Sepsis

Prospective genomic and epidemiologic surveillance of Klebsiella pneumoniae in a tertiary NICU.

BACKGROUND: Klebsiella pneumoniae complex (Kp) is a relevant neonatal pathogen colonizing preterm infants. While outbreak investigations often focus on multidrug-resistant strains, the epidemiology and genomic dynamics of wild-type Kp in nonoutbreak neonatal intensive care unit (NICU) settings remain elusive. METHODS: We conducted a 30-month (October 2021 to March 2024) cohort study with weekly ac...

Artificial intelligence and computerized decision support in adult intensive care: A systematic review of randomized controlled trials.

BACKGROUND: Artificial intelligence (AI) and computerized clinical decision support systems (CDSS) are increasingly applied in intensive care, yet their clinical impact remains uncertain, as most studies focus on model development rather than prospective evaluation. OBJECTIVES: To identify randomized controlled trials (RCTs) evaluating AI-based or CDSS interventions intended to influence real-time...

MethylSense: high accuracy machine learning-based diagnostics for Aspergillus fumigatus infection in chickens using host cell-free DNA methylation and Nanopore sequencing.

Avian aspergillosis, caused by Aspergillus fumigatus (Af), lacks sensitive antemortem diagnostics. Existing microbial cell-free DNA (cfDNA) tests are ...

Ultrasensitive, Rapid, and Incubation-Free Surface-Enhanced Raman Scattering Detection of Sulfasalazine with a GF@PDDA-Ag/rGO Functionalized Membrane and Machine Learning.

Developing rapid detection methods with high sensitivity and real-time capabilities is a critical challenge for monitoring antibiotic pollution. This ...

Machine Learning Models Using Hospital Admission Characteristics Do Not Optimally Predict Nosocomial Infection Development in a Global Cirrhosis Cohort.

BACKGROUND: Nosocomial infections (NI) in cirrhosis are associated with high mortality but could be preventable. Logistic regression (LR) models have ...

Automated Eosinophil Quantification Using Deep Learning to Predict Therapy Escalation in Pediatric Ulcerative Colitis.

BACKGROUND: Emerging evidence implicates eosinophils as important modulators of disease activity and therapeutic response in ulcerative colitis. Autom...

Machine learning-advanced hydrogel-based transcription-coupled positive-feedback CRISPR/Cas13a analysis for novel microRNA signatures in differential diagnosis of non-small cell lung cancer.

MicroRNAs (miRNAs) hold significant potential as biomarkers for the precise diagnosis of non-small cell lung cancer (NSCLC). However, miRNAs remain un...

Antibiotic resistance prediction with an attention-based bi-LSTM clinical decision support system.

BACKGROUND AND OBJECTIVE: Antimicrobial resistance is recognized by the World Health Organization as a significant global health threat. In clinical p...

Lactate-albumin ratio predicts in-hospital mortality in critically Ill patients with congestive heart failure and diabetes.

OBJECTIVE: To evaluate the predictive utility of the initial lactate-to-albumin ratio (LAR) measured within 24 h of admission for in-hospital all-caus...

A Transformer for Reaction-Aware Compound Explorations with GFlowNet in QSAR-Guided Molecular Design.

In drug discovery tasks, achieving a balance between high biological activity toward therapeutic targets and synthetic chemical feasibility is critica...

A frontotemporal dementia-like phenotype in schizophrenia: links to striatal dopamine and iron accumulation.

Some schizophrenia patients share characteristics with behavioral variant frontotemporal dementia (bvFTD) including gray matter volume (GMV) similarit...

Identification and multi-layered experimental validation of feature genes related to butyrate metabolism and oxidative stress in sepsis.

The mechanisms underlying sepsis remain poorly understood and specific therapeutic options remain lacking. Accumulating evidence suggests that butyrat...

Herbal extracts as antibiotic adjuvants against ESKAPE pathogens: mechanisms and therapeutic potential.

The escalating crisis of antimicrobial resistance, particularly driven by ESKAPE pathogens, poses a serious threat to global public health. With the s...

Automated estimation of drain output in postoperative patients using deep learning on clinical images.

Postoperative drains are essential components of care in general surgery and intensive care units, where accurate monitoring of drain output is critic...

Identification of Mitochondrial Signature Biomarkers and Molecular Mechanisms in Atherosclerotic Tissues and Blood: Combined Single-Cell and Bulk RNA Sequencing Analysis.

Atherosclerosis (AS) is a leading cause of cardiovascular disease and stroke. Although mitochondria's role in AS is recognized, effective molecular ta...

Association between platelet-albumin-bilirubin score and 30-day in-hospital mortality in patients with sepsis: evidence from a large database and machine learning modeling.

SyntheMol-RL: a flexible reinforcement learning framework for designing easily synthesizable antibiotics.

The rise of antibiotic-resistant pathogens such as Staphylococcus aureus has created an urgent need for new antibiotics. Generative artificial intelli...

Emerging technologies and AI-assisted tools in cardiopulmonary monitoring.

PURPOSE OF REVIEW: Cardiopulmonary monitoring is fundamental to critical care, yet traditional approaches rely on simplified thresholds that capture o...

A robotic wound care patient for evidence-based surgical site infection research.

BACKGROUND: Surgical site infections (SSIs) are among the most common and preventable postoperative complications, yet existing preclinical models lac...

Functional cortical network alterations in Parkinson's disease with wearing-off revealed by resting-state fNIRS and graph theory.

Wearing-off (WO) is a common motor complication in Parkinson's disease (PD), characterized by the re-emergence of symptoms before the next dose of dop...