Background:Adolescent depression necessitates the development of novel therapeutic approaches. Temporal interference stimulation (TIS) is a promising noninvasive neuromodulation technique capable of modulating deep-brain circuits; however, its feasibility in adolescent populations has not yet been established. This open-label pilot study evaluated the feasibility, safety, and tolerability of a five-day TIS protocol targeting the right amygdala in adolescents with depression. Clinical outcomes and neuroimaging findings were assessed as exploratory, hypothesis-generating objectives. Methods:Twelve adolescents with depression received five consecutive daily sessions of TIS (2000 Hz carrier frequency with a 100 Hz difference frequency; 20 min/day) targeting the right amygdala. Feasibility was evaluated on the basis of tolerability and adherence rates. Clinical outcomes were assessed using the 17-item Hamilton Depression Rating Scale (HAMD-17), Montgomery-Åsberg Depression Rating Scale (MADRS), 14-item Hamilton Anxiety Rating Scale (HAMA-14), and the THINC-integrated tool (THINC-it) at baseline, post-treatment, and at one-week and four-week follow-up assessments. Exploratory resting-state functional magnetic resonance imaging (fMRI) was performed to investigate neuromodulatory effects. Results:Nine participants completed the study, corresponding to a completion rate of 75%, with a tolerability rate of 100%. No device-related adverse events were reported. Trends toward improvement were observed in depressive symptoms, anxiety symptoms, and subjective cognitive functioning. From baseline to post-treatment, HAMD-17 and HAMA-14 scores decreased by 52.0% and 56.7%, respectively, and these improvements were maintained at the four-week follow-up, with a 53.3% reduction in depression severity. Exploratory fMRI analyses demonstrated acute increases in functional connectivity between the right amygdala and sensorimotor cortical regions during the first stimulation session. Conclusions:A five-day course of right amygdala-targeted TIS was feasible, safe, and well tolerated in adolescents with depression. The observed improvements in depressive and anxiety symptoms, together with acute alterations in amygdala-cortical functional connectivity, provide hypothesis-generating signals that warrant further investigation in rigorously designed sham-controlled trials. However, given the open-label and uncontrolled nature of the study, these improvements cannot be causally attributed to the intervention. Clinical Trial Registration:The study has been registered on https://clinicaltrials.gov/ (registration number: No: NCT06452849; registration link: https://clinicaltrials.gov/study/NCT06452849).
Background:Anxiety-related symptoms are frequently reported in patients with chronic myeloid leukemia (CML) receiving tyrosine kinase inhibitor (TKI) therapy. However, the role of TKIs, including imatinib, in development of anxiety remains unclear. The prefrontal cortex (PFC) is closely associated with anxiety-like behaviors, and its metabolic components, particularly lipid- and myelin-related metabolites, are involved in their regulation. Whether imatinib affects brain metabolism remains unknown. This study aimed to evaluate the effects of imatinib on anxiety-like behaviors and to investigate associated metabolic alterations in the PFC. Methods:Anxiety-like behaviors were assessed using a battery of behavioral assays in imatinib-treated mice. PFC tissues from imatinib-treated and control mice were subjected to untargeted metabolomic analysis. Results:Imatinib-treated mice exhibited selective alterations in anxiety-like behaviors. Metabolomic analysis revealed distinct metabolic profiles between the two groups, with significant changes in lipid-related pathways, particularly sphingolipid metabolism. These findings extend the current understanding of the metabolic basis of anxiety-like behaviors and suggest that TKI treatment may influence neuropsychiatric processes through metabolic remodeling of the PFC. Conclusions:This study highlights a potential link between TKI therapy and brain metabolism and provides a framework for understanding the neurobiological basis of anxiety-related effects. These findings may inform future research on the neuropsychiatric consequences of targeted cancer therapies.
Background:Artificial intelligence (AI) integration offers significant potential to improve mental healthcare, however, the reliability of large language models (LLMs) in performing nuanced clinical tasks remains an important and largely unanswered question. This study aimed to evaluate ChatGPT's performance in scoring the Hamilton Depression Rating Scale (HAMD-21) compared with expert raters using standardized patients (SPs). Methods:Three senior mental health experts created and portrayed scenarios for ten SPs representing diverse depressive symptom profiles. Recorded interviews were transcribed and used as input for ChatGPT-4o. HAMD-21 scores generated by ChatGPT were compared with those assigned by expert raters and with predefined script-based reference scores. Inter-rater reliability was assessed using intraclass correlation coefficient (ICC), and differences between raters were evaluated using Steiger's tests. Results:ChatGPT and the expert raters achieved good-to-excellent reliability for total HAMD-21 scores (experts: ICC = 0.9921; ChatGPT: ICC = 0.9739). However, expert raters achieved perfect ICCs on 11 individual items, whereas ChatGPT achieved perfect agreement on only 2 items. Steiger's test demonstrated that experts significantly outperformed ChatGPT on 10 individual items as well as on total scores (Z = 1.931, p = 0.0268). Qualitative review revealed that ChatGPT tended to overestimate scores on items related to insomnia and somatic symptoms (items 4-6 and 13) and frequently miscalculated total scores. Conclusions:ChatGPT demonstrated excellent agreement on total HAMD-21 scores in structured, text-based depression assessments, supporting the potential role of LLMs as adjunctive tools for standardized depression severity evaluation. However, item-level discrepancies and systematic scoring errors indicate that human oversight remains essential for clinically nuanced interpretation.
Background:The interrelationships among the negative symptoms of schizophrenia and factors affecting quality of life remain unclear. To address this gap, the present study explores the complex interrelationships among anhedonia, self-stigma, self-esteem, psychological resilience, and social support in individuals with schizophrenia. Methods:A comprehensive battery of measures was used to assess 447 patients with schizophrenia. Undirected network analysis was employed to examine the centrality of various factors, and Bayesian network analysis was used to explore the indirect influence of upstream variables on anhedonia through psychological factors. Results:Self-stigma was identified as the most central factor. Among the subdimensions of anhedonia, abstract anticipatory pleasure and contextual consummatory pleasure demonstrated the highest centrality. Negative symptoms of schizophrenia and social support were found to indirectly influence different aspects of anhedonia through psychological factors such as self-esteem and resilience. In one of the identified pathways, social support influenced psychological resilience, which in turn affected abstract anticipatory pleasure, contextual consummatory pleasure, and contextual anticipatory pleasure. Conclusions:Our findings suggest that social support is associated with pleasure experiences partly through psychological resilience and underscore the potential mediating role of psychological factors in linking clinical symptoms, social resources, and hedonic capacity in schizophrenia.
Background:Although the global burden of mental disorders has been extensively documented, systematic assessments of cross-country inequalities, particularly regarding how this burden varies across levels of socio-demographic development, remain limited. Methods:Data on disability-adjusted life-years (DALYs) attributable to mental disorders and the socio-demographic index (SDI) were obtained from the 2021 Global Burden of Disease Study. Absolute and relative inequalities were assessed using the slope index of inequality (SII) and concentration index (CI). Results:Between 1990 and 2021, the total number of DALYs attributable to mental disorders increased by 73.4%, with the largest increase observed among adults aged 30 to 54 years. Age-standardized DALY rates increased by 9.4%, primarily driven by anxiety disorders, eating disorders, and depressive disorders. Females exhibited higher age-standardized rates of depressive disorders, anxiety disorders, bipolar disorder, and eating disorders, whereas males had higher rates of schizophrenia, autism spectrum disorder, conduct disorder, attention-deficit/hyperactivity disorder (ADHD), and other mental disorders. Anxiety disorders and depressive disorders were the primary contributors to the increasing burden, particularly among women and adolescents. In 2021, the burden of mental disorders showed substantial geographical variation across countries and territories. Inequality analyses demonstrated that the SII for overall mental disorders increased from 69 to 243, whereas relative inequality remained stable over time. Across SDI strata, high-SDI countries experienced a greater burden of eating disorders, ADHD, schizophrenia, and anxiety disorders, while low-SDI countries experienced a greater burden of depressive disorders and idiopathic developmental intellectual disability. Conclusions:The burden of mental disorders remains substantial and unequally distributed worldwide. Persistent and widening disparities over the past three decades highlight the urgent need for strengthened global health policies and coordinated multilevel interventions aimed at reducing inequalities across countries with differing levels of socio-demographic development.
Understanding the physiological changes induced by ketamine in mood disorders, while reducing its side effects, is likely to contribute to a more comprehensive understanding of the physiology underlying mood disorders, as well as to the development of faster-acting and more efficacious antidepressant treatments. An extensive review of the literature on ketamine and the pathophysiology of depression indicates that ketamine's antidepressant efficacy has classically been attributed to noncompetitive antagonism of the n-methyl-d-aspartate receptor (NMDAR) on the neuronal postsynaptic membrane, thereby reducing excessive Ca²⁺ influx through the NMDAR channel. However, recent evidence suggests that ketamine's antidepressant efficacy is mediated not by synaptic NMDAR antagonism but rather by its direct effects on mitochondrial function, arising from its amphiphilic structure. It is proposed that astrocyte mitochondria represent the primary target of ketamine, with the broader effects induced by ketamine occurring downstream of the optimization of astrocyte mitochondrial function and, consequently, astrocyte function. Developmental stress and trauma are proposed to differentially prime specific regions of the central nervous system, rendering them more susceptible to subsequent stressors through the epigenetic regulation of astrocytes. This process increases astrocyte reactivity and dysregulates astrocyte mitochondrial function in response to subsequent stressors, while also increasing blood-brain barrier permeability within these regions. At stress-vulnerable sites, ketamine may upregulate adenosine, humanin, and melatonin, thereby restoring astrocyte function and attenuating inflammatory activity within the local astrocytic microenvironment, including microglia, neurons, and oligodendrocytes. Ketamine's modulation of mitochondrial function is proposed to be mediated via NMDARs located on the inner mitochondrial membrane, leading to alterations in mitochondrial ionic regulation that enhance astrocyte mitochondrial resilience to stress, possibly through a preconditioning mechanism. Ketamine-induced increases in melatonin and humanin are proposed to suppress microglial activation, promote white matter remyelination, and restore neuronal activity, as well as patterned intercellular and interregional communication. This hypothesis-driven overview evaluates ketamine's capacity to restore astrocyte mitochondrial function and thereby counteract the consequences of developmental stress and trauma that underlie vulnerability to subsequent stress-induced depression.
Background:A substantial proportion of adolescents with major depressive disorder (MDD) engage in non-suicidal self-injury (NSSI); however, the biological and psychological factors differentiating those with and without NSSI remain poorly characterized. This study aimed to investigate whether serum beta-endorphin levels, psychological pain, and anhedonia differ between these groups and to explore their associations with the presence of NSSI. Methods:The study sample comprised adolescents prospectively recruited during the study period and diagnosed with MDD according to the Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition, Text Revision (DSM-5-TR) criteria. Participants were categorized into adolescents with NSSI (NSSI+) and those without NSSI (NSSI-). Assessments included the Children's Depression Inventory (CDI), Psychache Scale (PAS), and Snaith-Hamilton Pleasure Scale (SHAPS). Serum beta-endorphin levels were measured using enzyme-linked immunosorbent assay (ELISA) from blood samples collected after an overnight fast. Results:The study cohort consisted of 104 adolescents with MDD, including 52 participants in the NSSI+ group and 52 in the NSSI- group. The sample comprised 85 females (81.7%) and 19 males (18.3%). Compared with the NSSI- group, adolescents in the NSSI+ group demonstrated significantly lower serum beta-endorphin levels and significantly higher levels of depressive symptoms, psychological pain, and anhedonia (all p < 0.05). In multivariable analyses, greater depression severity, higher psychological pain, and lower beta-endorphin levels were independently associated with the presence of NSSI. Exploratory mediation analyses suggested an indirect association between depression severity and NSSI through psychological pain. Conclusions:These findings highlight the relevance of both psychological and neurobiological factors in NSSI among adolescents with MDD and suggest that an integrated assessment of these factors may help identify adolescents at increased risk of this form of self-harm.
Background:In patients undergoing detoxification for benzodiazepine (BZD) dependence, withdrawal symptoms frequently persist into the low-concentration phase following drug discontinuation. Prolonged drug elimination may extend the duration of required medical supervision. Because lipophilic BZDs can accumulate in adipose tissue and be released gradually during detoxification, overweight patients may experience delayed elimination. This study quantitatively examined whether BZD elimination and the duration of withdrawal symptoms are prolonged in overweight patients. Methods:From 508 records of concentration-monitored detoxification, a retrospective sample of 290 inpatients matched for diet and physical activity was selected. All patients underwent detoxification according to the SAER protocol (Satiation, Anti-accumulation paradigm, Elimination, and Readaptation). Following (S) satiation with diazepam, further unnecessary (A) accumulation was prevented through aggressive day-by-day dose reductions guided by serum concentration monitoring. Subsequent tapering, leading to effective (E) elimination, was adjusted according to the evolving intensity of withdrawal symptoms, characterized by episodes of peak severity (withdrawal crises) interspersed with periods of relative relief. Completion of (R) readaptation was defined by the cessation of withdrawal symptoms after elimination. The duration of effective elimination, from peak serum concentration to undetectable levels, with particular attention to the post-discontinuation phase, was recorded. Concomitant medications known to influence BZD elimination were identified. Elimination parameters and the timing of clinically significant withdrawal crises were analyzed in relation to patients' body mass index (BMI). Results:Elimination duration was positively correlated with BMI (ρ = 0.39, p < 0.001). The timing of the strongest and/or the final crises also showed weak but significant positive correlations with BMI in the overall sample (ρ = 0.18 and 0.15, p < 0.01 and < 0.05 cutoff, respectively), and within the identified co-medication subgroups, including the valproate, carbamazepine, and no-modifier groups (ρ = 0.19-0.26, all p < 0.05). These associations accounted for a small proportion of the variance in overall time to withdrawal crisis (R2 = 0.02-0.07). Nevertheless, they translated into an additional 8-11 days of necessary monitored care among obese patients. Elimination duration was further prolonged in patients receiving valproate. Extended elimination was not associated with reduced withdrawal symptom severity. Conclusions:Among patients undergoing detoxification for BZD dependence, higher BMI was associated with prolonged drug elimination and a longer duration of recurring withdrawal crises, without attenuation of symptom severity. Although the observed associations were modest and potentially influenced by confounding factors, they suggest that overweight patients may require extended monitoring during detoxification. Prospective studies are needed to confirm these findings. To reduce the risk of delayed withdrawal crises and maintain treatment within reasonable time frames, minimizing excessive BZD accumulation through laboratory-guided dose adjustment is recommended.
Sleep disturbances are highly prevalent in autism spectrum disorder (ASD), yet their significance may extend beyond that of a common co-occurring condition. Growing evidence suggests that excitation/inhibition (E/I)-related network dysregulation may provide a valuable framework for understanding the association between sleep disturbances and variability in core ASD symptom expression. This review synthesizes findings from polysomnography, actigraphy, circadian rhythm research, neuroimaging, electrophysiological studies, and animal models to examine how E/I-related vulnerability in ASD may contribute to impaired sleep initiation and maintenance. It further explores how sleep and circadian disruption may, in turn, influence daytime symptom expression through alterations in synaptic homeostasis and network rebalancing. By proposing a bidirectional framework, this review aims to integrate current evidence on sleep-related symptom variability in ASD and to inform future longitudinal, mechanistic, and biomarker-driven research.
Background:There is increasing evidence that plasma osmolarity is an independent prognostic factor associated with mortality in patients with cardiovascular disease. Whole blood viscosity (WBV) is also associated with established cardiometabolic risk factors for cardiovascular disease. The present study aimed to investigate the effects of the acute phase of schizophrenia on physiological parameters, including WBV and plasma osmolarity, in male patients with schizophrenia. Methods:A total of 121 male patients with schizophrenia were included in this study. Routine blood test results were obtained from hospital records, and the laboratory values required for the calculation of viscosity and osmolarity were recorded. Laboratory data from the patients' most recent acute exacerbation were retrieved from hospital records and used as the acute-phase data. Results:There was no statistically significant difference in serum osmolarity between the acute and remission phases (p = 0.360). Blood urea nitrogen (BUN) and glucose levels were significantly higher during the remission phase, whereas sodium levels were significantly higher during the acute phase. No significant differences were observed in WBV values between the acute and remission phases (p > 0.05). Furthermore, there were no significant differences in WBV-related parameters, including hematocrit (HCT) and total protein, between the two phases. Low-density lipoprotein (LDL), high-density lipoprotein (HDL), total cholesterol, and triglyceride levels were significantly higher during the remission phase. Conclusions:Although differences were observed in osmolarity-related parameters and viscosity-associated metabolic variables between the acute and remission phases in male patients with schizophrenia, no statistically significant differences were found in serum osmolarity or WBV between the two phases.
Background:Deficits in hot executive functions (EFs), including risky decision-making, delay discounting, and emotion regulation, represent important yet relatively understudied features of attention-deficit/hyperactivity disorder (ADHD). Although physical exercise has been shown to improve cool EFs, its effects on hot EFs remain uncertain. Furthermore, conventional intervention approaches are often limited by accessibility and implementation barriers, underscoring the need for intelligent, home-based alternatives. Methods:In this three-arm randomized controlled trial, 145 children aged 6-10 years with ADHD were randomly assigned to an intelligent exercise group (EG1; n = 53), a traditional offline exercise group (EG2; n = 45), or a wait-list control group (CG; n = 47). Both intervention groups participated in a 12-week program consisting of three sessions per week, each lasting 45-60 minutes and integrating physical and cognitive training. Participants in EG1 completed the intervention through a custom-developed WeChat mini-program ("LeDongYing"), which incorporates computer vision-based motor assessment, dynamically personalized exercise prescriptions, real-time feedback, an artificial intelligence (AI)-assisted guidance agent, and a tailored exercise library. Participants in EG2 received coach-led, face-to-face training sessions. Outcome measures included risky decision-making, delay discounting, and emotion regulation. Intervention effects were evaluated using generalized linear mixed models, with potential confounders included as covariates. Results:For risky decision-making, EG1 demonstrated significantly greater improvements than CG in Block 3 (β = 3.38, p = 0.019), Block 4 (β = 6.89, p < 0.001), and total net score (β = 13.07, p = 0.012). EG2 also showed significantly greater improvements than CG in Block 3 (β = 3.49, p = 0.019) and Block 4 (β = 4.38, p = 0.009). No significant differences were observed between EG1 and EG2 for any risky decision-making outcome (all p > 0.05). For delay discounting, both EG1 (β = 0.12, p < 0.001) and EG2 (β = 0.12, p < 0.001) demonstrated significantly greater improvements than CG, with no significant difference between the two intervention groups (β = 0.00, p = 0.968).For emotion regulation, both EG1 (β = 3.38, p = 0.002) and EG2 (β = 2.71, p = 0.014) improved significantly more than CG, whereas no significant difference was observed between EG1 and EG2 (β = 0.66, p = 0.507). Adherence and participant satisfaction did not differ significantly between EG1 and EG2 (both p > 0.05). Conclusions:The intelligent exercise intervention appears to be an effective, scalable, and accessible non-pharmacological approach for improving hot executive functions in children with ADHD. Its efficacy was comparable to that of traditional face-to-face exercise programs, suggesting that this delivery model may help overcome implementation barriers and expand access to rehabilitation services without implying superiority over conventional approaches. Clinical Trial Registration:The study has been registered on https://www.chictr.org.cn/ (registration number: ChiCTR2200065413; registration link: https://www.chictr.org.cn/showproj.html?proj=182412).
Background:Artificial intelligence (AI) chatbots are rapidly becoming integrated into higher education, supporting human-computer interaction, knowledge explanation, rapid access to information, access to online learning resources, and personalized learning pathways. However, little is known about potential patterns of dependence on these technologies and their relationship with anxiety and depressive symptoms. This study aimed to conduct an initial psychometric evaluation of the Spanish version of the Artificial Intelligence Chatbot Dependence Scale (AICDS) and to explore its association with anxiety and depressive symptoms among university students. Methods:A cross-sectional study was conducted among 200 university students from Santa Rosa del Aguaray, Paraguay. Participants completed the AICDS together with screening measures of anxiety and depressive symptoms. Data were analyzed using R version 4.5.3. Confirmatory factor analysis using diagonally weighted least squares estimation with robust standard errors was performed to examine the scale's factor structure, and multiple linear regression models were used to evaluate associations between AICDS scores and anxiety and depressive symptoms. Results:The findings supported a unidimensional factor structure with acceptable-to-good model fit and high internal consistency (Cronbach's α = 0.833; McDonald's ω = 0.903). Fully standardized factor loadings ranged from 0.538 to 0.873. In bivariate analyses, students who screened positive for anxiety symptoms had higher AICDS scores than those who screened negative, although the effect size was small. However, this association was not maintained after adjustment for sociodemographic and academic covariates in multiple regression models. No significant association was observed between AICDS scores and depressive symptoms under two-tailed testing. Conclusions:These findings provide preliminary evidence supporting the internal consistency and factorial validity of the Spanish version of the AICDS in this sample. However, associations between AI chatbot dependence and anxiety or depressive symptoms were weak and not robust after adjustment. Further longitudinal and psychometric research is needed before broader conclusions can be drawn about the mental health implications of AI chatbot dependence among university students.
Background:Adolescents with depression pose a significant public health challenge, yet individual variability in treatment response to accelerated intermittent theta-burst stimulation (iTBS) for depression remains substantial. This study aims to integrate metabolomics with multimodal neuroimaging techniques to identify objective biomarkers of response to iTBS treatment and investigate the relationship between brain and metabolism. Methods:Patients received an accelerated iTBS protocol targeting the left dorsolateral prefrontal cortex. Assessments included plasma metabolomic profiling, resting-state and naturalistic functional magnetic resonance imaging, and clinical scale evaluations conducted at baseline and post-treatment. Results:The study enrolled 85 adolescents with depression and 48 healthy controls. 53 adolescent patients with depression completed the full course of iTBS treatment and provided blood samples for biomarker detection and analysis. Seventeen differential metabolites were identified that distinguished patients from controls and changed significantly after iTBS treatment. The area under the curve (AUC) for the metabolites 3-hydroxymethylglutaric acid, malonic acid, N-acetylphenylalanine, norepinephrine and tryptophanamide exceeds 0.8. The metabolites isovalerylcarnitine, taurochenodeoxycholic acid, taurodeoxycholic acid, and valerylcarnitine were significantly correlated with the reduction in scores on the Hamilton Depression Rating scale (HAMD). Furthermore, alterations in the metabolites 3-Indolepropionic acid, N-acetylphenylalanine, 3-Methylhistidine, Norepinephrine, Ortho-hydroxyphenylacetic acid, 3-Hydroxymethylglutaric acid and Indole-3-carboxaldehyde were associated with functional changes in key prefrontal regions, specifically, the Amplitude of Low-Frequency Fluctuations (ALFF) and Regional Homogeneity (ReHo) in the left superior frontal gyrus, and ReHo in the left middle frontal gyrus. Conclusions:This study uncovers preliminary evidence of a distinct metabolic signature in adolescent depression that normalizes following iTBS treatment and correlates with both prefrontal functional recovery and clinical improvement. The identified metabolites serve as potential candidate biomarkers and shed light on the brain-metabolism relationship. These findings offer preliminary candidate biomarkers for future investigations into interindividual variability in iTBS treatment response and offer a tentative framework for developing personalized neuromodulation strategies for adolescent depression. Clinical Trial Registration:The study has been registered on https://www.chictr.org.cn/ (registration number: ChiCTR2500106503 and ChiCTR2500113926; registration link: https://www.chictr.org.cn/showproj.html?proj=279390 and https://www.chictr.org.cn/showproj.html?proj=279455).
Background:Current treatments for major depressive disorder (MDD) are limited by efficacy and adverse effects. Transcranial alternating current stimulation (tACS) has emerged as a promising alternative. However, there is still a lack of systematic evaluation of its effectiveness. Recent studies suggest that currents greater than 7 milliamperes (mA) may be necessary to significantly alter potentials in deep brain regions associated with depression. We conducted a systematic review and exploratory meta-analysis to assess the overall efficacy and safety of tACS for MDD and to explore potential associations regarding current intensity by comparing high-intensity tACS (HI-tACS) and low-intensity tACS (LI-tACS) protocols. Methods:A systematic search of Embase, PubMed, Web of Science, the Cochrane Library, ClinicalTrials.gov, and WHO ICTRP was conducted from inception to January 5, 2026. Data were analyzed using a random-effects model, assessing changes in depressive scale scores, response and remission rates, discontinuation, and adverse events. Results:Randomized controlled trials with 438 participants were included. Compared to sham stimulation, active tACS was associated with a significant reduction in depressive symptoms (moderate effect size). In an exploratory subgroup analysis, HI-tACS was associated with a larger effect size (large effect) than LI-tACS (small effect), with lower heterogeneity observed within subgroups. The HI-tACS group also showed significantly higher response and remission rates. No significant differences in adverse events or treatment discontinuations were observed between the two subgroups. Conclusions:Our results suggest that tACS may be a potentially effective treatment for MDD. Data from exploratory subgroup analyses provide preliminary, hypothesis-generating evidence that higher intensity may be associated with improved outcomes. However, given the limited evidence base and substantial heterogeneity, as well as the fact that intensity co-varied with stimulation frequency and other parameters in the included trials, these findings do not establish a sole causal link for intensity. Future large-scale, controlled, multi-arm trials are needed to disentangle these factors and confirm these preliminary observations. The PROSPERO Registration:The study has been registered on https://www.crd.york.ac.uk/prospero/ (registration number: CRD42024589889; registration link: https://www.crd.york.ac.uk/PROSPERO/view/CRD42024589889).
Background:Ketamine may have antidepressant and anti-suicidal effects. However, the mechanism underlying ketamine-mediated improvement in cognitive impairment in patients with depression remains unclear. To improve patient cognition in depression using molecular docking and network pharmacology, we examined ketamine's key targets and identified its molecular mechanisms. Methods:To gain target information about cognitive impairment (1983) and depression (1874), we used three databases, including Online Mendelian Inheritance in Man, GeneCards, and DisGENET. Information on ketamine targets (63) was retrieved from public databases. To locate signaling pathways and core targets, we conducted bioinformatics analysis, including an enrichment analysis and protein-protein interaction (PPI) network analysis. To assess the interaction between core targets and ketamine, we carried out molecular docking. Results:We identified 20 ketamine target proteins of ketamine related to depression and cognitive impairment. Enrichment analyses revealed that ketamine influenced depression and cognitive function through multiple pathways, targets, and overall synergy. The important signaling pathways identified were "amphetamine addiction" and "dopaminergic synapse". Five core genes (monoamine oxidase (MAO)-A, MAO-B, glycogen synthase kinase-3β, sirtuin-1, epidermal growth factor receptor) were identified through PPI-network analyses. Our molecular docking results showed that binding was strong between these core genes and ketamine. Conclusions:The antidepressant and cognitive-enhancing effects of ketamine are primarily mediated through targets associated with inflammation, neural signaling, tumors, and neurodegeneration, as well as pathways such as amphetamine addiction, dopaminergic synapse, and the cyclic adenosine monophosphate (cAMP) signaling pathway. The findings provide theoretical support and guidance for optimizing clinical application strategies of ketamine and for designing new drugs.
Background:Emotion dysregulation and internalizing symptoms are increasingly recognized as central features of attention-deficit/hyperactivity disorder (ADHD), yet substantial emotional heterogeneity exists among affected adolescents. This study aimed to identify distinct emotional profiles in adolescents with ADHD by integrating emotion regulation difficulties, resilience, and internalizing symptoms using a person-centered, data-driven approach. Methods:This multicenter, cross-sectional study included 109 clinically referred adolescents aged 11-18 years with a Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-5) diagnosis of ADHD. Adolescents completed self-report measures of emotion regulation difficulties (Difficulties in Emotion Regulation Scale-16; DERS-16), resilience (Connor-Davidson Resilience Scale; CD-RISC-25), and internalizing symptoms (Revised Child Anxiety and Depression Scale; RCADS). Parents completed parent-report measures of their child's ADHD symptom severity (Swanson, Nolan, and Pelham Rating Scale; SNAP-IV) and perceived competence, as well as self-report measures of their own emotion regulation difficulties and resilience. Clinicians rated global severity using the Clinical Global Impression-Severity scale (CGI-S). K-means clustering was applied to standardized adolescent emotional variables to identify distinct profiles, which were evaluated using internal validation indices and clinical correlates. Between-cluster comparisons were conducted across demographic, clinical, and psychosocial variables. Correlation and mediation analyses were performed to examine associations among resilience, emotion regulation difficulties, and internalizing symptoms. Results:Four distinct emotional profiles were identified: (1) Low Emotion Dysregulation / High Resilience / Low Internalizing, (2) Moderate Emotion Dysregulation / Moderate Resilience / Moderate Internalizing, (3) Low-to-Moderate Emotion Dysregulation / Low Resilience / Low-to-Moderate Internalizing (descriptively labeled as "Low-resilience silent" profile), and (4) High Emotion Dysregulation / Low Resilience / High Internalizing. Emotional profiles differed significantly in emotion regulation difficulties, resilience, and internalizing symptom severity (all p < 0.001), but not in parent-reported ADHD symptom dimensions or clinician-rated severity. Perceived social competence, gender distribution, internalizing comorbidity, and medication patterns varied across profiles, whereas parental emotion regulation difficulties and resilience did not. Emotion regulation difficulties showed a significant indirect effect in the association between resilience and internalizing symptoms, such that lower resilience was associated with greater emotion regulation difficulties, which in turn were associated with higher internalizing symptom severity. Conclusions:Adolescents with ADHD exhibit clinically meaningful emotional profiles that are largely independent of core ADHD symptom severity. Emotion regulation difficulties represent a key mechanism linking resilience and internalizing symptoms. Profile-informed assessment incorporating brief measures of emotion regulation, resilience, and internalizing symptoms may enhance clinical formulation and help identify adolescents with silent emotional vulnerability who may otherwise be overlooked in routine care.
Background:Autism spectrum disorder (ASD) is a complex neurodevelopmental condition characterized by marked heterogeneity in cognitive, behavioral, and social functioning. Although oxytocin has been extensively investigated as a potential therapeutic agent for ASD, evidence regarding its clinical efficacy remains inconsistent and inconclusive. This systematic review and meta-analysis aimed to evaluate the therapeutic efficacy of intranasal oxytocin in improving core behavioral and social symptoms in individuals diagnosed with ASD by synthesizing evidence from randomized controlled trials. Methods:A systematic search of PubMed, Web of Science, and the Cochrane Library was conducted to identify peer-reviewed studies published up to February 16, 2025. Two independent reviewers performed study screening, data extraction, and critical appraisal of methodological quality and strength of evidence. Autism-related behavioral symptom scores were used as outcome measures. Meta-analyses were conducted using random-effects models. Results:Twelve randomized controlled trials encompassing a total of 733 participants met the inclusion criteria. Pooled results from the random-effects model indicated no statistically significant effect of oxytocin on social functioning outcomes (standardized mean difference [SMD] = -0.05, 95% confidence interval [CI]: -0.20 to 0.10; p = 0.54). Between-study heterogeneity was low (I2 = 4%; τ2 = 0.00). Exploratory subgroup analyses showed no significant differences across pre-specified moderators (all p > 0.05). Conclusions:The current body of evidence does not support a significant therapeutic effect of intranasal oxytocin on core behavioral symptoms in individuals with ASD. However, methodological limitations of the existing literature-including small sample sizes and heterogeneity in study design-limit the strength of conclusions that can be drawn regarding its potential clinical utility. Registration:The study has been registered on https://www.crd.york.ac.uk/prospero/ (registration number: CRD42024500088; registration link: https://www.crd.york.ac.uk/PROSPERO/view/CRD42024500088).
Background:Schizoaffective disorder (SZA) is a severe psychiatric condition characterized by overlapping affective and psychotic features; however, its sleep architecture remains poorly characterized. This systematic review and meta-analysis compared polysomnographic findings in drug-free patients with SZA with those of healthy controls (HC), patients with schizophrenia (SCZ), and patients with major depressive disorder (MDD). Methods:An extensive database search identified 40 studies. Nine case-control studies including 79 patients with SZA, 88 patients with SCZ, 79 HC, and 131 patients with MDD were included in the meta-analyses. Total sleep time, sleep efficiency, sleep latency, wake after sleep onset, and rapid-eye-movement (REM) and non-REM (NREM) sleep variables were analyzed. The primary outcome measure was the standardized mean difference (SMD). Data were analyzed using a random-effects model. Publication bias was assessed using Egger's regression test and funnel plot asymmetry. Results:Compared with HC, patients with SZA showed reduced total sleep time, increased sleep latency and wakefulness after sleep onset, reduced REM sleep duration, shortened REM latency, and reduced stage 4 sleep duration and percentage. Patients with SZA differed from those with MDD only in exhibiting increased sleep latency, whereas no significant differences were observed between patients with SZA and those with SCZ. Conclusions:Polysomnographic abnormalities in SZA demonstrate a general pattern of sleep disruption compared with HC, without clear differentiation from SCZ or MDD. Overall, current evidence does not support sleep architecture as a reliable biomarker for distinguishing SZA from related psychotic or affective disorders. These findings should be considered exploratory, given the small sample sizes, limited number of available studies, and substantial heterogeneity across studies. Further research is needed to determine whether specific sleep measures may better distinguish SZA from other psychiatric conditions.
