Bipolar Disorder

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 battery systems owing to their exceptionally high theoretical energy density, low cost, and environmental friendliness. However, their development continues to be hindered by the dissolution and sluggish conversion kinetics of the intermediate polysulfides. Efficient catalysts have shown significant poten...

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 runaway in lithium-ion batteries yet remains a formidable challenge due to the harsh chemical environment. Herein, we engineer a robust electrochemical sensor based on a CsPbBr3/Al2O3@EVA heterojunction architecture to achieve real-time, in situ tracking of lithium methoxide (CH3OLi) evolution. Thr...

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 from long-term antipsychotic use, yet its detection...

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 lithium-ion batteries. LiCoO2, as a prototypical layer...

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 (MitD) is increasingly recognized as a key driver of e...

Non-traditional metabolic indices predict incident circadian syndrome in middle-aged and older Chinese adults: a nationwide prospective cohort study and machine learning analysis.

BACKGROUND: Circadian syndrome (CircS) augments the conventional metabolic syndrome construct by adding disturbed sleep and depressive features. Wheth...

Acoustics of depression.

BACKGROUND: The sound of speech reflects the speaker's mood in a way that may enable objective measurement of depression from speech audio recordings....

TF-MCL: Time-frequency fusion and multi-domain cross-loss for self-supervised depression detection.

In recent years, there has been a notable increase in the use of supervised detection methods of major depressive disorder (MDD) based on electroencep...

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 lifetime, yet antidepressant selection relies predominant...

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 health consequences but a causal relationship has no...

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). Although at the group level, depressive symptoms tend to ...

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

The escalating demand for sustainable energy storage necessitates innovative battery materials beyond conventional systems. Biomass-derived carbons an...

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 treatment decisions and a better prognosis. There ...

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 Lebanese adults and adult Syrian refugees or migrant...

Using the Novel Translation Validity Index to Evaluate GenAI Translations of the Patient Health Questionnaire-9 Into Nine Languages.

Background and Purpose: Depressive symptoms affect 280 million people worldwide. Although generative artificial intelligence (GenAI) tools are increas...

Construction of a prediction model for depression risk in elderly patients with chronic obstructive pulmonary disease based on machine learning algorithms and analysis of influencing factors.

Patients with chronic obstructive pulmonary disease (COPD) are at a high risk of depression, which not only accelerates disease progression but also s...

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 characterized by a narrow therapeutic window, limited safety m...

Influences of adverse childhood experiences and weekly pregnancy stress on postpartum mental health symptoms: a machine learning examination.

PURPOSE: The goal of this study was to understand how the timing, level, and fluctuation of pregnancy stress affected women's postpartum mental health...

Prenatal serotonin reuptake inhibitor exposure and maternal depression symptoms are associated with altered fetal brain and placental development.

Maternal mental health is associated with fetal neurodevelopment. Identifying effective treatments for maternal psychiatric conditions is a public hea...