Sepsis

Rapid whole-genome sequencing of Plasmodium DNA from cryptic malaria cases in UK travellers provides insights into infection origins, transmission and antimalarial resistance.

BACKGROUND: The UK reports approximately 2000 imported malaria cases annually, necessitating effective surveillance to determine infection sources and transmission routes, inform strategies for prevention and detect molecular markers of drug resistance that may compromise treatment outcomes. Defined by their unclear route of infection, cryptic malaria cases pose a particular challenge for malaria ...

Comparative machine learning approaches to prognosticate clinical outcomes in oral and maxillofacial space infections: a retrospective analysis.

BACKGROUND: The objective of this study was to evaluate the performance of multiple machine learning algorithms to provide evidence supporting early intervention for high-risk patients with oral and maxillofacial space infections (OMSI), thereby reducing complication rates and improving overall clinical outcomes. METHODS: A retrospective cohort study was performed to analyse clinical data from 432...

Risk prediction of sepsis-associated acute kidney injury: development, validation of a machine learning model with multicenter data.

BACKGROUND: Sepsis-associated acute kidney injury (SA-AKI) is a common and severe complication in intensive care unit (ICU) patients, with high incide...

Multi-omics approaches to parkinsonism: genomic, proteomic, and non-coding RNA perspectives.

Parkinson's disease (PD) is a progressive neurodegenerative disorder with significant variability associated with substantial loss of dopaminergic neu...

Leveraging an Explainable Machine Learning Model for Early Identification of Acute Kidney Injury: A Retrospective Study.

BACKGROUND: Delayed identification of acute kidney injury (AKI) limits timely intervention, as diagnosis often depends on serum creatinine elevation a...

Rapid delineation of Acinetobacter baumannii dose responses to zosurabalpin based on machine learning-assisted interpretation of bacterial nanomotions.

UNLABELLED: Carbapenem-resistant Acinetobacter baumannii (CRAB) represents a major clinical threat, underscoring the urgent need for both new antibiot...

A Novel Machine Learning Approach for Predicting Prognosis of SFTS Patients in the Early Stages of Disease.

OBJECTIVE: Severe fever with thrombocytopenia syndrome (SFTS) is an emerging tick-borne disease characterized by high morbidity and mortality rates. T...

Advanced glucose control strategies leveraging Raman spectroscopy for optimized mammalian cell culture manufacturing.

Maintaining consistent quality in the manufacturing of biotherapeutic proteins in mammalian cell culture is challenging, with unplanned deviations cau...

Bacterial keratitis: a global review of current practices, challenges and innovations.

Bacterial keratitis is a major cause of corneal blindness worldwide, with marked differences in clinical presentation and risk factors across regions....

Deep learning analysis of 12-lead electrocardiograms for bloodstream infection prediction: a multi-center validation study.

BACKGROUND: Prompt diagnosis of bloodstream infections (BSIs) is critical for antimicrobial stewardship but hindered by blood culture delays of 48 h o...

Exploring feature limitations in antimicrobial resistance prediction: machine learning and deep learning in A. baumannii.

Antimicrobial resistance phenotype prediction (AMRPP) provides a computational alternative to conventional susceptibility testing. While most studies ...

Differential Effects of Prenatal Depression and Anxiety on Infant Sleep: Dual-Pathway Mechanisms Involving the HPA Axis and the Gut-Brain Axis.

STUDY OBJECTIVES: Prenatal psychological distress is associated with adverse offspring outcomes, including infant sleep disturbances and altered gut m...

Development and external validation of a machine learning prediction model for Epstein-Barr virus-associated hemophagocytic lymphohistiocytosis in children using routine blood parameters: a retrospective cohort study.

BACKGROUND: Epstein-Barr virus (EBV) infection is a common pediatric infectious disease. Infectious mononucleosis (IM) and hemophagocytic lymphohistio...

Development and external validation of an interpretable machine learning model for predicting prolonged postoperative ICU length of stay in coronary artery bypass grafting patients using MIMIC-IV 3.1 and eICU-CRD 2.0.

BACKGROUND: Prolonged postoperative intensive care unit (ICU) length of stay (LOS) after coronary artery bypass grafting (CABG) drives resource use ye...

Molecular, cellular and network mapping of brain structural deviations in patients with Post-COVID19 syndrome.

Post-COVID-19 syndrome encompasses persistent cognitive, neurological, and psychiatric symptoms following SARS-CoV-2 infection, profoundly affecting g...

Machine learning models to predict ICU admission of patients with COPD and depression: A retrospective cohort study.

This study aimed to develop and validate a machine learning (ML)-based predictive model to identify risk factors associated with intensive care unit (...

Genomic scale analysis of assembly-line polyketide synthase diversity and evolution.

Covering: up to 2026Assembly-line polyketide synthases (PKSs) are among the most sophisticated catalysts in nature, responsible for the biosynthesis o...

Deep Learning Assisted Heteroporous Covalent Organic Framework Hydrogels Enable Dual-Mode Tracking and Analysis to Parkinson's Management.

Resting tremor and dopamine dysregulation are closely linked in the pathophysiology of Parkinson's disease (PD), yet detecting their subtle early mani...

Automated Identification of Surgical Site Infections From Electronic Medical Records: Retrospective Observational Predictive Modeling Study.

BACKGROUND: Surgical site infections (SSIs) affect 160,000 to 300,000 patients annually, increasing postoperative mortality, causing significant compl...

NOX4 promotes cardiomyocyte ferroptosis-related injury in septic cardiomyopathy in associated with mitochondrial dysfunction and impaired NRF2 nuclear translocation.

Septic cardiomyopathy is a common early complication of sepsis, and its underlying mechanisms remain incompletely understood. In this study, we integr...