AIMC Topic: Methicillin-Resistant Staphylococcus aureus
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Rapid Screening of Methicillin-Resistant Using MALDI-TOF MS and Machine Learning: A Randomized, Multicenter Study.
Analytical chemistry
Jul 15, 2025
Methicillin-resistant (MRSA) is a major cause of healthcare-associated infections including bacteremia. The rapid detection of MRSA is essential for prompt treatment and improved outcomes. However, traditional MRSA screening and confirmatory tests b...
Microrobots for Antibiotic-Resistant Skin Colony Eradication.
ACS applied materials & interfaces
Jun 25, 2025
Self-propelled nano- and micromachines have immense potential as autonomous seek-and-act devices in biomedical applications. In this study, we present microrobots constructed with inherently biocompatible materials and propulsion systems tailored to ...
Discovery of CYP1A1 Inhibitors for Host-Directed Therapy against Sepsis.
Journal of medicinal chemistry
May 29, 2025
Bacterial sepsis remains a leading cause of death globally, exacerbated by the rise of multidrug resistance (MDR). Host-directed therapy (HDT) has emerged as a promising nonantibiotic approach to combat infections; thus, multiple HDT targets have bee...
Defining the biomarkers in anti-MRSA fractions of soil Streptomycetes by multivariate analysis.
Antonie van Leeuwenhoek
May 10, 2025
Methicillin-resistant Staphylococcus aureus (MRSA) is one of the most alarming antibiotic-resistant pathogens causing nosocomial and community-acquired infections. Actinomycetes, particularly Streptomycetes, have historically been a major source of n...
Machine learning-based prediction model for patients with recurrent Staphylococcus aureus bacteremia.
BMC medical informatics and decision making
Feb 24, 2025
BACKGROUND: Staphylococcus aureus bacteremia (SAB) remains a significant contributor to both community-acquired and healthcare-associated bloodstream infections. SAB exhibits a high recurrence rate and mortality rate, leading to numerous clinical tre...
Machine Learning-Assisted High-Throughput Screening for Anti-MRSA Compounds.
IEEE/ACM transactions on computational biology and bioinformatics
Dec 10, 2024
BACKGROUND: Antimicrobial resistance is a major public health threat, and new agents are needed. Computational approaches have been proposed to reduce the cost and time needed for compound screening.
Novel active Trp- and Arg-rich antimicrobial peptides with high solubility and low red blood cell toxicity designed using machine learning tools.
International journal of antimicrobial agents
Dec 5, 2024
BACKGROUND: Given the rising number of multidrug-resistant (MDR) bacteria, there is a need to design synthetic antimicrobial peptides (AMPs) that are highly active, non-hemolytic, and highly soluble. Machine learning tools allow the straightforward i...
Artificial intelligence-driven quantification of antibiotic-resistant Bacteria in food by color-encoded multiplex hydrogel digital LAMP.
Food chemistry
Dec 4, 2024
Antibiotic-resistant bacteria pose considerable risks to global health, particularly through transmission in the food chain. Herein, we developed the artificial intelligence-driven quantification of antibiotic-resistant bacteria in food using a color...
Deep learning model for personalized prediction of positive MRSA culture using time-series electronic health records.
Nature communications
Mar 6, 2024
Methicillin-resistant Staphylococcus aureus (MRSA) poses significant morbidity and mortality in hospitals. Rapid, accurate risk stratification of MRSA is crucial for optimizing antibiotic therapy. Our study introduced a deep learning model, PyTorch_E...
Effect of palladium(II) complexes on NorA efflux pump inhibition and resensitization of fluoroquinolone-resistant : and approach.
Frontiers in cellular and infection microbiology
Jan 15, 2024
leads to diverse infections, and their treatment relies on the use of antibiotics. Nevertheless, the rise of antibiotic resistance poses an escalating challenge and various mechanisms contribute to antibiotic resistance, including modifications to d...
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