Infectious Disease

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 susceptibility testing (AST) depends on culture-based workflows that are slow, labor-intensive, and poorly suited for rapid clinical decision-making. Moreover, standard AST primarily reports susceptibility phenotypes, while providing little insight into the poten...

Influenza-Like Illness Forecasting Using Multisource Data: Comparative Deep Learning Study.

BACKGROUND: Accurate forecasting of influenza-like illness (ILI) is crucial for public health. Integrating novel digital data streams (eg, internet searches and human mobility) with traditional surveillance can improve accuracy, but optimal modeling frameworks are underexplored. OBJECTIVE: This study aimed to develop and compare multisource data-driven models for forecasting ILI incidence trends. ...

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 ...

Metabolic engineering of Candida yeasts for biotechnological applications.

Candida yeasts represent a versatile yet underexploited platform for industrial biotechnology. These yeasts utilize a remarkably broad range of carbon...

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...

Network-guided transcriptomics identifies drug-linked host-response biomarkers in tuberculosis disease-state transition.

Distinguishing active tuberculosis (ATB) from the post-therapy state remains a key challenge in disease monitoring, as host-response signatures are of...

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...

Integration of the circulating miRNome and clinical information to predict 90-day mortality in elderly COVID-19 subphenotypes.

Elderly patients with coronavirus disease 2019 (COVID-19) exhibit high mortality rates. We assessed whether microRNA (miRNA) profiling provides progno...

Real-world analysis of depression-related adverse events associated with the adsorbed anthrax vaccine: integrating pharmacovigilance signals, machine learning risk prediction, and transcriptomic mechanisms.

BACKGROUND: Anthrax remains a life-threatening zoonotic disease in resource-limited settings. Adsorbed anthrax vaccine (AVA, BioThrax) is the only Uni...

SCDM-Net: Symbiotic causal debiasing for SERS-based exosome profiling in lung cancer.

Early detection of lung cancer improves patient prognosis. Surface-enhanced Raman scattering (SERS) analysis of exosomes provides an approach for lung...

From decay to discovery: A new antimicrobial peptide from Chrysomya megacephala (Diptera: Calliphoridae) larvae.

The larvae of Chrysomya megacephala (Diptera: Calliphoridae) thrive in environments rich in decaying organic matter and dead animals, which are often ...

Optimising Pharmacovigilance Efficiency with MLIT (Machine Learning for Intelligent Triage): A Tool for Statistical Safety Alerts.

BACKGROUND AND AIM: Pharmacovigilance is essential to ensuring patient safety by enabling timely identification of adverse reactions in increasingly c...

Automated Data-Efficient Symbolic Regression for Interpretable Bioprocess Model Development.

Bioprocessing is central to the sustainable manufacture of pharmaceuticals, food products, and renewable chemicals. Consequently, developing high-fide...

Deep Learning Algorithm-Guided Raman Spectroscopy for Real-Time Correlation of Critical Process Parameters and Titers in Lentiviral Vector.

Manufacturing scalability and cost efficiency of Lentiviral vector (LV) production for gene therapy are hampered by slow offline detection of critical...

Comparative Performance of AI Models and Clinicians in Evidence-Based Cardiovascular Disease Management for People Living With HIV: Comparative Study.

BACKGROUND: Although widespread antiretroviral therapy has extended the life expectancy of people living with HIV, cardiovascular disease (CVD) has em...

Recent advancements in artificial intelligence applications for the mitigation of antimicrobial resistance: challenges and opportunities.

Antimicrobial resistance (AMR) poses a significant global public health threat, and efforts to mitigate it have been aided by artificial intelligence ...

Myocarditis in the Modern Era: Navigating Diagnosis, Innovative Treatments, the COVID-19 Challenge and the Role of Artificial Intelligence.

Myocarditis is an inflammatory disease of the myocardium with diverse aetiologies, ranging from infections and autoimmune processes to drug-induced re...

Beyond Accuracy: A Mixed-Methods Audit of Chain-of-Thought Failures in LLM-Based COVID-19 Vaccine Stance Detection.

This mixed-methods study assessed whether reasoning-enabled large language models (LLMs) can classify stances towards COVID-19 vaccination on X (forme...

From bedside queries to complex care: AI for decision-making in infectious diseases.

BACKGROUND: Infectious Diseases require rapid decisions based on heterogeneous and evolving clinical data. At the same time, the shortage of infectiou...