Purpose: Atrial fibrillation (AF) is the most common heart rhythm disorder in the world. Radiofrequency catheter ablation (RFCA) has become the preferred method of treatment for drug-refractory AF. One of the rare (< 0.2%) but deadly (≈ 80%) complications of RFCA is Atrioesophageal fistula (AEF). Although the exact pathophysiological events in developing AEF are not fully understood, one hypothesis is that the underlying cause may be thermal damage to the mucosa (the esophagus lumen).
Method: The present study reports on a computer model of RFCA in the posterior wall of the left atrium (LA) which is in close proximity to the esophagus. A novel systematic approach was taken by considering a range of anatomical variations (obtained from clinical data) to study the spatial and temporal temperature data when RF energy was applied to cause a threshold temperature of 50 °C in the mucosa. The model is also used to investigate the spatial and temporal changes in mucosal temperature that may affect the reliability of the readings from esophageal temperature monitoring devices if they are not positioned accurately.
Results: The results suggest evidence of transmural esophageal lesions in all the anatomies except one, if the 50 °C temperature threshold is the only criteria used for identification of thermal damage. However, by taking into consideration the effect of time (temperature-time integral), only some anatomies were identified as being partially damaged. Investigating the temperature and the temperature gradient data during the ablation revealed that the increases in both the temperature and the temperature gradient were time, location and anatomy dependent. This finding may have significance in the design and development of next-generation temperature monitoring devices that will provide a temperature map rather than single point measurements.
Conclusion: Studies such as the present work may provide more convenient platforms for investigating the effect of the many factors involved in the RF procedure and how they may link to the development of AEF.
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Ann Bot
December 2024
Department of Agronomy, University of Agricultural Sciences and Natural Resources, Gorgan, Iran.
Background And Aims: Fire-released seed dormancy (SD) is a key trait for successful germination and plant persistence in many fire-prone ecosystems. Many local studies have shown that fire-released SD depends on heat and exposure time, dose of smoke-derived compounds, SD class, plant lineage and the fire regime. However, a global quantitative analysis of fire-released SD is lacking.
View Article and Find Full Text PDFNeurourol Urodyn
December 2024
Department of Physical Medicine and Rehabilitation, Rothschild Hospital, Sorbonne Université, Paris, France.
Context: Lower Urinary Tract Symptoms (LUTS) are defined by their distressing effect on patients' day-to-day life. Given the pressures on secondary care resources, LUTS may be overlooked or inadequately assessed and therefore patients may be burdened for an extended period before treatment.
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PNAS Nexus
January 2025
Department of Engineering Sciences and Applied Mathematics, Northwestern University, Evanston, IL 60208, USA.
The COVID-19 pandemic forced a societal shift from in-person to virtual activities, including scientific conferences. As society navigates a "new normal," the question arises as to the advantages and disadvantages of these alternative modalities. We introduce two new comprehensive datasets enabling direct comparison between virtual and in-person conferences: the first, from a series of nine small conferences, encompasses over 12,000 pairs of potential scientific collaborators across five virtual and four in-person meetings on a range of scientific topics; the expressed goal of these conferences is to create novel collaborations.
View Article and Find Full Text PDFFront Microbiol
December 2024
Key Laboratory of Industrial Biotechnology, Ministry of Education, School of Biotechnology, Jiangnan University, Wuxi, China.
Air-curing is the initial step in the processing of cigar tobacco leaves. However, the dynamics of microbial community and metabolic functions in different parts of tobacco leaves during this process remain largely unclear. In this study, amplicon-based high-throughput sequencing revealed that (9.
View Article and Find Full Text PDFFront Artif Intell
December 2024
HPC Laboratory, Department of Engineering and Geology, University "G. d'Annunzio" Chieti-Pescara, Pescara, Italy.
The construction industry is rapidly adopting Industry 4.0 technologies, creating new opportunities to address persistent environmental and operational challenges. This review focuses on how Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) are being leveraged to tackle these issues.
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