Bipolar Disorder

Developments in the design and therapeutic applications of GSK3β inhibitors.

Glycogen synthase kinase-3β (GSK3β) has emerged as one of the most thoroughly validated therapeutic targets in modern drug discovery, with dysregulation implicated in neurodegenerative diseases, metabolic disorders, cancer, psychiatric conditions, and inflammatory pathologies. This review provides a comprehensive and critical overview of recent advances in GSK3β inhibitor design, encompassing ATP-...

Tackling complexity in crystal structure determination of metal organic compounds using machine learning interatomic potentials.

We integrate ab initio crystal structure prediction with universal machine learning interatomic potentials (UMA and Orb-v3) to determine challenging metal organic compound structures. Our framework successfully resolves the previously unknown, technologically significant crystal structures of lithium phenolate, sodium cyclohexanolate, and lithium-benzimidazol-2-one, accelerating materials developm...

Real‑World Clinical Characterization of Major Depressive Disorder and Treatment‑Resistant Depression Supported by Natural Language Processing: Multicenter Observational Study From the MOOD Project.

BACKGROUND: Major depressive disorder (MDD) and treatment-resistant depression (TRD) are heterogeneous conditions in which key clinical details are sp...

Hybrid multi-scale CNN-Residual-LSTM approach for robust state-of-charge estimation in lithium-ion batteries.

Accurate estimation of State of Charge (SoC) and State of Health (SoH) values in battery management systems is crucial for maintaining energy efficien...

Measuring the Acceptance of Humanoid Robots in Adult Day Care Facilities.

INTRODUCTION: Socially assistive humanoid robots have emerged as promising tools for enhancing mood, engagement, and social connection in clinical and...

Inhibitory control deficits and ventral attention network alterations linked to apathy in schizophrenia.

Individuals with schizophrenia demonstrated impaired inhibitory control and apathy symptoms, which are characterized by a reduction in self-initiated ...

Dynamic Smart Membranes: Real-Time Perception, Self-Response, and AI-Driven Optimization for High-Safety Lithium-Based Batteries.

Lithium-based batteries are fundamental to modern energy storage systems, yet their safety remains a critical challenge due to risks such as thermal r...

A translational multimodal machine-learning prototype predicting valproate response in epilepsy treatment.

OBJECTIVE: Epilepsy affects ~1% of the global population and often requires lifelong antiseizure medication (ASM) therapy. Valproic acid (VPA) is a co...

Practical Lithium-Sulfur Batteries: An Integrated Design Roadmap from High-Loading Cathodes to High-Energy Pouch Cells.

The transition to a sustainable energy future requires electrochemical storage systems that surpass conventional lithium-ion batteries. The lithium-su...

From EEG signals to quantitative assessment: predicting depression severity using a novel deep learning framework.

The assessment of depression severity still relies primarily on subjective rating scales, with a lack of objective quantitative biomarkers. This study...

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 mechanisms remain unclear. Neuroimaging studies have sh...

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 underlying neural mechanisms remain elusive, primar...

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 an urgent need for recycling, for which existing ...

Aging beyond diagnosis: the MRI brain age gap across disorders.

The brain age gap (BAG), the difference between magnetic resonance imaging-predicted brain age and chronological age, is a proposed marker of neurobio...

The impaired inhibition of negative information in patients with major depressive disorder based on event-related potentials and machine learning algorithms.

Major depressive disorder (MDD) may exhibit deficits in the inhibition of negative information. This study investigated whether there are inhibition d...

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 cardiovascular events. Recent evidence suggests that the di...

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 attention. Although the likelihood of experiencin...

Neural Responses to Affective Sentences Reveal Signatures of Depression.

Major Depressive Disorder (MDD) is a highly prevalent mental health condition, and a deeper understanding of its neurocognitive foundations is essenti...

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 evidence base is uneven across use cases. This narrat...

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 heterogeneity in risk pathways. Conventional machin...