Analysis of Heart Rate Asymmetry During Sleep Stages

It is one of the hot spots in recent years to explore changes in the sleep stage by assessing autonomic nervous activity. In recent years, heart rate asymmetry (HRA) is often used to measure the activity of autonomic nerves. However, the relationship between HRA and sleep stage is not clear. We performed Porta’s index (PI), Guzik’s index (GI), slope index (SI) and area index (AI) analyses on RR intervals per 30-s for understanding the HRA during sleep. Two measurement protocols were set: 1) the HRA values were calculated; 2) the degrees of heart rate deviation from symmetry were estimated. Results showed that PI significantly decreased from N1 and N2 to N3 (p<0.01), and it is increased the highest in REM than other stages (p<0.05). The asymmetry of HRA were significantly lower in N3 (PI and AI p’s<0.05; GI and SI p’s<0.01), and it increased in REM (PI p<0.05; GI, SI and AI p’s<0.0001). The results suggested that HRA has the potential to be used in sleep stage monitoring.

The effect of passive lower limb training on heart rate asymmetry

Objective: Heart rate asymmetry (HRA) is an approach for quantitatively assessing the uneven distribution of heart rate accelerations and decelerations for sinus rhythm. We aimed to investigate whether automatic regulation led to HRA alternation during passive lower limb training. Methods: Thirty healthy participants were recruited in this study. The protocol included a baseline (Pre-E) and three passive lower limb training trials (E1, E2 and E3) with a randomized order. Several variance-based HRA variables were established. Heart rate variability (HRV) parameters, i.e., mean RR, SDNN, RMSSD, LF (n.u.), HF (n.u.) and VLF (ms2), and HRA variables, i.e., SD1a, SD1d, SD2a, SD2d, SDNNa and SDNNd, were calculated by using 5-min RR time series, as well as the normalized HRA variables, i.e., C1a, C1d, C2a, C2d, Ca and Cd. Results: Our results showed that the performance of HRA was distinguished. The normalized HRA was observed with significant changes in E1, E2 and E3 compared to Pre -E. Moreover, parts of non-normalized HRA variables correlated with HRV parameters, which indicated that HRA might benefit in assessing cardiovascular modulation in passive lower limb training. Conclusions: In summary, this study suggested that passive training led to significant HRA alternation and the application of HRA gave us the possibility for autonomic assessment.

Deriving electrophysiological phenotypes of paroxysmal atrial fibrillation based on the characteristics of heart rate variability

Aim. To analyze heart rate variability of patients with paroxysmal atrial fibrillation and identify electrophysiological phenotypes of the disease by using methods of exploratory analysis of twenty-four-hour electrocardiographic (Holter) recordings. Methods. 64 electrocardiogram recordings of patients with paroxysmal atrial fibrillation were selected from the open Long-Term Atrial Fibrillation Database (repository PhysioNet). 52 indices of heart rhythm variability were calculated for each recording, including new heart rate fragmentation and asymmetry indices proposed in the last 5 years. Data analysis was carried out with machine learning methods: dimensionality reduction with principal component analysis, hierarchical clustering and outlier detection. Feature correlation was checked by the Pearson criterion, the selected patients subgroups were confirmed by using MannWhitney and Student's tests. Results. For the vast majority of patients with paroxysmal atrial fibrillation, heart rate variability can be described by five parameters. Each of these parameters captures a distinct approach in heart rate variability classification: dispersion characteristics of interbeat intervals, frequency characteristics of interbeat intervals, measurements of heart rate fragmentation, indices based on heart rate asymmetry, mean and median of interbeat intervals. Two large phenotypes of the disease were derived based on these parameters: the first phenotype is a vagotonic profile with a significant increase of linear parasympathetic indices and paroxysmal atrial fibrillation lasting longer than 4.5 hours; the second phenotype with increased sympathetic indices, low parasympathetic indices and paroxysms lasting up to 4.5 hours. Conclusion. Our findings indicate the potential of nonlinear analysis in the study of heart rate variability and demonstrate the feasibility of further integration of nonlinear indices for arrhythmia phenotyping.

Simulations of Bay of Bengal tropical cyclones in a regional convection-permitting atmosphere–ocean coupled model

Tropical cyclones (TCs) in the Bay of Bengal can be extremely destructive when they make landfall in India and Bangladesh. Accurate prediction of their track and intensity is essential for disaster management. This study evaluates simulations of Bay of Bengal TCs using a regional convection-permitting atmosphere-ocean coupled model. The Met Office Unified Model atmosphere-only configuration (4.4 km horizontal grid spacing) is compared with a configuration coupled to a three-dimensional dynamical ocean model (2.2 km horizontal grid spacing). Simulations of six TCs from 2016–2019 show that both configurations produce accurate TC tracks for lead times of up to 6 days before landfall. Both configurations underestimate high wind speeds and high rain rates, and overestimate low wind speeds and low rain rates. The ocean-coupled configuration improves landfall timing predictions and reduces wind speed biases relative to observations outside the eyewall but underestimates maximum wind speeds in the eyewall for the most intense TCs. The coupled configuration produces weaker TCs than the atmosphere-only configuration, consistent with lower sea surface temperatures in the coupled model and an overestimated cooling response in TC wakes. Both model configurations accurately predict rain rate asymmetry, suggesting a good representation of TC dynamics. Much of the rain rate asymmetry variation in the simulations is related to wind shear variations, with a preference for higher rain rates in the down-shear left quadrant.

Hindbrain neuropore tissue geometry determines asymmetric cell-mediated closure dynamics in mouse embryos

Gap closure is a common morphogenetic process. In mammals, failure to close the embryonic hindbrain neuropore (HNP) gap causes fatal anencephaly. We observed that surface ectoderm cells surrounding the mouse HNP assemble high-tension actomyosin purse strings at their leading edge and establish the initial contacts across the embryonic midline. Fibronectin and laminin are present, and tensin 1 accumulates in focal adhesion-like puncta at this leading edge. The HNP gap closes asymmetrically, faster from its rostral than caudal end, while maintaining an elongated aspect ratio. Cell-based physical modeling identifies two closure mechanisms sufficient to account for tissue-level HNP closure dynamics: purse-string contraction and directional cell motion implemented through active crawling. Combining both closure mechanisms hastens gap closure and produces a constant rate of gap shortening. Purse-string contraction reduces, whereas crawling increases gap aspect ratio, and their combination maintains it. Closure rate asymmetry can be explained by asymmetric embryo tissue geometry, namely a narrower rostral gap apex, whereas biomechanical tension inferred from laser ablation is equivalent at the gaps’ rostral and caudal closure points. At the cellular level, the physical model predicts rearrangements of cells at the HNP rostral and caudal extremes as the gap shortens. These behaviors are reproducibly live imaged in mouse embryos. Thus, mammalian embryos coordinate cellular- and tissue-level mechanics to achieve this critical gap closure event.

Heart Rate Asymmetry Analysis During Head-Up Tilt Test in Healthy Men

The purpose of this study is to assess the cardiovascular system response to orthostatic stress in a group of 133 healthy men using heart rate asymmetry (HRA) methods. HRA is a feature of variability in human heart rate which is dependent upon external and internal body conditions. The initial phases of head-up tilt test (HUTT), namely, supine and tilt, were chosen as the external body affecting factors. Various calculation methods of HRA, such as Porta’s index (PI), Guzik’s index (GI), and its variance based components, were used to assess the heart rate variability (HRV) and its asymmetry. We compared 5-min ECG recordings from both supine and tilt phases of HUT test. Short-term HRA was observed in 54.1% of men in supine phase and 65.4% of men in tilt phase. The study revealed significant increase of GI (from 0.50 to 0.52, p &lt; 0.001) in the tilt phase as well as significant changes in HRV descriptors between HUTT phases. Our results showed that the variability of human heart rate and its asymmetry are sensitive to orthostatic stress. The study of short-term HRA is a potential additional tool to increase sensitivity in conditions where HUTT is a diagnostic tool, such as vasovagal syncope.

Forecasts of tropical cyclones in the Bay of Bengal in a regional convection-permitting atmosphere-ocean coupled model

&lt;p&gt;Tropical cyclones (TCs) forming over the Bay of Bengal can cause devastation when they make landfall in India and Bangladesh; accurate prediction of their track and intensity is essential for disaster management. TC intensity is moderated by heat, momentum and moisture exchanges between the atmosphere and ocean. In recent years there have been significant improvements in the skill of TC forecasts due to the implementation of coupled atmosphere-ocean models and high-resolution models capable of explicitly resolving small-scale physical processes influencing storm development.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;This study evaluates the representation of six TCs in the Bay of Bengal from 2016 to 2019, using both a Met Office Unified Model atmosphere-only configuration (ATM) with 4.4 km grid spacing, and coupled to a 2.2 km resolution NEMO (Nucleus for European Models of the Ocean) ocean model (CPL). To determine the impact of coupling on wind-driven mixing and ocean-atmosphere heat exchange, forecast sea surface temperature (SST) is compared to observations. The impact of coupling on track position and storm intensity is evaluated using predictions of minimum sea level pressure (MSLP) and 10 m maximum sustained winds (MSW). Representation of TC dynamics is assessed by analysing storm structure, using radius of maximum winds and rain rate asymmetry.&lt;/p&gt;&lt;p&gt;&amp;#160;&lt;/p&gt;&lt;p&gt;Results from the three most intense TC case studies (Fani, Titli, and Vardah) show that SSTs in ATM are too high, while SSTs in CPL are slightly too low, with an overestimation of the cooling response in TC wakes. TC track position errors are small, but intensity error metrics for MSLP and MSW show biases relative to observations. Peak intensity is overestimated for Titli and Vardah in the ATM model configuration; the CPL model configuration generally produces weaker storms than the ATM model configuration. Wind speeds outside the storm centre are high compared to observations, with a greater bias in the ATM model configuration. &amp;#160;Both model configurations produce accurate predictions of radius of maximum winds and rain rate asymmetry, suggesting a good representation of TC dynamics. Much of the variation in rain rate asymmetry in the forecasts can be explained by variations in wind shear.&lt;/p&gt;

Rationale, design and methods planned in a prospective study concerning the circadian rhythm of heart rate asymmetry in healthy subjects

Heart rate asymmetry (HRA) is a physiological phenomenon caused by an unequal (asymmetric) contribution of heart rate decelerations and accelerations to the variability (variance) and microstructure of the heart rhythm of sinus origin. HRA has been studied in healthy people and patients with heart failure, diabetes, obstructive sleep apnoea, ischaemic heart disease, and survivors of myocardial infarction. HRA is a particular form of the heart rate variability (HRV) phenomenon related to the changes in the duration of cardiac cycles of sinus origin. HRV is influenced by physical activity, age, gender or time of day. It has been reported that HRA expression differs between day and night. However, its circadian rhythm has not been analysed so far. Moreover, the differences in HRA expression related to gender, level of physical activity or age have not been investigated either. With this study, we aim to explore the circadian rhythm of the HRA features, as well as the relation of the HRA expression to gender, physical activity, sleep pattern and body composition in a group of at least 100 healthy adults of both sexes aged between 19 and 60. This study might provide reference values for HRA as well as confirming or dismissing the existence of circadian rhythm of this physiological phenomenon.

Toward a universal model for spatially structured populations

Microbial populations often have complex spatial structures, with homogeneous competition holding only at a local scale. Population structure can strongly impact evolution, in particular by affecting the fixation probability of mutants. Here, we propose a model of structured microbial populations on graphs, where each node of the graph contains a well-mixed deme whose size can fluctuate, and where migrations are independent from birth and death events. We study analytically and numerically the mutant fixation probabilities in different structures, in the rare migration regime. In particular, we demonstrate that the star graph continuously transitions between amplifying and suppressing natural selection as migration rate asymmetry is varied. This elucidates the apparent paradox in existing constant-size models on graphs, where the star is an amplifier or a suppressor depending on the details of the dynamics or update rule chosen, e.g. whether each birth event precedes or follows a death event. The celebrated amplification property of the star graph for large populations is preserved in our model, for specific migration asymmetry. We further demonstrate a general mapping between our model and constant-size models on graphs, under a constraint on migration rates, which directly stems from assuming constant size. By lifting this constraint, our model reconciles and generalizes previous results, showing that migration rate asymmetry is key to determining whether a given population structure amplifies or suppresses natural selection.