Bipolar Disorder

Identification of the core genes KLRB1 and RETN as potential shared diagnostic markers for major depressive disorder and systemic lupus erythematosus through bioinformatics and machine learning methodologies.

This study investigates the shared molecular mechanisms between major depressive disorder (MDD) and systemic lupus erythematosus (SLE) through integrated bioinformatics analysis. Analysis of multiple GEO datasets identified 23 common differentially expressed genes (coDEGs), primarily enriched in immune and metabolic pathways. Among 13 high-confidence hub genes derived from protein-protein interact...

Effective alternative strategies to combat challenges associated with MDR bacterial infections: Drug repurposing, role of artificial intelligence, and novel therapeutic options.

Antibiotic failure has emerged as a critical global health concern, driven by a combination of factors including the stagnation in the discovery of new antibiotics, the widespread emergence of resistance mechanisms among clinical bacterial isolates, and the persistence of recurrent infections caused by tolerant and non-responsive bacterial populations. This review explores contemporary and innovat...

Emotion classification using gait biomechanics and machine learning.

BACKGROUND: Emerging research suggests that emotions alter the way people walk, suggesting gait data may serve as a potential source for emotion recog...

LBMS-SAM: Segment anything model guided SEM image segmentation for lithium battery materials.

We conduct a comprehensive study on the quality inspection of lithium battery materials, which evaluates material conformity by analyzing particle siz...

Engineering of Stabilized Ru-Based Proton Exchange Membrane Water Electrolysis.

Proton exchange membrane water electrolysis (PEMWE) is a promising blueprint for the industrial production of green hydrogen in the short term, but it...

Resting-state functional connectivity of the fronto-limbic and default mode network as neural correlates of antidepressant response in major depressive disorder.

BACKGROUND: Major depressive disorder (MDD) is a leading cause of disability worldwide, yet antidepressant response remains highly variable, with many...

Unconscious elevated bottom-up processing in depression: Insights from dynamic causal modeling with EEG and fMRI.

INTRODUCTION: MRI compatible EEG systems enable simultaneous EEG-fMRI data assessment, which provides high spatial and high temporal resolution of neu...

An Internet of Things operating room platform for neurosurgery.

OBJECTIVE: The operating room (OR) is a data-rich environment and largely follows closed-door policies for health data security and privacy. To overco...

Machine learning prediction of suicide attempts in major depression: Feature selection and model development using national survey data.

BACKGROUND: The study aimed to explore the risk factors of suicidal attempts (SA) in patients with major depressive disorders (MDD). METHODS: Cross-se...

Integrating structural and functional brain features to classify major depressive disorder: a multi modal approach.

Major Depressive Disorder (MDD) is a common mental disorder that markedly impairs psychosocial functioning and quality of life. Multi-modal fusion met...

Screening for depression risk in asthma patients: Development and external validation of a machine learning-based predictive model.

BACKGROUND: Depression is prevalent among asthma patients, negatively impacting their quality of life, treatment adherence, and prognosis. This study ...

Interpretable machine learning models for predicting depression status and remission three years later in older adults in China: A longitudinal study.

BACKGROUND: Depression significantly impacts older adults, making it valuable to use machine learning to predict their future depressive status and as...

Uncovering predictors of bipolar II conversion to bipolar I: A machine learning analysis of national health records in Taiwan.

BACKGROUND: Bipolar II disorder (BD-II) can progress to bipolar I disorder (BD-I), carrying profound psychosocial consequences. However, limited resea...

Sleep disturbance recorded via wearable sensors predicts depression severity 9 years later.

BACKGROUND: Major depressive disorder (MDD) is prevalent and poses major public health implications. Autonomic nervous system (ANS) dysregulation and ...

Brain dynamics and depressive symptoms in young adults: Evidence from EEG.

BACKGROUND: Depression is a major public health concern, with a rising prevalence among adolescents and young adults. However, the neural mechanisms u...

Comorbid anxiety predicts lower odds of MDD improvement in a trial of smartphone-delivered interventions.

Comorbid anxiety disorders are common among patients with major depressive disorder (MDD), but their impact on outcomes of digital and smartphone-deli...

The similarities and differences of multiple chronic diseases risk factors across depressive symptoms trajectories among middle-aged and older Chinese adults: A 10-year longitudinal cohort study.

BACKGROUND: Depressive symptoms and multiple chronic diseases (MCDs) significantly contribute to the global disease burden among middle-aged and older...

Esflurbiprofen exerts a fast-onset antidepressant effect by blocking SERT-nNOS interaction.

Selective serotonin reuptake inhibitors (SSRIs) are characterized by delayed therapeutic onset largely due to their reliance on the desensitization of...

Classification of major depressive disorder using vertex-wise brain sulcal depth, curvature, and thickness with a deep and a shallow learning model.

Major depressive disorder (MDD) is a complex psychiatric disorder that affects the lives of hundreds of millions of individuals around the globe. Even...

Probiotics, psychobiotics, and postbiotics: a therapeutic modality for the management of schizophrenia.

Schizophrenia is a debilitating, chronic neuropsychiatric disorder, a multifactorial disorder combining genetic, neurodevelopmental, immunological, an...