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

Physician privacy concerns when disclosing patient data for public health purposes during a pandemic influenza outbreak

Background: Privacy concerns by providers have been a barrier to disclosing patient information for public health\ud purposes. This is the case even for mandated notifiable disease reporting. In the context of a pandemic it has been\ud argued that the public good should supersede an individual’s right to privacy. The precise nature of these provider\ud privacy concerns, and whether they are diluted in the context of a pandemic are not known. Our objective was to\ud understand the privacy barriers which could potentially influence family physicians’ reporting of patient-level\ud surveillance data to public health agencies during the Fall 2009 pandemic H1N1 influenza outbreak.\ud Methods: Thirty seven family doctors participated in a series of five focus groups between October 29-31 2009.\ud They also completed a survey about the data they were willing to disclose to public health units. Descriptive\ud statistics were used to summarize the amount of patient detail the participants were willing to disclose, factors that\ud would facilitate data disclosure, and the consensus on those factors. The analysis of the qualitative data was based\ud on grounded theory.\ud Results: The family doctors were reluctant to disclose patient data to public health units. This was due to concerns\ud about the extent to which public health agencies are dependable to protect health information (trusting beliefs),\ud and the possibility of loss due to disclosing health information (risk beliefs). We identified six specific actions that\ud public health units can take which would affect these beliefs, and potentially increase the willingness to disclose\ud patient information for public health purposes.\ud Conclusions: The uncertainty surrounding a pandemic of a new strain of influenza has not changed the privacy\ud concerns of physicians about disclosing patient data. It is important to address these concerns to ensure reliable\ud reporting during future outbreaks.University of Ottawa Open Access Author Fun

A next-generation liquid xenon observatory for dark matter and neutrino physics

The nature of dark matter and properties of neutrinos are among the most pressing issues in contemporary particle physics. The dual-phase xenon time-projection chamber is the leading technology to cover the available parameter space for weakly interacting massive particles, while featuring extensive sensitivity to many alternative dark matter candidates. These detectors can also study neutrinos through neutrinoless double-beta decay and through a variety of astrophysical sources. A next-generation xenon-based detector will therefore be a true multi-purpose observatory to significantly advance particle physics, nuclear physics, astrophysics, solar physics, and cosmology. This review article presents the science cases for such a detector