Sepsis

Cascade Sensor Array Involving Nanozyme with Glycoside Hydrolase-like Activity for the Accurate Identification of Six Aminoglycosides.

Developed sensor arrays commonly rely on directly sensing the effects of antibiotics on oxidoreductase-like activity, which has faced significant challenges in discriminating between structurally similar antibiotics. In this study, we constructed a hydrolysis-cascade sensor array in which hydrolase-like activity decoding was employed to amplify the chemical features input into the sensor array, th...

Deep learning-enabled discovery of antibiotics effective against Neisseria gonorrhoeae.

Neisseria gonorrhoeae is a common Gram-negative pathogen with increasing resistance to all recommended antibiotics. There is a critical need to improve the efficiency of the antibiotic hit discovery process to replenish the drug development pipeline. Here, we show that deep learning models can augment high-throughput screens to identify readily available molecules with narrow-spectrum activity aga...

From development to clinical practice: deployment of an interoperable and secure ML-based CDSS to aid in the early detection of sepsis.

Recent research has increasingly focused on machine learning (ML) models for early disease prediction, yet practical frameworks for integrating these ...

Surface-enhanced Raman spectroscopy and machine learning based profiling of β-lactam antibiotic-induced biochemical responses in methicillin-resistant and methicillin-susceptible Staphylococcus aureus strains.

The global escalation of antimicrobial resistance in Staphylococcus aureus (S. aureus) necessitates rapid analytical tools to reliably distinguish bet...

Hybrid deep learning-based rapid broad-Spectrum antimicrobial susceptibility prediction from whole-genome assemblies.

Antimicrobial resistance (AMR) is a global public health threat. Mortality and poor treatment outcomes are the key consequences of AMR. Conventional a...

An Integrated Rotation-Programmed and Gravity-Driven Microfluidic Platform for Direct Bacterial Detection from Whole Blood.

For the precise molecular detection of bloodstream infection, sample processing is critical, as it involves purifying pathogenic DNA to circumvent the...

Local infection signs at the catheter-insertion site: a large prospective multicentric cohort study.

OBJECTIVES: To describe the epidemiology of local signs at intravascular catheter insertion sites across catheter types and care settings, to compare ...

Predictive variables for early detection of sepsis in adults admitted to intensive care units: protocol for a systematic review.

INTRODUCTION: Sepsis is a life-threatening condition in intensive care units (ICUs), where any delay in diagnosis and treatment can lead to organ dysf...

Aligning neonatal sepsis triage diagnostics with WHO target product profiles in low- and middle-income countries.

Neonatal sepsis is a leading cause of infant morbidity and mortality in low- and middle-income countries (LMICs), yet despite this, progress in the de...

Optimizing Extracorporeal Cardiopulmonary Resuscitation Candidate Selection in out-of-Hospital Cardiac Arrest: A Machine-Learning Individualized Treatment Effect Approach Versus Rule-Based Criteria.

BACKGROUND: Extracorporeal cardiopulmonary resuscitation (ECPR) has demonstrated survival benefit in selected patients with out-of-hospital cardiac ar...

The gut microbiome in preterm infants: development, dysbiosis, and disease implications.

SUMMARYPreterm infants face a unique trajectory of gut microbiome assembly, shaped by the convergence of physiological immaturity, necessary clinical ...

Predicting survival in extremely preterm infants: A multicenter machine learning study from Spain.

BACKGROUND AND OBJECTIVE: Accurately predicting outcomes in extremely preterm infants remains a major challenge in neonatology. Traditional scores suc...

Trends in vibrational spectroscopy on optical waveguides.

Vibrational spectroscopy, due to its inherent specificity in providing a spectral "fingerprint" of molecular composition, is an important tool to iden...

Multi-emission metal-organic frameworks for ratiometric detection of tetracycline antibiotics.

The overuse of tetracycline (TC) antibiotics causes food residues that threaten human health. This study introduces a Zr-based dual-ligand fluorescent...

Lactate-Associated Gene Signatures as Predictors: A Comprehensive Analysis of Immune Profiles in Sepsis.

BackgroundSepsis is a complex disorder characterized by a dysregulated immune response to infection. Elevated lactic acid levels and lactylation modif...

Integrative transcriptomic and bioinformatic analyses predict candidate EMT-related genes in sepsis-associated acute lung injury.

Sepsis-associated acute lung injury (sepsis-ALI) is a complex pathological condition; its underlying mechanisms remain mostly obscure. Thus, in this s...

Reproducibility of AI-Generated Antibiotic Recommendations in Standardized Clinical Scenarios: A Proof-of-Concept Experimental Study.

BACKGROUND: Artificial intelligence (AI) tools are increasingly used to support antimicrobial prescribing, but most published literature focuses on ac...

Multifunctional Bioengineered Scaffolds and Adjunct Therapeutic Strategies for Diabetic Foot Ulcers.

Diabetic foot ulcers (DFUs) are chronic, non-healing wounds that affect up to 34% of diabetic patients. DFUs are complicated by infection in nearly 60...

A multidimensional risk prediction framework for malignant intestinal obstruction based on machine learning: computational model development and clinical validation.

Malignant intestinal obstruction (MIO) is a severe complication of advanced cancer. Traditional static assessment models struggle to capture its dynam...

Early cell-wall stress signatures enable 20-min ATR-FTIR discrimination of MRSA and MSSA.

Rapid identification of methicillin-resistant Staphylococcus aureus (MRSA) is crucial for early optimization of antibiotic treatment, but current rout...