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Vagal heart rate variability during rapid eye movement sleep reduces negative memory bias.
Front Behav Neurosci
February 2025
Department of Cognitive Science, University of California, Irvine, CA, United States.
Emotional memories change over time, but the mechanisms supporting this change are not well understood. Sleep has been identified as one mechanism that supports memory consolidation, with sleep selectively benefitting negative emotional consolidation at the expense of neutral memories, with specific oscillatory events linked to this process. In contrast, the consolidation of neutral and positive memories, compared to negative memories, has been associated with increased vagally mediated heart rate variability (HRV) during wakefulness.
View Article and Find Full Text PDFEfficacy of AI Models in Detecting Heart Failure Using ECG Data: A Systematic Review and Meta-Analysis.
Cureus
February 2025
General Medicine, Rehman Medical Institute, Peshawar, PAK.
Heart failure (HF) is the most common cause of death worldwide, characterized by low ejection fraction, substantial mortality, morbidity, and poor quality of life. Recent advancements in artificial intelligence (AI) present a promising avenue for enhancing diagnostic precision, particularly in the analysis of electrocardiogram (ECG) data. This systematic review and meta-analysis aim to synthesize current evidence on the diagnostic performance of AI models in detecting HF using ECG data.
View Article and Find Full Text PDFDeep learning-based prediction of atrial fibrillation from polar transformed time-frequency electrocardiogram.
PLoS One
March 2025
Medical Artificial Intelligence Laboratory, Division of Digital Healthcare, College of Software and Digital Healthcare Convergence, Yonsei University, Wonju, Republic of Korea.
Portable and wearable electrocardiogram (ECG) devices are increasingly utilized in healthcare for monitoring heart rhythms and detecting cardiac arrhythmias or other heart conditions. The integration of ECG signal visualization with AI-based abnormality detection empowers users to independently and confidently assess their physiological signals. In this study, we investigated a novel method for visualizing ECG signals using polar transformations of short-time Fourier transform (STFT) spectrograms and evaluated the performance of deep convolutional neural networks (CNNs) in predicting atrial fibrillation from these polar transformed spectrograms.
View Article and Find Full Text PDFParameter changes and influencing factors in sixty patients with interventional surgery for liver cancer diagnoses.
World J Gastrointest Surg
February 2025
Department of Interventional, Affiliated Wuxi Fifth Hospital of Jiangnan University (The Fifth People's Hospital of Wuxi), Wuxi 214000, Jiangsu Province, China.
Background: The development of hepatocellular carcinoma (HCC) is influenced by multiple factors. Interventional therapy offers an effective treatment option for patients with unresectable intermediate-to-advanced HCC. Interventional therapy can induce electrocardiographic (ECG) abnormalities that may be associated with liver dysfunction, electrolyte disorders, and cardiac injury.
View Article and Find Full Text PDFSynergistic effects of ginsenoside Rb1 and peroxiredoxin 6 in enhancing myocardial injury treatment through anti-inflammatory, anti-oxidative, and anti-apoptotic mechanisms.
J Ginseng Res
March 2025
Laboratory of Cancer Precision Medicine, The First Hospital of Jilin University, East Minzhu Road, Changchun, Jilin, China.
Aim: Ginsenosides have notable bioactivity in treating cardiovascular diseases, but the mechanisms of their combined use with Peroxiredoxin 6 (PRDX6) in myocardial injury remain unclear. This study explores the synergistic effects of Ginsenoside Rb1 (Gs-Rb1) and PRDX6, aiming to provide a theoretical foundation for their therapeutic potential.
Methods: We established a rat model of isoproterenol (ISO)-induced myocardial injury and observed that combination therapy was more effective than single-drug treatments, as shown by ECG monitoring and Masson staining.
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