Electrophysiologic Studies and Radiofrequency Catheter Ablation of Ectopic Atrial Tachycardia in Children

Ectopic atrial tachycardia (EAT) often resists medical therapy, making radiofrequency catheter ablation (RFCA) the preferred treatment. This study reviewed the records of 35 patients who underwent electrophysiologic studies (EPS) and 39 RFCA procedures for EAT during a 10-year period. Of the 35 patients, 10 (28%) presented with decreased ventricular function and tachycardia-induced cardiomyopathy (TIC). The EAT originated on the right atrial side in 19 patients (54%) and on the left atrial side in the remaining 16 patients (46%). The right atrial sites included the right atrial appendage (RAA) (n = 9, 25%), the tricuspid annulus (n = 7, 20%), and the crista terminalis (n = 3). The left atrial sites included the left atrial appendage (LAA) (n = 6, 17%), the pulmonary veins (n = 5, 14%), the mitral annulus (n = 3), and the posterior wall of the left atrium (n = 2). The mechanism of all EAT probably is automaticity. All EATs could be abolished using RFCA. Follow-up data were available for all patients 2 to 8 years after RFCA. All 35 patients remained recurrence free, and ventricular function improved for all 10 patients with TIC. The origin of EAT in children differed from its origin in adults. The authors conclude that RFCA is a safe and effective treatment option for children with refractory EAT and should be considered early in the course of their illness

Rhinovirus Genome Variation during Chronic Upper and Lower Respiratory Tract Infections

Routine screening of lung transplant recipients and hospital patients for respiratory virus infections allowed to identify human rhinovirus (HRV) in the upper and lower respiratory tracts, including immunocompromised hosts chronically infected with the same strain over weeks or months. Phylogenetic analysis of 144 HRV-positive samples showed no apparent correlation between a given viral genotype or species and their ability to invade the lower respiratory tract or lead to protracted infection. By contrast, protracted infections were found almost exclusively in immunocompromised patients, thus suggesting that host factors rather than the virus genotype modulate disease outcome, in particular the immune response. Complete genome sequencing of five chronic cases to study rhinovirus genome adaptation showed that the calculated mutation frequency was in the range observed during acute human infections. Analysis of mutation hot spot regions between specimens collected at different times or in different body sites revealed that non-synonymous changes were mostly concentrated in the viral capsid genes VP1, VP2 and VP3, independent of the HRV type. In an immunosuppressed lung transplant recipient infected with the same HRV strain for more than two years, both classical and ultra-deep sequencing of samples collected at different time points in the upper and lower respiratory tracts showed that these virus populations were phylogenetically indistinguishable over the course of infection, except for the last month. Specific signatures were found in the last two lower respiratory tract populations, including changes in the 5′UTR polypyrimidine tract and the VP2 immunogenic site 2. These results highlight for the first time the ability of a given rhinovirus to evolve in the course of a natural infection in immunocompromised patients and complement data obtained from previous experimental inoculation studies in immunocompetent volunteers

Novel non-invasive algorithm to identify the origins of re-entry and ectopic foci in the atria from 64-lead ECGs: A computational study.

Atrial tachy-arrhytmias, such as atrial fibrillation (AF), are characterised by irregular electrical activity in the atria, generally associated with erratic excitation underlain by re-entrant scroll waves, fibrillatory conduction of multiple wavelets or rapid focal activity. Epidemiological studies have shown an increase in AF prevalence in the developed world associated with an ageing society, highlighting the need for effective treatment options. Catheter ablation therapy, commonly used in the treatment of AF, requires spatial information on atrial electrical excitation. The standard 12-lead electrocardiogram (ECG) provides a method for non-invasive identification of the presence of arrhythmia, due to irregularity in the ECG signal associated with atrial activation compared to sinus rhythm, but has limitations in providing specific spatial information. There is therefore a pressing need to develop novel methods to identify and locate the origin of arrhythmic excitation. Invasive methods provide direct information on atrial activity, but may induce clinical complications. Non-invasive methods avoid such complications, but their development presents a greater challenge due to the non-direct nature of monitoring. Algorithms based on the ECG signals in multiple leads (e.g. a 64-lead vest) may provide a viable approach. In this study, we used a biophysically detailed model of the human atria and torso to investigate the correlation between the morphology of the ECG signals from a 64-lead vest and the location of the origin of rapid atrial excitation arising from rapid focal activity and/or re-entrant scroll waves. A focus-location algorithm was then constructed from this correlation. The algorithm had success rates of 93% and 76% for correctly identifying the origin of focal and re-entrant excitation with a spatial resolution of 40 mm, respectively. The general approach allows its application to any multi-lead ECG system. This represents a significant extension to our previously developed algorithms to predict the AF origins in association with focal activities

Non-invasive localization of atrial ectopic beats by using simulated body surface P-wave integral maps

Non-invasive localization of continuous atrial ectopic beats remains a cornerstone for the treatment of atrial arrhythmias. The lack of accurate tools to guide electrophysiologists leads to an increase in the recurrence rate of ablation procedures. Existing approaches are based on the analysis of the P-waves main characteristics and the forward body surface potential maps (BSPMs) or on the inverse estimation of the electric activity of the heart from those BSPMs. These methods have not provided an efficient and systematic tool to localize ectopic triggers. In this work, we propose the use of machine learning techniques to spatially cluster and classify ectopic atrial foci into clearly differentiated atrial regions by using the body surface P-wave integral map (BSPiM) as a biomarker. Our simulated results show that ectopic foci with similar BSPiM naturally cluster into differentiated non-intersected atrial regions and that new patterns could be correctly classified with an accuracy of 97% when considering 2 clusters and 96% for 4 clusters. Our results also suggest that an increase in the number of clusters is feasible at the cost of decreasing accuracy.This work was partially supported by The "Programa Prometeu" from Conselleria d'Educacio Formacio I Ocupacio, Generalitat Valenciana (www.edu.gva.es/fio/index_es.asp) Award Number: PROMETEU/2016/088 to JS; The "Plan Estatal de Investigacion Cientifica y Tecnica y de Innovacion 2013-2016" from the Ministerio de Economia, Industria y Competitividad of Spain, Agencia Estatal de Investigacion (www.mineco.gob.es) and the European Commission (European Regional Development Funds - ERDF -FEDER) (ec.europa.eu/regional_policy/es/funding/erdf/) Award Number: DPI2016-75799-R to JS and The "Programa Estatal de Investigacion, Desarrollo e Innovacion Orientado a los Retos de la Sociedad" from the Ministerio de Economia y Competitividad of Spain, Agencia Estatal de Investigacion (www.mineco.gob.es) and the European Commission (European Regional Development Funds - ERDF -FEDER) (ec.europa.eu/regional_policy/es/funding/erdf/) Award Number: TIN2014-59932-JIN to AFA and RS. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Ferrer Albero, A.; Godoy, EJ.; Lozano, M.; Martínez Mateu, L.; Alonso Atienza, F.; Saiz Rodríguez, FJ.; Sebastián Aguilar, R. (2017). Non-invasive localization of atrial ectopic beats by using simulated body surface P-wave integral maps. PLoS ONE. 12(7):1-23. https://doi.org/10.1371/journal.pone.0181263S12312

The Wor1-like Protein Fgp1 Regulates Pathogenicity, Toxin Synthesis and Reproduction in the Phytopathogenic Fungus Fusarium graminearum

WOR1 is a gene for a conserved fungal regulatory protein controlling the dimorphic switch and pathogenicity determents in Candida albicans and its ortholog in the plant pathogen Fusarium oxysporum, called SGE1, is required for pathogenicity and expression of key plant effector proteins. F. graminearum, an important pathogen of cereals, is not known to employ switching and no effector proteins from F. graminearum have been found to date that are required for infection. In this study, the potential role of the WOR1-like gene in pathogenesis was tested in this toxigenic fungus. Deletion of the WOR1 ortholog (called FGP1) in F. graminearum results in greatly reduced pathogenicity and loss of trichothecene toxin accumulation in infected wheat plants and in vitro. The loss of toxin accumulation alone may be sufficient to explain the loss of pathogenicity to wheat. Under toxin-inducing conditions, expression of genes for trichothecene biosynthesis and many other genes are not detected or detected at lower levels in Δfgp1 strains. FGP1 is also involved in the developmental processes of conidium formation and sexual reproduction and modulates a morphological change that accompanies mycotoxin production in vitro. The Wor1-like proteins in Fusarium species have highly conserved N-terminal regions and remarkably divergent C-termini. Interchanging the N- and C- terminal portions of proteins from F. oxysporum and F. graminearum resulted in partial to complete loss of function. Wor1-like proteins are conserved but have evolved to regulate pathogenicity in a range of fungi, likely by adaptations to the C-terminal portion of the protein

Phenomenological models of synaptic plasticity based on spike timing

Synaptic plasticity is considered to be the biological substrate of learning and memory. In this document we review phenomenological models of short-term and long-term synaptic plasticity, in particular spike-timing dependent plasticity (STDP). The aim of the document is to provide a framework for classifying and evaluating different models of plasticity. We focus on phenomenological synaptic models that are compatible with integrate-and-fire type neuron models where each neuron is described by a small number of variables. This implies that synaptic update rules for short-term or long-term plasticity can only depend on spike timing and, potentially, on membrane potential, as well as on the value of the synaptic weight, or on low-pass filtered (temporally averaged) versions of the above variables. We examine the ability of the models to account for experimental data and to fulfill expectations derived from theoretical considerations. We further discuss their relations to teacher-based rules (supervised learning) and reward-based rules (reinforcement learning). All models discussed in this paper are suitable for large-scale network simulations