Simulating Dynamics of Circulation in the Awake State and Different Stages of Sleep Using Non-autonomous Mathematical Model With Time Delay

We propose a mathematical model of the human cardiovascular system. The model allows one to simulate the main heart rate, its variability under the influence of the autonomic nervous system, breathing process, and oscillations of blood pressure. For the first time, the model takes into account the activity of the cerebral cortex structures that modulate the autonomic control loops of blood circulation in the awake state and in various stages of sleep. The adequacy of the model is demonstrated by comparing its time series with experimental records of healthy subjects in the SIESTA database. The proposed model can become a useful tool for studying the characteristics of the cardiovascular system dynamics during sleep

Phenological shifts of abiotic events, producers and consumers across a continent

Ongoing climate change can shift organism phenology in ways that vary depending on species, habitats and climate factors studied. To probe for large-scale patterns in associated phenological change, we use 70,709 observations from six decades of systematic monitoring across the former Union of Soviet Socialist Republics. Among 110 phenological events related to plants, birds, insects, amphibians and fungi, we find a mosaic of change, defying simple predictions of earlier springs, later autumns and stronger changes at higher latitudes and elevations. Site mean temperature emerged as a strong predictor of local phenology, but the magnitude and direction of change varied with trophic level and the relative timing of an event. Beyond temperature-associated variation, we uncover high variation among both sites and years, with some sites being characterized by disproportionately long seasons and others by short ones. Our findings emphasize concerns regarding ecosystem integrity and highlight the difficulty of predicting climate change outcomes. The authors use systematic monitoring across the former USSR to investigate phenological changes across taxa. The long-term mean temperature of a site emerged as a strong predictor of phenological change, with further imprints of trophic level, event timing, site, year and biotic interactions.Peer reviewe

Problem of power spectra estimation in application to the analysis of heart rate variability

We investigated how the parameters of the spectral analysis affect standard deviation and error of the estimation of well-known indices for the heart rate variability. We compared the nonparametric Fourier transform to the parametric approach based on autoregressive models. We also investigated how the precision of the indices estimation depends on the choice of the window function, parameterization of the Bartlett’s method, and the lengths of time series. For each set of parameters, we calculated the sensitivity and specificity of the resulting indices when diagnosing arterial hypertension. To isolate and investigate the errors caused by inaccuracy of the spectral analysis itself, we conducted our study using the mathematical models of heart rate variability for healthy subjects and arterial hypertension patients, for which the correct values of the spectral indices are known. The obtained results suggest that the analysis of 20-min signals, comparing to 5-min signals, significantly decreases the standard deviation of the estimations and increases both their sensitivity and specificity. We found no advantages of using the parametric approach over the Fourier transform. We have shown that application of the Hann’s window function and normalization of the spectral indices decreases the sensitivity and specificity of the medical diagnostics

Dynamics of 0.1 Hz Oscillations Synchronization in Cardiovascular System during the Treatment of Acute Myocardial Infarction Patients

Aim: The aim was the studying of synchronization between 0.1 Hz oscillations in heart rate (HR) and plethysmographic peripheral microcirculation (PM) in acute myocardial infarction (AMI) patients and in healthy subjects. Material and Method: 12 healthy volunteers aged 26±5 years and 125 patients with AMI aged 65±9 years were involved in the study. Simultaneous registration of electrocardiogram and photoplethysmogram were performed during 10 min. In AMI patients the signals were recorded twice: the first record was done during 3-5 days after AMI, the second record was done during the third week after AMI. Phase differences between HR and PM oscillations were used to measure the degree of synchronization (S). Data are submitted as medians with inter-quartile ranges (25%, 75%). Results: S was 65.8% (50.5%; 79.5%) in healthy subjects whereas in AMI patients at the first week after AMI S was 16.3% (9.4%; 24.6%) (p<0.001). In records made at the third week after AMI index S was 18.4% (11.2%; 28.2%). Two groups of AMI patients were identified on the basis of individual S dynamics. In 100 AMI patients no dynamics of S was observed during the observation period and in 25 AMI patients the increase of S was observed. The group of AMI patients with increase of S had greater HR values during the first week after AMI. Conclusion: The index S of synchronization of 0.1 Hz oscillations in HR and PM appears to be a sensitive indicator of autonomic control dynamic disturbances in AMI patients

Biomarkers of the psychophysiological state during the cognitive tasks estimated from the signals of the brain, cardiovascular and respiratory systems

Diagnostics of the psychophysiological state at rest and under stressful conditions is an important problem. We tested various biomarkers of the psychophysiological state of healthy volunteers at rest and while completing stress-inducing cognitive tasks, namely the Stroop color word test and mental arithmetic test. We tested the biomarkers based on the analysis of electroencephalograms, respiratory signals, and the signals of cardiovascular system. We investigated both the individual characteristics of these signals in the low-frequency range (less than 0.5 Hz), and characteristics of their interaction. According to our results, the most sensitive biomarkers of cognitive task stress are nonlinear phase coherence between the 0.15 and 0.40 Hz oscillations in the respiratory signal and heart rate variability, and integral power of the 0.15–0.40 Hz oscillations in the frontal lobe EEG leads

Lattice anharmonicity and polar soft mode in ferrimagnetic M-type hexaferrite BaFe

The polar phonon modes in BaFe12O19 single crystal are studied in the temperature range from 6 to 300 K by polarized infrared spectroscopy. The phonon spectrum of the crystal is strongly anharmonic and unstable with respect to long-wavelength fluctuations of the dielectric permittivity along the hexagonal axis. Our results suggests that in BaFe12O19 hexaferrite symmetry lowering to the polar phase with the space group P63mc can be expected