Background: brain-derived neurotrophic factor (BDNF) may play a role during neurorehabilitation following ischemic stroke. This study aimed to elucidate the possible role of BDNF during early recovery from ischemic stroke assisted by motor training. Methods: fifty patients were included after acute recovery from ischemic stroke: 21 first received classical rehabilitation followed by ‘motor rehabilitation using motion sensors and augmented reality’ (AR-rehabilitation), 14 only received AR-rehabilitation, and 15 were only observed. Serum BDNF levels were measured on the first day of stroke, on the 14th day, before AR-based rehabilitation (median, 45th day), and after the AR-based rehabilitation (median, 82nd day). Motor impairment was quantified clinically using the Fugl–Meyer scale (FMA); functional disability and activities of daily living (ADL) were measured using the Modified Rankin Scale (mRS). For comparison, serum BDNF was measured in 50 healthy individuals. Results: BDNF levels were found to significantly increase during the phase with AR-based rehabilitation. The pattern of the sequentially measured BDNF levels was similar in the treated patients. Untreated patients had significantly lower BDNF levels at the endpoint. Conclusions: the fluctuations of BDNF levels are not consistently related to motor improvement but seem to react to active treatment. Without active rehabilitation treatment, BDNF tends to decrease.

Background. Variability of glycemia is an important problem in the control of diabetes mellitus. It can be assumed that cognitive impairment associated with this disease is due to the fact that variability of glycemia affects not only the structure, but also metabolism of the brain. Objective — the study was aimed at assessing the values of glycemia variability, as well as their relationship with neuropsychological testing and magnetic resonance imaging data in patients with type 1 diabetes mellitus (DM1). Material and methods. We carried out a one-stage observational study of sex and age matched patients with DM1 and individuals without diabetes. All participants underwent neuropsychological testing, magnetic resonance imaging (MRI), and proton magnetic resonance spectroscopy (PMRS) of the brain; fasting plasma glucose and glycated hemoglobin (HbA1c) levels were assessed. The results of continuous monitoring of glycemia were analyzed in DM1 patients followed by calculation of glycemic variability coefficients. Results. DM1 58 patients demonstrated decrease in neuropsychological testing scores (p<0.05), decrease in the gray matter volume (p=0.004), and increase in the white matter volume (p=0.001), as well as impaired metabolism of the brain (p<0.05). Correlations between the total result of the MoCa test and LI (r=–0.34; p=0.008), MODD (r=–0.36; p=0.005), and ADRR (r=–0.28; p=0.032) were found. Negative relationship between the CONGA index and the volume of the left hippocampus (r=–0.27; p=0.044) was found. There were also some correlations between the glycemic variability indexes and the content of the main metabolites in different areas of the brain (p<0.05). Conclusion. MD1 patients with cognitive dysfunction demonstrated anatomical and metabolic brain disorders associated with glycemic variability.

Medical article медицинская статья

Background: Motor recovery after stroke is based on neuronal plasticity and the structural reorganization of the brain. Questions are debated about the proper moment to start rehabilitation in the acute period of stroke, the significance of rehabilitation interventions during the so-called “plastic window”, and the advantages of modern and traditional programs. The aims of this study were to evaluate the role of different rehabilitation strategies and their combinations for motor recovery and the impact on functional disability by way of neurological and functional outcomes 3 months after ischemic stroke. Methods: We used three rehabilitation approaches: early rehabilitation from the first day of stroke (Phase I), traditional exercise programs (Phase II), and an author’s new method of biofeedback rehabilitation using motion sensors and augmented reality (AR) rehabilitation (Phase III). Clinical and functional outcomes were measured on the 90th day after stroke. We developed algorithms for quantifying the quality of movements during the execution of tasks in the motor domains of the AR rehabilitation program. Results: Phase I of rehabilitation led to an improvement in functional independence, and the recovery of motor functions of the extremities with an absence of mortality and clinical deterioration. AR rehabilitation led to significant improvement both with respect to clinical and functional scores on scales and to variables reflecting the quality of movements. Patients who were actively treated during Phases II and III achieved the same final level of motor recovery and functional outcomes as that of participants who had only received AR rehabilitation during Phase III. Patients who underwent outpatient observation after Phase I showed a deficit of spontaneous motor recovery on the 90th day after stroke. Conclusions: Early rehabilitation was successful but was not enough; rehabilitation programs should be carried out throughout the entire “sensitive period” of poststroke plasticity. The newly developed AR biofeedback motion training is effective and safe as a separate rehabilitation method in the early recovery period of moderately severe, hemiparalytic, and ischemic stroke. These two rehabilitation approaches must be applied together or after each other, not instead of each other, as shown in clinical practice.

Sarcopenia is characterized by a progressive loss of muscle mass, strength, and function, leading to poor outcomes and reduced quality of life. In middle age, the decrease in muscle mass begins to be progressive. Bioimpedancemetry allows diagnosing this condition before the onset of clinical symptoms. The purpose of the study: to evaluate the parameters of body composition in the early diagnosis of sarcopenia in middle-aged people. Materials and Methods: The participants were divided into two groups the main one with sarcopenia 146 people and the control group 75 people. The complex of examinations included: neuropsychological testing (Hospital Anxiety and Depression Scale (HADS), quality of life questionnaire for patients with sarcopenia (SarQoL), short health assessment form (SF-36)), 4-meter walking speed test, dynamometry and bioimpedancemetry. The results of neuropsychological examination did not differ in the main and control groups. Patients with sarcopenia showed a decrease in muscle strength according to dynamometry. The scores of the walking speed assessment test in the study group were significantly higher than in the control group. The main and control groups had excessive body weight. According to the results of bioimpedanceometry, the main group had increased fat mass, percentage of fat mass, visceral fat area, and fat mass index compared with the control group. Skeletal muscle mass was less in the main group, probable sarcopenia was confirmed by decreased appendicular mass, decreased protein and mineral content was also recorded. There was a more pronounced decrease in cell mass in the main group. In patients with sarcopenia the volume of intracellular and extracellular fluid was less than in the control group. Significant differences were considered at p0.05. Conclusions: the introduction of bioimpedancemetry and dynamometry into early screening for muscle mass reduction will allow timely start of therapeutic and preventive measures even in middle age, which will lead to a decrease in the progression of sarcopenia in the elderly, as well as improve the quality of life.

This literature review is devoted to the study of recent advances in the field of neurorehabilitation using robotic technologies. Objective: to study best practices of applying robotic rehabilitation technologies in stroke patients, its clinical efficacy and influence on the molecular mechanisms of neuroplasticity. Keywords were searched in the Web of Science, Core Collection, Scopus and PubMed databases.Results.Robotic neurorehabilitation occupies a certain place in the comprehensive rehabilitation of patients with motor deficiency after stroke. An interdisciplinary patient-oriented approach and consistency at all stages of medical rehabilitation are especially important when using rehabilitation methods that implement advances in robotics and information technologies in patients after stroke. Rehabilitation with the use of high-tech computerized rehabilitation systems operating in the biofeedback mode is one of the promising areas and requires further neurophysiological and laboratory studies to create scientifically based methodological approaches. It will have great social significance and tangible economic effects from improving the quality of neurorehabilitation and reducing its duration.