Many neuro-degenerative diseases are difficult to diagnose in their early stages. For example, early diagnosis of Mild Cognitive Impairment (MCI) requires a wide variety of tests to distinguish MCI symptoms and normal consequences of aging. In this article, we use the wavelet–skeleton approach to find some characteristic patterns in the electroencephalograms (EEGs) of healthy adult patients and patients with cognitive dysfunctions. We analyze the EEG activity recorded during natural sleep of 11 elderly patients aged between 60 and 75, six of whom have mild cognitive impairment, and apply a nonlinear analysis method based on continuous wavelet transformskeletons. Our studies show that a comprehensive analysis of EEG signals of the entire sleep state allows us to identify a significant decrease in the average duration of oscillatory patterns in the frequency band [12; 14] Hz in the presence of mild cognitive impairment. Thus, the changes in this frequency range can be interpreted as related to the activity in the motor cortex, as a candidate for developing the criteria for early objective MCI.

The genetic architecture of blood pressure (BP) includes more than 30 genes, the polymorphic variants of which cause phenotypic heterogeneity of BP. Given that a human genetic information is largely stable from birth, it can act as an early predictor of hypertension (HTN). Identification of polymorphic variants of genes associated with a high HTN risk may be one of the promising areas of early diagnosis and prevention of this disease. In addition, the availability of this data will make it possible to clarify the prognosis of patients already with HTN, as well as to personalize the treatment approach. The review analyzes the papers devoted to the molecular genetic basis of hypertension and identifies the possible role of gene polymorphism of the renin-angiotensin-aldosterone system in hypertension development. A large number of studies have revealed an association between HTN and polymorphic variants of the ACE, AGT, AGTR1 genes. In addition, polymorphism of these genes is involved in the development of atherosclerosis and related diseases, kidney and central nervous system disorders, and justifies the effectiveness of angiotensin-converting enzyme inhibitors in the treatment of HTN.

Показатели регуляции сосудистого тонуса и полиморфизм генов, ассоциированный с кардиоваскулярным риском, у молодых, относительно здоровых лиц

This paper presents the results of a study of the characteristics of phase synchronization between electrocardiography(ECG) and electroencephalography (EEG) signals during night sleep. Polysomnographic recordings of eight generally healthy subjects and eight patients with obstructive sleep apnea syndrome were selected as experimental data. A feature of this study was the introduction of an instantaneous phase for EEG and ECG signals using a continuous wavelet transform at the heart rate frequency using the concept of time scale synchronization, which eliminated the emergence of asynchronous areas of behavior associated with the “leaving” of the fundamental frequency of the cardiovascular system. Instantaneous phase differences were examined for various pairs of EEG and ECG signals during night sleep, and it was shown that in all cases the phase difference exhibited intermittency. Laminar areas of behavior are intervals of phase synchronization, i.e., phase capture. Turbulent intervals are phase jumps of 2π. Statistical studies of the observed intermittent behavior were carried out, namely, distributions of the duration of laminar sections of behavior were estimated. For all pairs of channels, the duration of laminar phases obeyed an exponential law. Based on the analysis of the movement of the phase trajectory on a rotating plane at the moment of detection of the turbulent phase, it was established that in this case the eyelet intermittency was observed. There was no connection between the statistical characteristics of laminar phase distributions for intermittent behavior and the characteristics of night breathing disorders (apnea syndrome). It was found that changes in statistical characteristics in the phase synchronization of EEG and ECG signals were correlated with blood pressure at the time of signal recording in the subjects, which is an interesting effect that requires further research.