Bulletin of RSMU

ISSN Print 2500–1094 ISSN Online 2542–1204

Bulletin of RSMU

BIOMEDICAL JOURNAL OF PIROGOV UNIVERSITY (MOSCOW, RUSSIA)

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Levitskaya OS, Lebedev MA

Brain-computer interfaces (BCIs) are a promising technology intended for the treatment of diseases and trauma of the nervous system. BCIs establish a direct connection between the brain areas that remain functional and assistive devices, such as powered prostheses and orthoses for the arms and legs, motorized wheelchairs, artificial sensory organs and other technologies for restoration of motor and sensory functions. BCIs of various kinds are currently developing very rapidly, aided by the progress in computer science, robotic applications, neurophysiological techniques for recording brain activity and mathematical methods for decoding neural information. BCIs are often classified as motor BCIs (the ones that reproduce movements), sensory BCIs (the ones that evoke sensations), sensorimotor BCIs (the ones that simultaneously handle motor and sensory functions), and cognitive BCIs intended to regulate the higher brain functions. All these BCI classes can be either invasive (i. e. penetrating the body and/or the brain) or noninvasive (i.e. making no o little contact with the body surface). Noninvasive BCI are safe to use and easy to implement, but they suffer from signal attenuation by scalp and skin, its contamination with noise and artifacts, and an overall low information transfer rate. Invasive BCIs are potentially more powerful because they utilize implanted grids that can both record neural signals in high-resolution and apply stimulation to the nervous tissue locally to deliver information back to the brain. BCI technologies are being developed not only for individual use, but also for collective tasks performed by multiple interconnected brains.

Received: 2016-03-11

Published online: 2017-01-05

DOI: 10.24075/brsmu.2016-02-01

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VIEWS 3971

The article presents preliminary results of iMove research study. By the time of this publication, the data of 47 patients have been processed. The patients in the experimental group (n = 36) were trained in kinesthetic motor imagery using brain-computer interface (BCI) and a controllable exoskeleton. In the control group, BCI imitation procedures were carried out. In average, the patients had 9 training sessions with a duration of up to 40 minutes. On completing the training, only the experimental group showed improvement in scores (results are presented as median and quartiles (25 %; 75 %)): grasp score increased from 0.5 (0.0; 13.0) to 3.0 (0.0; 15.5) points (р = 0.003) and pinch score increased from 0.5 (0.0; 7.5) to 1.0 (0.0; 12.0) points (р = 0.005) on ARAT scale. In the experimental group, a significant improvement in motor function was found in 33.3 % patients on ARAT scale, and in 30.5 % patients on Fugl-Meyer scale. In the control group, those scores were lower: 9.1 % and 18.2 % patients, respectively.

Received: 2016-03-30

Published online: 2017-01-05

DOI: 10.24075/brsmu.2016-02-02

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VIEWS 3960

Bogdanov EA, Petrov VA, Botman SA, Sapunov VV, Stupin VA, Silina EV, Sinelnikova TG, Patrushev MV, Shusharina NN

Concurrent use of electrophysiological signals of various types, such as obtained from electroencephalogram (EEG), electromyogram (EMG), electrooculogram (EOG), and others, increases the effectiveness of systems for external device control, namely, neural prostheses, exoskeletons, robotic wheelchairs and teleoperated robots. This article presents the results of the first tests of a multifunctional neurodevice capable of detecting EEG, EMG and EOG signals simultaneously (with EOG signals photoplethysmogram, SpO<sub>2</sub> and temperature modules of the neurodevice were used). Measurement results were then compared to the data obtained from KARDi3 device (Medical Computer Systems, Russia) and Fluke 17b multimeter with a plug-in thermistor (Fluke Corporation, USA). The informative value and accuracy of both datasets were comparable. We also studied the effectiveness of EEG and EMG signal hybridization on the basis of the neurodevice of interest; it allowed for an increase of classification accuracy in all subjects by an average of 12.5 % up to the mean of 86.8 % (from 75 to 97 %).

Received: 2016-03-31

Published online: 2017-01-05

DOI: 10.24075/brsmu.2016-02-04

Comments 0

VIEWS 3667

Stepanichev MYu, Ivanov AD, Lazareva NA, Moiseeva YuV, Gulyaeva NV

β-amyloid peptide (Аβ) is an important component of the neurodegeneration mechanism in Alzheimer’s disease. This work investigates the effect of intrahippocampal injection of Аβ(25–35) fragment on nerve growth factor (NGF) signalling. Aggregated Аβ(25–35) was injected into rat dorsal hippocampus. Rats in the control group received injections of the peptide with an inverted amino acid sequence and a solvent. It was shown that Аβ(25–35) induces neuron death in rat hippocampus. Neurodegeneration was accompanied by a statistically significant increase (p < 0.05) in p75NTR neurotrophin receptor expression in all animals who had received exogenous peptides, and by an increased level of NGF in the hippocampus of those rats who had been injected with Аβ(25–35). The study results demonstrate that changes in the hippocampus induced by Аβ(25–35) are accompanied by increased NGF signalling, which, to some extent, supports the current clinical data obtained from patients with Alzheimer’s. The changes mentioned above are compensatory. However, both damage reparation and further degenerative processes can be the ultimate outcome.

Received: 2016-02-14

Published online: 2017-01-05

DOI: 10.24075/brsmu.2016-01-02

Comments 0

VIEWS 3380

Borisevich DI, Shatalova LV, Korostin DO, Ilinsky VV

Prediction of mutation pathogenicity and its effect on the phenotype is an important task of modern bioinformatics. This task is particularly difficult in regard to single nucleotide polymorphisms, as their effect is very hard to predict. Information on pathogenic mutations is provided by curated databases such as Online Mendelian Inheritance in Man (OMIM) and The Human Gene Mutation Database (HGMD) which include data from experimental works. However, as different authors interpret the term “mutation pathogenicity” differently, it is necessary to double-check data before using them. We have assessed HGMD database quality using the most common bioinformatic tools, namely, snpEff, polyphen2 and SIFT. Our study relied on the characteristics specific for harmless mutations: high frequency in a population, weak effect on amino acid sequence of a protein, low pathogenicity as computed by the utilities used in the study. As a result, we have identified clearly harmless variants among those in the mutation database, as well as ambiguous ones in which a mutation type depends on characteristics and tools used for the analysis.

Received: 2016-02-10

Published online: 2017-01-05

DOI: 10.24075/brsmu.2016-01-03

Comments 0

VIEWS 3476

Balatskiy AV, Chotchaeva FR, Ivanov AD, Samokhodskaya LM, Tkachuk VA

A number of studies have shown that a CDH13-encoded T-cadherin protein, which is a receptor for low density lipoproteins and adiponectin, an adipocyte hormone, is associated with atherosclerosis and coronary heart disease (CHD) development. Some single nucleotide polymorphisms in CDH13 gene affect the expression of T-cadherin and the levels of adiponectin and blood plasma lipids, but the connection between these polymorphisms and CHD development has not been studied yet. In this work the role of rs12051272, rs4783244, rs12444338 and rs11646213 single nucleotide polymorphisms in CHD development and its manifestations was investigated. The study enrolled men under 55 years of age: 79 patients with stable effort angina with no prior myocardial infarction, 107 patients with prior myocardial infarction being the first manifestation of CHD, and 99 healthy subjects. All subjects were clinically examined; laboratory tests and genotyping were conducted. The results of genotyping were evaluated using SNPStats on-line software. This study has not found a connection between CDH13 gene polymorphisms and CHD development. However, it was shown that rs12051272 polymorphism is associated with the specifics of the disease onset: GT genotype was detected in 13 (16.5 %) patients with stabile effort angina and only in 3 (2.8 %) patients with myocardial infarction (odd ratio of 7.54; 95 % confidence interval of 2.01–28.35). Thus, the study demonstrates that CDH13 gene polymorphism can affect atherogenesis and CHD manifestations.

Received: 2015-12-29

Published online: 2017-01-05

DOI: 10.24075/brsmu.2016-01-04

Comments 0

VIEWS 3461

Gorozhantsev YuN

Longer observation periods have been proven to increase the diagnostic value of Holter ECG monitoring for paroxysmal atrial fibrillation mainly. The aim of this work was to study the diagnostic efficacy of a long-term ECG monitoring in detecting various types of arrhythmias and to assess the uneven distribution of arrhythmias over different observation days. In this study 27 patients were examined, including 13 men and 14 women with a mean age of 42.8 ± 10.8 years, their complaints suggesting various types of tachy- and bradyarrhythmias. Compact recorders and original software were used. ECG recording time was 5-7 days. Using quantity criteria characterizing the level of uneven inter-day distribution of arrhythmias, advantages of long-term observations over a 24-hour monitoring were confirmed for such arrhythmias as sinus pauses over 2.5 seconds, a second degree AV block, paroxysmal supraventricular tachycardia, single and paired ventricular extrasystoles, ventricular salvos, ventricular tachycardia.

Received: 2015-09-11

Published online: 2017-01-05

DOI: 10.24075/brsmu.2016-01-05

Comments 0

VIEWS 3492

Astapov AA, Davydov DV, Egorov AI, Drozdov DV, Glukhovskij EM

The uniqueness of electrical activity of every human heart prompts us to use the ECG as a biometric parameter in various security and authentication systems as it is easy and cheap to extract the signal and difficult to fake it or obtain nonconsensually. At the moment various approaches to researching a possibility of human identification by ECG are used. Identification mode includes the following stages: data collection, procession, feature extraction, classification. Researchers use different mathematical algorithms at every stage: principal component analysis, wavelets, neural networks, etc. This article reviews the most significant studies of ECG based human identification and compares their results and accuracy of conceptual approaches.

Received: 2015-12-07

Published online: 2017-01-05

DOI: 10.24075/brsmu.2016-01-06

Comments 0

VIEWS 3604