The pineal gland is a small and poorly studied neuroendocrine gland located in the epithalamus. There is growing interest in the pineal gland due to its role in regulating human biological rhythms, which is associated with melatonin production, and its close neuroendocrine link between the brain's hormonal and neurally mediated activity. The paper examines the anatomical and physiological features of the pineal gland, its structural variations, and the role of the melatonin it produces in the pathogenesis of several mental and neurological disorders.

INTRODUCTION: Pineal cysts are a common finding on brain MRI, but their which remains unclear. A theory has been put forward that non-occlusive cysts can compress the deep cerebral veins, leading to intracranial hypertension.OBJECTIVE: Тo study the variant MRI appearance of the pineal gland.MATERIALS AND METHODS: 48 volunteers underwent an MRI examination using a 1.5 T Toshiba Exelart Vantage device to assess the presence of MRI signs of central venous hypertension, taking into account the morphological variants of the pineal gland structure, and a category was assigned based on the calculated tectum-splenium-cyst ratio and thalamic coefficient. The mean age of men was 41.27±4.63, of women — 31.5±2.58 years. The study participants were divided into three groups: the 1st group — no pineal cyst, the 2nd group — pineal cyst less than 10 mm, the 3rd group —a cyst larger than 10 mm.RESULTS: Based on the obtained tectum-splenium-cyst ratios and the ADC coefficient, it was found that in the volunteer group with cysts larger than 10 mm, 8 out of 15 people were at increased risk of developing central venous hypertension (categories 3 and 4). Category 4 patients had the narrowest aqueduct (1.1–1.2 mm). In the 2nd group, in persons with a pineal cyst less than 10 mm, there were no signs of aqueductal stenosis or tectal plate compression. In the 3rd group, in persons without a pineal cyst, there were also no signs of aqueductal stenosis or tectal plate compression, however, category 3 was assigned to 8 volunteers, which may be due to other causes of venous outflow impairment.CONCLUSION: A large pineal cysts occur in younger patients, and in the presence of aqueductal narrowing and an increased risk of venous hypertension may cause clinical manifestations such as headaches, dizziness, and sleep disturbances. When patients present with relevant complaints, categorization based on DWI and SSFP is an additional criterion that reflects the degree of impact of the pineal cyst on adjacent structures.

INTRODUCTION: The differential diagnosis of mild cognitive impairment (MCI), due to the high prevalence in the population and the rapid increase in incidence, is an urgent task. The most common causes leading to the development of cognitive impairment are Alzheimer’s disease (AD), cerebrovascular pathology, and their combination. AD usually manifests as an amnestic type of mild cognitive impairment (aMCI) at the pre-dementia stage. Subcortical vascular mild cognitive impairment (svMCI) is considered as the prodromal stage of subcortical vascular dementia. According to the results of pathomorphological studies, it was found that subfields of the hippocampal formation are selective vulnerability to AD, ischemia/hypoxia, and aging.Currently, using the FreeSurfer 6.0 software, it is possible to obtain quantitative indicators of the hippocampal formation subfields in vivo.The current trend in medicine is the development and implementation of new diagnostic solutions based on artificial intelligence and machine learning. One of the machine learning algorithms is binary logistic regression, which we used in the course of the study for the differential diagnosis of MCI of various origins.OBJECTIVE: To develop a method for the differential diagnosis of mil cognitive impairment of various origins.MATERIALS AND METHODS: The study included patients with the syndrome of mild cognitive impairment who were examined in the department of geriatric psychiatry of the V.M.Bekhterev National Medical Research Center for Psychiatry and Neurology, from which two groups were formed: group 1 — patients with aMCI, group 2 — patients with svMCI. Conditionally healthy volunteers, comparable in age, sex and level of education, made up the 3rd group (control). MRI examination was performed using a Excelart Vantage Atlas XGV magnetic resonance imaging system (Toshiba, Japan) with a magnetic field strength of 1.5 T, followed by MR morphometry of the subfields of the hippocampal formation.Statistics: Statistical analysis was carried out using data that was converted from a database in Microsoft Excel to the statistical package IBM SPSS 21. To develop a differential diagnosis method, based on the data obtained, the binary regression method and ROC analysis were used.RESULTS: Based on the obtained MR-morphometry data, a method was developed using the binary logistic regression equation. The value of p≥0.5 makes it possible to classify the patient to the aMCI group, and the value of p<0.5 — to the svMCI. The sensitivity of the method is 90%, the specificity is 80%, and the accuracy is 85%.DISCUSSION: Using binary logistic regression, the selection of variants of sets of variables (quantitative indicators) was carried out, for which ROC curves were constructed. The selection criterion was the area under the ROC curve — the AUC criterion (Area Under the Curve). The largest area under the curve (AUC=0.824) in the differential diagnosis of aMCI from svMCI was determined for the combination of the volume of the left subiculum and the thickness of the right entorhinal cortex.Since patients in the aMCI group have a significantly lower number of vascular foci than in the svMCI group (p<0.05), at the next stage, one more variable, the volume fraction, was added to the selected combination of two variables (volume of the left subiculum and thickness of the right entorhinal cortex) hypointense foci. When conducting an ROC analysis with a combination of three variables, an increase in AUC to 0.892 was noted. Further, using a combination of three variables and a binary logistic regression equation, a method for differential diagnosis of aMCI from svMCI was developed.CONCLUSION: The method of differential diagnosis based on binary logistic regression using MR morphometry data allows to distinguish patients with aMCI from patients with svMCI with high sensitivity and specificity.

The aim of our study was to research the literature data available for analysis of the melatonin role in the neurological and mental disorders origin. Materials and methods: to compile a literature review by keywords, articles there were selected and analyzed in the MEDLINE / PubMed and e-library databases from 1993 to 2021. For a detailed analysis, 42 literature sources were selected for the melatonin role in the development of neurological and mental disorders. Results: Melatonin is a hormone with unique adaptive capabilities. Violation of its production, both quantitatively and its rhythm, is the starting point, leading at the initial stages to desynchronizes, followed by the emergence of organic pathology. Consequently, the very fact of a violation of melatonin production can be the cause of various diseases. It was found that the volume of the pineal gland can change with the development of various types of neurological and psychiatric diseases, which is associated with a violation of the synthesis of melatonin and serotonin. Melatonin has been found to have important protective properties in Alzheimer's disease - the ability to inhibit the formation of beta-amyloid peptide in the brain, which is the morphological basis of this disease. The same correlation was found in patients with autism, psychosis and obsessive-compulsive disorder compared with healthy volunteers. Regarding the neuroprotective properties of melatonin, it should be noted its effectiveness in age-related diseases (Alzheimer's, Parkinson's, vascular diseases) Conclusion: Melatonin can be considered as a unique bioregulator, adaptogen and stabilizer of the whole organism and, in particular, the functions of the central nervous system. It has been proven that disruption of melatonin metabolism leads to various neurological and mental disorders.

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