Bacterial Infection

An update on experimental to large-scale production of bacteriophages against superbugs: a review.

The escalating problem of antibiotic resistance has sparked renewed interest in bacteriophages (phages) as potential substitutes for conventional antibiotics in treating infectious diseases, improving food safety, and advancing sustainable agriculture. The key phage research processes, such as host range, burst size, and environmental stability tests, strongly influence phage production processes....

A Machine Learning Approach to Microcalorimetric Pattern Classification of Pathogens in Synovial Fluid.

Isothermal microcalorimetry (IMC) is a promising tool for diagnosing periprosthetic joint infection (PJI), based on real-time measurement of growth-related heat production of pathogens, and faster than conventional microbial cultures. However, the feasibility of identifying specific pathogens in clinical samples using IMC has yet to be proven. This study implements machine learning and transfer le...

Computational exploration of global venoms for antimicrobial discovery with Venomics artificial intelligence.

The rise of antibiotic-resistant pathogens, particularly gram-negative bacteria, highlights the urgent need for novel therapeutics. Drug-resistant inf...

Machine learning-selected minimal features drive high-accuracy rule-based antibiotic susceptibility predictions for via metagenomic sequencing.

Antimicrobial resistance (AMR) represents a critical global health challenge, demanding rapid and accurate antimicrobial susceptibility testing (AST) ...

Antimicrobial Peptides Design Using Deep Learning and Rational Modifications: Activity in Bacteria, Candida albicans, and Cancer Cells.

Resistance to antimicrobial agents has become a global threat, estimated to cause 10-million deaths annually by 2050. Antimicrobial peptides are emerg...

Improving meningitis surveillance and diagnosis with machine learning: Insights from São Paulo.

INTRODUCTION: Meningitis, an inflammatory condition of the membranes surrounding the brain and spinal cord, can be caused by various agents. Bacterial...

Inhibiting heme piracy by pathogenic Escherichia coli using de novo-designed proteins.

Iron is an essential nutrient for most bacteria and is often growth-limiting during infection, due to the host sequestering free iron as part of the i...

Deep Learning-Assisted Rapid Bacterial Classification Based on Raman Spectroscopy of Bacteria Lysed by Acoustically Driven Fiber-Tip Vibration.

Rapid and accurate identification of bacterial pathogens is critical for effective clinical decision-making and combating antibiotic resistance. Surfa...

Citywide metagenomic surveillance of food centres reveals local microbial signatures and antibiotic resistance gene enrichment.

The distribution of microorganisms in built environments with high human traffic, such as food centres, can potentially have a significant impact on p...

Gut microbiota composition is related to anxiety and aggression scores in companion dogs.

There is mounting evidence for a link between behaviour and the gut microbiome in animal and human health. However, the role of the gut microbiome in ...

CombiANT reader: Deep learning-based automatic image processing tool to robustly quantify antibiotic interactions.

Antibiotic resistance is a severe danger to human health, and combination therapy with several antibiotics has emerged as a viable treatment option fo...

Predicting the impact of climate warming on soil quality using bacteria and machine learning.

In the context of global warming, a substantial portion of global soil is in a state of degradation, which poses a significant threat to biodiversity ...

Automated identification of spotted-fever tick vectors using convolutional neural networks.

Ticks are key ectoparasites for the One Health approach, as they are vectors of pathogens that infect humans, domestic and wild animals. The bacteria ...

Dual-Branch Attention Fusion Network for Pneumonia Detection.

Pneumonia, as a serious respiratory disease caused by bacterial, viral or fungal infections, is an important cause of increased morbidity and mortalit...

Applying machine learning to classify table olives using bacterial metataxonomic data.

In recent years, metataxonomic analysis has been increasingly used to characterize microbial communities in fermented foods. Moreover, advances in bio...

Machine learning for the prediction of urosepsis using electronic health record data.

Urosepsis, a medical condition resulting from the progression of urinary tract infection (UTI), is a leading cause of death in the US. Urosepsis occur...

Unveiling etiology and mortality risks in community-acquired pneumonia: A machine learning approach.

Community-acquired pneumonia (CAP) is associated with high mortality, and accurate diagnosis and risk prediction are essential for improving patient o...

Unlocking microbial community succession and key influencing factors during bioelectrocatalytically-driven simultaneous removal of ammonia nitrogen and sulfate from wastewater.

Ammonia nitrogen (NH-N) and sulfate (SO) removal by Anaerobic ammonium oxidation (Anammox) and sulfate-reducing bacteria (SRB) was studied in dual-cha...

Associations between weight gain, integrase inhibitors antiretroviral agents, and gut microbiome in people living with HIV: a cross-sectional study.

Dolutegravir and bictegravir are second-generation HIV integrase strand transfer inhibitors (INSTIs) that were previously associated with abnormal wei...

Experimentally profiling dielectric properties of Escherichia coli and Staphylococcus aureus by movement velocity and force.

The gradual research in integrating artificial intelligence in the Dielectrophoresis system is rapid since the evolution of AI in every aspect of tech...