Bipolar Disorder

Different prefrontal cortex activity patterns in bipolar and unipolar depression during verbal fluency tasks based on functional near infrared spectroscopy study.

This study aimed to investigate the functionality of the prefrontal cortex in patients with unipolar depression (UD) and bipolar depression (BD) using functional near-infrared spectroscopy (fNIRS) during a verbal fluency task (VFT). Additionally, it evaluated the reliability of fNIRS as a diagnostic tool for cognitive assessments through a deep learning approach using one-dimensional convolutional...

Machine learning-based model for behavioural analysis in rodents applied to the forced swim test.

The Forced Swim Test (FST) is a widely used preclinical model for assessing antidepressant efficacy, studying stress response, and evaluating depressive-like behaviours in rodents. Over the last 10 years, more than 5500 scientific articles reporting the use of the FST have been published. Despite its widespread use, the FST behaviours are still manually scored, resulting in a labor-intensive and t...

Integrating Molecular Dynamics and Machine Learning for Solvation-Guided Electrolyte Optimization in Lithium Metal Batteries.

Optimizing liquid electrolytes is essential for achieving long-term cycling stability and high safety in lithium metal batteries. However, severe side...

De novo design and bioactivity prediction of mitotic kinesin Eg5 inhibitors using MPNN and LSTM-based transfer learning.

Breast cancer, the most commonly diagnosed disease worldwide, has been linked to the overexpression of the kinesin Eg5 protein, a spindle motor protei...

Alterations in Gut Microbiota-Brain Axis in Major Depressive Disorder as Identified by Machine Learning.

Major depressive disorder (MDD) is a complex mental health condition whose causes may extend beyond purely biological explanations and are increasingl...

Evaluating a brief smartphone-based stress management intervention with heart rate biofeedback from built-in sensors in a three arm randomized controlled trial.

Perceived stress is prevalent in industrial societies, negatively impacting mental health. Smartphone-based stress management interventions provide ac...

Leveraging machine learning to uncover the hidden links between trusting behavior and biological markers.

Understanding the decision-making mechanisms underlying trust is essential, particularly for individuals with mental disorders who often experience di...

Development of prediction models for screening depression and anxiety using smartphone and wearable-based digital phenotyping: protocol for the Smartphone and Wearable Assessment for Real-Time Screening of Depression and Anxiety (SWARTS-DA) observational study in Korea.

INTRODUCTION: Depression and anxiety are highly prevalent mental health conditions that significantly affect quality of life and cause societal burden...

Functional connectivity alterations of the pregenual anterior cingulate cortex by ketamine and the modulation by lamotrigine.

BACKGROUND: Neuroimaging studies have linked the beneficial effects of subanaesthetic ketamine doses in psychiatric conditions characterized by chroni...

Prospective prediction of first onset of major depressive disorder in midlife using machine learning.

PURPOSE: In this paper we leverage machine learning (ML) models to prospectively predict the first onset of Major Depressive Disorder (MDD), one of th...

Multitarget Generate Electrolyte Additive for Lithium Metal Batteries.

Electrolyte additives are crucial for accelerating the commercialization of lithium metal batteries (LMBs), yet designing effective additives is chall...

Smartphone eye-tracking with deep learning: Data quality and field testing.

Eye-tracking is widely used to measure human attention in research, commercial, and clinical applications. With the rapid advancements in artificial i...

Comparative cytokine signatures and cognitive deficits in early-onset schizophrenia and adolescent major depression: Toward refined diagnostic classification frameworks.

BACKGROUND: This study analyzed plasma cytokine patterns in individuals with schizophrenia (SCZ), major depressive disorder (MDD), and healthy control...

Psychedelics, entactogens and psychoplastogens for depression and related disorders.

Currently, the most actively investigated rapidly acting antidepressants, anxiolytics and/or anti PTSD agents, include psychedelics e.g. psilocybin, L...

Machine learning identifies prominent risk factors for depressive symptoms among Chinese children and adolescents.

BACKGROUND: Identifying key risk factors for depressive symptoms in children and adolescents is crucial for prevention. However, few studies have expl...

Transfer learning-motivated intelligent fault diagnosis framework for cross-domain knowledge distillation.

Transfer learning, as a transformative learning paradigm, has revolutionized the application of artificial intelligence (AI) frameworks, garnering wid...

Real-world effectiveness of cariprazine in major depressive disorder and bipolar I disorder in the United States.

AIMS: The efficacy of cariprazine for major depressive disorder (MDD) (adjunctive therapy) and bipolar I (BP-I) depression has been demonstrated in cl...

Multivariate brain morphological patterns across mood disorders: key roles of frontotemporal and cerebellar areas.

BACKGROUND: Differentiating major depressive disorder (MDD) from bipolar disorder (BD) remains a significant clinical challenge, as both disorders exh...

Enhancing differentiation between unipolar and bipolar depression through integration of machine learning and electroencephalogram analysis.

To enhance the differentiation between unipolar depression (UPD) and bipolar depression (BPD), this study integrates machine learning and deep learnin...

Detection of Depressive Symptoms in College Students Using Multimodal Passive Sensing Data and Light Gradient Boosting Machine: Longitudinal Pilot Study.

BACKGROUND: Depression is the top contributor to global disability. Early detection of depression and depressive symptoms enables timely intervention ...