To establish a method for the simultaneous quantification of diazepam (DIA) and its active metabolites, nordazepam (NorD) and oxazepam (OXAZ), and provide a reference range for therapeutic concentrations in patients with alcohol dependence.

Simple and direct protein precipitation was used to extract the biological samples. Subsequent separation was performed on an Agilent XDB-C18 column (50 mm × 4.6 mm, 1.8 μm) with a column temperature maintained at 35 °C and a flow rate of 0.5 mL/min via ultra-high performance liquid chromatography–tandem mass spectrometry (UPLC-MS/MS). The mobile phase consisted of methanol–water containing 5 mM ammonium formate (75:25, v/v). Detection was conducted using electrospray ionization in multiple reaction monitoring modes: m/z 284.6→193.2 for DIA, m/z 270.5→140.1 for NorD, m/z 286.9→241.1 for OXAZ, m/z 289.6→198.2 for DIA-D5, m/z 275.5→140.0 for NorD-D5, and m/z 291.9→246.1 for OXAZ-D5. The linear response range for DIA, NorD, and OXAZ was 1–1500 ng/mL.

The key parameters of the bioanalytical method were validated: the average extraction recovery was 95%–101% (CV <6%); calibration curves exhibited good linearity over the concentration range (R² ≥0.99 for all analytes); accuracy was within 85%–115%; and intra-day and inter-day precision were satisfactory (CVs <15%). The concentrations of analytes in 26 routine therapeutic drug monitoring (TDM) samples from patients with alcohol dependence were determined.

We developed and validated a rapid, simple, and economic UPLC-MS/MS method for the quantification of DIA, NorD, and OXAZ in human serum. The method is well-suited for the determination of serum levels of DIA and its active metabolites in patients with alcohol dependence, and could be further applied to TDM and subsequent studies.

Transnasal Humidified Rapid-Insufflation Ventilatory Exchange (THRIVE) technique prolongs apnea duration. However, there is limited knowledge regarding the effectiveness and safety of THRIVE technique compared to conventional facemask ventilation during electroconvulsive therapy (ECT) in Chinese patients with major mental disorders.

Seventy adult individuals with major mental disorders (schizophrenia, n = 17; bipolar disorder, n = 25; major depressive disorder, n = 28) undergoing their first ECT session were assigned to either the THRIVE group (n = 35) or the facemask group (n = 35) based on the random sequence. The primary outcome was the lowest peripheral oxygen saturation (SpO₂) levels. Secondary outcomes included the incidence of oxygen desaturation, electroencephalogram seizure duration, stimulation dosage, mean arterial pressure (MAP), average SpO₂ levels, and heart rate (HR). Airway-related complications were documented within 24 hours following ECT.

In the THRIVE group, the lowest SpO₂ levels were notably higher than those in the facemask group (p < 0.05). Patients receiving THRIVE technique had consistently higher average SpO₂ levels than those receiving conventional facemask ventilation (p < 0.05). The incidence of oxygen desaturation in THRIVE group was lower than that in facemask group (p > 0.05). Moreover, significant differences between two study groups were not observed in terms of electroencephalogram seizure duration, stimulation dosage, MAP, and HR (all ps > 0.05). No airway-related complications were reported in either group.

In this preliminary open-label randomized controlled trial, the THRIVE technique appeared to be more effective than conventional facemask ventilation in preserving SpO₂ levels during ECT in major mental disorders, establishing itself as a safe and effective oxygenation alternative.

No: ChiCTR2400084318, https://www.chictr.org.cn/showproj.html?proj=229304.

Major depressive disorder (MDD) is associated with altered organization of functional brain networks. This study aims to evaluate the classification efficacy of three brain networks constructed by Pearson correlation (PC), sparse representation (SR), and group sparse representation (GSR) in distinguishing patients with MDD from healthy controls (HCs).

The present study involved the recruitment of 117 Chinese participants, comprising 61 individuals diagnosed with MDD and 56 HCs, all of whom underwent functional magnetic resonance imaging (fMRI). Brain time-series signals were extracted from 116 regions to construct whole-brain networks utilizing PC, SR, and GSR. A linear support vector machine (SVM) classifier with least absolute shrinkage and selection operator (LASSO) feature selection was trained using leave-one-out cross-validation (LOOCV) to optimize generalizability. An independent dataset of Chinese (124 first-episode drug-naïve MDD and 105 HCs) was utilized for additional validation.

Compared to the PC and SR, the GSR network yielded superior classification results, with an area under the receiver operating characteristic curve of 0.85, an accuracy of 0.81, and a sensitivity of 0.95. Similar results were observed in the independent MDD dataset. We identified 17 brain connections and 27 brain regions within the GSR network.

Our findings support the adoption of GSR-based brain networks as a robust tool for MDD diagnosis, challenging the conventional reliance on PC in neuroimaging research.

Deficits in visual working memory (vWM) represent a core cognitive impairment in schizophrenia; however, the dynamic spatiotemporal characterization of their underlying neural mechanisms remains unclear. The present study employed multivariate pattern classification (MVPC) and searchlight analysis to investigate neural signaling differences between patients with schizophrenia (PSZ) and healthy control subjects (HCS) during a vWM task.

A total of 46 participants (22 PSZ, 24 HCS) completed a change detection task comprising three conditions: two targets, zero distractors (2T0D); two targets, two distractors (2T2D); and four targets, zero distractors (4T0D). Contralateral delay activity (CDA) was extracted through event-related potential (ERP) analysis. MVPC was applied in the temporal dimension, while a searchlight approach was employed in the spatial dimension to decode memory load (2T0D/2T2D/4T0D) and memory side (left/right) information.

CDA amplitude was significantly reduced in the PSZ group, particularly in the 2T2D condition (p = 0.01), indicating that the scope and control of attention elicited comparable CDA amplitudes. MVPC analysis revealed that decoding accuracy in the PSZ group was significantly lower than in the HCS group during the time window of 93–652 ms (p_corrected < 0.05), suggesting diminished efficiency of neural information encoding during the delay period. The searchlight analysis identified the most pronounced decrease in decoding accuracy within the left parietal region in the PSZ group, consistent with the hypothesis of abnormal functional connectivity in the inferior parietal gyrus (IPG).

This study reveals the spatiotemporal dynamics of vWM deficits in schizophrenia, characterized by ERP decoding technology. It offers a novel target for the development of neuromarker-based cognitive interventions.

Schizophrenia, one of the most disabling mental disorders, affects approximately seven per 1000 individuals worldwide and has an estimated heritability of around 80%; however, its pathophysiology remains incompletely understood. The disorder has been linked to dysregulation of multiple neurotransmitter systems, including dopamine, serotonin, γ-aminobutyric acid (GABA), and glutamate. GABA, the primary inhibitory neurotransmitter in the central nervous system, is synthesized by the enzymes glutamic acid decarboxylase 67 (GAD67) and glutamic acid decarboxylase 65 (GAD65), encoded by the GAD1 and GAD2 genes, respectively. The genes (SST) and parvalbumin (PVALB) encode somatostatin and parvalbumin, which are characteristic markers of specialized GABAergic interneuron subpopulations involved in maintaining excitatory–inhibitory balance and supporting cortical circuit function. While reduced GAD1 expression has been consistently reported in schizophrenia, findings regarding GAD2 expression have been inconsistent.

In this study, we examined the expression of GAD1, GAD2, SST, and PVALB across three biological levels: postmortem brain tissue, peripheral blood samples, and patient-derived induced pluripotent stem cell (iPSC)-derived brain organoids, compared with healthy controls. The meta-analysis of brain tissue included seven independent datasets (295 samples: 151 individuals with schizophrenia and 144 healthy controls) and was conducted in accordance with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Patient-derived iPSC organoids were used to investigate early neurodevelopmental alterations, while a separate meta-analysis of peripheral blood gene expression included 293 samples (160 schizophrenia, 133 controls) to explore biomarker potential.

Both GAD1 and GAD2 were significantly downregulated in postmortem brain samples (meta-analytic effect sizes <–0.5) and in iPSC-derived organoids, supporting the hypothesis that reduced expression of these genes emerges prior to clinical onset and may contribute to disease development. In contrast, decreased expression of SST and PVALB was observed in brain tissue but not in organoids, suggesting that alterations in these interneuron markers may occur at later stages of the disease. Notably, reduced PVALB expression was also detected in peripheral blood samples, indicating its potential utility as a peripheral biomarker for schizophrenia.

Further studies are required to clarify the causal role of reduced GABAergic activity in schizophrenia pathogenesis and to evaluate the clinical relevance of PVALB expression for diagnosis and treatment monitoring.

To investigate differences in biological characteristics and factors associated with depressive disorder with or without nonsuicidal self-injury (NSSI) in adolescents.

This study enrolled adolescents aged 12–18 years, including patients with first-episode depression and healthy controls. According to the Diagnostic and Statistical Manual of Mental Disorders, patients were divided into an NSSI group and a non-NSSI group. Collected data included demographic variables (sex, age, years of education), psychological scale scores (Self-Rating Anxiety Scale [SAS], Self-Rating Depression Scale [SDS]), and biological indicators (folate, immunoglobulins, complement, inflammatory factors). Differences among the three groups were compared using analysis of variance, and correlates of NSSI were explored using regression analysis.

The study included 110 patients with first-episode depression and 55 healthy controls. Among the patients, 57 were classified into the NSSI group and 53 into the non-NSSI group. The following results were obtained: (1) The three groups differed significantly in sex, SAS and SDS scores, and levels of folate, complement 3 (C3), and interleukins 6 and 4 (p < 0.05). (2) Female sex and high C3 levels were positively associated with NSSI, whereas age and high folate levels were inversely associated with NSSI. High folate levels were a protective correlate in the non-NSSI group.

Demographic factors such as sex and age influence the development of depressive disorders with comorbid NSSI. In addition, levels of C3 and folate may be related to NSSI behavior in patients with depression.

Non-suicidal self-injury (NSSI) is on the rise in adolescent populations and its addictive profile, marked by frequent repetition, severe damage, and higher suicide risk, has raised broad concern. Childhood trauma is a key influencing factor that enhances emotional sensitivity and increases susceptibility to NSSI. Rumination, characterized by persistent negative thoughts, may mediate this association by amplifying emotional distress, as suggested by the emotional cascade model. Guided by the Interaction of Person–Affect–Cognition–Execution (I-PACE) model, this study employed network analysis to investigate the interactive associations among childhood trauma, rumination, and NSSI addiction in adolescents, aiming to identify core and bridge symptoms.

We enrolled 1169 adolescents with NSSI and collected data using demographic questionnaires along with the Ottawa Self-Injury Inventory, Childhood Trauma Questionnaire, and Ruminative Responses Scale. Undirected network and Bayesian network analyses were applied to examine the complex associations among symptoms and mediation analysis was performed guided by the directed acyclic graph structure.

By integrating both directed and undirected network models, symptom rumination and emotional abuse were identified as central nodes influencing the addictive nature of self-injury. Mediation analysis supported the pathway suggested by the directed acyclic graph (DAG), showing that symptom rumination mediated the relationship between emotional abuse and NSSI addiction. Network comparison further indicated that this link between self-injury addiction and symptom rumination was stronger in the addiction group than in the non-addiction group.

In Chinese adolescents, timely identification and intervention targeting rumination on emotionally abusive experiences may reduce the onset and persistence of NSSI addiction.

Late-onset depression (LOD), particularly when accompanied by cognitive impairment, represents a significant risk factor for dementia. Prevailing perspectives emphasize that cognitive impairment arises from interactions among multiple brain regions. However, current approaches to identifying brain network patterns associated with cognitive impairment largely rely on group-level analyses with multiple-comparison corrections, which may obscure complex and interconnected relationships between brain regions. Our previous research demonstrated that alterations in brain network properties in patients with LOD are closely associated with cognitive function. We therefore hypothesised that aberrant interactions among multiple brain regions in LOD lead to changes in network properties and subsequent cognitive dysfunction.

This study aimed to investigate the interregional brain interactions underlying cognitive impairment in LOD by leveraging the robust interpretability of neural network models. Specifically, we sought to: (1) develop a neural network model of LOD-related cognitive impairment based on brain network properties; and (2) apply a reverse correlation approach to identify connectivity features associated with cognitive impairment in LOD.

No statistically significant differences were observed in tthe structural network properties when comparing the LOD and control participant groups across various thresholds. Using a neural network–based reverse correlation method, the most prominent differences were identified in the inferior, middle, and anterior regions of the left temporal pole when comparing patients with LOD with and without mild cognitive impairment (MCI).

Alterations in the internal structure of the temporal lobe may represent potential anatomical biomarkers for the early prediction of Alzheimer’s disease, providing novel insights into the pathophysiological mechanisms underlying LOD-related MCI. The research framework proposed in this study effectively addresses the challenge of detecting subtle intergroup anatomical differences in studies with limited sample sizes. Moreover, the reverse correlation approach is not restricted to multilayer neural networks; as machine learning models become increasingly powerful and accessible, this method offers a practical and interpretable alternative for exploratory neuroimaging research.

Suicide ideation (SI) is a critical concern, and understanding its neurocognitive underpinnings is essential for improved risk assessment. This study investigates altered neurocognitive processing during face recognition in individuals with depression and SI, utilizing a multimodal approach combining eye-tracking, electroencephalography (EEG), and deconvolution modeling.

Eye-tracking and EEG data were recorded during face recognition tasks in individuals with depression, with and without SI. We analyzed visual attention patterns (fixation durations, saccadic velocities) and event-related potentials to emotional stimuli. Deconvolution analysis separated microsaccade-related activities (like regression-based event-related potential (rERP) and regression-based fixation-related potential (rFRP)).

Individuals with SI exhibited attentional biases toward emotional faces, characterized by shorter first fixation durations and faster saccadic velocities. Reduced rERP amplitudes in response to surprise and decreased rFRP amplitudes during sad conditions were also observed, suggesting altered neural responses. Integrating eye-tracking and EEG data (the area under the curve (AUC) = 0.771) improved the accuracy of detecting SI compared to eye-tracking alone (AUC = 0.643).

These findings provide novel evidence for altered neurocognitive processing of emotional faces in individuals with depression and SI. The multimodal approach highlights the potential of combining eye-tracking and EEG measures as biomarkers for identifying individuals at risk. Future research should focus on larger, more diverse samples and longitudinal designs to validate these findings and translate them into clinical applications.

This cohort study examined changes in cognitive outcomes, subjective memory, and depressive symptoms in an understudied area: electroconvulsive therapy (ECT) delivered in a naturalistic ambulatory setting with a heterogeneous, clinically complex sample of individuals with mixed mood disorders.

Participants were adults (mean age = 45.7 years; female gender = 69%) receiving ambulatory ECT for a major depressive episode (Major Depressive Disorder = 81.4%; Bipolar Spectrum Disorder = 18.9%); 62.9% had at least 1 co-occurring mental health diagnosis. Clinical and cognitive assessments were completed at baseline (n = 100), mid-ECT (n = 94), 2–4 weeks (n = 64), 6-months (n = 34), and 12-months (n = 19) post-ECT. Neurocognitive performance was assessed using the Repeatable Battery for Assessment of Neuropsychological Status® (RBANS) at all timepoints, except mid-ECT and subjective memory was assessed using the Squire Subjective Memory Questionnaire (SSMQ).

Overall, cognitive performance was lower than expected compared to premorbid estimates at baseline but did not significantly worsen following ECT (p > 0.05), with the exception of a transient decline in verbal fluency scores. Patients endorsed elevated subjective memory complaints before and after ECT, which differed by treatment response as indicated by a significant Time by Response Group interaction p = 0.039. There were significant main effects of time in both ‘Responders' (≥50% improvement in Beck Depression Inventory [BDI-II] score post-ECT), p < 0.001 and ‘Non-Responders' (<50% improvement in BDI-II) p = 0.021. Within group, after controlling for multiple comparisons, there was a clear trend for SSMQ scores to improve across most time points in the ‘Responder' group, but subjective memory declined and remained around baseline level in the ‘Non-Responder' group across follow-up. In the sample as a whole, rapid reduction in BDI-II scores from baseline to mid-ECT predicted rapid improvement in SSMQ scores, p = 0.013.

Clinically complex adults referred to ECT for depression presented with prominent memory concerns and performed below expectation compared to their estimated premorbid cognitive functioning at baseline. Naturalistic delivery of ECT did not appear to be associated with prolonged adverse cognitive outcomes; however, subjective memory concerns and below-expected cognitive performance persisted during follow-up. Treatment response impacted subjective memory outcomes, with only ‘Responders' endorsing slightly reduced, though still persistent, subjective memory concerns following ECT. Conclusions on the long-term impacts of ECT are tempered by the high lost to follow up (LTFU) rate observed across follow-up assessments (66% LTFU at 6-months, 81% LTFU at 12-months). Nonetheless, these findings emphasize the need to address subtle cognitive deficits and memory complaints that persist following ECT, even in individuals demonstrating clinical improvement.

Eating disorders (EDs) in adolescence are associated with marked emotional difficulties and broad functional impairment. The objective of this study was to examine the relationships among alexithymia, resilience, internalizing symptoms (anxiety and depression), and functional impairment in adolescents with EDs.

A cross-sectional, case-control study included 51 adolescents diagnosed with EDs according to Diagnostic and Statistical Manual of Mental Disorders, 5th Edition criteria (primarily anorexia nervosa, bulimia nervosa, and binge eating disorder) and 57 matched controls. Adolescents completed self-report measures assessing alexithymia, resilience, and internalizing symptoms, and parents reported on functional impairment.

Adolescents with EDs showed significantly greater functional impairment at both global and subdomain levels, along with higher levels of depressive and anxiety symptoms, higher alexithymia scores, and lower resilience than did controls. Difficulty describing feelings (DDF) was the only variable significantly associated with ED group membership. Within the ED group, functional impairment was positively correlated with depressive symptoms, anxiety symptoms, DDF, and difficulty identifying feelings (DIF), and was negatively correlated with resilience. Depressive symptoms were significantly associated with functional impairment, and mediation analyses indicated that the association between DIF and global functional impairment was statistically mediated by depressive symptoms.

These findings suggested that adolescents with EDs experience widespread functional difficulties, with depressive mood, exacerbated by challenges in emotion identification, potentially contributing to these impairments.

The aim of this study was to examine whether social media use motives mediate sex differences in social media addiction.

Three hundred adults (50.0% women; mean age = 39.28 years, standard deviation = 10.91) in South Korea completed the Social Network Site Use Motives Scale–Revised and the Bergen Social Media Addiction Scale.

Sex differences were found in social media addiction; that is, women reported higher levels of social media addiction than men. In addition, coping motives partially explained the sex differences in social media addiction. Although indirect effects were also observed for enhancement and pastime motives, the effects were not statistically significant after correction for multiple comparisons.

The findings indicate that women are more vulnerable to social media addiction than men, due in part to a difference in coping motives. Thus, interventions targeting coping motives may effectively reduce the risk of social media addiction among Korean adult women.

Adolescent smartphone overuse is associated with physical inactivity and mental health problems, such as anxiety. However, few studies have analyzed these factors jointly using both linear and non-linear methods. This study aimed to predict smartphone addiction using physical activity and mental health indicators from the 2020 and 2023 Korea Youth Risk Behavior Survey, applying Least Absolute Shrinkage and Selection Operator (LASSO), multiple machine learning models, and SHapley Additive exPlanations (SHAP) analysis.

A total of 86,744 adolescents were classified into general (n = 63,963), potential risk (n = 20,383), and high-risk (n = 2398) smartphone user groups. For the binary classification, general users were compared with combined-risk users. Twelve key predictors were selected using LASSO. Logistic Regression, Random Forest, Extreme Gradient Boosting (XGBoost), and Light Gradient Boosting Machine (LightGBM) models were implemented with Synthetic Minority Over-sampling Technique balancing; SHAP was used to compare variable importance across models.

LASSO identified moderate physical activity (β = –0.156), strength physical activity (–0.149), loneliness (0.144), smartphone usage time (0.085), and anxiety (0.078) as major predictors. Random Forest and Logistic Regression showed the best recall (0.63 and 0.60); LightGBM had the highest accuracy (0.726). It also achieved the highest Area Under the Receiver Operating Characteristic Curve (AUROC) (0.7108); XGBoost showed the lowest AUROC (0.5621). SHAP consistently ranked anxiety and smartphone usage time as the top predictors, with sleep and physical activity showing variable importance.

Anxiety and smartphone usage time were consistently dominant predictors. Physical activity variables contributed in some models but showed inconsistent importance. These findings highlight the central role of mental health, with behavioral factors playing a secondary, model-specific role.

Anxiety disorders are among the most prevalent psychiatric conditions during adolescence and are closely associated with maladaptive cognitive processes and impaired quality of life (QoL). However, the magnitude of these associations and the factors moderating them remain inconsistent across studies. This meta-analysis aimed to synthesize the available empirical evidence on the relationships between negative cognitions, QoL, and anxiety in adolescents, and to examine potential moderating variables.

In accordance with the PRISMA 2020 guidelines, a systematic literature search was conducted across PubMed, Embase, PsycINFO, Web of Science, Scopus, and grey literature sources. Eligible studies included adolescents aged 10–19 years and reported correlation coefficients between negative cognitions or QoL and anxiety. A total of 42 studies (N = 27,845) were included and pooled using random-effects models, with Fisher’s z-transformed correlation coefficients as the primary effect size. Moderator analyses examined the influence of measurement instruments, sample characteristics (clinical vs. non-clinical), age, gender distribution, and study quality.

Across 34 studies (n = 21,006), negative cognitions showed a moderate positive association with anxiety (r = 0.41, 95% CI: 0.37–0.45, p < 0.001). Across 26 studies (n = 15,784), QoL demonstrated a moderate inverse association with anxiety (r = –0.36, 95% CI: –0.41 to –0.31, p < 0.001). Substantial heterogeneity was observed for both outcomes (I² = 68% for negative cognitions and 72% for QoL). Moderator analyses revealed stronger associations in clinical samples (negative cognition–anxiety r = 0.47; QoL–anxiety r = –0.42) compared with school- or community-based samples. Gender distribution significantly moderated effect sizes, with studies including more than >60% female participants reporting stronger associations (negative cognition–anxiety r = 0.44; QoL–anxiety r = –0.39, both p < 0.05). Measurement instruments also influenced results: the Dysfunctional Attitude Scale yielded the strongest associations between negative cognitions and anxiety (r = 0.45, p < 0.001), whereas QoL–anxiety associations were most pronounced when assessed using the KIDSCREEN instrument (r = –0.39, p < 0.001). Age group and country income level did not significantly moderate associations, although slightly stronger correlations were observed among older adolescents (15–19 years) compared with younger adolescents. Sensitivity analyses and publication bias assessments supported the robustness of the findings.

Negative cognitions and reduced quality of life are robustly associated with anxiety in adolescents, particularly in clinical samples and in studies with a predominance of female participants. These findings provide strong support for cognitive–behavioral models of adolescent anxiety and underscore the importance of integrating cognitive restructuring with quality-of-life–enhancing strategies in prevention and intervention programs. Future longitudinal and cross-cultural research is needed to clarify causal mechanisms and to optimize mental health care for adolescents.

Schizophrenia primarily depends on pharmacotherapy, which has demonstrated limited efficacy in enhancing cognitive impairments. High-definition transcranial direct current stimulation (HD-tDCS) and computerized cognitive remediation therapy (CCRT) hold potential for improving cognitive impairments. This study aims to investigate the effects of combining HD-tDCS with CCRT on cognition and to explore the mechanisms of this approach in schizophrenia.

This is the protocol of a randomized controlled trial.

Schizophrenia patients will be randomly assigned to one of 4 groups: HD-tDCS + CCRT group (Group 1), HD-tDCS group (Group 2), CCRT group (Group 3), and a control group (Group 4). The central electrode will be personalized using magnetic resonance imaging (MRI)-guided localization in the medial prefrontal cortex (mPFC). CCRT includes 6 therapeutic modules and 10 distinct tasks. Both HD-tDCS and CCRT will be administered once daily, 5 days per week, for 4 consecutive weeks, culminating in a total of 20 sessions. Assessments will occur at baseline (T0), after 10 sessions (T1), after 20 sessions (T2), and after 6 months of follow-up (T3). The primary outcome measure is the change in cognition. We will employ multimodal MRI, serum concentrations of brain-derived neurotrophic factor (BDNF) and glial cell line-derived neurotrophic factor (GDNF) to explore the underlying mechanisms.

An involvement of mPFC and synaptic plasticity in response to HD-tDCS and CCRT is hypothesized.

The study will provide empirical evidence for the effectiveness of combined therapy at an individual level, explore its mechanisms, and may ultimately result in personalized medicine.

ChiCTR2500102731, https://www.chictr.org.cn/hvshowprojectEN.html?id=276964&v=1.0.

Major depressive disorder (MDD) has been increasingly associated with neuroinflammatory and neurovascular dysfunction. Claudin-5, a key tight junction protein essential for blood–brain barrier integrity, has an unclear role as a peripheral biomarker in MDD. This study examined serum Claudin-5 alongside systemic inflammatory indices—including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), the inflammation score (INFLA), and suicidal ideation in antidepressant-naive or medication-free (for at least three months) adult MDD patients.

73 antidepressant-naive or drug-free MDD patients and 74 age- and sex-matched healthy controls were enrolled. Depression severity and suicidality were assessed using the Hamilton Depression Rating Scale (HAM-D) and Beck Scale for Suicide Ideation (BSSI). Serum Claudin-5, C-reactive protein (CRP), and complete blood counts were measured, and inflammatory indices (NLR, PLR, MLR, INFLA) were calculated. Between-group comparisons, correlation analyses, and receiver operating characteristic (ROC) analyses were performed.

MDD patients showed significantly reduced Claudin-5 and elevated NLR, PLR, CRP, and INFLA scores compared with controls (all p < 0.05). Claudin-5 was not associated with symptom severity, suicidality, or inflammatory indices. ROC analysis for serum Claudin-5 indicated fair accuracy in distinguishing MDD from controls (AUC = 0.737) but limited value for predicting suicidal ideation (AUC = 0.628).

Reduced serum Claudin-5 in untreated MDD may indicate relatively stable endothelial alterations rather than acute, state-dependent changes. Although Claudin-5 alone had limited prognostic value for suicidality, inflammatory indices—particularly NLR and INFLA—showed stronger associations. Integrating vascular and immune biomarkers may enhance biological stratification and suicide risk assessment in depression and guide future multimodal studies.

Bipolar disorder (BD) is characterized by persistent cognitive deficits. These deficits contribute to functional impairment and often respond poorly to pharmacotherapy. Although deep transcranial magnetic stimulation (dTMS) has demonstrated antidepressant efficacy, there is limited knowledge about its cognitive effects and comprehensive clinical performance in BD. In this study, we assessed the cognitive outcomes, clinical efficacy, and safety of H1-coil dTMS in BD patients.

In this randomized, double-blind, sham-controlled trial, 100 inpatients with BD received 4 weeks of active or sham H1-coil dTMS. The MATRICS (Measurement and Treatment Research to Improve Cognition in Schizophrenia) Consensus Cognitive Battery (MCCB) was used to investigate the cognitive function, and the 17-item Hamilton Depression Rating Scale (HDRS-17) was used to assess depressive symptoms from baseline to week 4.

Both groups, active and sham dTMS, showed significant cognitive improvements across most domains (p < 0.05), with no statistically significant between-group differences (all p > 0.05). At the endpoint, the active dTMS group showed statistically significantly lower HDRS-17 scores and a higher response rate than the sham group (mean difference = 2.94, 95% CI [0.10, 5.78], p = 0.04); 50% vs. 24%; OR = 3.17, 95% CI [1.35, 7.44], p = 0.007). All treatments demonstrated a favorable safety profile, with only mild and transient adverse effects.

In patients with BD, active dTMS was well-tolerated and was associated with a higher response rate and statistically significant (albeit modest) lower depressive symptom scores compared to sham stimulation, without inducing cognitive adverse effects. However, no specific cognitive benefit beyond its antidepressant effect was established. Overall, these results indicate that dTMS has potential as an adjunctive treatment option for bipolar depression, particularly when medications are limited or poorly tolerated.

NCT06524505. Registered 23 July, 2024, https://clinicaltrials.gov/study/NCT06524505.