Bacterial Infection

Accelerating antimicrobial stewardship: An AI-CDSS approach to combating multidrug-resistant pathogens in the era of increasing resistance.

OBJECTIVES: The World Health Organization has identified Klebsiella pneumoniae (KP) and Pseudomonas aeruginosa (PA) as significant public health threats owing to high antibiotic resistance. Traditional antibiotic susceptibility testing (AST) methods, crucial for determining the most suitable treatment regimen, typically require approximately 48-96 h (2-4 days) to yield results, including bacterial...

Discovery of naturally inspired antimicrobial peptides using deep learning.

Non-ribosomal peptides (NRPs) are promising lead compounds for novel antibiotics. Bioinformatic mining of silent microbial NRPS gene clusters provide crucial insights for the discovery and de novo design of bioactive peptides. Here, we describe the efficient discovery and antibacterial evaluation of novel peptides inspired by metabolite scaffolds encoded by NRPS gene clusters from 216,408 bacteria...

Active capture-directed bimetallic nanosubstrate for enhanced SERS detection of Staphylococcus aureus by combining strand exchange amplification and wavelength-selective machine learning.

Staphylococcus aureus (S. aureus) is the leading risk factor for food safety and human health. Herein, a novel wavelength-selective machine learning -...

Machine Learning Accelerated Discovery of Antimicrobial Inorganic Nanomaterials.

The growing prevalence of infectious diseases and the increasing threat of bacterial resistance have drawn widespread attention to antimicrobial inorg...

Evolutionary accumulation modeling in AMR: machine learning to infer and predict evolutionary dynamics of multi-drug resistance.

Can we understand and predict the evolutionary pathways by which bacteria acquire multi-drug resistance (MDR)? These questions have substantial potent...

Femtosecond Laser Treatment of Ti Surfaces: Antibacterial Mechanisms and Deep Learning-Based Surface Recognition.

Bacterial infections have been demonstrated to cause the premature failure of implants. A reliable strategy for preserving biocompatibility is to phys...

The Biogeography of Soil Bacteria in Australia Exhibits Greater Resistance to Climate Change Than Fungi.

Soil microorganisms are crucial to ecosystem health, and their composition and distribution are shaped by a range of environmental factors. However, t...

Microbial degradation potential of microplastics in urban river sediments: Assessing and predicting the enrichment of PE/PP-degrading bacteria using SourceTracker and machine learning.

Microplastic mitigation strategies that adapt to various actual aquatic environments require the ability to predict their microbial degradation potent...

An anatomically enhanced and clinically validated framework for lung abnormality classification using deep features and KL divergence.

Detecting lung abnormalities via chest X-rays is challenging due to understated tissue variations often ignored by traditional methods. Augmentation t...

Intelligent FA/FNA alternating strategy for nitrite-oxidizing bacteria inhibition: Data-driven prediction and process control.

Alternating treatment with free ammonia (FA) and free nitrous acid (FNA) is an effective strategy to inhibit nitrite-oxidizing bacteria (NOB) in parti...

XenoBug: machine learning-based tool to predict pollutant-degrading enzymes from environmental metagenomes.

Application of machine learning-based methods to identify novel bacterial enzymes capable of degrading a wide range of xenobiotics offers enormous pot...

Paving the way for bacteria-based drug delivery: biohybrid microrobots emerging from microrobotics and synthetic biology.

Advances in microrobotics and synthetic biology are paving the way for innovative solutions to long-standing challenges in drug delivery. Both fields ...

Applying machine learning with MobileNetV2 model for rapid screening of vaginal discharge samples in vaginitis diagnosis.

Vaginitis is a prevalent gynecological condition that impacts women's quality of life, with most women likely to experience it at least once. Traditio...

Machine Learning and Deep Learning Techniques for Prediction and Diagnosis of Leptospirosis: Systematic Literature Review.

BACKGROUND: Leptospirosis, a zoonotic disease caused by Leptospira bacteria, continues to pose significant public health risks, particularly in tropic...

Accurate prediction of virulence factors using pre-train protein language model and ensemble learning.

BACKGROUND: As bacterial pathogens develop increasing resistance to antibiotics, strategies targeting virulence factors (VFs) have emerged as a promis...

GNNs and ensemble models enhance the prediction of new sRNA-mRNA interactions in unseen conditions.

Bacterial small RNAs (sRNAs) are pivotal in post-transcriptional regulation, affecting functions like virulence, metabolism, and gene expression by bi...

RABiTPy: an open-source Python software for rapid, AI-powered bacterial tracking and analysis.

Bacterial tracking is crucial for understanding the mechanisms governing motility, chemotaxis, cell division, biofilm formation, and pathogenesis. Alt...

Prediction of airborne bacterial concentrations and identification of critical factors in contaminated waste facilities: Insights into interpretable machine learning models.

The efficient prediction of airborne bacterial concentrations is crucial for better understanding and management of environmental sanitation risks in ...

Modeling heterogeneity, commitment, and memory of bacterial spore germination.

Spores of bacteria are metabolically dormant, resistant to microbicides, and vectors of food spoilage and diseases and survive for years in their dorm...

The gut microbiome and metabolome in children with a first febrile urinary tract infection: a pilot study.

BACKGROUND: Urinary tract infection (UTI) is a common bacterial infection in the pediatric population. Febrile urinary tract infection (fUTI) can lead...