Bacterial Infection

Artificial intelligence predicts healthcare workers' antibiotic use intentions from psychological and behavioral measures across multiple theories.

Antimicrobial resistance (AMR) remains a global health priority, partly driven by non-guideline-conc...

Evaluation of a machine learning system for genomic antimicrobial susceptibility determination on a clinically representative test set.

UNLABELLED: Next-generation sequencing is anticipated to transform infectious disease treatment by e...

Stage-wise environmental recovery patterns and cross-domain interactions of planktonic bacterial communities in Zhanjiang Bay following typhoon disturbance.

Typhoon events can abruptly alter local biogeochemical cycles, which may strongly influence microbia...

Bacterial fructan-metabolizing enzymes: modular architecture and biotechnological potential.

Bacterial fructan-metabolizing enzymes exhibit substantial structural and mechanistic diversity to s...

Microbiome-Based Modeling of CAR-T Therapy Response in Lymphoma: Insights From Shotgun Metagenomics Sequencing.

The interplay between the commensal microbiota and the mammalian immune system may influence the out...

The escalating threat of multidrug-resistant organisms: COVID-19 impact, global burden, and the Taiwanese experience.

INTRODUCTION: The COVID-19 pandemic has intensified global health challenges, including a silent but...

Bioinspired Multifunctional Hydrogels for Deep Learning-Enabled Wound pH Visual Monitoring and Treatment.

Smart wound dressings capable of real-time environmental monitoring and therapeutic intervention are...

Infection-targeted innovations in anastomotic leak management: endoscopic advances, antimicrobial biomaterials, and precision strategies.

Anastomotic leakage (AL) is a devastating complication of gastrointestinal surgery and a critical so...

Confidence-based prediction of antibiotic resistance at the patient level.

Rapid and accurate diagnostics of bacterial infections are necessary for efficient treatment of anti...

Optical photothermal infrared (OPTIR) spectroscopy assisted by machine learning for lactic acid bacteria identification at strain level.

Lactic acid bacteria (LAB) are widely used in food, health, and biotechnology sectors, where accurat...

Interpretable Machine Learning Integrates Flavor Classification with Source Attribution for Low-Salt Soy Sauce Optimization.

Low-salt soy sauce (LSS) supports healthier diets but suffers flavor defects compared with high-salt...

Smartphone-based multispectral autofluorescence analysis of bacteria mixtures of staphylococci using convolutional neural network.

Improved screening for pulmonary Kaposi sarcoma in a low-resource setting.

OBJECTIVE: The lung is commonly involved in advanced Kaposi sarcoma (KS) but diagnosis of pulmonary ...

HMRPred: A Machine Learning-Based Web Resource for Identification of Heavy Metal Resistance Proteins.

Heavy metal contamination poses a significant threat to environmental health, agriculture, and micro...

SERS technology helps bacterial inactivation in vivo: including detection, identification, and evaluation.

The problem of bacterial infection and antimicrobial resistance has become a major challenge threate...

Engineered Supramolecular Therapeutics in Development for Combating Antibiotic-Resistant Bacterial Infections.

The emergence of antibiotic-resistant bacteria has rendered conventional antibiotic treatments ineff...

Identification of Chlamydia pneumoniae and NLRP3 inflammasome activation in Alzheimer's disease retina.

Chlamydia pneumoniae is an intracellular bacterium implicated in Alzheimer's disease (AD), but its r...

A machine learning-based prediction model for poor prognosis in sepsis using lymphocyte count: a national, multicenter prospective cohort.

Sepsis-induced immunosuppression leads to poor prognosis. Circulating lymphocyte count (LC), as an e...

Integrative analysis identifies lactylation-related biomarkers in sepsis via bioinformatics and machine learning.

BACKGROUND: Protein lactylation is a novel post-translational modification driven by lactate and has...

Machine learning reveals ecological thresholds and predicts future bacterial community shifts in a chronically eutrophic estuary.

Effectively managing eutrophic estuaries under climate change requires a quantitative understanding ...

A Smartphone-Read, Machine Learning-Enhanced Lanthanide Hydrogel Sensor for Multimodal and On-Site Detection of Kanamycin in Food Safety.

Residual kanamycin from veterinary use poses a persistent threat to environmental safety and public ...