Bipolar Disorder

Urinary copper is linked to regional cortical volume reductions in adolescents with major depressive disorder.

Major depressive disorder (MDD) is highly prevalent among adolescents, but its neurobiological mecha...

The multilevel exploration test, a novel paradigm to measure exploratory behavior in depression animal models and the involvement of the PL-ZI circuit.

Diminished drive is one of the core symptoms of major depressive disorder (MDD) diagnosis, yet its u...

Recycling nickel-rich cathodes toward structural and functional circularity: a perspective.

The increasing use of nickel-rich (Ni ≥ 0.6) layered oxide cathodes in lithium-ion batteries creates...

Accelerated biological aging in bipolar disorder as determined by artificial intelligence-based electrocardiographic assessment.

BACKGROUND: Individuals with bipolar disorder (BD) are at increased risk for major adverse cardiovas...

Using Digital Phenotyping for Depression Screening in Community-Dwelling Older Adults: Bayesian Multilevel Hurdle Model Machine Learning Approach.

BACKGROUND: With the rapidly aging population, mental health among older adults has received growing...

Current themes of AI in mental health: Actionable evidence and guardrails for mood and anxiety care.

Currently, artificial intelligence (AI) is clinically relevant to mood and anxiety care, but the evi...

Heterogeneous pathways to depressive and anxiety disorders: A cluster-based predictive study in a nationwide longitudinal cohort.

BACKGROUND: Early prediction of depressive and anxiety disorders is challenging due to substantial h...

Dual-Atom Catalysts for Synergistic Adsorption and Adjustment of Reaction Kinetics of Polysulfides: Design Strategies, Characterizations and Mechanisms.

Lithium-sulfur (Li-S) batteries have been considered among the most promising next-generation batter...

Tracking Byproducts Lithium Methoxide in Li-Ion Batteries via Interface-Stabilized Perovskite Quantum Dots-Based Sensors.

Monitoring internal electrolyte decomposition byproducts is pivotal for the early warning of thermal...

Cross-Dataset Evaluation of an Automated Video-Based Model for Detecting Tardive Dyskinesia Using the Clinician's Tardive Inventory: Validation Study.

BACKGROUND: Tardive dyskinesia (TD) is a common, often underrecognized movement disorder resulting f...

Stacking-Dependent Interfacial Water Dynamics Govern the Aqueous Degradation of Layered LiCoO2 Cathodes.

Despite their high energy density, layered cathode materials suffer from instability in aqueous lith...

Identification of Mitochondrial Dysfunction-Related Candidate Biomarkers and Analysis of the Immune Cell Infiltration in Epilepsy.

Epilepsy is a severe neurological disorder with complex pathogenesis. Mitochondrial dysfunction (Mit...

Acoustics of depression.

BACKGROUND: The sound of speech reflects the speaker's mood in a way that may enable objective measu...

Machine Learning for Comparative Antidepressant Selection in Major Depressive Disorder: Systematic Review.

BACKGROUND: Major depressive disorder (MDD) affects approximately 1 in 6 adults during their lifetim...

Emulated trial of artificial intelligence use and subsequent depressive outcomes in a survey of US adults.

BACKGROUND: Generative artificial intelligence (AI) use has been suggested to have adverse mental he...

Developing a Clinical Prediction Model for Nonimprovement of Depressive Symptoms at Discharge After Treatment of Eating Disorders.

OBJECTIVE: Depressive symptoms are highly prevalent among people with eating disorders (ED). Althoug...

Quantitative scrutiny of biomass-derived battery electrodes: A strategic analysis.

The escalating demand for sustainable energy storage necessitates innovative battery materials beyon...

Machine learning-based differentiation of major depressive disorder and bipolar disorder using entropy-derived EEG biomarkers in drug-naïve patients.

Contribution of Longitudinal Mobile Health Measures in the Dynamic Track of Patients With Major Depressive Disorder: Multiple Centers, Prospective Cohort Study Using Functional Data Analysis and Machine Learning.

BACKGROUND: Continuous follow-up for patients with major depressive disorder (MDD) is essential for ...

Predicting depressive and anxiety symptoms among Lebanese and Syrian adults in a suburb of Beirut, Lebanon, during concurrent crises: nested cross-sectional study.

OBJECTIVE: This study aimed to develop prediction models for symptoms of poor mental health among Le...

Determinants and Machine Learning Prediction of Subtherapeutic Sodium Valproate Concentrations in Epilepsy Management in Xinjiang, China.

BACKGROUND AND OBJECTIVE: Valproic acid is a classic antiepileptic drug; however, it is characterize...