Digital Mental Health Interventions for Alleviating Depression and Anxiety During Psychotherapy Waiting Lists: Systematic Review.

BACKGROUND: Depression and anxiety have become increasingly prevalent across the globe. The rising need for treatment and the lack of clinicians has resulted in prolonged waiting times for patients to receive their first session. Responding to this gap, digital mental health interventions (DMHIs) have been found effective in treating depression and anxiety and are potentially promising pretreatments for patients who are awaiting face-to-face psychotherapy. Nevertheless, whether digital interventions effectively alleviate symptoms for patients on waiting lists for face-to-face psychotherapy remains unclear. OBJECTIVE: This review aimed to synthesize the effectiveness of DMHIs for relieving depression and anxiety symptoms of patients on waiting lists for face-to-face therapy. This review also investigated the features, perceived credibility, and usability of DMHIs during waiting times. METHODS: In this systematic review, we searched PubMed, PsycINFO, Cochrane, and Web of Science for research studies investigating the effectiveness of DMHIs in reducing either depression or anxiety symptoms among individuals waiting for face-to-face psychotherapy. The search was conducted in June 2024, and we have included the studies that met the inclusion criteria and were published before June 6, 2024. RESULTS: Of the 9267 unique records identified, 8 studies met the eligibility criteria and were included in the systematic review. Five studies were randomized controlled trials (RCTs), and 3 studies were not. Among the RCTs, we found that digital interventions reduced depression and anxiety symptoms, but the majority of interventions were not more effective compared to the control groups where participants simply waited or received a self-help book. For the non-RCTs, the interventions also reduced symptoms, but without control groups, the interpretation of the findings is limited. Finally, participants in the included studies perceived the digital interventions to be credible and useful, but high dropout rates raised concerns about treatment adherence. CONCLUSIONS: Due to the lack of effective interventions among the reviewed studies, especially among the RCTs, our results suggest that waiting list DMHIs are not more effective compared to simply waiting or using a self-help book. However, more high-quality RCTs with larger sample sizes are warranted in order to draw a more robust conclusion. Additionally, as this review revealed concerns regarding the high dropout rate in digital interventions, future studies could perhaps adopt more personalized and human-centered functions in interventions to increase user engagement, with the potential to increase treatment adherence and effectiveness.

Network Structure of Interpersonal Sensitivity in Patients With Mood Disorders: A Network Analysis.

OBJECTIVE: Interpersonal sensitivity, characterized by a heightened awareness of others' behavior and emotions, is linked to mood disorders. However, current literature lacks a comprehensive analysis of how some items of the Interpersonal Sensitivity Measure (IPSM) interrelate and contribute to the overall construct. This study constructed a network for interpersonal sensitivity symptomatology to identify core IPSM items in patients with mood disorders. METHODS: The IPSM, a 36-item self-report scale, was utilized to evaluate interpersonal sensitivity symptoms in 837 participants (major depressive disorder [MDD], n=265; bipolar I disorder [BD I], n=126; and bipolar II disorder [BD II], n=446). We performed exploratory graph analysis, employing regularized partial correlation models to estimate the network structure. Centrality analysis identified core IPSM symptoms for each mood disorder group. Network comparison tests assessed structural differences between the MDD and BD subgroups. RESULTS: Network analysis detected five communities. Item 10 ("I worry about being criticized for things that I have said or done") showed the highest value in strength. Multiple items on "Interpersonal Worry/Dependency" and "Low Self-Esteem" showed high strength centrality. Network structure invariance and global strength invariance test results indicated no significant differences between the MDD and BD subgroups. CONCLUSION: Our findings emphasize the importance of addressing "Interpersonal Worry/Dependency" and "Low Self-Esteem" in the IPSM network among mood disorder patients based on core items of the network. Additionally, targeted treatments and comprehensive strategies in this aspect could be crucial for managing mood disorders.

Factors Contributing to the Development of Neuropsychiatric Manifestations in Persons With Multiple Sclerosis: A Systematic Review.

Multiple sclerosis (MS) is the most common chronic demyelinating disease affecting the central nervous system (CNS) and is distinguished by neuroinflammation and neurodegeneration. It has four categories based on clinical course, with relapsing-remitting being the most common type. MS predominantly manifests with motor and sensory dysfunctions. However, neuropsychiatric manifestations such as depression, anxiety, schizophrenia, and bipolar disorder are not uncommon. Various factors may contribute to the development of these manifestations; therefore, this study aimed to unravel them. This systematic review implemented the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 guidelines. Five databases (PubMed, PubMed Central (PMC), ScienceDirect, Cochrane Library, and Google Scholar) were used to acquire articles published in the past five years. After screening and quality appraisal were completed, eight articles were deemed eligible for inclusion in this study. The study designs included cohort, cross-sectional, randomized-controlled trial (RCT), case report, case-control, and narrative review. The development of neuropsychiatric manifestations in persons with MS is influenced by various factors. These were categorized into morphological changes of the brain, immunological mechanisms, socioeconomic factors, and individual factors for discussion. Each factor was found to intermingle with the others, requiring further research to understand the features that each factor contributes. This is crucial for improving the quality of life (QOL) and prognosis for persons living with MS.

Red kratom and red corvette: A case of mania induced by kratom withdrawal.

Background: Kratom, derived from the Mitragyna speciose, a  plant native to Southeast Asia, is a substance that is gaining popularity in the United States as a self-medication tool for opiate withdrawal and pain management. Its active compounds, mitragynine, and 7-hydroxymitragynine, interact with various receptors in the body, resulting in a spectrum of clinical effects.Case: A 56-year-old male with a history of depression and cannabis use disorder arrived at the Emergency Department in a state of severe agitation with erratic behavior and aggression. Further evaluation revealed a recent abrupt discontinuation of Kratom use. A psychiatric consultation was requested and done by our consultation-liaison team, diagnosing Kratom withdrawal as the most likely cause of his acute mania. Neuropsychiatric symptoms arising from Kratom toxicity is a well-documented phenomenon; however, to our knowledge, this may be the first documented case of acute mania induced by Kratom withdrawal.

Prevalence of Depression in Patients and Survivors of Breast Cancer: A Systematic Review.

Depression is an illness prevalent worldwide and much more common in certain groups of people. Individuals suffering from breast cancer as well as the survivors of breast cancer are at an increased risk of developing depression. We conducted this systematic review using articles from different countries of the world to get an estimate of the prevalence of depression in this specified population. For this, we collected about 262 articles from Google Scholar, PubMed, and ScienceDirect, and after strict scrutiny, 13 articles were used to extract our data. From our collected data, we were able to get an estimate of depression prevalence rates among breast cancer patients and survivors globally and identify different factors that affected these rates. More cohort studies must be done so that more precise information about the causes, preventions, and therapies of depression specifically in breast cancer patients and survivors may be gathered.

Neurocognitive Characteristics of Patients Who Visited a Psychiatric Outpatient Clinic Requesting Treatment for Adult Attention-Deficit/Hyperactivity Disorder.

OBJECTIVE: This study investigated the neurocognitive characteristics of patients who visited an outpatient clinic requesting diagnosis and treatment for adult attention-deficit/hyperactivity disorder (ADHD). METHODS: The patients' electronic medical records were retrospectively reviewed. Neurocognitive test results were compared using Student's t-test according to their chief complaint, depressive symptoms, childhood history, and intelligence quotient (IQ). Neurocognitive characteristics affecting subjective symptoms of ADHD were analyzed by linear regression. RESULTS: The study included 106 patients. They did not have significant deficits in neurocognitive tests. Patients with depressive symptoms showed more impulsive responses (hit reaction time [p=0.037] and commission error [p=0.024]) and self-reported ADHD symptoms (p=0.001). Verbal (p=0.036) and visual memory (p=0.020) were significantly deficient in patients with a childhood ADHD diagnosis. Patients with a low IQ had significant deficits in various domains. Depressive symptoms and vigilance were significantly related to subjective symptoms of ADHD (adjusted R2=0.430, ß=0.457, p=0.002). CONCLUSION: Our results imply that the neurocognitive function of patients with subjective ADHD symptoms was not abnormal but was affected by depressive symptoms.

Empathy-related abnormalities among women with premenstrual dysphoric disorder: clinical and functional magnetic resonance imaging study.

BACKGROUND: Empathy refers to the cognitive and emotional reactions of an individual to the experiences of another. Women with premenstrual dysphoric disorder (PMDD) report severe social difficulties during the luteal phase of their menstrual cycle. AIMS: This clinical and functional magnetic resonance imaging study aimed to explore affective and cognitive empathy in women with PMDD, during the highly symptomatic luteal phase. METHOD: Overall, 32 women with PMDD and 20 healthy controls participated in the study. The neuroimaging data were collected using a highly empathy-engaging movie. First, we characterised the synchrony of neural responses within PMDD and healthy groups, using the inter-individual correlation approach. Next, using network cohesion analysis, we compared connectivity within and between brain networks associated with affective and cognitive empathy between groups, and assessed the association of these network patterns with empathic measures. RESULTS: A consistent, although complex, picture of empathy abnormalities was found. Patients with PMDD showed decreased neural synchrony in parietal and frontal key nodes of cognitive empathy processing (theory-of-mind network), but higher neural synchrony in the anterior insula and anterior cingulate cortex, a part of the salience network, implicated in affective empathy. Positive correlations between cognitive perspective-taking scores and neural synchrony were found within the theory-of-mind network. Interestingly, during highly emotional moments, the PMDD group showed increased functional connectivity within this network. CONCLUSIONS: Similar to major depression, individuals with PMDD show enhanced affective empathy and reduced cognitive empathy. These findings echo clinical observations reported when women with PMDD have a dysregulated emotional response to negative stimuli.

Are Depressive Symptoms in Obstructive Sleep Apnea Attributable to a Syndrome of Dysregulation of Rhythms and Hyperactivity (DYMERS)?

Background: Obstructive sleep apnea (OSA) is characterized by repeated airway obstructions during sleep, causing hypopnea, apnea, intermittent hypoxia, and sleep fragmentation. The severity of OSA is measured using the apnea-hypopnea index (AHI), with AHI ≥ 5 indicating OSA. This study aims to assess the frequency and type of depressive disorder characteristics of OSA patients and to evaluate the impact on quality of life, also considering the presence of hyperactivity. Methods: A case-control study using OSA patients referred to Cagliari's sleep disorder center. Controls were matched by age and sex from community databases. OSA diagnoses were made with AHI > 15. Depressive episodes were identified using BDI-SF, and H-QoL (Health related Quality of Life) was measured with the SF-12, focusing on item 10 for hyper-energy. Results: The clinical sample (n = 25) had a higher frequency of depressive episodes (36%) compared to controls (7% and 4%). Depressed OSA patients had worse H-QoL and higher hyper-energy scores, but the additional burden from depression was relatively low. Conclusions: The OSA sample has a higher frequency of depressive episodes compared to the general population. Depressive episodes in OSA patients are linked to higher scores on item 10 of the SF-12, indicating hyper-energy despite lower overall quality of life scores. While OSA significantly impacts quality of life, the additional burden from depression is less severe than in other chronic diseases. These findings suggest that depressive episodes in OSA may be related to rhythm dysregulation and hyperactivity (DYMERS).

Hyperactivity and Risk for Dysregulation of Mood, Energy, and Social Rhythms Syndrome (DYMERS): Standardization of a Simple One-Item Screener versus the Mood Disorder Questionnaire (MDQ).

Background: This study aims to verify the accuracy of item 10 on the energy level of the Short-Form Health Survey (SF-12) in an item screening according to Mood Disorder Questionnaire (MDQ) results, providing a measure of hyper-energy. Methods: Regression techniques were employed in a dataset comprising 4093 records of respondents to test both linear and nonlinear relationships between predictor and outcome variables (energy level and symptoms considered in the MDQ). We examined the relationship of energy level with cases identified using MDQ with a cut-off of 7. Results: Levels of energy, as rated on item 10 of the SF-12, were related to the MDQ score with sensitivity = 0.72 and specificity = 0.70. In linear regression, the associations were stronger with MDQ items on excessive energy or activity, showing a medium effect size and an explained variance of 10% or higher. A greater association was observed for items on excessive energy and activity, as expected, as well as for items concerning self-confidence, sociability, and talkativeness. Conclusions: This result may have implications for the research on risk factors and the pathogenesis of the dysregulation of mood, energy, and social rhythms syndrome (DYMERS), a syndrome that is hypothesized to occur in stressful conditions like those shown under the COVID-19 pandemic.

A scoping review about the portrayal of depression and anxiety in mainstream and social media.

Media portrayal of mental disorders has a significant impact on awareness and stigma. Given the high prevalence of depression and anxiety as mental disorders, it is crucial to understand how they are represented. This scoping review aimed to map the existing literature on the portrayal of depression and anxiety in mainstream and social media. A comprehensive search was conducted in PubMed and PsychInfo, resulting in the inclusion of 20 records that predominantly examined social media and newspapers. Findings indicate that social media discussions on depression were mostly supportive and non-stigmatising. Public figures and role models played a significant role in encouraging open communication. Research on newspapers and other media forms yielded mixed results yet leaning towards positive portrayals. Limited studies explored anxiety portrayal. While acknowledging potential limitations in generalisability, this review emphasises the importance of accurately depicting mental health in media, particularly on social media platforms, while highlighting the need for broader investigations into anxiety representation.

Antidepressants for treating depression among older adults with dementia: A systematic review and meta-analysis.

BACKGROUND: Depression and dementia represent significant health challenges in older adults. Despite guidelines recommending antidepressants, their efficacy in depressed patients with dementia remains undetermined. OBJECTIVE: This review, in following a living systematic review approach, primarily aims to determine the effect of any-type antidepressant on the level of depressive symptoms in older adults with dementia and secondly if there is an effect of any-type antidepressants on cognitive state, quality of life, and functionality in the old-age population with dementia. METHODS: Systematic review and meta-analysis of RCTs from Medline, Embase, and Cochrane Register. Participants were ≥65 years, with both depression and any type of dementia. Certainty-of-Evidence was assessed through the Cochrane Risk-of-Bias tool and GRADE. Analysis involved standardized mean difference, with 95 % confidence-intervals (CIs). FINDINGS: Of the 27,771 screened articles, 8 studies (617 participants), treated with SSRI, SSNRI, atypical, and tricyclic antidepressants were retained for quantitative synthesis. No evidence for an effect was found (SMD -0.10 [-0.26, 0.07]), nor when subgrouped based on depression severity or dementia level, nor for secondary outcomes. INTERPRETATION: This review did not find evidence of a clinical effect of antidepressants for treating depression in older adults with dementia. Methodological challenges might contribute to this finding.

A novel prediction model for the probability of aggressive behavior in patients with mood disorders: Based on a cohort study.

BACKGROUND: Accurately predicting the probability of aggressive behavior is crucial for guiding early intervention in patients with mood disorders. METHODS: Cox stepwise regression was conducted to identify potential influencing factors. Nomogram prediction models were constructed to predict the probabilities of aggressive behavior in patients with mood disorders, and their performance was assessed using consistency index (C-index) and calibration plots. RESULTS: Research findings on 321 patients with mood disorders indicated that being older (HR = 0.92, 95% CI: 0.86-0.98), single (HR = 0.11, 95% CI: 0.02-0.68), having children (one child, HR = 0.07, 95%CI: 0.01-0.87; more than one child, HR = 0.33, 95%CI: 0.04-2.48), living in dormitory (HR = 0.25, 95%CI: 0.08-0.77), non-student (employee, HR = 0.24, 95% CI: 0.07-0.88; non-employee, HR = 0.09, 95% CI: 0.02-0.35), and higher scores in subjective support (HR = 0.90, 95% CI: 0.82-0.99) were protective factors. On the contrary, minorities (HR = 5.26, 95% CI: 1.23-22.48), living alone (HR = 4.37, 95% CI: 1.60-11.94), having suicide history (HR = 2.51, 95% CI: 1.06-5.95), and having higher scores in EPQ-E (HR = 1.04, 95% CI: 1.00-1.08) and EPQ-P (HR = 1.03, 95% CI: 1.00-1.07) were identified as independent risk factors for aggressive behavior in patients with mood disorders. The nomogram prediction model demonstrated high discrimination and goodness-of-fit. CONCLUSIONS: A novel nomogram prediction model for the probability of aggressive behavior in patients with mood disorders was developed, effective in identifying at-risk populations and offering valuable insights for early intervention and proactive measures.

Prevalence of Common Child Mental Health Disorders Using Administrative Health Data and Parent Report in a Prospective Community-Based Cohort from Alberta, Canada: Prévalence des troubles communs de santé mentale de l'enfant à l'aide des données de santé administratives et des rapports des parents dans une cohorte prospective communautaire d'Alberta, Canada.

OBJECTIVE: Knowing the prevalence of mental health difficulties in young children is critical for early identification and intervention. In the current study, we examine the agreement among three different data sources estimating the prevalence of diagnoses for attention deficit hyperactivity disorder (ADHD) and emotional disorders (i.e., anxiety or mood disorder) for children between birth and 9 years of age. METHODS: Data from a prospective pregnancy cohort was linked with provincial administrative health data for children in Alberta, Canada. We report the positive agreement, negative agreement, and Cohen's Kappa of parent-reported child diagnoses provided by a health professional ("parent report"), exceeding a clinical cut-off on a standardized questionnaire completed by parents (the Behavior Assessment System for Children, 3rd edition ["BASC-3"]), and cumulative inpatient, outpatient, or physician claims diagnoses ("administrative data"). RESULTS: Positive and negative agreement for administrative data and parent-reported ADHD diagnoses were 70.8% and 95.6%, respectively, and 30.5% and 94.9% for administrative data and the BASC-3, respectively. For emotional disorders, administrative data and parent-reported diagnoses had a positive agreement of 35.7% and negative agreement of 96.30%. Positive and negative agreement for emotional disorders using administrative data and the BASC-3 were 20.0% and 87.4%, respectively. Kappa coefficients were generally low, indicating poor chance-corrected agreement between these data sources. CONCLUSIONS: The data sources highlighted in this study provide disparate agreement for the prevalence of ADHD and emotional disorder diagnoses in young children. Low Kappa coefficients suggest that parent-reported diagnoses, clinically elevated symptoms using a standardized questionnaire, and diagnoses from administrative data serve different purposes and provide discrete estimates of mental health difficulties in early childhood.Plain Language Title: Prevalence of child mental health disorders according to different data sources in Canada.

Knowing the prevalence of mental health difficulties in young children is critical for informing mental health policy and decision-making. Yet, different sources yield different estimates and we do not know how these estimates compare. In the current study, we examine the agreement among three different information sources estimating the prevalence of diagnoses for attention deficit hyperactivity disorder (ADHD) and emotional disorders (i.e., anxiety or mood disorder) for children between birth and 9 years of age. To estimate the prevalence of mental disorders, we asked parents if their child had ever been diagnosed, we asked parents to complete a questionnaire using clinical symptom cut-offs for diagnosis, and we looked at data collected in the health care system to see if a child was ever diagnosed by a healthcare provider. We found that for ADHD, parent report that their child had received a diagnosis and their child having received a diagnosis in the healthcare system were similar. There were larger differences between a parent report of elevated symptoms on a questionnaire and whether they had been diagnosed by a healthcare provider. For emotion disorders, there were larger differences between parent report that their child had received a diagnosis and whether one was documented in the health record. Overall, there was somewhat low agreement between these three sources of data. We conclude that the different sources of data used in this study provide different estimates of ADHD and emotional disorder diagnoses in children. Therefore, when trying to understand the burden of child mental health disorders in young children, it is important to consider multiple sources to obtain a comprehensive picture of the issue.

The Effect of COVID-19 on Mood Disorders in Urban and Suburban Detroit.

Introduction: The COVID-19 pandemic has increased the global experience of anxiety and depression owing to social isolation and government-mandated quarantine for transmission reduction. To date, literature surrounding the mental health effects of COVID-19 for the U.S. population is limited. Methods: This is a retrospective study from a large metropolitan Detroit health system. Patient encounters between December 23, 2018 and June 22, 2021, with March 23, 2020 being the start of Michigan state-wide lockdown, were used to define pre- and post-COVID-19 encounters, respectively. The data were divided into Detroit and non-Detroit on the basis of patient ZIP code. All patients aged ≥13 years with a visit with a family medicine provider were included. Outcome variables included Patient Health Questionnaires-2 and -9 and General Anxiety Disorder-7 scores; diagnoses of depression, anxiety, adjustment, and grief disorders; antidepressant prescriptions; and behavioral health referrals. Logistic regression was used to determine the incidence of composite mood disorder, depression, and anxiety. Results: A total of 20,970 individuals were included in this study: 10,613 in the Detroit subgroup and 10,357 in the non-Detroit subgroup. A total of 88.2% of the Detroit population were Black, and 70% were female. Logistic regression shows that the incidence of composite mood disorder decreased with increasing age (OR=0.787, 0.608, 0.422, and 0.392; p<0.001). Male sex is a protective factor (OR=0.646, p<0.001). Federal insurance is the only factor presenting a statistically significant increased risk (OR=1.395, p<0.001). There was no statistical difference between residing in urban and suburban areas in the incidence of composite mood disorder (OR=0.996, p=0.953). Conclusions: This research demonstrates that residing in an urban setting did not increase the risk of developing a mental health disorder during the COVID-19 period.

Prevalence and factors associated with fatigue in patients with major depressive disorder or bipolar disorder.

AIMS: To study the prevalence of fatigue and factors associated with fatigue in patients with major depressive disorder (MDD) or bipolar disorder (BD). METHODS: Two hundred fifty-three outpatients with MDD or BD at the initial assessment were used to study the prevalence of fatigue and relationship between fatigue and other clinical correlates. The severity of fatigue was measured with Iowa Fatigue Scale (IFS), and depression and anxiety symptom-severity were measured with the QIDS-16-SR (the 16-item Quick Inventory of Depressive Symptomatology - Self-Report) and Zung-SAS (Zung Self-Rating Anxiety Scale). Correlation between IFS and QIDS-16-SR total scores, QIDS-16-SR item scores or Zung-SAS total scores, and independent factors associated with fatigue was assessed with simple or multiple linear regression analysis. RESULTS: Overall, 28.4 % of MDD and 29.8 % of BD patients did not have fatigue, but 41.2 % of MDD and 45.0 % of BD patients had fatigue, and 30.4 % of MDD and 25.2 % of BD patients had severe fatigue. Depression/anxiety severity was significantly correlated with fatigue. However, after controlling current psychiatric comorbidities, demographics, some social factors, and psychotropic use, only QIDS-16-SR scores were still significantly and positively correlated with IFS scores in both MDD and BD. Differential correlations between IFS scores and item scores of QIDS-16-SR in MDD and BD were observed. LIMITATION: Cross-sectional. CONCLUSIONS: In this outpatient sample, fatigue was highly prevalent in patients with MDD or BD. The independent association of depressive severity with the severity of fatigue highlights the importance of complete resolution of depressive symptoms in treating MDD and BD.

Cannabis and anhedonia: A systematic review.

This paper employs a systematic review to examine the correlation between anhedonia and marijuana use, exploring whether individuals with anhedonia use marijuana as a coping mechanism or if marijuana use plays a role in the onset of anhedonia. The search utilised PubMed and Web of Science databases, following PRISMA guidelines for paper selection. A total of 21 papers were selected to address this inquiry, and assessments were carried out using the Risk of Bias in Non-randomized Studies of Exposures (ROBINS-E) tool. The results revealed that 17 studies exhibited moderate and low risk of bias. The evaluation encompassed a total of 12,427 participants, including both animals and humans. Experimental animal studies focused on exploring the association between cannabidiol (CBD) and anhedonia, while human studies primarily employed observational research, examining various forms of anhedonia in individuals with or without mental disorders such as depression or psychosis. These studies also delved into understanding the effects of anhedonia during adolescence and explored the causal relationship between these concepts. The findings indicate a reciprocal rather than unidirectional relationship, establishing that initial anhedonia predisposes individuals to cannabis use, and subsequent consumption significantly intensifies the anhedonia experienced. Particularly, the studies placed special emphasis on adolescents and individuals with mental disorders.

Mitochondrial Biomarkers and Metabolic Syndrome in Bipolar Disorder.

The object of this study is test whether mitochondrial blood-based biomarkers are associated with markers of metabolic syndrome in bipolar disorder, hypothesizing higher lactate but unchanged cell-free circulating mitochondrial DNA levels in bipolar disorder patients with metabolic syndrome. In a cohort study, primary testing from the FondaMental Advanced Centers of Expertise for bipolar disorder (FACE-BD) was conducted, including 837 stable bipolar disorder patients. The I-GIVE validation cohort consists of 237 participants: stable and acute bipolar patients, non-psychiatric controls, and acute schizophrenia patients. Multivariable regression analyses show significant lactate association with triglycerides, fasting glucose and systolic and diastolic blood pressure. Significantly higher levels of lactate were associated with presence of metabolic syndrome after adjusting for potential confounding factors. Mitochondrial-targeted metabolomics identified distinct metabolite profiles in patients with lactate presence and metabolic syndrome, differing from those without lactate changes but with metabolic syndrome. Circulating cell-free mitochondrial DNA was not associated with metabolic syndrome. This thorough analysis mitochondrial biomarkers indicate the associations with lactate and metabolic syndrome, while showing the mitochondrial metabolites can further stratify metabolic profiles in patients with BD. This study is relevant to improve the identification and stratification of bipolar patients with metabolic syndrome and provide potential personalized-therapeutic opportunities.

Wearable Data From Subjects Playing Super Mario, Taking University Exams, or Performing Physical Exercise Help Detect Acute Mood Disorder Episodes via Self-Supervised Learning: Prospective, Exploratory, Observational Study.

BACKGROUND: Personal sensing, leveraging data passively and near-continuously collected with wearables from patients in their ecological environment, is a promising paradigm to monitor mood disorders (MDs), a major determinant of the worldwide disease burden. However, collecting and annotating wearable data is resource intensive. Studies of this kind can thus typically afford to recruit only a few dozen patients. This constitutes one of the major obstacles to applying modern supervised machine learning techniques to MD detection. OBJECTIVE: In this paper, we overcame this data bottleneck and advanced the detection of acute MD episodes from wearables' data on the back of recent advances in self-supervised learning (SSL). This approach leverages unlabeled data to learn representations during pretraining, subsequently exploited for a supervised task. METHODS: We collected open access data sets recording with the Empatica E4 wristband spanning different, unrelated to MD monitoring, personal sensing tasks-from emotion recognition in Super Mario players to stress detection in undergraduates-and devised a preprocessing pipeline performing on-/off-body detection, sleep/wake detection, segmentation, and (optionally) feature extraction. With 161 E4-recorded subjects, we introduced E4SelfLearning, the largest-to-date open access collection, and its preprocessing pipeline. We developed a novel E4-tailored transformer (E4mer) architecture, serving as the blueprint for both SSL and fully supervised learning; we assessed whether and under which conditions self-supervised pretraining led to an improvement over fully supervised baselines (ie, the fully supervised E4mer and pre-deep learning algorithms) in detecting acute MD episodes from recording segments taken in 64 (n=32, 50%, acute, n=32, 50%, stable) patients. RESULTS: SSL significantly outperformed fully supervised pipelines using either our novel E4mer or extreme gradient boosting (XGBoost): n=3353 (81.23%) against n=3110 (75.35%; E4mer) and n=2973 (72.02%; XGBoost) correctly classified recording segments from a total of 4128 segments. SSL performance was strongly associated with the specific surrogate task used for pretraining, as well as with unlabeled data availability. CONCLUSIONS: We showed that SSL, a paradigm where a model is pretrained on unlabeled data with no need for human annotations before deployment on the supervised target task of interest, helps overcome the annotation bottleneck; the choice of the pretraining surrogate task and the size of unlabeled data for pretraining are key determinants of SSL success. We introduced E4mer, which can be used for SSL, and shared the E4SelfLearning collection, along with its preprocessing pipeline, which can foster and expedite future research into SSL for personal sensing.

Sixty years of recurrence prevention in mood disorders. / Szescdziesiat lat profilaktyki nawrotów chorób afektywnych.

This year, we observe sixty's anniversary of the article by a British psychiatrist, Geoffrey Hartigan, demonstrating, for the first time, the possibility of preventing of the recurrence of mood disorders by using lithium salts. Herein, a history of prevention of recurrences of mood disorders both worldwide and in Poland will be presented concerning both lithium and other mood-stabilizing drugs. The merit for verifying the prophylactic lithium effect in the 1960-1970s should be given to Danish researchers, Mogens Schou and Poul Baastrup. In Poland, the first paper on prophylactic lithium appeared already in 1971. In the 1970s, French researchers showed prophylactic activity of valproic acid amide, and Japanese researchers - carbamazepine. In the 1980th, studies on valproic acid amide were performed in the 2nd Psychiatric Clinic of the Institute of Psychiatry and Neurology led by Prof. Puzynski. Since the mid-1990s, 2nd generation of mood-stabilizing drugs has been introduced, including some atypical antipsychotics (clozapine, olanzapine, quetiapine, aripiprazole, risperidone) and anticonvulsant drug, lamotrigine, showing prophylactic activity in bipolar mood disorder. The studies on lithium resulted in the identification of factors connected with its prophylactic efficacy as well as the antisuicidal, antiviral, and neuroprotective effects of this drug. From a sixty-year perspective following Hartigan's article, it seems that his pioneering concept on the possibility of pharmacological influence on the course of mood disorders was fully confirmed. Current Polish recommendations on pharmacological prophylaxis of mood disorders were presented in the books "Standardy leczenia niektórych zaburzen psychicznych" and "Psychofarmakologia kliniczna", both published in 2022.