Consecutive treatments of methamphetamine promote the development of cardiac pathological symptoms in zebrafish.

Chronic methamphetamine use, a widespread drug epidemic, has been associated with cardiac morphological and electrical remodeling, leading to the development of numerous cardiovascular diseases. While methamphetamine has been documented to induce arrhythmia, most results originate from clinical trials from users who experienced different durations of methamphetamine abuse, providing no documentation on the use of methamphetamine in standardized settings. Additionally, the underlying molecular mechanism on how methamphetamine affects the cardiovascular system remains elusive. A relationship was sought between cardiotoxicity and arrhythmia with associated methamphetamine abuse in zebrafish to identify and to understand the adverse cardiac symptoms associated with methamphetamine. Zebrafish were first treated with methamphetamine 3 times a week over a 2-week duration. Immediately after treatment, zebrafish underwent electrocardiogram (ECG) measurement using an in-house developed acquisition system for electrophysiological analysis. Subsequent analyses of cAMP expression and Ca2+ regulation in zebrafish cardiomyocytes were conducted. cAMP is vital to development of myocardial fibrosis and arrhythmia, prominent symptoms in the development of cardiovascular diseases. Ca2+ dysregulation is also a factor in inducing arrhythmias. During the first week of treatment, zebrafish that were administered with methamphetamine displayed a decrease in heart rate, which persisted throughout the second week and remained significantly lower than the heart rate of untreated fish. Results also indicate an increased heart rate variability during the early stage of treatment followed by a decrease in the late stage for methamphetamine-treated fish over the duration of the experiment, suggesting a biphasic response to methamphetamine exposure. Methamphetamine-treated fish also exhibited reduced QTc intervals throughout the experiment. Results from the cAMP and Ca2+ assays demonstrate that cAMP was upregulated and Ca2+ was dysregulated in response to methamphetamine treatment. Collagenic assays indicated significant fibrotic response to methamphetamine treatment. These results provide potential insight into the role of methamphetamine in the development of fibrosis and arrhythmia due to downstream effectors of cAMP.

A Novel ECG Denoising Scheme Using the Ensemble Kalman Filter.

Monitoring of electrocardiogram (ECG) provides vital information as well as any cardiovascular anomalies. Recent advances in the technology of wearable electronics have enabled compact devices to acquire personal physiological signals in the home setting; however, signals are usually contaminated with high level noise. Thus, an efficient ECG filtering scheme is a dire need. In this paper, a novel method using Ensemble Kalman Filter (EnKF) is developed for denoising ECG signals. We also intensively explore various filtering algorithms, including Savitzky-Golay (SG) filter, Ensemble Empirical mode decomposition (EEMD), Normalized Least-Mean-Square (NLMS), Recursive least squares (RLS) filter, Total variation denoising (TVD), Wavelet and extended Kalman filter (EKF) for comparison. Data from the MIT-BIH Noise Stress Test database were used. The proposed methodology shows the average signal to noise ratio (SNR) of 10.96, the Percentage Root Difference of 150.45, and the correlation coefficient of 0.959 from the modified MIT-BIH database with added motion artifacts.

Lullaby: A Novel Algorithm to Extract Fetal QRS in Real Time Using Periodic Trend Feature.

Fetal heart rate (fHR) is an important indicator for monitoring of fetal cardiac health and development. The widely-used method based on ultrasound, however, is not continuous and often requires an expert to perform; thus, it is mostly used in clinics during checkups. The advances in wearable technology have paved the way for home assessment of fHR via the extraction of the mother's abdominal electrocardiogram (ECG) acquired by novel patches. Several methods have been developed for such; however, the computation is either too slow for real-time monitoring or too heavy to be performed in a wearable. In this work, we develop and validate the Lullaby algorithm - a novel method for fetal QRS extraction from aECG. The results showed that Lullaby is almost 7 times faster than existing methods with a better F1-score of 0.815, holding promise to transform perinatal monitoring.