Infectious Disease

Systemic immune-inflammation (SII) index as a novel prognostic biomarker in critically ill patients with sepsis: analysis of the MIMIC-IV cohort and predictive modeling based on machine learning.

Application of machine learning for the diagnosis and prognosis of sepsis-induced acute respiratory distress syndrome: a systematic review and meta-analysis.

AMP-CapsNet: a multi-view feature fusion approach for antimicrobial peptide prediction using capsule networks.

Antimicrobial peptides (AMPs) are universally found in both intracellular and extracellular settings and have significant antibiotic-resistant bacteri...

Development of surface enhanced Raman spectra coupled with machine learning analysis for differentiation of closely related species within Enterobacter cloacae complex.

Machine learning model predicts prognosis in SARS-CoV-2-infected autoimmune encephalitis patients.

OBJECTIVE: To assess the neurological prognosis of patients with autoimmune encephalitis (AE) after severe acute respiratory syndrome coronavirus 2 (S...

Carbon-phosphorus exchange rate constrains density-speed trade-off in arbuscular mycorrhizal fungal growth.

Symbiotic nutrient exchange between arbuscular mycorrhizal (AM) fungi and their host plants varies widely depending on their physical, chemical, and b...

Structure-Based Prediction of QT Prolongation Risk Using Graph Neural Networks: An Integrative Approach Combining In Vitro hERG Assays and Pharmacovigilance Data.

Drug-induced QT-interval prolongation, a non-specific biomarker of increased risk for Torsades de Pointes (TdP), is a major safety concern in drug dev...

FungiGuard: identification of plant antifungal peptides with artificial intelligence.

Antifungal peptides (AFPs) are crucial for plant defense against biotic stress. Yet, no artificial intelligence tool specifically classifies plant AFP...

Artificial Intelligence Platform EnzySFC for Enzyme Screening and Functional Conversion: Completely Redirecting Nitrilase to Nitrile Hydratase Function.

Catalytic promiscuity provides fundamental insights into enzyme evolution. To address the multiobjective challenges in discovering and evolving promis...

A machine learning model for predicting 28-day mortality in patients with alcoholic cirrhosis and sepsis: a study based on the MIMIC-IV database.

OBJECTIVE: To develop and validate the best machine learning model for predicting 28-day mortality in septic patients with alcoholic cirrhosis (AC), l...

Diagnostic-Mediated Interactive Superlattices Engineering for Threshold-Saltatory Visual Assessment of Tuberculous Meningitis.

Nonlinear dynamic monitoring is crucial for assessing l-tryptophan (l-Trp) dysregulation progression in tuberculous meningitis (TBM); yet remains chal...

Nanoparticle approaches for hepatitis therapy and clinical translation.

BACKGROUND: Hepatitis B and C viruses (HBV and HCV) remain major global health challenges, contributing significantly to liver-related morbidity and m...

Combating Antiviral Drug Resistance: A Multipronged Strategy.

ConspectusViral proteases are essential enzymes required for viral replication and assembly, making them prime antiviral drug targets. However, under ...

Single-round evolution of RNA aptamers with GRAPE-LM.

The directed evolution of biomolecules is an iterative process. Although advancements in language models have expedited protein evolution, effectively...

Label-free serum SERS combined with RFE-GBDT algorithm for non-invasive screening of liver cancer.

Early diagnosis of liver cancer is crucial for developing clinical treatment strategies and improving patient survival rates. However, current diagnos...

Microvascular phenotypes in pediatric sepsis identified by machine learning: prognostic implications for organ dysfunction and mortality.

Gellan gum/ artemisia sphaerocephala Krasch gum composite films integrated with machine learning for real-time freshness assessment.

The widespread use of non-degradable plastic food packaging poses serious environmental and food safety concerns, motivating the development of biodeg...

Improving pandemic prediction: integrating Physics-Informed Neural Networks and symbolic regression for COVID-19 modeling.

This study refines the SIDARTHE model for Italy's COVID-19 outbreak using a hybrid, data-driven framework. A two-stage approach compares Maximum Likel...

Synergistic impact of Gram-negative bacterial co-infection on invasive pulmonary aspergillosis in non-neutropenic patients: a machine learning-based risk stratification approach.

BACKGROUND: Invasive pulmonary aspergillosis (IPA) is increasingly recognized in non-neutropenic patients, where coexisting bacterial infections, part...

AI-augmented decision-making in face matching: comparing concurrent and non-concurrent advice presentation.

A primary aim of human-AI teaming is to achieve better collaborative performance than either can achieve alone. Despite considerable efforts in this d...