Water-Wave Vortices and Skyrmions.

Topological wave structures-phase vortices, skyrmions, merons, etc.-are attracting enormous attention in a variety of quantum and classical wave fields. Surprisingly, these structures have never been properly explored in the most obvious example of classical waves: water-surface (gravity-capillary) waves. Here, we fill this gap and describe (i) water-wave vortices of different orders carrying quantized angular momentum with orbital and spin contributions, (ii) skyrmion lattices formed by the instantaneous displacements of the water-surface particles in wave interference, and (iii) meron (half-skyrmion) lattices formed by the spin-density vectors, as well as (iv) spatiotemporal water-wave vortices and skyrmions. We show that all these topological entities can be readily generated in linear water-wave interference experiments. Our findings can find applications in microfluidics and show that water waves can be employed as an attainable playground for emulating universal topological wave phenomena.

Optimizing Therapeutic Hypothermia Depths in Acute Type A Aortic Dissection Repair.

INTRODUCTION: Existing evidence regarding the impact of hypothermic circulatory arrest (HCA) depth in acute type A aortic dissection (ATAAD) repair lacks robustness concerning blood loss and mortality. We aimed to assess whether using mild and moderate HCA (MMHCA) versus deep and profound HCA (DPHCA) in ATAAD repair is associated with reduced bleeding risk, lower in-hospital mortality, and improved long-term survival. METHODS: This retrospective cohort study spanned from 2003 to 2023. ATAAD repair patients were identified from hospital records, with exclusion criteria applied to those who died before surgery, those with symptoms lasting longer than 14 d, and those who operated on without HCA. Patients in the DPHCA group underwent surgery with HCA (T ≤ 20°C), while those in the MMHCA group had temperatures ranging from 34°C to 20.1°C. RESULTS: Out of 549 eligible ATAAD patients, the MMHCA group exhibited a reduced rate of chest re-exploration for bleeding (39% versus 14%, P < 0.005), decreased blood loss after surgery (1637 mL versus 1045 mL, P < 0.005), and lower volumes for red blood cell transfusions (1375 mL versus 903 mL, P < 0.005) compared with the DPHCA group. Additionally, the MMHCA group had lower crude and age- and sex-adjusted in-hospital mortality rates, with a mortality rate ratio of 0.65 (P = 0.003). Cox regression analysis revealed a 25% reduction in long-term mortality for the MMHCA group compared with the DPHCA group (hazard ratio = 0.75; P = 0.045). CONCLUSIONS: ATAAD repair using MMHCA and antegrade cerebral perfusion is associated with lower blood loss and improved immediate and long-term survival.

Mind Language Disturbances and PET-Signs of Depression vs Alzheimer's Disease: Are There Any Common Patterns Identified?

BACKGROUND: There is a broad appreciation that a diagnosis of depression (D) in the elderly is a strong risk factor for incident dementia, particularly Alzheimer's disease (AD). Indeed, the two disorders might constitute a dyad, although their causal relationship is uncertain, given the likely bidirectional and compounding effects of social withdrawal and loss of previous activities, and the manifestation of language disturbances, cognitive dysfunction, and social disruption that are typical of both conditions. We argue that language declines in D and AD share common patterns and biological underpinnings, and that D/AD patients might benefit from intensive language remediation training aiming to improve the functioning of neural networks that are linked to similar cognitive impairments. METHODS: A literature search in PubMed database included topics of language disturbances, cognitive impairments, and molecular brain imaging by positron emission tomography (PET) to identify common patterns in D and AD regarding language decline and its neurobiological underpinnings. RESULTS: Language disturbances show a particular commonality in the two disorders, manifesting in simplified language and particular speech markers (e.g., lexical and semantic repetitions, arguably due to ruminations in D and memory deficits in AD). PET can reveal abnormal protein deposits that are practically diagnostic of AD, but cerebrometabolic deficits to PET with the glucose tracer FDG show a certain commonality in D and AD. Typical findings of hypometabolism in the frontal lobes doubtless underlie the executive function deficits, where frontal hypometabolism in prodromal D increases with AD progression. This may reflect overlapping changes in noradrenaline and other neurotransmitter (e.g. serotonin) changes. Cerebrometabolic deficits associated with language dysfunction may inform targeted language remediation treatments in the D/AD progression. CONCLUSIONS: Language remediation techniques targeting specific language disturbances might present an important complimentary treatment strategy along with an adjusted pharmacotherapy approach and standard psychosocial rehabilitation interventions. We see a need for investigations of language remediation informed by the overlapping pathologies and language disturbances in D and AD.

Interpersonal Psychotherapy in Russia: Remembering Past Losses of the Heart, Keeping Mindful of the Culture of Melancholy, and Reconnecting with a Supportive Social Environment.

BACKGROUND: The dissolution of the Soviet Union brought economic instability and variety of social changes, resulting in fluctuating suicide rates and highlighting the national phenomenon of a melancholy cultural trait across the general population. The socio-political changes in Russia post-1991 led to increased rates of depressive and stress-related disorders, as well as opening avenues for integrating foreign psychotherapeutic methods, including Interpersonal Psychotherapy (Klerman-Weissman IPT), into the treatment of mental disorders. This narrative review explores the adaptation and efficacy of IPT in Russia, particularly for depressive and stress-related disorders. MATERIAL AND METHODS: We assembled key PhD theses related to the topic of IPT use in Russia. One such study involved 120 female patients aged 23-45 years with adjustment disorders, treated at the Omsk Rehabilitation Treatment Hospital. Participants were divided into an IPT group (n=80) and a control group (n=40) receiving treatment as usual (TAU). The IPT group underwent 12-16 individual sessions, each lasting 60 minutes, held twice a week. The main study group was further divided into four sub-groups based on specific interpersonal problems: loss of loved ones, interpersonal conflicts, social role changes, and social isolation. RESULTS: Both groups showed improvement in anxiety, dyssomnia, and motor retardation, with the IPT group demonstrating more sustained improvement. At the 8-week endpoint, full recovery from depression was observed in 50% of the IPT group, compared to only 20% in the TAU group. The IPT group also showed significant improvements in coping strategies, with a notable decrease in avoidance behaviors and an increase in problem-solving strategies, also targeting melancholy national phenomenon via training acceptance skills and practicing an active life position to aware the self-responisbility and achieve a of well-being state of emotional balance. The group IPT method was also experimentally combined with the person-oriented (reconstructive) psychotherapy, which has a long and successful history of within the group format, and has enabled shortening of the standard course of person-oriented reconstructive treatment. CONCLUSIONS: IPT method has proven efficacy in treating depressive and stress-related disorders in Russia, by addressing deeper pathogenetic levels of mental and behavioral formations. The Russian Society of Psychiatrists and Russian Psychotherapy Association have recommended its broader implementation in Russian mental health institutions, and has included IPT in the Russian National Guidelines for Psychiatry.

Self-Harm Behavior and Suicidality Among Adolescents in Samara Region.

INTRODUCTION: Self-harm behavior is a significant global concern, with Russia among the countries with high prevalence rates. Adolescents and young adults (15-29 years old) are particularly vulnerable, with suicide being the fourth leading cause of death in this age group. Our objective was to present statistics on suicidality and non-suicidal self-harm behavior (NSSH) among adolescents in the Samara region and to identify psychosocial differences between patients hospitalized for the first time and those hospitalized repeatedly. SUBJECTS AND METHODS: This study is a retrospective chart analysis of adolescents hospitalized due to suicidal ideation or attempts in 2023. Data were collected from hospital records, comprising a diverse sample of adolescents. RESULTS: The sample included 76 adolescents, with a significant gender imbalance, as 84.2% were female. Chronic family conflicts presumably were the most influential factor, rather than family composition. Data on hereditary predisposition were subjective and presumably did not correlate with the number of hospitalizations. Fetal hypoxia was the only notable perinatal pathology. Self-harm behavior was more common in readmissions, while suicidal thoughts were present in similar proportions in both initial and repeat hospitalizations. The main reasons for self-harm behavior were the desire to gain control over life or to relieve emotional pain. Only 2.6% of cases were directly aimed at suicide. CONCLUSIONS: Identified risk factors for suicidal behavior among adolescents included female gender, an unfavorable family environment, and NSSH, which, although not directly suicidal, increased the risk of future suicidal behavior. These factors should be considered in the diagnosis and prevention of suicidal behavior.

The Population Typology of Conspiracy Beliefs About Sars-Cov-2 Origin in Russia Based on Predictive Modelling of COMET-G Study Data: Incoherent Attitude Indicator as a Predisposing Factor for Developing Mental Disturbances.

BACKGROUND: We examined the prevalence and spread of conspiracy beliefs about the origins of the COVID-19 pandemic among representatives of the Russian population. Our study aimed to identify belief clusters and develop predictive models to understand the factors that influence conspiracy beliefs, particularly in the context of how they might evolve in response to socio-political events and cause mental disturbances, thus in relation to specific pathways of the infodemic and psychodemic waves that spread among vulnerable population groups. METHODS: Data respondents to the international COMET-G study living in Russia during pandemic period (n=7,777) were analyzed using descriptive statistics, K-means clustering, and various machine learning models, including gradient boosting. We identified distinct populations depending on predominant beliefs about COVID-19 pandemic origins, and applied game theory (Shapely additive explanations) to determine the most influential variables in predicting cluster membership. RESULTS: Four distinct belief clusters emerged, which we designate as Naturalists, Conspiracists, COVID-Sceptics, and the Incoherent Attitude groups. The Incoherent Attitude cluster constituted 20.8% of the sample, and was particularly associated with mental health signs such as sleep disturbances and the use of psychotropic medications. Internet use and mental health-related factors, as well as the respondents' education level, were key predictors of mental disturbances with mediating effects of the conspiracy views across all clusters. Conspiracy beliefs about COVID-19 origin were highly fluid/variable, often being shaped by external sociopolitical factors rather than objective health data. CONCLUSIONS: The cluster with Incoherent Attitude regarding COVID-pandemic origins, which had an association with psychoticism, showed a greater predisposition for mental health problems, than did the Conspiracist, Naturalist and Sceptic clusters. We suppose that underlying psychoticism bears a relation to their sleep problems and resorting to use of psychotropic medications. These results emphasizes the global health need for implementing target-focused and selective strategies that address public misinformation and promote the adoption of critical thinking skills to mitigate the impact of conspiracy theories, considering the factors of education level and pre-existing mental disorders.

Virtual Reality / Augmented Reality (VR/AR) Approach to Develop Social and Communication Skills in Children and Adolescents with Autism Spectrum Disorders Without Intellectual Impairment.

BACKGROUND: Autism spectrum disorder (ASD) is a complex neurodevelopmental disorder that affects a significant proportion of the world's population, particularly children and adolescents. The sensory processing issues can be an evidence-based target for therapeutic/corrective interventions by controlling the intensity and targeted replacement of maladaptive sensory stimuli with neutral stimuli using virtual reality or augmented reality. SUBJECTS AND METHODS: We searched for articles on Pubmed. The search query included ((VR or virtual reality) or (AR or augmented reality)) and (children or adolescents) and (ASD or autism spectrum disorder or autism). RESULTS: Our criteria were met by 25 articles. 19 articles used VR, 5 articles used AR and 1 article used MR. Most interventions offer children and adolescents with ASD individualized tasks. Immersive VR games developed collaborative skills. Other systems encourage and teach directed facial gaze. Evaluation of the effectiveness of learning in VR/AR environment is carried out by means of different scales, qualitative analysis of surveys, questionnaires and interviews, studying the number and duration of eye contacts between the participant and the avatar. It should be noted that almost all studies were conducted on small samples, so their results allow us to draw only preliminary conclusions about the effectiveness of VR /AR. CONCLUSIONS: The following key areas of VR/AR technologies for children and adolescents with high-functioning ASD can be identified: communicating with an avatar, including answering its questions, tracking the child's gaze and encouraging the child to look at the face, placing it in social situations close to real life, practicing common everyday situations, learning to recognize emotions. A VR/AR-based therapy approach may help children with autism spectrum disorder without cognitive impairment to develop higher levels of adaptation in terms of social and communication skills. However, more research is needed to evaluate the effectiveness of different methods.

Depression and Anxiety Among COVID-19 Patients Admitted to a "Red Zone" Intensive Care Unit: Do the Factors of Self-Awareness of Somatic Health, Anxiety, and Depression Contribute to the Course of Sars-Cov-2 Infection?

BACKGROUND: The prevalence of depressive disorders in the general population increased significantly during the COVID-19 pandemic. The aim of this study is to examine the relationship between history of anxiety and depressive disorders and COVID-19 outcome, hospitalization and severity of anxiety and depression, and whether such relationships are explicable by direct impact of the disease. SUBJECTS AND METHODS: We conducted a questionnaire survey among 98 inpatients in the Department of Infectious Diseases of the Clinics of Samara State Medical University. The self-report questionnaire consisted of 120 items, including socio-demographic characteristics of participants, State-Trait Anxiety Inventory, and the Center for Epidemiologic Studies Depression Scale, with items reflecting subjective feelings about the COVID-19 pandemic. We used one-factor analysis of variance to compare between groups for those indicators that conformed to a normal distribution, and the chi-square test (χ2) or Fisher's exact test to analyze group differences in the distribution of categorical variables was used. RESULTS: The mean (SD) total score on the STAI anxiety scale among hospitalized patients (51 (10.1)) significantly exceeded that of the COMET-G control group (44.9 (11.7) (H=22.8, p<0.001). There was a similar difference in the severity of depression as measured by the CES-D scale (23.4 (12.6) versus 18.0 (11.8), H=15.2 and p<0.001). In contrast to the general population, there were no statistically significant differences in anxiety and depression severity in the matched samples 52 subjects fulfilling the criteria of age, gender, and general perception of health condition. CONCLUSIONS: Anxiety and depression scores among ICU (red zone) inpatients significantly exceeded the scores observed in the COMET-G general population group. Our study did not confirm expected relationship between symptoms of anxiety and depression (based on questionnaire response) and the risk of severe course of COVID-19 (e.g. hospitalization) in matched samples, but proved that the factor of self-awareness of health state may be related to the COVID-19 course severity. Future research would benefit from clinical interview of inpatients and follow-up monitoring of affective disorders to specify whether anxiety and particular type of depression (e.g., anxious) are selectively related to the severity of COVID-19 course and risks of affective disorders persistence after somatic recovery. The accumulation of mental disorders with age, and the bidirectional association of mood disorders and infectious diseases should be considered when assessing the risk factors.

Systematic Review and Meta-Analysis Confirm the Moderate Efficacy of High-Frequency r-TMS in Alzheimer's Disease: Mediating Effects of Anhedonia-Apathy and Add-On Motor-Cognitive Excersizes.

OBJECTIVES: Alzheimer's disease (AD) presents a major global health issue of significant socio-economic impact. Pharmacological treatments for AD have limited efficacy, prompting the exploration of alternative therapies, such as repetitive transcranial magnetic stimulation (rTMS), a promising non-invasive technique to enhance cognitive function in AD patients. Our systematic review and meta-analysis aim to evaluate the efficacy of rTMS in relation to cognitive function in AD patients, identify optimal rTMS stimulation parameters, and understand the underlying neural mechanisms. METHODS: We conducted a comprehensive literature search in PubMed using predefined search terms to identify original research articles investigating the effects of rTMS on cognitive function in AD patients. We selected only randomized controlled trials (RCTs) with sufficient quantitative data for comparing active rTMS to the sham-coil treatment, and then performed a random effects meta-analysis using standardized mean differences (SMDs) to synthesize the effects across studies. RESULTS: The systematic review included 22 studies, among which 14 RCTs met our criteria for meta-analysis. High-frequency rTMS, particularly targeting the dorsolateral prefrontal cortex (DLPFC), evoked significant cognitive improvements in AD patients, with a moderate positive effect size of rTMS on cognitive function (Hedges' g=0.580, 95% CI [0.268, 0.892], p<0.001), albeit with substantial heterogeneity (I²=59%). Funnel plot asymmetry and Egger's test suggested a potential publication bias, but fail-safe N analysis indicated a robust finding. Moreover, anhedonia-apathy symptoms and motor-cognitive exercises mediated the efficacy of tTMS in ameliorating cognitive functioning across several studies. CONCLUSION: rTMS demonstrates moderate efficacy in improving cognitive function in AD-patients, most distinctly with high-frequency rTMS stimulation protocols targeting the DLPFC area. The meta-analysis support rTMS as a viable therapeutic intervention for cognitive enhancement in AD. Future promising research should focus on personalized treatment strategies targeting mediating factors, baseline connectivity patterns, and TMS-induced neuroplasticity in AD.

Risk Assessment Suicidality Scale (RASS)-Based On-Line Calculator Targeting Early Prevention of Suicides in General Population: from COMET-G Study Results Towards Integration of the Screening Tool into Routine Clinical Practice.

BACKGROUND: Suicide is a major global health concern, particularly among young people. This study evaluates an online suicide risk calculator based on the Risk Assessment of Suicidality Scale (RASS), which is designed to enhance accessibility and early detection of suicide risk. METHODS: The study involved 444 participants who completed the RASS via an online calculator. Results were compared with data from the COMET-G study's Russian sample (n=7572). Descriptive statistics, correlation analysis, and two-way ANOVA were used to analyze the data. RESULTS: The mean age of participants was 22.71 years (SD=7.94). The mean total RASS standardized score was 837.7 (SD=297.8). There was a significant negative correlation between age and RASS scores (r=-0.463, p<0.0001). The online calculator sample showed significantly higher RASS scores compared to the COMET-G sample, with 71% of online users scoring above the 90th percentile of the COMET-G sample. CONCLUSION: Our study demonstrated the advantage of the on-line suicidality risk calculator based on the RASS scale as a sensitive tool in detecting suicidal behaviours and measuring the severity of suicidality risks, offering a capability for broad reach and immediate assessment during clinical conversation between doctor and patient. Moreover, the RASS on-line psychometric instrument, when being freely distributed among the general population over internet sources, enabled to attract vulnerable groups of respondents with significantly higher suicidality risks. Future research should focus on integrating such tools into comprehensive suicide prevention programs and developing appropriate follow-up monitoring strategies for high risk-cases.

Virtual Reality (VR) Device with Integrated Biofeedback Sensors (ReViSide) to Cope with Emotional Burnout State Among Employees Experiencing Stress at Workplace: Problem Overview and Action Plan.

INTRODUCTION: In this study we examine the issue of employee burnout, caused by long-term exposure to workplace stressors, considering its complex phenomenology in the context of contemporary psychological and psychiatric views. Towards the development of innovative technologies to correct burnout in the context of psychosocial rehabilitation, we present our study protocol involving the ReViSide virtual reality (VR) and biofeedback intervention, including monitoring of respiratory rates and EEG rhythms. METHODS: The randomized controlled trial protocol includes adult participants aged 18 to 65 years (n=140) who exhibit emotional burnout in the workplace. The intervention group will undergo a course of VR correction (ReViSide), while the control group receives a standard psychocorrection. The primary endpoint will be level of emotional burnout to the Maslach Burnout Inventory (MBI). We shall also assess anxiety, depression, asthenia and subjective improvement in condition using validated scales (HADS, HARS, HDRS, VAS-A, PGI-C). RESULTS: We shall test our hypothesis that the VR-correction group will show significant improvements in MBI scores, particularly in emotional exhaustion, depersonalization, and personal accomplishment, compared to the control group. Secondary outcome measures are likewise expected to demonstrate more prominent improvements in the VR group, correlating with the magnitude of burnout reduction to MBI. Analysis of EEG data may reveal changes in alpha rhythm patterns during VR sessions, potentially correlating with reduced distress levels. CONCLUSIONS: We designed this study to test the integration of an interdisciplinary approach for treating burnout, highlighting the ReViSide technology. Confirming the efficacy of this approach for psychosocial rehabilitation targeting burnout states among employees should improve their stress resilience, daily motivation, and work productivity in the context of the modern high working pressure environment and demanding corporate culture.

The Use of eHealth for Pharmacotherapy Management With Patients With Respiratory Disease, Cardiovascular Disease, or Diabetes: Scoping Review.

BACKGROUND: eHealth is increasingly considered an important tool for supporting pharmacotherapy management. OBJECTIVE: We aimed to assess the (1) use of eHealth in pharmacotherapy management with patients with asthma or chronic obstructive pulmonary disease (COPD), diabetes, or cardiovascular disease (CVD); (2) effectiveness of these interventions on pharmacotherapy management and clinical outcomes; and (3) key factors contributing to the success of eHealth interventions for pharmacotherapy management. METHODS: We conducted a scoping review following the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping review) statement. Databases searched included Embase, MEDLINE (PubMed), and Cochrane Library. Screening was conducted by 2 independent researchers. Eligible articles were randomized controlled trials and cohort studies assessing the effect of an eHealth intervention for pharmacotherapy management compared with usual care on pharmacotherapy management or clinical outcomes in patients with asthma or COPD, CVD, or diabetes. The interventions were categorized by the type of device, pharmacotherapy management, mode of delivery, features, and domains described in the conceptual model for eHealth by Shaw at al (Health in our Hands, Interacting for Health, Data Enabling Health). The effectiveness on pharmacotherapy management outcomes and patient- and clinician-reported clinical outcomes was analyzed per type of intervention categorized by number of domains and features to identify trends. RESULTS: Of 63 studies, 16 (25%), 31 (49%), 13 (21%), and 3 (5%) included patients with asthma or COPD, CVD, diabetes, or CVD and diabetes, respectively. Most (38/63, 60%) interventions targeted improving medication adherence, often combined for treatment plan optimization. Of the 16 asthma or COPD interventions, 6 aimed to improve inhaled medication use. The majority (48/63, 76%) of the studies provided an option for patient feedback. Most (20/63, 32%) eHealth interventions combined all 3 domains by Shaw et al, while 25% (16/63) combined Interacting for Health with Data Enabling Health. Two-thirds (42/63, 67%) of the studies showed a positive overall effect. Respectively, 48% (23/48), 57% (28/49), and 39% (12/31) reported a positive effect on pharmacotherapy management and clinician- and patient-reported clinical outcomes. Pharmacotherapy management and patient-reported clinical outcomes, but not clinician-reported clinical outcomes, were more often positive in interventions with ≥3 features. There was a trend toward more studies reporting a positive effect on all 3 outcomes with more domains by Shaw et al. Of the studies with interventions providing patient feedback, more showed a positive clinical outcome, compared with studies with interventions without feedback. This effect was not seen for pharmacotherapy management outcomes. CONCLUSIONS: There is a wide variety of eHealth interventions combining various domains and features to target pharmacotherapy management in asthma or COPD, CVD, and diabetes. Results suggest feedback is key for a positive effect on clinician-reported clinical outcomes. eHealth interventions become more impactful when combining domains.

Aging Brain, Dementia and Impaired Glymphatic Pathway: Causal Relationships.

Cellular and molecular processes that are of key importance in the development of neuroinflammation and increased cytokine response, activation of microglia and astrogliosis, contributing to the accumulation of metabolites and aberrant proteins in the brain tissue due to their overproduction and insufficient clearance, concomitant disturbance of architecture and sleep patterns are interconnected and induce brain aging with the formation its complex neurobiological mechanism. The study of these processes brings us closer to understanding the main determinants of healthy and unhealthy aging, primary prevention and preclinical diagnosis of age-related diseases, as well as to solving problems of longevity and increasing quality of life. The imbalance of homeostatic functions that support the exchange of fluids and solutes in the brain tissue is observed both in physiological aging and in the development of pathology of the nervous system with long-term consequences - from impaired synaptic signaling to the development of neurodegenerative diseases. Dementia is one of the major health problems worldwide and is very complex in terms of pathophysiology. Therefore, one of the priorities of fundamental neurobiology is to elucidate the main morbid mechanisms of Alzheimer's disease as the most common form of dementia. The hypotheses of ß-amyloid and tau protein largely explain the main pathological features of Alzheimer's disease, however, there remains a need for further research on biomarkers with high validity and predictive applicability in people without cognitive impairment and clinical symptoms and in the early stages of the disease. There is a need to intensify the search for effective solutions to slow or stop the progression of the disease, especially therapeutic approaches that modify the disease at the preclinical stage, when it is most beneficial to change its course. At the same time, the discovery of aquaporin-dependent clearance pathways in the brain made it possible to identify new mechanisms underlying the etiology and progression of neurodegeneration and neuroinflammation. Glial-mediated clearance plays a fundamental role in the process of physiological aging, the development of age-related changes in the brain, and neurodegenerative processes. We analyzed 273 articles posted in PubMed database selected by keywords "glymphatic system, Alzheimer's disease, dementia, amyloid Aß, aquaporin, aging, brain clearance". A total of 102 full-text articles were included in this review. This article presents up-to-date evidence on the causes and consequences in the study of the relationship between dysfunction of the glymphatic pathway and the accumulation of pathological proteins with insufficient excretion of toxic metabolites from the brain parenchyma, which is considered a key factor in the development of Alzheimer's dementia.

G.T. MSRS On-Line Calculator Targeting the Early Diagnosis of Mixed Affective States: the Multicenter Study Project Design on the Approbation and Validity of the Three Language Versions of the Rating Scale.

BACKGROUND: Mixed affective states (MS) are often misdiagnosed by the clinicians and lead to the inappropriate treatment strategies contributing to the severe forms, poor outcome with higher rates of comorbid conditions and worse remission quality in affective and bipolar disorders, as well as to a decreased psychosocial functioning of these patients. The development of reliable tools for the MS assessments or so called the phenomenon of mixity in affective disorders, is still an unmet need of psychiatric research and clinical practice. In this paper, we present PC program "Multilingual IBM-PC on-line calculator for early diagnosis of the mixed affective states" based on the Giuseppe Tavormina Mixed States Rating Scale (G.T. MSRS) (Russian, English, Italian language versions) created by the ICERN group using programming language JavaScript, working for such operation systems (OS) as Windows, Linux, MacOs, Android, iOS, and aims to contribute to the accurate assessment of the presence and severity of the mixed states among affective disorders. SUBJECTS AND METHODS: The G.T. Mixed States Rating Scale on-line calculator consists of 11 items which evaluate various aspects of MS in patients with major depression, bipolar or recurrent depressive disorder. A total score is automatically calculated, considering the type of affective temperament according to the Akiskal's and Tavormina's schemas, thus, the specific sub-groups of MS are differentiated based on the ranges: Medium-light (2-6), Medium (7-12), and High (13-19) Mixity level. The study will enroll 330 participants during two (three months follow-up) visits (110 native speakers in each of the three languages) of both genders aged from 18 till 55 y.o. with the diagnoses of depressive episodes, major depression, bipolar or recurrent depressive disorder according to the DSM-5 criteria. Assessments will be provided by the two investigators (second one will be blinded to the G.T. MSRS results obtained by the first researcher), based on the use of DSM-5 clinical interview, Young Mania Rating Scale, Montgomery-Åsberg Depression Rating Scale, Clinical Global Impression - Severity scale (CGI-S), Clinical Global Impression - Improvement scale (CGI-I), Patient Global Impression of Change (PGIC). RESULTS: The study will assess the agreement between the diagnostic category/clinical impression and the on-line G.T. MSRS calculator use results, its test-retest reliability, and diagnosis stability for further assessment of the on-line G.T. MSRS calculator validity and clinical utility. Secondary variables will evaluate internal reliability and such statistical analyses as Cronbach's alpha, Cohen's Kappa, biserial correction, and agreement between initial and follow-up diagnoses. CONCLUSIONS: Current multicenter validation study of the on-line G.T. MSRS calculator will enhance the understanding of the mixity phenomenon and its clinical implication, aiming to improve the treatment strategies to manage the course of mental disorder, quality of life and psychosocial functioning in patients with affective (bipolar) disorders, accompanied by MS, and a clinical recommendation for the routine administration of the user-friendly on-line G.T. MSRS version in clinical practice.

Beliefs in Conspiracy Theories and Mental Health in the Student Community of Latvia During the COVID-19 Outbreak.

BACKGROUND: The objective of this study was to investigate self-reported changes in mental health and their association with various sociodemographic factors and beliefs in conspiracy theories among university and college students in Latvia during the second state of emergency caused by COVID-19. SUBJECTS AND METHODS: This cross-sectional study was conducted as part of an international research project, where university and college students were anonymously asked to complete an online self-report questionnaire. Changes in anxiety and depression were assessed using self-rated questions. Statistical analysis involved Pearson's chi-square test and univariate binary logistic regression.ression. RESULTS: The study comprised 1047 students, with 828 females (79.08% aged 21.71±0.09). Worsening in self-reported anxiety was more prevalent among females (69.3%, p<0.001), unemployed respondents (70.0%, p=0.003), individuals who were were not working during the lockdown (70.3%, p<0.001), those experiencing deterioration in general health condition (93.0%, p<0.001), and those belonging to or having knowledge of someone in a vulnerable group (69.5%, p=0.004). Worsening self-reported depression was more prevalent in respondents who did not work during the lockdown (63.9%, p=0.014) and those with deteriorating general health conditions (93.0%, p<0.001). Increased odds ratios (OR) for experiencing changes in anxiety and depression were associated with beliefs in the following conspiracy theories: 'Recommended measures are an attempt to restrict human rights' (OR=1.49, p=0.019 and OR=2.40, p<0.001, respectively). Furthermore, increased OR for experiencing changes in depression were associated with beliefs in the following conspiracy theories: 'The COVID-19 vaccine was ready before the virus spread' (OR=3.11, p=0.007), 'COVID-19 has a lower mortality rate" (OR=1.85, p<0.001)', 'Recommended measures are an attempt to restrict human rights' (OR=2.40, p<0.001), and 'The COVID-19 outbreak is the creation of world leaders' (OR=2.17, p=0.003). CONCLUSIONS: Self-reported changes in depression and anxiety were associated with certain beliefs in specific conspiracy theories.

Comparing the Anti-Depressive Effect of Electroconvulsive Therapy (ECT) Versus Transcranial Magnetic Stimulation (TMS) in the Treatment of Patients with Depression.

BACKGROUND: Electroconvulsive therapy (ECT) is one of the most effective treatments for depressive disorders. However, ECT has a number of limitations, such as significant side effects in the neurocognitive domain and the requirement for general anesthesia. Transcranial magnetic stimulation (TMS) is an intervention that applies electric stimulation to the brain without causing convulsions, thus representing an attractive alternative to ECT. The aim of our study is to review systematic reports of the effectiveness of ECT and TMS in the treatment of depressive spectrum disorders. SUBJECTS AND METHODS: We performed search queries in PubMed and eLibrary databases, which retrieved 391 articles, of which 14 met our inclusion criteria for the analysis. The articles comprised three comparisons: TMS vs SHAM, ECT vs sham ECT (SECT), and ECT vs PHARM. The protocol parameters analyzed for TMS were coil type, targeted brain area, amplitude of resting motor threshold, duration of session, number of sessions in total and per week, number and pulses per session and inter-train pause. For ECT, we evaluated the type of ECT device, targeted brain area, type of stimuli, and for ECT vs PHARM we recorded types of anesthesia and antidepressant medication. RESULTS: Three of 6 studies showed a therapeutic effect of TMS compared to placebo; efficacy was greater for TMS frequency exceeding 10 Hz, and with stimulation of two areas of cerebral cortex rather than a single area. There was insufficient data to identify a relationship between the success of TMS and intertrain pause (IP). Three of four studies showed a therapeutic effect of ECT compared to placebo. Three studies of bilateral ECT showed a significant reduction in depression scores compared to the SECT groups. ECT protocols with brief pulses were generally of lesser efficacy. Four of 5 ECT vs PHARM studies showed superior efficacy of ECT compared to PHARM. Among several antidepressants, only the ketamine study showed greater efficacy compared to ECT. CONCLUSIONS: There of six TMS studies and 7 of 9 ECT studies showed efficacy in reducing depressive symptoms. A prospective study of crossover design might reveal the relative efficacies of ECT and TMS.

Neuronetwork Approach in the Early Diagnosis of Depression.

BACKGROUND: Depression is a common mental illness, with around 280 million people suffering from depression worldwide. At present, the main way to quantify the severity of depression is through psychometric scales, which entail subjectivity on the part of both patient and clinician. In the last few years, deep (machine) learning is emerging as a more objective approach for measuring depression severity. We now investigate how neural networks might serve for the early diagnosis of depression. SUBJECTS AND METHODS: We searched Medline (Pubmed) for articles published up to June 1, 2023. The search term included Depression AND Diagnostics AND Artificial Intelligence. We did not search for depression studies of machine learning other than neural networks, and selected only those papers attesting to diagnosis or screening for depression. RESULTS: Fifty-four papers met our criteria, among which 14 using facial expression recordings, 14 using EEG, 5 using fMRI, and 5 using audio speech recording analysis, whereas 6 used multimodality approach, two were the text analysis studies, and 8 used other methods. CONCLUSIONS: Research methodologies include both audio and video recordings of clinical interviews, task performance, including their subsequent conversion into text, and resting state studies (EEG, MRI, fMRI). Convolutional neural networks (CNN), including 3D-CNN and 2D-CNN, can obtain diagnostic data from the videos of the facial area. Deep learning in relation to EEG signals is the most commonly used CNN. fMRI approaches use graph convolutional networks and 3D-CNN with voxel connectivity, whereas the text analyses use CNNs, including LSTM (long/short-term memory). Audio recordings are analyzed by a hybrid CNN and support vector machine model. Neural networks are used to analyze biomaterials, gait, polysomnography, ECG, data from wrist wearable devices, and present illness history records. Multimodality studies analyze the fusion of audio features with visual and textual features using LSTM and CNN architectures, a temporal convolutional network, or a recurrent neural network. The accuracy of different hybrid and multimodality models is 78-99%, relative to the standard clinical diagnoses.

Peripheral Blood Mononuclear Cell-Related Biomarkers in Schizophrenia.

INTRODUCTION: Schizophrenia is a severe mental illness causing significant impairment in personal, family, social, educational, occupational, and other important areas of life. While there is no widely accepted endophenotype, peripheral blood cells may serve as an accessible model of intracellular changes in schizophrenia. METHODS: We reviewed the literature on the query "peripheral blood mononuclear cells AND schizophrenia" in Medline (Pubmed), selecting studies that searched for specific biomarkers of schizophrenia. We considered both diagnostic biomarkers and biomarkers of therapeutic response, specific schizophrenia disorders or differential diagnostic biomarkers. RESULTS: We retrieved 41 articles matching the search criteria, among which were studies that considered changes in the production of pro-inflammatory and anti-inflammatory markers, proteins, receptors, enzyme activity, and gene expression as potential biomarkers. CONCLUSION: Approaches analysing a biological axis or a group of related biomarkers may hold the greatest promise for identifying schizophrenia. In addition, pharmacological status, smoking status, inflammatory markers and glucose metabolites, the presence of comorbidities should be considered. Certain biomarkers, while not specific for the diagnosis of schizophrenia, may indicate the prognosis and effectiveness of treatment in the established diagnosis.

Post-COVID Neuropsychiatric Complications in Children and Adolescents: a Study Design for Early Diagnosis and Treatment Using Innovative Technologies.

BACKGROUND: The COVID-19 pandemic has had significant impacts on the child and adolescent population, with long-term consequences for physical health, socio-psychological well-being, and cognitive development, which require further investigation. We herein describe a study design protocol for recognizing neuropsychiatric complications associated with pediatric COVID-19, and for developing effective prevention and treatment strategies grounded on the evidence-based findings. METHODS: The study includes two cohorts, each with 163 participants, aged from 7 to 18 years old, and matched by gender. One cohort consisted of individuals with a history of COVID-19, while the other group presents those without such a history. We undertake comprehensive assessments, including neuropsychiatric evaluations, blood tests, and validated questionnaires completed by parents/guardians and by the children themselves. The data analysis is based on machine learning techniques to develop predictive models for COVID-19-associated neuropsychiatric complications in children and adolescents. RESULTS: The first model is focused on a binary classification to distinguish participants with and without a history of COVID-19. The second model clusters significant indicators of clinical dynamics during the follow-up observation period, including the persistence of COVID-19 related somatic and neuropsychiatric symptoms over time. The third model manages the predictors of discrete trajectories in the dynamics of post-COVID-19 states, tailored for personalized prediction modeling of affective, behavioral, cognitive, disturbances (academic/school performance), and somatic symptoms of the long COVID. CONCLUSIONS: The current protocol outlines a comprehensive study design aiming to bring a better understanding of COVID-19-associated neuropsychiatric complications in a population of children and adolescents, and to create a mobile phone-based applications for the diagnosis and treatment of affective, cognitive, and behavioral conditions. The study will inform about the improved management of preventive and personalized care strategies for pediatric COVID-19 patients. Study results support the development of engaging and age-appropriate mobile technologies addressing the needs of this vulnerable population group.

Boosting topological zero modes using elastomer waveguide arrays.

We employ the Su-Schrieffer-Heeger model in elastic polymer waveguide arrays to design and realize traveling topologically protected modes. The observed delocalization of the optical field for superluminal defect velocities agrees well with theoretical descriptions. We apply mechanical strain to modulate the lattices' coupling coefficient. This work demonstrates a novel, to the best of our knowledge, platform for rapid prototyping of topological photonic devices and establishes strain-tuning as a viable design parameter for topological waveguide arrays.