Sepsis

Machine learning prediction of human antibiotic resistance risk using 16S rRNA profiles.

Antimicrobial resistance poses a growing global health threat, yet large-scale surveillance and risk evaluation remain constrained by the cost and accessibility of metagenomic sequencing. Here, we demonstrate that antibiotic resistance risk, integrating gene mobility, human accessibility, clinical relevance, and host pathogenicity, can be quantitatively inferred from microbial taxonomic compositio...

Comparison of a Computable Pediatric Sepsis Phenotype Tool in Argentinian and U.S. Cohorts.

OBJECTIVE: Sepsis is a leading cause of mortality in low- and middle-income countries. This study identifies computable pediatric sepsis phenotypes (PedSep A, B, C, and D) previously derived in a U.S. cohort in a new independent Argentine cohort to assess plausibility for its use in personalized clinical trials in Pan-American children. DESIGN: This retrospective cohort study uses data from the Ar...

The miRNA-virus Axis in RNA Virus Infections: Mechanisms, Therapeutic Targeting, and Systems Biology Approaches.

RNA viruses are a diverse and rapidly evolving group of pathogens that significantly contribute to worldwide morbidity and mortality, propelled by ele...

Development and evaluation of a multi-source machine learning model to predict critical illness and death in patients with substance misuse.

OBJECTIVES: Patients with substance misuse are at high risk for clinical deterioration, and pre-hospital encounters constitute important risk factors....

Artificial intelligence research in journals indexed in the web of science "infectious diseases" category: a bibliometric analysis, 2016-2025.

PURPOSE: Artificial intelligence (AI) is increasingly being applied in the field of infectious diseases. This study aimed to characterize publication ...

Construction of an associative model for prolonged intensive care unit stay in sepsis patients combined with myocardial injury.

OBJECTIVE: This study aimed to identify the factors contributing to Prolonged Length of Stay (PLOS) in intensive care units for sepsis patients combin...

Imaging Biomarkers in Parkinson's Disease and Movement Disorders: Emerging Insights from Multimodal Neuroimaging.

This editorial introduces a special issue detailing the rapid evolution of multimodal neuroimaging biomarkers for Parkinson's disease (PD) and related...

Machine learning-based quantitative structure-activity relationship model for antibiotic prediction and discovery.

Antimicrobial resistance (AMR) is a critical global health problem that has become increasingly alarming in recent years. The discovery of new antibio...

CCT2 Promotes Immune Escape in Colorectal Cancer by Regulating the JAK1-STAT3-PD-L1 Axis.

BACKGROUND: Colorectal cancer (CRC) is a major global health burden. While immune checkpoint inhibitors have greatly advanced cancer therapy, their th...

Development and Validation of a Machine Learning-Based Bedside Score (IPA-2T2C2DW) for Invasive Pulmonary Aspergillosis in Critically Ill Non-Neutropenic Immunocompromised Hosts.

OBJECTIVE: To develop and validate machine learning-based diagnostic models for IPA using data available within 24 hours of ICU admission, construct t...

Erjingwan Alleviates Parkinson's Disease via Activation of PPARA-Mediated Autophagy.

Parkinson's disease (PD) is characterized by progressive dopaminergic neuronal degeneration and neuroinflammation. Traditional Chinese medicine (TCM) ...

Postoperative Nocardia cyriacigeorgica infection after glioblastoma resection: correlating metagenomic next-generation sequencing with conventional microbiology.

Postoperative nocardial infection after cranial surgery is rare and difficult to diagnose because Nocardia spp. grow slowly in conventional culture. M...

Single-Atom Nanozymes for High-Efficiency Cancer Immunotherapy by Targeting Tumor Microenvironment.

Tumor immunotherapy has emerged as a transformative strategy for cancer treatment. However, its clinical efficacy remains limited by the immunosuppres...

[Advances in phage therapy for pneumonia caused by Klebsiella pneumoniae].

Klebsiella pneumoniae (KP) has emerged as a formidable nosocomial pathogen in the era of antimicrobial resistance, with mortality from pneumonia cause...

Prediction of Antimicrobial Resistance in People Living With Cystic Fibrosis Using Machine Learning.

Antimicrobial resistance (AMR) is a growing challenge in people living with cystic fibrosis (pwCF), who often experience chronic lung infection and re...

Multimodal Raman-Gene Framework for Interpretable Phenotypic Antibiotic Resistance and Health Risk Stratification.

The increasing burden of antibiotic-resistant bacteria presents a major challenge for clinical management, as conventional antimicrobial susceptibilit...

Antibiotic Mixture Exposure in Meconium Affects Child Neurodevelopment via Altering Early-Life Gut Microbiome and Metabolome.

Previous evidence has established associations of antibiotic exposure in early life with neurodevelopmental disorders. However, previous studies have ...

Critical Care-Specific vs General-Purpose Large Language Models in Emergency Intensive Care Unit Diagnosis: Single-Center Retrospective Paired Comparative Study.

BACKGROUND: The emergency intensive care unit (EICU) manages the most critically ill patients, where rapid and accurate diagnosis is essential yet cha...

Real-world evidence on antibiotic use among privately insured beneficiaries in Saudi Arabia: a retrospective analysis of claims data.

OBJECTIVES: Inappropriate and broad-spectrum antibiotic use contributes to antimicrobial resistance (AMR) and higher healthcare costs. In Saudi Arabia...

Integration of RNA-seq and scRNA-seq to investigate the role of cell cycle-related biomarkers in sepsis.

BACKGROUND: Sepsis is a life-threatening organ dysfunction arising from a dysregulated host response to infection. Cell-cycle disturbance is increasin...