Bacterial Infection

Quaternized polysaccharides: A focused review on molecular engineering, antimicrobial mechanisms, and advanced applications.

The escalating threat of antibiotic resistance has intensified the search for sustainable antimicrobial alternatives. Quaternized polysaccharides, a class of cationic biopolymers derived from renewable biomass, offer significant potential due to their potent broad-spectrum activity, unique non-specific mechanisms, and excellent biocompatibility. This review systematically elucidates the molecular ...

Mapping the subgingival HerBiome and HisBiome over the human healthspan.

BACKGROUND: Understanding the intricate relationship between sex, age, and the oral microbiome is crucial for deciphering the onset and progression of numerous age-related oral and systemic diseases. METHODS: Subgingival plaque was collected from 781 periodontally and systemically healthy females and 160 males spanning 0 to 80 years. 16S amplicon sequencing was performed. 80 million sequences were...

Early detection of ampicillin susceptibility in Enterococcus faecium with MALDI-TOF MS and machine learning.

BACKGROUND: Enterococcus faecium can cause severe infections and is often resistant to the first-line antibiotic ampicillin. Consequently, clinicians ...

Biophysical properties and phenotypes of cell clusters detached from Staphylococcus epidermidis biofilms after matrix-targeted disruption.

Bacterial cells detached from Staphylococcus epidermidis biofilms are found to release predominantly as small oblate clusters (∼1.9 µm) in both untrea...

Predicting oil contamination in water using machine learning on microbial compositions.

We present a compact and generative machine-learning framework that predicts oil contamination based on microbial community compositions from experime...

Piperacillin/tazobactam plus erythromycin improves clinical outcomes in AECOPD with bacterial lower respiratory tract infections: a retrospective cohort study.

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 rol...

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 infection...

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...