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    ИсслСдованиС Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠ² Ρ‚Ρ€Π΅Π²ΠΎΠ³ΠΈ ΠΈ дСпрСссии Ρƒ Π»ΠΈΡ† c мягким ΠΊΠΎΠ³Π½ΠΈΡ‚ΠΈΠ²Π½Ρ‹ΠΌ сниТСниСм Π² условиях ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ COVID-19

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    Background. The COVID-19 pandemic is a major stressor with predictable negative impacts on mental health, especially for vulnerable populations, which include older people. Emotional disorders, a decrease in intellectual, physical, social activity are the risk factors for the development of cognitive decline in older people; in the situation of the COVID-19 pandemic, the influence of all these factors is exacerbated. In this regard, it seems relevant to study the level of emotional disorders and factors affecting the emotional state of patients with mild cognitive impairment (MCI) in the context of the COVID-19 pandemic in comparison with the period before the pandemic. Aims: emotional state assessment in patients over 55 years old with MCI during the COVID-19 pandemic and identification of factors influencing the emotional state of these patients. Materials and methods: A cross-sectional single-center observational study of patients with MCI who applied to the Memory Clinic in the autumn of 2018 (n = 121), 2019 (n = 114), in the autumn of 2020 (n = 70), and in the spring of 2020 (n = 110). Patients were examined using the Hospital Anxiety and Depression Scale (HADS), the Montreal Cognitive Assessment (MoCA), the MiniMental State Examination (MMSE), and the Khachinsky Modified Ischemia Assessment Scale. In 2020, in addition to these scales, a questionnaire Personal experience of COVID-19 pandemic was applied to assess the experience associated with the new coronavirus infection. Results: The severity of emotional disorders, assessed by HADS scale, did not differ between groups (F = 0.751; p = 0.522 and F = 0.310; p = 0.818 for the HADS anxiety and depression subscales, respectively). Adjustment for covariates (scores on the Khachinsky and/or MoCA and/or MMSE scales) did not affect the significance of differences between groups on the HADS subscales, regardless of the correction for multiple comparisons. Pathway modeling analysis demonstrated the low ability of the models to predict emotional state based on risk factors (age, gender, Khachinsky score) and cognitive symptoms (MoCA and MMSE scores) all coefficients r 0.7. A change in intellectual activity (decrease) and subjective impression of the difficulties obtaining medical care were associated with a higher score on the HADS anxiety scale. Decreased physical health and decreased personal communication were associated with higher scores on the HADS depression scale. Clinically pronounced changes in the emotional state were noted only in relation to anxiety, which depended on the changes in intellectual activity. Conclusions: severity of anxiety and depression was not increased in patients with MCI, regardless of the control of additional factors. No differences were found in the contribution of risk factors (age, gender, vascular and atrophic factors of cognitive decline) and cognitive dysfunction to the formation of emotional disorders in comparing with previous years.ОбоснованиС. ПандСмия COVID-19 являСтся ΠΌΠΎΡ‰Π½Ρ‹ΠΌ стрСссогСнным Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠΌ с ΠΏΡ€ΠΎΠ³Π½ΠΎΠ·ΠΈΡ€ΡƒΠ΅ΠΌΡ‹ΠΌ ΠΎΡ‚Ρ€ΠΈΡ†Π°Ρ‚Π΅Π»ΡŒΠ½Ρ‹ΠΌ влияниСм Π½Π° психичСскоС Π·Π΄ΠΎΡ€ΠΎΠ²ΡŒΠ΅, Π² особСнности уязвимых Π³Ρ€ΡƒΠΏΠΏ насСлСния, ΠΊ ΠΊΠΎΡ‚ΠΎΡ€Ρ‹ΠΌ относятся люди ΡΡ‚Π°Ρ€ΡˆΠ΅Π³ΠΎ возраста. Π­ΠΌΠΎΡ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Π΅ Π½Π°Ρ€ΡƒΡˆΠ΅Π½ΠΈΡ, ΡƒΠΌΠ΅Π½ΡŒΡˆΠ΅Π½ΠΈΠ΅ ΠΈΠ½Ρ‚Π΅Π»Π»Π΅ΠΊΡ‚ΡƒΠ°Π»ΡŒΠ½ΠΎΠΉ, физичСской, ΡΠΎΡ†ΠΈΠ°Π»ΡŒΠ½ΠΎΠΉ активности ΡΠ²Π»ΡΡŽΡ‚ΡΡ Ρ„Π°ΠΊΡ‚ΠΎΡ€Π°ΠΌΠΈ риска развития ΠΊΠΎΠ³Π½ΠΈΡ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ сниТСния Ρƒ людСй ΡΡ‚Π°Ρ€ΡˆΠ΅Π³ΠΎ возраста, Π² ситуации ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ COVID-19 влияниС всСх этих Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠ² усугубляСтся. Π’ связи с этим прСдставляСтся Π°ΠΊΡ‚ΡƒΠ°Π»ΡŒΠ½Ρ‹ΠΌ ΠΈΠ·ΡƒΡ‡ΠΈΡ‚ΡŒ ΡƒΡ€ΠΎΠ²Π΅Π½ΡŒ ΡΠΌΠΎΡ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… Π½Π°Ρ€ΡƒΡˆΠ΅Π½ΠΈΠΉ ΠΈ Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠ², Π²Π»ΠΈΡΡŽΡ‰ΠΈΡ… Π½Π° ΡΠΌΠΎΡ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠ΅ состояниС ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² с мягким ΠΊΠΎΠ³Π½ΠΈΡ‚ΠΈΠ²Π½Ρ‹ΠΌ сниТСниСм (МКБ), Π² условиях ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ COVID-19 Π² сравнСнии с ΠΏΠ΅Ρ€ΠΈΠΎΠ΄ΠΎΠΌ Π΄ΠΎ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ. Π¦Π΅Π»ΠΈ исслСдования ΠΎΡ†Π΅Π½ΠΊΠ° ΡΠΌΠΎΡ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠ³ΠΎ состояния Ρƒ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² ΡΡ‚Π°Ρ€ΡˆΠ΅ 55 Π»Π΅Ρ‚ с МКБ Π² ΠΏΠ΅Ρ€ΠΈΠΎΠ΄ ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠΈ COVID-19 ΠΈ выявлСниС Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠ², ΠΎΠΊΠ°Π·Ρ‹Π²Π°ΡŽΡ‰ΠΈΡ… влияниС Π½Π° ΡΠΌΠΎΡ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠ΅ состояниС Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΠΊΠΎΠ½Ρ‚ΠΈΠ½Π³Π΅Π½Ρ‚Π° ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ². ΠœΠ΅Ρ‚ΠΎΠ΄Ρ‹. ΠŸΠΎΠΏΠ΅Ρ€Π΅Ρ‡Π½ΠΎΠ΅ ΠΎΠ΄Π½ΠΎΡ†Π΅Π½Ρ‚Ρ€ΠΎΠ²ΠΎΠ΅ Π½Π°Π±Π»ΡŽΠ΄Π°Ρ‚Π΅Π»ΡŒΠ½ΠΎΠ΅ исслСдованиС ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² с МКБ, ΠΎΠ±Ρ€Π°Ρ‚ΠΈΠ²ΡˆΠΈΡ…ΡΡ Π² ΠšΠ»ΠΈΠ½ΠΈΠΊΡƒ памяти осСнью 2018 (n = 121), 2019 (n = 114), осСнью (n = 70) ΠΈ вСсной (n = 110) 2020 Π³. ΠŸΠ°Ρ†ΠΈΠ΅Π½Ρ‚Ρ‹ ΠΏΡ€ΠΎΡ…ΠΎΠ΄ΠΈΠ»ΠΈ обслСдования с использованиСм Π“ΠΎΡΠΏΠΈΡ‚Π°Π»ΡŒΠ½ΠΎΠΉ ΡˆΠΊΠ°Π»Ρ‹ Ρ‚Ρ€Π΅Π²ΠΎΠ³ΠΈ ΠΈ дСпрСссии (Hospital Anxiety and Depression Scale, HADS), ΠœΠΎΠ½Ρ€Π΅Π°Π»ΡŒΡΠΊΠΎΠΉ ΡˆΠΊΠ°Π»Ρ‹ ΠΎΡ†Π΅Π½ΠΊΠΈ ΠΊΠΎΠ³Π½ΠΈΡ‚ΠΈΠ²Π½Ρ‹Ρ… Ρ„ΡƒΠ½ΠΊΡ†ΠΈΠΉ (Montreal Cognitive Assessment, MoCA), Π¨ΠΊΠ°Π»Ρ‹ ΠΊΡ€Π°Ρ‚ΠΊΠΎΠΉ ΠΎΡ†Π΅Π½ΠΊΠΈ психичСского состояния (MiniMental State Examination, MMSE), ΠœΠΎΠ΄ΠΈΡ„ΠΈΡ†ΠΈΡ€ΠΎΠ²Π°Π½Π½ΠΎΠΉ ΡˆΠΊΠ°Π»Ρ‹ ΠΎΡ†Π΅Π½ΠΊΠΈ ишСмии Π₯ачинского. Π’ 2020 Π³. ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚Π°ΠΌ Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡ‚Π΅Π»ΡŒΠ½ΠΎ ΠΊ ΡƒΠΊΠ°Π·Π°Π½Π½Ρ‹ΠΌ шкалам ΠΏΡ€Π΅Π΄ΡŠΡΠ²Π»ΡΠ»ΡΡ опросник Π›ΠΈΡ‡Π½Ρ‹ΠΉ ΠΎΠΏΡ‹Ρ‚ Π² связи с ΠΏΠ°Π½Π΄Π΅ΠΌΠΈΠ΅ΠΉ COVID-19 для ΠΎΡ†Π΅Π½ΠΊΠΈ ΠΎΠΏΡ‹Ρ‚Π°, связанного с Π½ΠΎΠ²ΠΎΠΉ коронавирусной ΠΈΠ½Ρ„Π΅ΠΊΡ†ΠΈΠ΅ΠΉ. Π Π΅Π·ΡƒΠ»ΡŒΡ‚Π°Ρ‚Ρ‹. Π’Ρ‹Ρ€Π°ΠΆΠ΅Π½Π½ΠΎΡΡ‚ΡŒ ΡΠΌΠΎΡ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… расстройств, ΠΎΡ†Π΅Π½Π΅Π½Π½Ρ‹Ρ… ΠΏΠΎ шкалС HADS, Π½Π΅ Ρ€Π°Π·Π»ΠΈΡ‡Π°Π»ΠΈΡΡŒ ΠΌΠ΅ΠΆΠ΄Ρƒ Π³Ρ€ΡƒΠΏΠΏΠ°ΠΌΠΈ (F = 0,751; p = 0,522 ΠΈ F = 0,310; p = 0,818 для подшкал Ρ‚Ρ€Π΅Π²ΠΎΠ³ΠΈ ΠΈ дСпрСссии HADS соотвСтствСнно). ΠŸΠΎΠΏΡ€Π°Π²ΠΊΠ° Π½Π° ΠΊΠΎΠ²Π°Ρ€ΠΈΠ°Π½Ρ‚Ρ‹ (Π±Π°Π»Π»Ρ‹ ΠΏΠΎ шкалам Π₯ачинского, ΠΈ/ΠΈΠ»ΠΈ MoCA, ΠΈ/ΠΈΠ»ΠΈ MMSE) Π½Π΅ влияла Π½Π° Π·Π½Π°Ρ‡ΠΈΠΌΠΎΡΡ‚ΡŒ Ρ€Π°Π·Π»ΠΈΡ‡ΠΈΠΉ ΠΌΠ΅ΠΆΠ΄Ρƒ Π³Ρ€ΡƒΠΏΠΏΠ°ΠΌΠΈ ΠΏΠΎ подшкалам HADS Π²Π½Π΅ зависимости ΠΎΡ‚ провСдСния ΠΏΠΎΠΏΡ€Π°Π²ΠΊΠΈ Π½Π° мноТСствСнныС сравнСния. Анализ модСлирования ΠΏΡƒΡ‚Π΅ΠΉ продСмонстрировал Π½ΠΈΠ·ΠΊΡƒΡŽ ΡΠΏΠΎΡΠΎΠ±Π½ΠΎΡΡ‚ΡŒ ΠΌΠΎΠ΄Π΅Π»Π΅ΠΉ Π² ΠΎΡ‚Π½ΠΎΡˆΠ΅Π½ΠΈΠΈ ΠΏΡ€ΠΎΠ³Π½ΠΎΠ·Π° ΡΠΌΠΎΡ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠ³ΠΎ состояния Π½Π° основании Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠ² риска (возраст, ΠΏΠΎΠ», Π±Π°Π»Π» ΠΏΠΎ шкалС Π₯ачинского) ΠΈ ΠΊΠΎΠ³Π½ΠΈΡ‚ΠΈΠ²Π½Ρ‹Ρ… симптомов (Π±Π°Π»Π»Ρ‹ MoCA ΠΈ MMSE) всС коэффициСнты r 0,7. ИзмСнСниС ΠΈΠ½Ρ‚Π΅Π»Π»Π΅ΠΊΡ‚ΡƒΠ°Π»ΡŒΠ½ΠΎΠΉ активности (Π² сторону Π΅Π΅ сниТСния) ΠΈ ΡΡƒΠ±ΡŠΠ΅ΠΊΡ‚ΠΈΠ²Π½ΠΎΠ΅ Π²ΠΏΠ΅Ρ‡Π°Ρ‚Π»Π΅Π½ΠΈΠ΅ ΠΎ трудности получСния мСдицинской ΠΏΠΎΠΌΠΎΡ‰ΠΈ Π°ΡΡΠΎΡ†ΠΈΠΈΡ€ΠΎΠ²Π°Π»ΠΈΡΡŒ с Π±ΠΎΠ»Π΅Π΅ высоким Π±Π°Π»Π»ΠΎΠΌ ΠΏΠΎ шкалС Ρ‚Ρ€Π΅Π²ΠΎΠ³ΠΈ HADS. Π£Ρ…ΡƒΠ΄ΡˆΠ΅Π½ΠΈΠ΅ физичСского Π·Π΄ΠΎΡ€ΠΎΠ²ΡŒΡ ΠΈ ΡƒΠΌΠ΅Π½ΡŒΡˆΠ΅Π½ΠΈΠ΅ Π»ΠΈΡ‡Π½ΠΎΠ³ΠΎ общСния Π±Ρ‹Π»ΠΈ связаны с Π±ΠΎΠ»Π΅Π΅ высокими Π±Π°Π»Π»Π°ΠΌΠΈ ΠΏΠΎ шкалС дСпрСссии HADS. ΠšΠ»ΠΈΠ½ΠΈΡ‡Π΅ΡΠΊΠΈ Π²Ρ‹Ρ€Π°ΠΆΠ΅Π½Π½Ρ‹Π΅ измСнСния ΡΠΌΠΎΡ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½ΠΎΠ³ΠΎ состояния ΠΎΡ‚ΠΌΠ΅Ρ‡Π°Π»ΠΈΡΡŒ Ρ‚ΠΎΠ»ΡŒΠΊΠΎ Π² ΠΎΡ‚Π½ΠΎΡˆΠ΅Π½ΠΈΠΈ Ρ‚Ρ€Π΅Π²ΠΎΠ³ΠΈ, которая зависСла ΠΎΡ‚ Ρ„Π°ΠΊΡ‚ΠΎΡ€Π° измСнСния ΠΈΠ½Ρ‚Π΅Π»Π»Π΅ΠΊΡ‚ΡƒΠ°Π»ΡŒΠ½ΠΎΠΉ активности. Π—Π°ΠΊΠ»ΡŽΡ‡Π΅Π½ΠΈΠ΅. Π£ ΠΏΠ°Ρ†ΠΈΠ΅Π½Ρ‚ΠΎΠ² с МКБ осСнью 2020 Π³. Π½Π΅ выявлСно Ρ€Π°Π·Π»ΠΈΡ‡ΠΈΠΉ ΠΏΠΎ выраТСнности Ρ‚Ρ€Π΅Π²ΠΎΠ³ΠΈ ΠΈ дСпрСссии ΠΏΠΎ ΡΡ€Π°Π²Π½Π΅Π½ΠΈΡŽ с вСсной 2020 Π³. осСнью 20182019 Π³Π³. Π²Π½Π΅ зависимости ΠΎΡ‚ контроля Π΄ΠΎΠΏΠΎΠ»Π½ΠΈΡ‚Π΅Π»ΡŒΠ½Ρ‹Ρ… Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠ² (Π±Π°Π»Π»Ρ‹ ΠΏΠΎ шкалам Π₯ачинского, MoCA, MMSE). НС ΠΎΠ±Π½Π°Ρ€ΡƒΠΆΠ΅Π½ΠΎ Ρ€Π°Π·Π»ΠΈΡ‡ΠΈΠΉ Π²ΠΎ Π²ΠΊΠ»Π°Π΄Π΅ Ρ„Π°ΠΊΡ‚ΠΎΡ€ΠΎΠ² риска (возраст, ΠΏΠΎΠ», сосудистыС ΠΈ атрофичСскиС Ρ„Π°ΠΊΡ‚ΠΎΡ€Ρ‹ ΠΊΠΎΠ³Π½ΠΈΡ‚ΠΈΠ²Π½ΠΎΠ³ΠΎ сниТСния) ΠΈ ΠΊΠΎΠ³Π½ΠΈΡ‚ΠΈΠ²Π½ΠΎΠΉ дисфункции Π² Ρ„ΠΎΡ€ΠΌΠΈΡ€ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΠΌΠΎΡ†ΠΈΠΎΠ½Π°Π»ΡŒΠ½Ρ‹Ρ… расстройств Π² сравнСнии с ΠΏΡ€Π΅Π΄Ρ‹Π΄ΡƒΡ‰ΠΈΠΌΠΈ Π³ΠΎΠ΄Π°ΠΌΠΈ

    Historical preconditions for the formation of modern psychiatric hospital replacement care in the format of the cluster-modular system of the modern megapolis

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    The article analyzes first results of the functioning of the psychiatric service as a result of the introduction of a cluster-modular system into its organizational structure on the example of the State Budget Healthcare Institution β€œPsychiatric Clinical Hospital No. 13 of the Moscow City Health Department”. This study was conducted using the methods of study and generalization of experience, sociological, comparative and statistical analysis. The main performance indicators of the units of the cluster-modular system of the State Budgetary Institution β€œPKB No. 13 DZM” for 2015-2019 are studied. Β© 2021, Rossiiskaya Akademiya Nauk, Institut Istorii (Russian Academy of Sciences, Institute of General Hist. All rights reserved

    "Инь-ян" Π³Π΅Π½Ρ‹ Π² ΠΎΠ½ΠΊΠΎΠΏΠ°Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ, ΡˆΠΈΠ·ΠΎΡ„Ρ€Π΅Π½ΠΈΠΈ ΠΈ аутистичСских расстройствах

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    This literature review focuses on the genes associated with the development of diseases with inverse comorbidity, including schizophrenia, autism spectrum disorders, and most common cancers. In recent decades, there have been a number of studies reporting that individuals with mental disorders are less likely to have cancer than people in the general population. However, patients with combination of these diseases die faster than cancer patients without mental disorders. Molecular mechanisms underlying this effect are still poorly understood. Schizophrenia, autism spectrum disorders, and cancer are multifactorial and multi-symptomatic pathologies. Multiple studies have described hundreds of candidate genes potentially associated with these diseases. The present review summarizes the information on 10 yin-yang genes that can be associated with both mental disorders and cancer. However, the mechanism of yin-yang gene functioning and their biological role are often different in diseases with inverse comorbidity.ЦСлью ΠΎΠ±Π·ΠΎΡ€Π° стал Π°Π½Π°Π»ΠΈΠ· Π½Π°ΡƒΡ‡Π½Ρ‹Ρ… исслСдований, ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ Ρ…Π°Ρ€Π°ΠΊΡ‚Π΅Ρ€ΠΈΠ·ΡƒΡŽΡ‚ Π³Π΅Π½Ρ‹, ассоциированныС с Ρ€Π°Π·Π²ΠΈΡ‚ΠΈΠ΅ΠΌ Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ с ΠΎΠ±Ρ€Π°Ρ‚Π½ΠΎΠΉ ΠΊΠΎΠΌΠΎΡ€Π±ΠΈΠ΄Π½ΠΎΡΡ‚ΡŒΡŽ, Π²ΠΊΠ»ΡŽΡ‡Π°Ρ ΡˆΠΈΠ·ΠΎΡ„Ρ€Π΅Π½ΠΈΡŽ, расстройства аутистичСского спСктра ΠΈ Π½Π°ΠΈΠ±ΠΎΠ»Π΅Π΅ распространСнныС ΠΎΠ½ΠΊΠΎΠΏΠ°Ρ‚ΠΎΠ»ΠΎΠ³ΠΈΠΈ. Π’ послСдниС дСсятилСтия ΠΎΠΏΡƒΠ±Π»ΠΈΠΊΠΎΠ²Π°Π½Ρ‹ дСсятки ΠΌΠ΅Π΄ΠΈΠΊΠΎ-биологичСских исслСдований, ΠΎΠΏΠΈΡΡ‹Π²Π°ΡŽΡ‰ΠΈΡ… наблюдСния, Ρ‡Ρ‚ΠΎ ΡΡƒΠ±ΡŠΠ΅ΠΊΡ‚Ρ‹ с психичСскими Π½Π΅Π΄ΡƒΠ³Π°ΠΌΠΈ Ρ€Π΅ΠΆΠ΅ ΡΡ‚Ρ€Π°Π΄Π°ΡŽΡ‚ онкологичСскими заболСваниями ΠΏΠΎ ΡΡ€Π°Π²Π½Π΅Π½ΠΈΡŽ с ΠΎΠ±Ρ‰Π΅ΠΉ популяциСй. Однако Π² случаях сочСтанного развития этих полярных Π±ΠΎΠ»Π΅Π·Π½Π΅ΠΉ Π»Π΅Ρ‚Π°Π»ΡŒΠ½Ρ‹ΠΉ исход наступаСт быстрСС ΠΏΠΎ ΡΡ€Π°Π²Π½Π΅Π½ΠΈΡŽ с психичСски Π·Π΄ΠΎΡ€ΠΎΠ²Ρ‹ΠΌΠΈ онкологичСскими Π±ΠΎΠ»ΡŒΠ½Ρ‹ΠΌΠΈ. ΠœΠΎΠ»Π΅ΠΊΡƒΠ»ΡΡ€Π½Ρ‹ΠΉ ΠΌΠ΅Ρ…Π°Π½ΠΈΠ·ΠΌ этого явлСния Π½Π° сСгодня Π½Π΅ ΠΈΠ·ΡƒΡ‡Π΅Π½. ШизофрСния ΠΈ расстройства аутистичСского спСктра, онкологичСскиС заболСвания ΡΠ²Π»ΡΡŽΡ‚ΡΡ ΠΌΠ½ΠΎΠ³ΠΎΡ„Π°ΠΊΡ‚ΠΎΡ€Π½Ρ‹ΠΌΠΈ ΠΈ ΠΌΡƒΠ»ΡŒΡ‚ΠΈΡΠΈΠΌΠΏΡ‚ΠΎΠΌΠ°Ρ‚ΠΈΡ‡Π΅ΡΠΊΠΈΠΌΠΈ патологиями. Π’ Π½Π°ΡƒΡ‡Π½Ρ‹Ρ… исслСдованиях Π°Π½Π½ΠΎΡ‚ΠΈΡ€ΠΎΠ²Π°Π½Ρ‹ сотни ΠΊΠ°Π½Π΄ΠΈΠ΄Π°Ρ‚Π½Ρ‹Ρ… Π³Π΅Π½ΠΎΠ², ассоциированных с этими патологиями. Π’ настоящСм ΠΎΠ±Π·ΠΎΡ€Π΅ ΠΎΠ±ΠΎΠ±Ρ‰Π΅Π½Π° Π³Ρ€ΡƒΠΏΠΏΠ° ΠΎΠ±Ρ‰ΠΈΡ… 12 «инь-ян» Π³Π΅Π½ΠΎΠ², ΠΊΠΎΡ‚ΠΎΡ€Ρ‹Π΅ ΠΌΠΎΠ³ΡƒΡ‚ Π±Ρ‹Ρ‚ΡŒ ассоциированы с Ρ€Π°Π·Π²ΠΈΡ‚ΠΈΠ΅ΠΌ ΠΊΠ°ΠΊ психичСских, Ρ‚Π°ΠΊ ΠΈ онкологичСских Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ. Однако ΠΌΠ΅Ρ…Π°Π½ΠΈΠ·ΠΌ функционирования «инь-ян»-Π³Π΅Π½ΠΎΠ² ΠΈ ΠΈΡ… биологичСская Ρ€ΠΎΠ»ΡŒ Π·Π°Ρ‡Π°ΡΡ‚ΡƒΡŽ ΠΎΡ‚Π»ΠΈΡ‡Π½Ρ‹ для Π·Π°Π±ΠΎΠ»Π΅Π²Π°Π½ΠΈΠΉ с ΠΎΠ±Ρ€Π°Ρ‚Π½ΠΎΠΉ ΠΊΠΎΠΌΠΎΡ€Π±ΠΈΠ΄Π½ΠΎΡΡ‚ΡŒΡŽ

    Bacterial metabolites of human gut microbiota correlating with depression

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    Depression is a global threat to mental health that affects around 264 million people worldwide. Despite the considerable evolution in our understanding of the pathophysiology of depression, no reliable biomarkers that have contributed to objective diagnoses and clinical therapy currently exist. The discovery of the microbiota-gut-brain axis induced scientists to study the role of gut microbiota (GM) in the pathogenesis of depression. Over the last decade, many of studies were conducted in this field. The productions of metabolites and compounds with neuroactive and immunomodulatory properties among mechanisms such as the mediating effects of the GM on the brain, have been identified. This comprehensive review was focused on low molecular weight compounds implicated in depression as potential products of the GM. The other possible mechanisms of GM involvement in depression were presented, as well as changes in the composition of the microbiota of patients with depression. In conclusion, the therapeutic potential of functional foods and psychobiotics in relieving depression were considered. The described biomarkers associated with GM could potentially enhance the diagnostic criteria for depressive disorders in clinical practice and represent a potential future diagnostic tool based on metagenomic technologies for assessing the development of depressive disorders. Β© 2020 by the authors. Licensee MDPI, Basel, Switzerland
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