Suicide claims >720,000 lives annually; major depressive disorder (MDD) carries the highest population-attributable risk. Suicidal ideation (SI), the most proximal modifiable predictor of attempt,is poorly captured by subjective scales. We developed and internally validated machine-learning models to detect SI in Chinese MDD in-patients using routine electronic medical records.

This study aimed to develop and internally validate machine-learning (ML) models that exploit routine electronic medical record (EMR) data to identify recent SI in Chinese in-patients with MDD.

A retrospective cohort of 721 in-patients with major depressive disorder (MDD), including 399 with suicidal ideation (SI-positive), was recruited from the Fourth People's Hospital of Hefei between January 2020 and August 2023. The dataset was stratified into training (70%) and test (30%) sets. All preprocessing steps (median imputation and Z-score normalization) and Boruta feature selection were performed exclusively on the training set using R software (version 4.4.2), with multicollinearity removed for variables with a variance inflation factor (VIF) > 5 or a pairwise Pearson correlation coefficient |r| > 0.75. Six machine learning algorithms-random forest (RF), logistic regression (LR), LightGBM, support vector machine (SVM), K-nearest neighbor (KNN), and XGBoost-were trained using GridSearchCV combined with 10-fold stratified cross-validation, with model fine-tuning via the class_weight = 'balanced' parameter. Model performance was evaluated on the independent test set using multiple metrics, including the area under the receiver operating characteristic curve (AUC), area under the precision-recall curve (PR-AUC), accuracy, sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV). SHAP analysis, implemented in Python (version 3.12), was used to enhance model interpretability. Stratified subgroup analysis (stratified by sex and age) and sensitivity analysis (comparing the optimal RF model with the traditional LR baseline model via DeLong's test) were conducted to verify the robustness and superiority of the proposed model.

Random Forest achieved the best discrimination (AUC 0.857) and maintained stable discrimination across sexes (AUC = 0.843 in females and 0.822 in males), demonstrating higher sensitivity in females (0.883) and higher specificity in males (0.900).Top risk features: Compared with SI-negative patients, SI-positive patients were predominantly male (74.4% vs. 53.7%), married (80.7% vs. 63.4%), and had a lower educational level (83.7% vs. 29.5% without higher education). Furthermore, both their current age and age at depression onset were significantly greater (all P < 0.001).

ML models, especially Random Forest, can effectively identify recent SI risk in Chinese MDD patients using readily available clinical data.

This investigation sought to systematically evaluate the independent and synergistic effects of chronic exposure to atmospheric pollutants and household solid fuel consumption on the likelihood of depressive and anxiety-related symptoms.

Logistic regression models and the qg-computation model were performed to assess the individual and combined effects of ambient and indoor air pollution with depressive and anxious symptoms risk.

Long-term exposure to PM₁, PM_2.5, and PM₁₀ and indoor solid fuel use for cooking and heating were all positively associated with a higher risk of anxious and depressive symptoms (P < 0.05). Besides, each 10 μg/m³ increment in NO₂ was significantly associated with anxious symptoms risk (OR = 1.06, 95% CI: 1.01, 1.11). Both PM₁ and PM_2.5 contributed to anxious and depressive symptoms, with PM₁ exerting a more pronounced effect. There were additive interaction effects of solid fuel use for heating with PM₁₀ exposure on anxious (RERI = -0.96, 95% CI: -1.27, -0.65) and depressive symptoms (RERI = -0.43, 95% CI: -0.74, -0.13) risks, as well as solid fuel use for heating with NO₂ exposure on anxious symptoms (RERI = -0.45, 95% CI: -0.75, -0.15) risk. Moreover, heating fuel altered the effects of PM_2.5 and PM₁₀ on the risk of anxious symptoms, as well as the effect of PM₁₀ on the risk of depressive symptoms, while cooking fuel altered the effect of exposure to PM_2.5 on the risk of depressive symptoms.

Our study emphasizes the importance of addressing indoor solid fuel use and strengthening air quality management to safeguard public mental health.

The neuropeptide oxytocin (OXT) is thought to modulate important aspects of prosocial behavior. In a seminal paper, Kosfeld et al. (2005) reported that intranasally administered OXT modulated trusting behavior in an economic trust game. Several attempts to conceptually replicate these findings yielded mixed results, which might be partly due to small sample sizes that can reduce the ability to detect, or reject, meaningful effects. We performed a large-scale replication (n = 211) of Kosfeld et al. (2005) with specific attention for small effects and subpopulations whose trusting behavior may be sensitive to OXT manipulations. Moreover, we conducted a pooled analysis of the two largest, recent, replications by merging our data with data from Declerck et al. (2020; n = 321). We found no evidence that intranasal OXT administration increases trusting behavior, neither in our data nor in the pooled dataset. While equivalence testing in our dataset was inconclusive, equivalence testing in the pooled dataset (n = 532) indicated that the effect of OXT administration on trusting behavior lies within a minimal range of effects, suggesting that the effect is too small to be of interest to (most) lab-based studies due to feasibility constraints of collecting data from larger samples required to reject smaller effect sizes. In addition, we found no evidence that OXT administration effects on trusting behavior are influenced by baseline trust, reward sensitivity, and punishment sensitivity. Our findings invite a critical evaluation of current methodology in OXT research and a reconsideration of OXT's involvement in social behaviors and beyond.

Obsessive-Compulsive Personality Disorder (OCPD) is marked by a pervasive preoccupation with orderliness, perfectionism, and control, often overlapping with Obsessive-Compulsive Disorder (OCD) in terms of rigid and repetitive behaviors. While OCD behaviors are ego-dystonic and confined to specific areas of life, OCPD behaviors are ego-syntonic and affect overall functioning. Although the relationship between OCD and OCPD has been object of investigation, the impact of OCPD comorbidity on OCD remains underexplored. This study examines potential clinical differences between OCD patients with and without comorbid OCPD, with a specific focus on duration of untreated illness (DUI).

A sample of 300 patients diagnosed with OCD was consecutively recruited from a OCD Tertiary Clinic. Patients with OCD were divided into two groups: those with OCD-only and those with comorbid OCPD. Sociodemographic and clinical variables were collected and compared between groups. An additional age- and sex-matched sensitivity analysis was performed to further assess the robustness of the main findings.

Out of the 300 patients with OCD, 18.6% (n = 56) were also diagnosed with OCPD. The age at first pharmacological treatment was significantly higher in the OCD with OCPD group compared to the OCD-only group (32.16 ± 17.06 years vs. 27.48 ± 11.17 years; p < .05). The DUI was significantly longer in the OCD with OCPD group (9.2 ± 12.4 years vs. 6.10 ± 8.06 years; p < .05). These findings remained significant after controlling for potential confounding by age and sex through a 1:1 matched sensitivity analysis.

Almost one out of five patients with OCD has comorbid OCPD. The ego-syntonic nature of OCPD beliefs may contribute to treatment delays, underscoring the importance of early identification of this specific comorbidity in OCD patients to improve treatment outcomes.

Recent functional near-infrared spectroscopy (fNIRS) studies have shown reduced left cortical hemodynamic responses in major depressive disorder (MDD), suggesting a promising neuroimaging biomarker for diagnosis. However, given MDD's pronounced clinical heterogeneity and widespread cognitive impairments, reliance on a single task-based activation index may be insufficiently sensitive. Therefore, this study aims to combine three Chinese verbal fluency tasks (VFTs) with distinct cognitive demands to delineate MDD-related aberrant neural response patterns and to derive more comprehensive, robust fNIRS biomarkers for objective diagnostic classification.

This study recruited 60 patients with MDD and 60 demographically matched healthy controls (HCs). Hemodynamic changes in the left cortex were measured using a 48-channel fNIRS during the three VFTs. Demographics information, clinical characteristics and VFT performance were also collected.

Each Chinese VFT variant elicited a different pattern of left cortical activation. Relative to HCs, patients with MDD exhibited significantly reduced activation in both the left dorsolateral and medial prefrontal cortices. Moreover, integrating neural activation indices across all three VFTs substantially enhanced the discrimination between MDD patients and HCs compared with any single task.

In light of the heterogeneous nature of depression and its broad impact on multiple cognitive domains, combining multiple cognitive paradigms may develop richer and more reliable fNIRS-based biomarkers for the identification of MDD.

Burnout is highly prevalent and impacts health and well-being. A lack of formal diagnosis and definition criteria has resulted in uncertainty regarding measurement and appropriate interventions. Neurofeedback (NF) training has shown potential in modulating patterns of stress and producing neural changes, however, its application to burnout is still in question.

This systematic review aimed to explore the impact of NF training on the management of burnout.

This systematic review was pre-registered on PROSPERO and adhered to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA).

The search yielded a total of N = 178 articles. After screening, a total sample of N = 6 studies was included in the final review that met the study's inclusion and exclusion criteria. Results showed NF training improved negative characteristics associated with burnout, especially when combined with other intervention methods. However, a lack of specificity was found in most study designs and intervention protocols with inconsistent burnout measures and sampling bias.

Specific recommendations for the field were identified including consistency in study designs and NF training protocols; definition of burnout and measures used; and increasing sample representations to include diverse populations and contexts.

Temporal lobe epilepsy (TLE) impacts multiple brain networks. Aberrant functional connectivity has been demonstrated in resting-state networks (RSNs) that mediate higher brain functions in TLE. This study aimed to identify the reproducible patterns of altered functional connectivity in TLE in a large, international cohort through ENIGMA-Epilepsy.

Resting-state functional MRI datasets from nine centers across North America, South America, Europe and South Africa, including 442 people with TLE and 387 healthy adults, were analyzed. We examined group differences in whole-brain connectivity in patients compared to controls in seven major RSNs. We also investigated whole-brain connectivity maps for key nodes within the default mode network (DMN). Furthermore, the associations between connectivity patterns and clinical variables were assessed.

We found lower within-network connectivity scores (13.6% on average) and higher between-network connectivity scores (129% on average) in non-limbic RSN in TLE. This pattern was reproducible across all seven sites and most robust for DMN and visual networks. Patterns of connectivity were not associated with age of seizure onset or disease duration and were mostly similar in patients with left and right TLE with a few exceptions; isolated regions of high connectivity in left TLE and lower connectivity in right TLE compared to controls.

We show strong evidence of lower connectivity within most RSNs and higher connectivity outside of these networks that was highly consistent across geographically diverse sites, demonstrating the robustness and generalizability of our findings. The findings demonstrate a consistent disruption of network organization in TLE that may underlie cognitive co-morbidities and seizure propagation patterns observed in this patient population.

In this international ENIGMA-Epilepsy study, resting-state fMRI data from 442 individuals with TLE showed reduced connectivity within major resting-state networks (about 14% lower) and markedly increased connectivity between networks (about 129% higher), compared to 387 healthy controls. These patterns were highly reproducible across sites. Connectivity alterations were not related to age of onset or disease duration and were largely similar across left and right TLE, aside from small, region-specific differences. Overall, the study demonstrates a robust, widespread reorganization of brain network connectivity in TLE, which may help explain associated cognitive difficulties and seizure spread.

Despite its status as the gold standard for treating fear and anxiety, exposure therapy leaves room for optimization. Clarifying and testing the clinical relevance of proposed mechanisms may enhance outcomes. This randomized controlled trial (DRKS00031220) examined the effects of four psychological strategies aimed at facilitating exposure outcomes in individuals with clinically significant fear of flying due to specific phobia or agoraphobia (N = 519).

All participants underwent a standardized large-group one-session treatment (LG-OST) including psychoeducation, debriefing, and an in vivo exposure flight. Participants were randomized to one of four conditions targeting distinct mechanisms: peer support (SUPPORT), self-efficacy (SELF-EFFIC), expectancy violation (EXPECT), or coping with bodily fear symptoms (COPE). These mechanisms were reinforced prior and during paralleled exposure flights, conducted in separate aircraft per condition.

Across all conditions, LG-OST led to substantial symptom reduction short- and long-term. Fear ratings halved, over 50% flew again within the 6-month follow-up interval, and ∼70% no longer met diagnostic criteria. However, no condition yielded superior outcomes. While manipulation checks confirmed partial activation of target mechanisms (e.g., greater perceived peer support in SUPPORT, increased use of breathing techniques in COPE), these effects did not translate into differential clinical benefits.

Findings support the efficacy and scalability of LG-OST, while suggesting that tailoring preparatory strategies to specific mechanisms may have limited added value. They also highlight the need to advance mechanistic research to better understand the intertwined processes underlying exposure success. Future work should focus on improving accessibility and sustaining long-term gains.

The immunopathogenesis of autoimmune neurological syndromes (AINS) with antibodies against the 65 kDa isoform of glutamic acid decarboxylase (anti-GAD65 AINS) remains poorly understood. To elucidate underlying disease mechanisms and identify relevant cell populations, we performed single-cell RNA and immune repertoire sequencing of cerebrospinal fluid (CSF) and peripheral blood mononuclear cells (PBMCs) of eight anti-GAD65 AINS individuals compared to eight noninflammatory controls. In addition, PBMCs from 19 anti-GAD65 AINS individuals and 20 healthy controls were analyzed by multidimensional flow cytometry, and brain tissue specimens from four anti-GAD65 AINS individuals were examined histologically. We detected higher frequencies of stem cell-like memory T cells (TSCM) within the PBMCs and a marked enrichment and clonal expansion of activated CD4⁺ TSCM in the CSF of anti-GAD65 AINS individuals. Expanded T cells exhibited increased expression of proinflammatory genes. Histological analyses confirmed intraparenchymal CD8⁺ TSCM in three of four anti-GAD65 AINS individuals and rare meningeal/intraparenchymal CD4⁺ TSCM in one person. Although CSF B cell receptors (BCRs) displayed little to no clonal expansion, recombinant expression of 40 CSF BCRs revealed that 25% were GAD65-reactive with increased somatic hypermutations compared to non-GAD65-reactive BCRs. These findings further support the concept of an antigen-specific intrathecal immune response. In summary, we characterize the immune landscape of anti-GAD65 AINS at single-cell resolution and identify clonally expanded TSCM with cytotoxic properties as a hallmark of this disease.