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Objective: We present a novel method for detecting atrial fibrillation (AFib) by analyzing Lead II electrocardiograms (ECGs) using a unique set of features., Methods: For this purpose, we used specific signal processing techniques, such as proper orthogonal decomposition, continuous wavelet transforms, discrete cosine transform, and standard cross-correlation, to extract 48 features from the ECGs. Thus, our approach aims to more effectively capture AFib signatures, such as beat-to-beat variability and fibrillatory waves, than traditional metrics. Moreover, our features were designed to be physiologically interpretable. Subsequently, we incorporated an XGBoost-based ECG classifier to train and evaluate it using the publicly available 'Training' dataset of the 2017 PhysioNet Challenge, which includes 'Normal,' 'AFib,' 'Other,' and 'Noisy' ECG categories., Results: Our method achieved an accuracy of 96 % and an F1-score of 0.83 for 'AFib' detection and 80 % accuracy and 0.85 F1-score for 'Normal' ECGs. Finally, we compared our method's performance with the top-classifiers from the 2017 PhysioNet Challenge, namely ENCASE, Random Forest, and Cascaded Binary. As reported by Clifford et al., 2017, these three best performing models scored 0.80, 0.83, 0.82, in terms of F1-score for 'AFib' detection, respectively., Conclusion: Despite using significantly fewer features than the competition's state-of-the-art ECG detection algorithms (48 vs. 150-622), our model achieved a comparable F1-score of 0.83 for successful 'AFib' detection., Significance: The interpretable features specifically designed for 'AFib' detection results in our method's adaptability in clinical settings for real-time arrhythmia detection and is even effective with short ECGs (<10 heartbeats)., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Cardiovascular diseases are currently the most common cause of death in developed countries. Due to lifestyle and environmental factors, this problem is only expected to increase in the future. Reactive oxygen species (ROS) are a key player in the onset of cardiovascular diseases but also have important functions in healthy cardiac tissue. Here, the interplay between ROS generation and cardiac mechanical forces is shown, and the state of the art and a perspective on future directions are discussed. To this end, an overview of what is currently known regarding ROS and mechanosignaling at a subcellular level is first given. There the role of ROS in mechanosignaling as well as the interplay between both factors in specific organelles is emphasized. The consequences at a larger scale across the population of heart cells are then discussed. Subsequently, the roles of ROS in embryogenesis, pathogenesis, and aging are further discussed, exemplifying some aspects of mechanoregulation. Finally, different models that are currently in use are discussed to study the topics above., (© 2024 The Author(s). Advanced Healthcare Materials published by Wiley‐VCH GmbH.)

Programmed cell death (PCD) is crucial for normal development and homeostasis. Our first insights into the genetic regulation of apoptotic cell death came from in vivo studies in the powerful genetic model system of C. elegans. More recently, novel developmental cell death programs occurring both embryonically and post-embryonically, and sex-specifically, have been elucidated. Recent studies in the apoptotic setting have also shed new light on the intricacies of phagocytosis in particular. This review provides a brief historical perspective of the origins of PCD studies in C. elegans, followed by a more detailed description of non-canonical apoptotic and non-apoptotic death programs. We conclude by posing open questions and commenting on our outlook on the future of PCD studies in C. elegans, highlighting the importance of advanced imaging tools and the continued leveraging of C. elegans genetics both with classical and modern cutting-edge approaches., Competing Interests: Declaration of Competing Interest The authors declare no competing interests., (Copyright © 2023. Published by Elsevier Ltd.)