricular delay settings in patients under cardiac resynchronization therapy is a complex task that might benefit from prior information based on models. Biophysical models can be used to predict the sequence of electrical heart activation in a patient given a set of parameters which should be personalized to the patient. In this paper, we use electroanatomical maps to personalize the endocardial activation of the right ventricle, and the different tissue conductivities in a pig model with left bundle branch block, to reproduce personalized biventricular activations. Following, we tested the personalized heart model by virtually simulating cardiac resynchronization therapyThis work was supported by the "Plan Estatal de Investigacion Cientifica y Tecnica y de Innovacion 2013-2016" from the Ministerio de Economia, Industria y Competitividad of Spain and Fondo Europeo de Desarrollo Regional (FEDER) DPI2016-75799-R (AEI/FEDER, UE), and by the Direccion General de Politica Cientifica de la Generalitat Valenciana (PROMETEU 2016/088)Gómez García, JF.; Trenor Gomis, BA.; Sebastián Aguilar, R. (2020). Prediction of CRT Activation Sequence by Personalization of Biventricular Models from Electroanatomical Maps. Lecture Notes in Computer Science. 12009:342-351. https://doi.org/10.1007/978-3-030-39074-7_36S34235112009Auricchio, A., et al.: Characterization of left ventricular activation in patients with heart failure and left bundle-branch block. Circulation 109(9), 1133–9 (2004). https://doi.org/10.1161/01.CIR.0000118502.91105.F6Bristow, M.R., et al.: Comparison of medical therapy, pacing, and defibrillation in heart failure (COMPANION) investigators: cardiac-resynchronization therapy with or without an implantable defibrillator in advanced chronic heart failure. N. Engl. J. Med. 350(21), 2140–50 (2004). https://doi.org/10.1056/NEJMoa032423Carpio, E.F., et al.: Optimization of lead placement in the right ventricle during cardiac resynchronization therapy. A simulation study. Front. Physiol. 10, 74 (2019). https://doi.org/10.3389/fphys.2019.00074Dawoud, F., et al.: Non-invasive electromechanical activation imaging as a tool to study left ventricular dyssynchronous patients: implication for crt therapy. J. Electrocardiol. 49(3), 375–82 (2016). https://doi.org/10.1016/j.jelectrocard.2016.02.011Doste, R., et al.: A rule-based method to model myocardial fiber orientation in cardiac biventricular geometries with outflow tracts. Int. J. Numer. Method Biomed. Eng. 35(4), e3185 (2019). https://doi.org/10.1002/cnm.3185Garcia-Bustos, V., Sebastian, R., Izquierdo, M., Molina, P., Chorro, F.J., Ruiz-Sauri, A.: A quantitative structural and morphometric analysis of the purkinje network and the purkinje-myocardial junctions in pig hearts. J. Anat. 230(5), 664–678 (2017). https://doi.org/10.1111/joa.12594Lopez-Perez, A., Sebastian, R., Ferrero, J.M.: Three-dimensional cardiac computational modelling: methods, features and applications. Biomed. Eng. Online 14, 35 (2015). https://doi.org/10.1186/s12938-015-0033-5Moss, A.J., et al.: MADIT-CRT trial investigators:cardiac-resynchronization therapy for the prevention of heart-failure events. N. Engl. J. Med. 361(14), 1329–38 (2009). https://doi.org/10.1056/NEJMoa0906431Soto Iglesias, D., et al.: Quantitative analysis of electro-anatomical maps: application to an experimental model of left bundle branch block/cardiac resynchronization therapy. IEEE J. Transl. Eng. Health Med. 5, 1900215 (2017). https://doi.org/10.1109/JTEHM.2016.2634006Tobon-Gomez, C., et al.: Understanding the mechanisms amenable to crt response: from pre-operative multimodal image data to patient-specific computational models. Med. Biol. Eng. Comput. 51(11), 1235–50 (2013). https://doi.org/10.1007/s11517-013-1044-