ECG scaling properties of cardiac arrhythmias using detrended fluctuation analysis

QuinoMit Q10-Fluid attenuates hydrogen peroxide-induced irregular beating in mouse pluripotent stem cell-derived cardiomyocytes

BACKGROUND

Coenzyme Q10 (CoQ10) is a crucial component of the mitochondrial structure which is involved in producing more than 90% of cellular ATP. This study aimed to investigate the protective effects and underlying mechanisms of QuinoMit Q10-Fluid against hydrogen peroxide (H₂O₂)-induced arrhythmias on cardiomyocytes (CMs).

METHODS

Undifferentiated stem cell-derived CMs were cultured in the presence of different concentrations of QuinoMit Q10-Fluid. To investigate if CoQ10 has anti-apoptotic activity, CMs were exposed to H₂O₂ for up to 100 h with or without CoQ10. The expression levels of cardiac reference genes were determined by RT-PCR. The structural and functional properties of CMs were examined by immunofluorescence and the xCELLigence system. Caspase 3/7 assay was also performed for cell apoptosis study.

RESULTS

The study showed that QuinoMit Q10-Fluid inhibits the proliferation of pluripotent stem cells at high concentrations and had less effect on cardiomyogenesis. However, the beating rate of clusters containing CMs generated under QuinoMit Q10-Fluid (1:100) was significantly increased. This increase was accompanied by the up-regulated expression level of some important cardiac markers during differentiation. Treatment of CMs with H₂O₂ notably induced irregular beating and decreased the amplitude of the beating signal of CMs, concomitantly with increased caspase-3/7 activity. However, CMs pretreated with QuinoMit exhibited a protective effect against H₂O₂-induced arrhythmia.

CONCLUSION

Our results reveal that QuinoMit Q10-Fluid attenuates H₂O₂-induced irregular beating in mouse pluripotent stem cell-derived CMs, at least partly by reducing the generation of ROS, suggesting a protective effect against CM dysfunctions.

The Analysis of How Apnea Influences the Autonomic Nervous System Using Short-Term Heart Rate Variability Indices

Objective

Frequent cessations of respiration can greatly increase the prevalence rate of arrhythmia. It has been confirmed that cardiac modulation is regulated by the autonomic nervous system (ANS). And heart rate variability (HRV) is widely used as a method to evaluate the function of the ANS. Therefore, we analyzed whether apnea can affect the balance and normal function of the ANS using short-term HRV indices.

Methods

Forty-five healthy subjects were asked to breathe normally and hold their breathing to simulate 10 times apnea. Thirty-six patients from the dataset of a sleep laboratory for the diagnosis of sleep disorders with 10 times apnea were included in analysis. We calculated short-term HRV indices of subjects in normal respiratory and apneic states, respectively.

Results

Compared with the normal respiratory state, respiration cease would lead to the values of Mean-RR, nLF, LF/HF, and α1 which significantly increased, whereas the values of rMSSD and nHF significantly decreased.

Conclusions

Cessations of respiration would lead to an imbalance in the function of the ANS, as well as an increase in fractal characteristics of the heart. These changes in the physiological state are likely to induce and cause the occurrence of arrhythmia, which is regulated by the ANS.

Scaling and correlation properties of RR and QT intervals at the cellular level

We study complex scaling properties of RR and QT intervals of electrocardiograms (ECGs) with their equivalences at the cellular level, that is, inter-beat intervals (IBI) and field potential durations (FPD) of spontaneously beating human-induced pluripotent stem cell-derived cardiomyocyte (hiPSC-CM) aggregates. Our detrended fluctuation analysis and Poincaré plots reveal remarkable similarities between the ECG and hiPSC-CM data. In particular, no statistically significant difference was found in the short- and long-term scaling exponents α₁ and α₂ of RR and QT intervals and their cellular equivalences. Previously unknown scaling properties of FPDs of hiPSC-CM aggregates reveal that the increasing scaling exponent of QT intervals as a function of the time scale, is an intrinsic feature at the cellular level.

Fractal analysis of heart rate variability as a predictor of mortality: A systematic review and meta-analysis

Previous studies have suggested benefits of applying fractal analysis to intervals between R waves in electrocardiography as an additional prognostic marker. The aim of this study was to investigate whether fractal analysis can provide an independent predictor of cardiac mortality or all-cause mortality. Prognostic cohort studies reporting fractal heart rate variability results from 24-h Holter monitor recordings were selected for comparison. Populations were subdivided into four groups-post-myocardial infarction, left ventricular dysfunction, other cardiac, and non-cardiac patients-and analysed using ANOVA, Forest plots (using pooled mean difference), and Funnel plots. The most significant mean differences were recorded in short-term fractal self-similarity (α₁) (-0.17, 95% CI [-0.21, -0.13], p < 0.00001) and the traditional measure called standard deviation of NN intervals (SDNN) (-13.31, 95% CI [-18.89, -7.73], p < 0.00001) between the deceased and survivor groups. Fractal measures of long-term fractal self-similarity (α₂), 1/f scaling (β), and traditional heart rate variability measures of high frequency to low frequency ratio show promise. This review indicated that fractal measure α₁ and traditional measure SDNN could be potential predictors of mortality, but require further assessment to determine appropriate thresholds for clinical significance and additional targeted prognostic studies to properly define their applicability as prognostic markers. Therefore, clinicians should interpret fractal and traditional measures with caution since such measures have yet to be fully described as biomarkers for clinical application.