Bipolar Disorder

Integrative analysis of signaling and metabolic pathways, immune infiltration patterns, and machine learning-based diagnostic model construction in major depressive disorder.

Major depressive disorder (MDD) is a multifactorial disorder involving genetic and environmental factors, with unclear pathogenesis. This study aims to explore the pathogenic pathway of MDD and its relationship with immune responses and to discover its potential targets by bioinformatics methods. We first applied gene set variation analysis (GSVA) and seven different immune infiltration algorithms...

Data-Knowledge-Dual-Driven Electrolyte Design for Fast-Charging Lithium Ion Batteries.

Electric vehicles (EVs) starve for minutes-level fast-charging lithium-ion batteries (LIBs), while the heat gathering at high-rate charging and torridity conditions has detrimental effects on electrolytes, triggering rapid battery degradation and even safety hazards. However, the current research on high-temperature fast-charging (HTFC) electrolytes is very lacking. We revolutionized the conventio...

Joint resting state and structural networks characterize pediatric bipolar patients compared to healthy controls: a multimodal fusion approach.

Pediatric bipolar disorder (PBD) is a highly debilitating condition, characterized by alternating episodes of mania and depression, with intervening p...

Acoustic and Natural Language Markers for Bipolar Disorder: A Pilot, mHealth Cross-Sectional Study.

BACKGROUND: Monitoring symptoms of bipolar disorder (BD) is a challenge faced by mental health services. Speech patterns are crucial in assessing the ...

Longitudinal brain age in first-episode mania youth treated with lithium or quetiapine.

It is unclear if lithium and quetiapine have neuroprotective effects, especially in early stages of bipolar and schizoaffective disorders. Here, an ag...

Machine learning-based differentiation of schizophrenia and bipolar disorder using multiscale fuzzy entropy and relative power from resting-state EEG.

Schizophrenia (SZ) and bipolar disorder (BD) pose diagnostic challenges due to overlapping clinical symptoms and genetic factors, often resulting in m...

Semantic signals in self-reference: The detection and prediction of depressive symptoms from the daily diary entries of a sample with major depressive disorder.

Individuals with major depressive disorder (MDD) experience fewer positive and more negative emotions and use fewer positive words to describe themsel...

The Association of Elevated Depression Levels and Life's Essential 8 on Cardiovascular Health With Predicted Machine Learning Models and Interpretations: Evidence From NHANES 2007-2018.

The association between depression severity and cardiovascular health (CVH) represented by Life's Essential 8 (LE8) was analyzed, with a novel focus ...

Establishing a Validation Framework of Treatment Discontinuation in Claims Data Using Natural Language Processing and Electronic Health Records.

Measuring medication discontinuation in claims data primarily relies on the gaps between prescription fills, but such definitions are rarely validated...

An enhanced CNN-Bi-transformer based framework for detection of neurological illnesses through neurocardiac data fusion.

Classical approaches to diagnosis frequently rely on self-reported symptoms or clinician observations, which can make it difficult to examine mental h...

Gene age gap estimate (GAGE) for major depressive disorder: A penalized biological age model using gene expression.

Recent associations between Major Depressive Disorder (MDD) and measures of premature aging suggest accelerated biological aging as a potential biomar...

Multivariate Classification of Adolescent Major Depressive Disorder Using Whole-brain Functional Connectivity.

RATIONALE AND OBJECTIVES: Adolescent major depressive disorder (MDD) is a serious mental health condition that has been linked to abnormal functional ...

Predicting Final Restoration Color Using Neural Network Models: The Impact of Substrate Lightness Versus Ceramic Shade, Translucency and Thickness.

OBJECTIVES: This study aimed to assess the influence of background color, ceramic shade, translucency, and thickness on the color matching of lithium ...

Psychedelic Drugs in Mental Disorders: Current Clinical Scope and Deep Learning-Based Advanced Perspectives.

Mental disorders are a representative type of brain disorder, including anxiety, major depressive depression (MDD), and autism spectrum disorder (ASD)...

Battery state of health estimation under fast charging via deep transfer learning.

Accurate state of health (SOH) estimation is essential for effective lithium-ion battery management, particularly under fast-charging conditions with ...

Heterogeneous Graph Representation Learning Framework for Resting-State Functional Connectivity Analysis.

Brain functional connectivity analysis is important for understanding brain development and brain disorders. Recent studies have suggested that the va...

A comprehensive review of neurotransmitter modulation via artificial intelligence: A new frontier in personalized neurobiochemistry.

The deployment of artificial intelligence (AI) is revolutionizing neuropharmacology and drug development, allowing the modulation of neurotransmitter ...

Altered resting-state brain activity in patients with major depression disorder and bipolar disorder: A regional homogeneity analysis.

BACKGROUND: Major Depressive Disorder (MDD) and Bipolar Disorder (BD) exhibit overlapping depressive symptoms, complicating their differentiation in c...

Develop and validate machine learning models to predict the risk of depressive symptoms in older adults with cognitive impairment.

BACKGROUND: Cognitive impairment and depressive symptoms are prevalent and closely interrelated mental health issues in the elderly. Traditional metho...

Using Natural Language Processing Methods to Build the Hypersexuality in Bipolar Reddit Corpus: Infodemiology Study of Reddit.

BACKGROUND: Bipolar is a severe mental health condition affecting at least 2% of the global population, with clinical observations suggesting that ind...