Anxiety & Stress

Artificial Intelligence-Driven Multi-Omics Analysis Reveals Hydroxytyrosol Targeting of the TXNIP-NLRP3 Inflammasome Axis in Traumatic Brain Injury.

Traumatic brain injury (TBI) induces secondary neuroinflammation driven by oxidative stress, inflammasome activation, and immune remodeling, yet specific mechanism-guided pharmacological interventions remain limited. This study established an artificial intelligence (AI)-integrated network pharmacology and multi-omics framework to evaluate whether hydroxytyrosol (HT), an olive-derived natural poly...

Integrated Toxicogenomic Analysis Reveals Potential Molecular Signatures Associated with Cadmium-Related Osteoarthritis.

Osteoarthritis (OA) is a common chronic joint disease, and cadmium (Cd) exposure may contribute to its progression. This study integrated network toxicology, transcriptomic datasets from the Gene Expression Omnibus (GEO), weighted gene co-expression network analysis (WGCNA), and machine-learning methods to identify molecular signatures potentially associated with Cd exposure-related OA. A total of...

Neuroimmune pharmacotherapy across the skin-brain axis: mechanisms, therapeutic targets, and AI-enabled precision approaches.

The skin-brain axis is a bidirectional neuroimmune network linking cutaneous inflammation with central neuroinflammation, stress signaling, and behavi...

Breaking the Autophagy-Oxidative Stress Vicious Cycle in Alzheimer's Disease: Lactiflorin Unlocks P62 Dual Phosphorylation via ULK1 Targeting.

ETHNOPHARMACOLOGICAL RELEVANCE: The dried root of Paeonia lactiflora Pall. has a long history of medicinal use in traditional Chinese medicine. Classi...

Development and Validation of a Computer-Assisted Screw Trajectory Planning Model Based on Iterative Closest Point Registration and Weighted K-Nearest Neighbors Algorithms for Cortical Bone and Pedicle Screw Techniques.

Study DesignRetrospective study.ObjectivesTo develop and validate a computer-assisted model for planning screw trajectories to support modified cortic...

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...

Nurses' Ethical Awareness, Attitudes, Anxiety, and Intention to Use Artificial Intelligence Technology.

Artificial intelligence (AI) is increasingly influencing nursing practice and care delivery. This cross-sectional correlational study examined nurses'...

Physics-Informed Neural Networks Meet Multimodal Large Language Models: Biomechanical Simulation in Aortic Aneurysm.

Axial dissections of the thoracic artery are common causes of death in people diagnosed with aortic dissection; however, decisions to intervene on asc...

Combined predictive value of TyG index and PLR for mental health in Chinese adults: A machine learning approach.

OBJECTIVE: To investigate the independent and combined associations of the triglyceride-glucose (TyG) index and platelet-to-lymphocyte ratio (PLR) wit...

Integrated multi-omics analyses identify an RAS-SLC11A2-associated molecular framework linking iron metabolism with PCOS-related cardiometabolic risk.

INTRODUCTION: PCOS is a common endocrine disorder with elevated cardiometabolic risk, yet the role of the renin-angiotensin system (RAS)-iron metaboli...

Machine Learning Models for Predicting Pain, Fatigue, Depression, Anxiety, and Malnutrition in Cancer Patients: A Systematic Review and Meta-Analysis.

INTRODUCTION: Cancer-related symptoms including pain, fatigue, depression, anxiety, and malnutrition drive poor quality of life and adverse clinical o...

Harmonising Depression and Anxiety Measures Across International Cohorts: A Framework Validated Using Measurement Invariance.

AIMS: Cross-national research on mental health trajectories requires harmonised measures that are valid and comparable. However, measurement scales of...

Detecting short-term post-traumatic stress disorder symptom increases among veterans: machine-learning analysis integrating wearable sensor and daily self-report data.

BACKGROUND: Post-traumatic stress disorder (PTSD) symptoms can fluctuate substantially over short periods, yet routine screening typically relies on i...

Takotsubo syndrome diagnosis: the biomarker-based BioTAK score.

BACKGROUND AND AIMS: Takotsubo syndrome (TTS) closely mimics acute coronary syndrome (ACS). Early differentiation remains challenging because diagnosi...

Integrated pan-cancer analysis reveals a cancer-associated fibroblast oxidative stress response signature predicting immunotherapy response and prognosis.

Oxidative stress plays a significant regulatory role in tumor immune responses and can influence the efficacy of immunotherapy. Accordingly, therapeut...

Spatial synaptic pruning mechanism of NAC microglia in differential regulation of PTSD- and depression-like behaviors.

BACKGROUND AND AIMS: Post-traumatic stress disorder (PTSD) comorbid with depression is a prevalent, treatment-refractory clinical syndrome. Emerging e...

Myocardial Fibrosis in Pediatric Heart Disease: Mechanisms, Imaging Biomarkers, Clinical Consequences, and Emerging Antifibrotic Therapies.

Myocardial fibrosis is increasingly recognized as a central determinant of adverse cardiac remodeling and long-term cardiovascular outcomes in childre...

Antibiotic Resistance in Helicobacter pylori: Pathogenic Mechanisms and Eradication Barriers.

Antibiotic resistance in Helicobacter pylori is an important factor in the ineffectiveness of eradication regimens. The rate of resistance is not cons...

Development of a machine learning prediction model for overactive bladder in female nurses: the NURS study.

PURPOSE: To develop and internally validate interpretable machine-learning models for identifying individuals with a higher probability of overactive ...