Search Results (6,784)

Background/Objectives: Major Depressive Disorder is a serious mental disorder that negatively affects an individual’s health and quality of life. The diagnosis of this disease is based on clinical interviews, questionnaires, and the patient’s self-reports. The objective of this study is to develop a biological diagnostic system based on the analysis of EEG signals and brain regions, rather than relying on self-reports. Methods: In this study, the EEG signals in the Multimodal Open Mental Disorder Analysis (MODMA) dataset were divided into six anatomical regions: prefrontal, frontal, central, parietal, temporal, and occipital. Empirical Wavelet Transform and Empirical Mode Decomposition methods were applied separately to the channels in each region, resulting in three IMF components. A total of 23 features, including statistical, nonlinear, spectral, and model-based (AR) features, were extracted from each IMF component. In addition to these features, asymmetry features between the left and right hemispheres were also included. Feature dimensions ranging from 10 to 40 were selected via the mRMR method, and the extracted feature sets were classified using SVM, k-NN, RUSBoost, Random Forest, and Meta-Ensemble machine learning models with Leave-One-Subject-Out (LOSO) validation. Results: According to the analysis results, the highest accuracy rate in Major Depressive Disorder (MDD) diagnosis was achieved by classifying features extracted from the frontal and prefrontal regions. The EMD signal processing method demonstrated superior performance compared to the EWT method. An accuracy rate of 98.11% was achieved using Random Forest and Meta-Ensemble models. Conclusions: In the proposed method, Explainable Artificial Intelligence (XAI) based SHAP analysis was applied to provide reliable and interpretable features for MDD diagnosis based on brain regional analysis. Full article

This narrative review examines perimenopause as a critical transitional phase in women’s lives, often accompanied by elevated vulnerability to anxiety and depression. Dysfunction of the gut–brain axis is one of the key factors contributing to perimenopausal mood disorders and is currently receiving extensive attention. GBA dysfunction can trigger neurotransmitter metabolic imbalance, intestinal barrier impairment, and neuroinflammatory responses. Tryptophan (Trp) and γ-aminobutyric acid (GABA) serve as essential precursors and direct modulators of key neurotransmitters, and the dysregulation of their metabolic pathways has been implicated in perimenopausal anxiety and depression in animal models and limited clinical observations. Trp influences 5-hydroxytryptamine (5-HT) by affecting emotional states. GABA is the primary inhibitory neurotransmitter in the central nervous system and is closely associated with anxiety and depression. Fluctuations in estrogen levels during perimenopause significantly alter the composition and metabolic activity of the gut microbiota, which in turn affects Trp metabolism and GABA synthesis through increased intestinal permeability, activation of immune-inflammatory responses, and disruption of hypothalamic–pituitary–adrenal (HPA) axis function. Although traditional hormone replacement therapy and pharmacological treatments are effective, they are associated with some side effects. Preliminary evidence from in vitro and animal studies suggests that nutritional interventions targeting Trp and GABA metabolism within the gut–brain axis may offer a novel research direction, though their efficacy in perimenopausal women remains to be established. Potential nutritional strategies, including supplementation with Trp and its precursors, inhibition of the kynurenine pathway (KP), and supplementation with probiotics and prebiotics, can modulate Trp and GABA metabolism. This review focuses on Trp and GABA metabolic regulation via the gut–brain axis to explore pathogenesis of perimenopausal anxiety and depression and summarize potential nutritional intervention targets, thereby providing a scientific basis for emotional management in perimenopausal women. Full article

Background: Body image disturbance (BID) involves a distorted perception of one’s body, whereas body dissatisfaction (BDS) reflects negative affective evaluation of body appearance. Both are central features of eating disorders such as anorexia nervosa (AN), but their expression in siblings of affected individuals remains underexplored, particularly in younger populations. Methods: This cross-sectional preliminary study included 53 full sisters of adolescent patients with severe AN treated in a tertiary hospital. Participants underwent anthropometric assessment and completed standardized measures of BID, BDS, physical activity, eating-related attitudes, perfectionism, anxiety, and depressive symptoms. Results: Participants exhibited marked body size overestimation (mean relative BID = +45.2%), with 64.2% classified as high overestimators and 3.8% as underestimators. Overestimation was most pronounced in the waist, chest, and calves. BID was not significantly associated with BDS or with anthropometric measures, including body mass index. BDS showed significant positive correlations with depressive symptoms and self-oriented perfectionism, whereas BID was positively associated with physical activity. No significant associations were found between BID or BDS and age, socioeconomic status, or birth order. Conclusions: Sisters of adolescents with severe AN show substantial perceptual distortion of body size without corresponding levels of body dissatisfaction, suggesting partial independence between perceptual and affective components of body image. These findings identify a potentially vulnerable group and highlight the need for longitudinal studies to clarify mechanisms and inform preventive strategies. Full article

Major depressive disorder (MDD) is not reducible to a single neurotransmitter deficit. Current explanations commonly involve monoaminergic dysfunction, hypothalamic–pituitary–adrenal axis dysregulation, immune-inflammatory activation, impaired neuroplasticity and synaptic dysfunction, together with metabolic and neurovascular abnormalities. Lipidomic studies have repeatedly identified glycerophospholipid abnormalities in MDD, but their mechanistic meaning remains unresolved because changes in bulk lipid abundance do not explain how altered lipid metabolism becomes a receptor-level neural signal. This review develops a testable interpretation of the lysophosphatidylcholine (LPC)–autotaxin (ATX)–lysophosphatidic acid (LPA)–LPA receptor (LPAR) axis in which LPC species generated during phospholipid turnover provide ATX substrates, ATX activity determines local LPA generation, LPA production and inactivation shape ligand availability, and LPAR signaling links the lipid product to neural output. This structure shifts the focus from total lipid abundance to matched assessment of lipid species, enzyme activity, anatomical site and receptor subtype. Human studies report lower serum and cerebrospinal fluid (CSF) ATX in MDD, lower CSF LPA 22:6 in MDD and schizophrenia, and negative total LPA findings that caution against biomarker oversimplification. Depression-relevant and broader stress- or anxiety-related experimental studies show that ATX, LPA and LPAR perturbation can affect hippocampal function, synaptic physiology, emotional behavior and stress resilience. The key unresolved issue is whether brain-accessible LPC species, active ATX, locally generated LPA, LPA inactivation capacity and receptor-specific output can be demonstrated within the same MDD-relevant fluid, brain-interface site or neural circuit. Future work should therefore move from fluid-level association toward pathway closure through targeted and spatial lipidomics, anatomical ATX activity mapping, LPA inactivation assays, blood–brain barrier (BBB)/interface analysis, LPAR perturbation and matched circuit or behavioral readouts. Full article

Major depressive disorder (MDD) affects approximately 280 million people worldwide, yet conventional pharmacotherapy achieves remission in only 30–50% of patients, intensifying the search for novel biological substrates. This systematic review, conducted according to PRISMA 2020 guidelines across six electronic databases (2014–March 2025), synthesised 89 studies examining gut microbiota composition in adults with MDD compared to healthy controls. MDD was consistently associated with reduced alpha diversity and a recurrent dysbiotic pattern, herein proposed as a depressive dysbiosis signature, characterised by depletion of butyrate-producing genera (Faecalibacterium, Roseburia, Eubacterium, Coprococcus) and enrichment of pro-inflammatory taxa (Alistipes, Eggerthella, Streptococcus). While this pattern was observed across multiple cohorts, significant inter-study heterogeneity precludes its definition as a universal microbial signature for MDD. Beta diversity analyses demonstrated robust compositional separation between cohorts. Plausible mechanistic pathways included compromised short-chain fatty acid production, increased intestinal permeability, low-grade systemic inflammation, tryptophan shunting toward the kynurenine pathway, and hypothalamic–pituitary–adrenal axis dysregulation. Preclinical faecal microbiota transplantation provided translational evidence consistent with a causal interpretation, while randomised probiotic trials demonstrated significant reductions in depressive symptom severity compared with placebo. Probiotic effects are strain-specific according to ISAPP consensus; generalisation across strains is not warranted. Gut microbiota dysbiosis represents a biologically plausible mediator of depression pathophysiology, with a recurrent dysbiotic pattern, characterised by depletion of butyrate-producing taxa and enrichment of pro-inflammatory genera, showing emerging diagnostic and therapeutic potential. Full article

Major Depressive Disorder (MDD) has a multifactorial etiology and pathogenesis that significantly impacts an individual’s quality of life. One of the possible correlations for its onset is the activation of inflammatory responses resulting in neurodegeneration and, consequently, the emergence of depressive symptoms. Interleukin-1β is a regulatory cytokine of the immune and nervous systems that acts on several processes, including mood regulation. This systematic review analyzed the IL1B (C-511T) (rs16944) variant’s CC and CT genotype frequencies and their associations with MDD in different populations while also verifying the TT genotype’s influence on response to antidepressant therapy. This review involved searching five databases, and articles were selected according to the PECOS inclusion criteria, resulting in eight articles. The findings highlight distinct clinical outcomes: the CC genotype was more frequently associated with greater MDD symptom severity, whereas the TT genotype was predominantly associated with antidepressant treatment response; thus, these associations should not be considered equivalent in terms of susceptibility to disease onset. However, despite these findings, other studies have found no significant association between this genetic variant and MDD. Therefore, further studies across different populations are needed to better understand the role of this polymorphism in the etiology of this disorder. Full article

Background: Major depressive disorder, particularly in its treatment-resistant form, remains a leading cause of global disability. When pharmacotherapy and psychotherapy fail, neuromodulation techniques such as electroconvulsive therapy (ECT) and repetitive transcranial magnetic stimulation (rTMS) are increasingly utilized. However, variability in protocols and outcome reporting continues to generate uncertainty regarding their comparative benefits and safety profiles. Objective: To comprehensively map and synthesize the available evidence on the clinical benefits and adverse effects of ECT and rTMS in adults with major depressive disorder and treatment-resistant depression. Methods: A scoping review was conducted following PRISMA-Sc guidelines and registered in PROSPERO; PubMed–MEDLINE, Scopus, and the Virtual Health Library were searched from inception to October 2022. Observational and experimental studies evaluating ECT and or rTMS in adults with depressive disorders were included. Data were extracted on study design, population characteristics, stimulation parameters, clinical outcomes, and adverse effects. Methodological quality was assessed using National Heart, Lung, and Blood Institute tools. Results: A total of 165 studies comprising 10,701 participants were included. ECT and rTMS were consistently associated with clinically meaningful reductions in depressive symptom severity across heterogeneous protocols. ECT demonstrated the most robust response rates, particularly in treatment-resistant and severe depression, while rTMS showed substantial efficacy with a more favorable safety profile. Adverse effects were more frequent and severe with ECT, including transient cognitive disturbances and cardiovascular complications, whereas rTMS was predominantly associated with mild, self-limited side effects such as headache and scalp discomfort. Considerable heterogeneity in stimulation parameters and diagnostic subgroups was observed across studies. Conclusions: Both ECT and rTMS represent effective neuromodulation strategies for major depressive disorder and treatment-resistant depression. ECT remains the most potent intervention in highly refractory cases, whereas rTMS offers a less invasive alternative with strong tolerability. Standardization of stimulation protocols, biomarker-informed stratification, coadjuvancy analysis, and long-term controlled studies are necessary to refine clinical positioning and advance precision neuromodulation in depression care. Full article

Rs9939609 marker in FTO Alpha-Ketoglutarate-Dependent Dioxygenase (FTO) gene, rs7895307 in Transcription Factor 7-Like 2 (TCF7L2) gene, and rs75493593 in Solute Carrier Family 16 Member 11 (SLC16A11) gene have been associated with anthropometric, metabolic, and clinical variables, but have not been concurrently studied in Mexican children and adolescents with adiposity or mental disorders. In this cross-sectional association study, we genotyped these markers by means of TaqMan real-time polymerase chain reaction in two at-risk pediatric cohorts recruited in Mexico City. Group 1 (n = 175) comprised children and adolescents with overweight/obesity. Group 2 (n = 296) consisted of non-medicated adolescents meeting the Diagnostic and Statistical Manual of Mental Disorders, fourth edition criteria for Attention Deficit/Hyperactivity Disorder or a mood disorder. Anthropometric measurements (body mass index —BMI—, waist circumference, body fat percentage), metabolic indices (fasting glucose, lipid profile, Homeostatic Model Assessment for Insulin Resistance), and psychiatric diagnoses were evaluated. In Group 1, the FTO A allele (genotypes AA/AT) was significantly associated with severe obesity according to BMI Z scores (p = 0.004, O.R. 3.33, 95% CI [1.42–7.77]), and it was a predictor of waist circumference (B = 6.16, 95% CI [1.78–10.55], p = 0.006) and muscle percentage (B = 4.21%, 95% CI [0.91–7.51%], p = 0.013) using linear regression models adjusted for age and sex. In Group 2, TCF7L2 AA genotype was associated with increased odds of depression (B = 0.83, p = 0.003, OR = 2.29, 95% CI [1.32–3.96]). While SLC16A11 G allele showed a possible association with insulin resistance or glucose levels, confirmation is needed. These exploratory results highlight the need for larger, well characterized cohort studies to confirm the associations. Full article

To address cross-subject domain shift and insufficient complementary fusion of time-frequency information in EEG-based emotion recognition, this paper proposes a multi-task adversarial network: Path Adversarial Dual-Branch Network for EEG Emotion Recognition (PADB-Net). The model adopts a dual-branch parallel architecture for time and frequency domains, processing raw EEG waveforms and differential entropy features respectively, and extracts discriminative features using lightweight depthwise separable convolutions and channel attention. A path adversarial module is introduced for the first time in emotion recognition to align time-domain and frequency-domain feature distributions, solving the single-branch dominance problem in dual-branch fusion. Together with a domain adversarial module, the overall distributions of source and target domains as well as the internal distributions of the two modality branches are aligned within a unified framework. Experiments on a dataset containing healthy subjects and patients with major depressive disorder show that the full model significantly outperforms single-adversarial and non-adversarial baselines in accuracy, AUC, F1-score, sensitivity, and specificity, verifying the synergistic gain of the dual-adversarial mechanism. On the HybridBCI dataset, PADB-Net achieves 77.80% accuracy, 84.50% AUC, and 79.40% F1-score with only 6.45 K trainable parameters. When transferred to the public SEED dataset for three-class emotion recognition, the model attains F1-scores of 71.83% (negative), 68.99% (neutral), and 73.37% (positive), demonstrating strong cross-dataset generalizability. Full article

Inflammatory bowel disease is an inflammatory disorder associated with systemic immune activation, contributing to neuroinflammation, behavioral impairments and disruption of the gut–brain axis. The present study investigated the effects of p-Coumaric acid derivatives: Artepillin C (ART-C), Baccharin (BAC), and Drupanin (DRU) on colonic damage, behavioral alterations, and oxidative stress in a dextran sulfate sodium (DSS)-induced colitis by administration of 3% DSS. Mice were treated with p-Coumaric acid derivatives (0.3, 1, or 3 mg/kg, p.o.), and disease activity index and colon length were evaluated as clinical parameters. Behavioral assessments included the open field test, novel object recognition test, elevated plus maze, and tail suspension test. Oxidative stress and inflammatory markers were quantified in colon, serum, cortex, and hippocampus, alongside histological analysis of colonic tissue. DSS administration induced clinical and histopathological alterations, increased oxidative stress, and impaired recognition memory, as well as anxiety- and depressive-like behaviors. p-Coumaric acid derivatives attenuated colonic damage, preserved tissue architecture, improved recognition memory, and reduced anxiety- and depressive-like behaviors, particularly at higher doses. These effects were associated with modulation of antioxidant defenses and reduction of lipid peroxidation and inflammatory markers. p-Coumaric acid derivatives exert protective effects in DSS-induced colitis, highlighting their potential as therapeutic agents for intestinal and neurobehavioral alterations associated with IBD. Full article

Cardiovascular disease is the leading cause of death in women, yet prevention and management have historically relied on male-centered models. Sex and gender critically influence risk, clinical presentation, and outcomes. Depression, anxiety, and psychosocial stress, more prevalent in women, act as key amplifiers of cardiovascular risk. We conducted a clinically oriented narrative review based on a broad, non-systematic search of major databases, integrating evidence selected for relevance and methodological robustness to clarify biological and psychosocial mechanisms linking mental health and cardiovascular disease in women. Affective disorders and stress contribute to cardiovascular risk through interconnected pathways, including hormonal fluctuations, autonomic and neuroendocrine dysregulation, inflammation, endothelial dysfunction, and heightened platelet reactivity. These mechanisms interact with gender-related exposures such as caregiving burden, occupational stress, and interpersonal violence. Stress-related phenotypes, including mental stress, induced ischemia and takotsubo syndrome, exemplify the heart-brain axis and its clinical implications. Incorporating mental health into cardiovascular risk assessment is essential for precision prevention in women. A women-centered approach should include systematic psychosocial evaluation, multidisciplinary care, and tailored strategies to improve risk control, adherence, and outcomes. Full article

Background/Objectives: Antidepressant treatment response is highly variable, and CYP2D6 metabolizer phenotype has been proposed as a contributor to this variability. It was examined whether CYP2D6 metabolizer phenotype is associated with real-world antidepressant treatment outcomes in a large population-based cohort. Methods: Using genetic and longitudinal primary care prescription data from the UK Biobank, we evaluated associations between CYP2D6 metabolizer phenotype and prescription-based proxies of treatment outcomes, including discontinuation, switching, and side effects. Analyses were stratified by antidepressant and adjusted for demographic covariates. Results: Among 26,957 individuals of European ancestry prescribed CYP2D6-metabolized antidepressants, reduced metabolic capacity was significantly associated with early discontinuation of paroxetine (N = 5718), venlafaxine (N = 2327), and mirtazapine (N = 3340). For paroxetine, poor metabolizers had higher odds of discontinuation compared with normal metabolizers and, among discontinuers, were more likely to stop immediately rather than later. Similar early discontinuation signals were observed for venlafaxine, with intermediate metabolizers showing increased risk. Mirtazapine also demonstrated increased odds of early discontinuation among poor metabolizers. No significant association was observed for fluoxetine. Associations with switching were limited, and no significant associations were detected for side effects. Conclusions: CYP2D6 variation appears to primarily influence early antidepressant discontinuation within the first 30 days of treatment, particularly for paroxetine, venlafaxine, and mirtazapine, rather than treatment switching or side effects. These findings provide observational support relevant to drug-specific gene interactions and suggest a role for CYP2D6-guided prescribing in clinical practice, notably in the first 30 days of antidepressant treatment. Full article

National crude suicide mortality rates (CMRs) in Japan trended downward throughout the 2010s, yet the CMR for the youth population moved in the opposite direction, rising from the mid-2010s onwards. To clarify the risk groups and underlying mechanisms of increasing student suicides, the temporal fluctuations of CMRs of students in middle school, high school, special vocational school, and university were analyzed by joinpoint regression analysis, and identification of high CMR groups were detected by a linear mixed-effect model using government suicide databases. CMRs of female students in all school categories increased from the mid-2010s. CMRs of male students in middle and high schools increased, whereas those in university and special vocational school moved from a decreasing to a stable level. Among the average of CMRs from 2022 to 2025, the highest CMR was observed in part-time high school students, which was approximately fivefold higher than the average of all students overall. The major leading suicide motives for all student subgroups were concerned with underachievement and career-path-associated problems within school-related problems. Family-related problems, such as conflict with parents and parental reprimands, were leading suicide motives for middle school students, but these impacts attenuated with age. Instead, the impacts of psychiatric disorders, including depression and other psychiatric disorders, enhanced with age. Student suicides attributed in the government suicide database to these leading suicide motives showed an upward inflexion, moving from a decreasing or stable pattern to a rising one, beginning in the mid-2010s. Taken together, these patterns indicate that mental health concerns among students have re-emerged as a substantial motive behind student suicide from the mid-2010s. Full article

Background: Food insecurity is a risk factor for binge eating behaviours and related disorders; however, the mechanisms underlying this association remain unclear. This study examined reward-based eating, psychological distress, and diet quality as potential mechanisms underscoring this association. Methods: Participants (N = 176) completed self-reports measuring reward-based eating (Reward-Based Eating Drive scale), distress (Depression, Anxiety and Stress scale), and diet (Australian Eating Survey), alongside a well-validated food insecurity survey, as part of a broader biopsychosocial assessment study. Parallel mediation analysis was utilised to explore the candidate variables as potential mediators between food insecurity and binge eating indicated by the Binge Eating Scale. Results: Food insecurity independently predicted binge eating behaviours, in association with the mediating variables. Reward-based eating and psychological distress were statistically significant mediators, but diet quality was not. Conclusions: Food insecurity is associated with binge eating through both reward drive and distress. Future research should investigate how both social and psychological interventions may leverage these mechanisms to overcoming binge eating. Full article

Objective: Disorders of gut–brain interaction (DGBIs) are characterized by functional impairments without identifiable organic causes, with their prevalence increasing with age. Emerging evidence suggests that selective serotonin reuptake inhibitors (SSRIs), such as escitalopram oxalate, may influence DGBIs through the brain–gut axis, though the precise mechanisms driving their therapeutic effects remain unclear. This study investigated the impact of escitalopram oxalate on elderly patients with DGBIs in an outpatient department to elucidate these mechanisms. Methods: This study was an observational cohort study. We recruited elderly patients diagnosed with DGBIs. Patients receiving standard treatment alone were assigned to the control group, while patients receiving standard treatment plus 10 mg of escitalopram oxalate daily were assigned to the exposure group. Emotional and gastrointestinal symptoms were assessed at baseline and after 12 weeks of treatment using validated symptom scales. Additionally, stool samples were collected at both time points and analyzed via 16S amplicon sequencing to evaluate the changes in gut microbiota. Results: A total of 83 elderly patients with DGBIs were included in the study, comprising 40 patients in the control group and 43 in the exposure group. After 12 weeks, the exposure group showed significantly greater reductions in their scores on the Gastrointestinal Symptom Rating Scale (GSRS), Short-Form Leeds Dyspepsia Questionnaire (SF-LDQ), Zung Self-Rating Depression Scale (SDS) and Zung Self-Rating Anxiety Scale (SAS) compared with the control group (e.g., GSRS: 17.00 ± 0.85 vs. 22.58 ± 3.18, p < 0.001; p < 0.01 for all other scale comparisons), with higher effective and recovery rates. Notably, the exposure group showed significant alterations in the abundance of four genus-level taxa (Blautia, Butyricicoccus, Prevotellaceae UCG-003, and Streptococcus) and two species-level taxa (Eubacterium-hallii-group and Parabacteroides-merdae). Conclusions: The escitalopram oxalate treatment was associated with significant improvements in both emotional and gastrointestinal symptoms in elderly patients with DGBIs. These improvements may be linked to alterations in specific gut microbiota taxa, offering a preliminary hypothesis for further investigating the underlying mechanisms of the gut–brain axis. Full article