Bacterial Infection

The interplay between Peptostreptococcus and Fusobacterium as novel signatures in colorectal cancer recurrence.

BACKGROUND: After resection surgery, recurrence occurs in more than 30% of colorectal cancer (CRC) patients. Previous studies have highlighted the role of the gut microbiota in CRC initiation and progression; however, the microbial features associated with recurrence remain not completely understood. In particular, integrated multi-omics biomarkers, the interactions between microorganisms, as well...

Development and validation of an artificial intelligence-based model for predicting teicoplanin plasma concentrations in intensive care unit patients with pulmonary infections: a retrospective study.

INTRODUCTION: Teicoplanin is widely used to treat pulmonary infections, particularly in critically ill patients with gram-positive bacterial infections. However, its plasma concentration varies substantially between individuals owing to heterogeneity in renal function, comorbidities, and concomitant medications, leading to subtherapeutic or toxic exposures. Therapeutic drug monitoring (TDM) remain...

Unraveling the diagnostic and prognostic signatures of oral microbiota in head and neck cancer.

BACKGROUND: Head and neck cancer, predominantly squamous cell carcinoma, has emerged as a significant global health concern. Growing evidence has esta...

Novel Deep-Learning Unsupervised Domain Adaptation Method for Mitigating Batch, Strain, and Instrument Variations to Enhance Raman Spectroscopy-Based Bacterial Pathogen Identification.

The escalating threat of antibiotic resistance demands a rapid and accurate pathogen identification. While Raman spectroscopy combined with deep learn...

Single-Cell Nanomotion and Machine Learning for Parallel Bacterial Identification and Antibiotic Screening.

Rapid and accurate identification of bacterial infections and their resistance to antibiotics is critical to effective clinical decision-making and co...

Response of the authors to the letter to the editor regarding "Development of a machine learning-based predictive model for long-term adverse outcomes in neonatal bacterial meningitis".

Dietary exposure to antimicrobial residues in eggs: Traceability-driven risk heterogeneity and national monitoring optimization in China.

Egg production is growing rapidly to meet global protein demand, but in low- and middle-income countries, heavy antimicrobial use, fragmented supply c...

Engineering Antimicrobial Peptides via Motif Assembly for Combating Multidrug-Resistant Pathogens.

Hybridization of common motifs from known antimicrobial peptides (AMPs) is a promising strategy for designing a new class of antimicrobial agents with...

Letter to the editor regarding "Development of a machine learning-based predictive model for long-term adverse outcomes in neonatal bacterial meningitis".

Precisely Identifying Growth Phases of Living Bacteria using Open-Set Deep Learning-Driven Single-Cell Raman Spectroscopy.

Owing to population cellular heterogeneity, it is still challenging to identify and determine the growth phases of spore-forming bacterial cells from ...

RaMoA: Raman Microspectroscopy and Deep Learning for the Classification of Antimicrobial Mechanism of Action.

We propose an innovative technology based on the combination of Raman microspectroscopy and deep learning to classify the Mechanism of Action (MoA) of...

FTIR spectroscopy of peripheral blood mononuclear cells and machine learning: Spectral biomarkers for bacteremia, focal bacterial, and viral infections.

The rapid and accurate differentiation of bacteremia, focal bacterial infections (FBI), and viral illnesses in febrile immunocompromised patients is a...

A Multidisciplinary Approach for Predicting the Microbiological Spoilage of Chicken Breast Fillets due to Cold-chain Disruption.

Cold-chain disruptions during storage and distribution of raw poultry can significantly reduce product shelf-life and safety. This study evaluated the...

Identifying Temporal Drivers for Microbial Community Assembly in Wastewater Treatment by Stochastic Physics-Informed Deep Learning Based on Limited-View and Sparsely Sampled Data.

Microbial community assembly (MCA) is the key to biological wastewater treatment by dynamically shaping the functional populations responsible for pol...

Rapid Proteome-Wide Discovery of Protein-Protein Interactions With ppIRIS.

Protein-protein interactions (PPIs) are central to cellular processes and host-pathogen dynamics across all domains of life, yet comprehensive interac...

Targeting metabolism to combat anticancer and antibacterial drug resistance.

Drug resistance is a major challenge in cancer and infectious diseases, requiring innovative solutions. Recent research suggests that bacteria and can...

Fingerprinting Fluorescent In Situ Hybridization Enables Multiplexed Identification of Pathogenic Bacteria.

Fluorescence in situ hybridization (FISH) is a highly specific technique for pathogenic bacteria detection that requires no culturing and provides sim...

Culture-Free Microfluidics for Ultra-Rapid Antimicrobial Susceptibility Testing with AI in Resource-Limited Settings.

The misuse of antibiotics has accelerated the rise of antimicrobial resistance (AMR), particularly in resource-limited regions, posing a critical thre...

MoCETSE: A mixture-of-convolutional experts and transformer-based model for predicting Gram-negative bacterial secreted effectors.

Identifying effector proteins of secretion systems in Gram-negative bacteria is crucial for deciphering their pathogenic mechanisms and guiding the de...

Latent Supervision: A Method for Improved Performance and Calibration of Machine Learning Classification Models in Ophthalmology.

PURPOSE: Standard supervised learning assumes deterministic labels (e.g., positive or negative, present or absent), neglecting the diagnostic uncertai...