Bipolar Disorder

Predicting longitudinal depressive symptom trajectories among older Chinese adults with chronic health conditions: An interpretable machine learning study.

OBJECTIVE: This study leveraged interpretable machine learning (ML) to map heterogeneous trajectories of depressive symptoms in Chinese older adults with chronic diseases, aiming to develop an interpretable, prediction-oriented framework for personalized mental health interventions. METHODS: We analyzed four-wave longitudinal data from 5492 participants in the China Health and Retirement Longitudi...

Combined Unipolar and Bipolar Voltage Mapping at Redo Ablation After Cryoballoon Pulmonary Vein Isolation: Associations With Subsequent Arrhythmia Recurrence.

Post-traumatic Psychopathology and Cardiovascular Risk: A Danish Case-Control Study of Sex-Specific Associations.

BACKGROUND: There is increasing recognition that trauma exposure and related psychiatric consequences predict cardiovascular disease risk. However, mo...

Integration of network pharmacology, molecular docking, and molecular dynamics simulation to elucidate the mechanism of Psychotria rubra in depression treatment.

Depression is a chronic mental disorder with high disability and mortality rates, affecting approximately 95 million individuals in China alone. The l...

A Clinical AI-Based System (MoodMon) for Affective Disorders: Algorithm Development and Validation.

BACKGROUND: Psychiatry needs objective technological tools to address global staffing shortages, stigma, and other systemic challenges. An AI-based sy...

Emotionally engaged speech reveals acoustic markers of depression and suicide risk.

BACKGROUND: Major depressive disorder exists along a continuum, from health through remission to active depression. Differentiating these states remai...

Low operating power, low activation threshold, and diverse all-optical nonlinear activation based on a PPLN resonator.

Optical neural networks (ONNs) are considered next-generation physical implementations of artificial neural networks, yet their capabilities are const...

Unsupervised Identification of Population Clusters With Distinct Low Back Pain Profiles.

BACKGROUND CONTEXT: Low back pain (LBP) is a leading cause of disability worldwide, yet population-level stratification of LBP risk remains limited. U...

Digital and Biomarker-Based Monitoring for Schizophrenia-Treatment Adherence.

BACKGROUND: Nonadherence to antipsychotics affects nearly half of patients with schizophrenia, leading to rehospitalization, suicidality, and reduced ...

State-Specific Segmental Abnormalities of White Matter Structure and Function in Pediatric Bipolar Disorders.

OBJECTIVE: White matter (WM), as the critical infrastructure for neural communication, is implicated in pediatric bipolar disorder (PBD) pathophysiolo...

Transient Elevation and Subsequent Normalization of Brain Age Gap During the Postpartum Period.

The postpartum period involves substantial brain changes, but whether these represent pathological aging or adaptive plasticity remains unclear. We ap...

Bioinformatics Analysis of the Diagnostic Value of Copper and Zinc Metabolism-Related Genes in Major Depressive Disorder: An In Silico Multi-Cohort Study.

This study aimed to identify copper and zinc metabolism-related genes as potential diagnostic biomarkers for major depressive disorder through an inte...

The design and optimization of a chitosan-based lamotrigine-loaded intranasal mucoadhesive nanomicelle solution using response surface methodology and artificial neural networks.

The study aimed to develop and optimize chitosan-based mucoadhesive nanomicelles for intranasal delivery of lamotrigine (LTG), to enhance epilepsy tre...

Early Retinal UCHL1 Dysregulation Coupled With Synaptic Loss Reflects Alzheimer's Disease Severity.

Synaptic dysfunction is a major driver of cognitive decline in Alzheimer's disease (AD), yet its extent and molecular basis in the retina remain poorl...

Silicon-based anode materials for high-capacity lithium-ion batteries: recent advances and challenges.

Silicon is a promising anode material for high-energy-density lithium-ion batteries because of its high theoretical capacity, low operating potential,...

MIDAS: A multimodal interview-based framework for depression assessment from clinical interviews.

Automated depression assessment from clinical interviews is a challenging intelligent healthcare task because depressive states are reflected not only...

Identification of suicidal ideation in major depressive disorder: A machine learning approach with multimodal digital features.

Current detection models for suicidal ideation (SI) among depressed patients have primarily relied on clinical and biological features. This study aim...

Depression prediction and key factors: A comparative analysis of logistic regression and machine learning models.

OBJECTIVES: Factors associated with depression were explored in this study through logistic regression, and predictive performance was compared with v...

MSPPGT: A Multi-Scale Pyramid Pooling-Based Graph Transformer Framework for Neuropsychiatric Disorder Diagnosis.

Graph Neural Networks (GNNs) model functional connectivity patterns between brain regions via neighborhood information aggregation. However, most GNN ...

Edge-centric brain connectomes reveal two molecularly distinct neurobiological subtypes of adolescent major depressive disorder.

Adolescent major depressive disorder (MDD) is a heterogeneous disorder that complicates diagnosis and treatment. However, the mechanisms underlying th...