AIMC Topic: Methicillin-Resistant Staphylococcus aureus

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Machine Learning-Assisted High-Throughput Screening for Anti-MRSA Compounds.

IEEE/ACM transactions on computational biology and bioinformatics
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
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
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
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
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...

antibacterial activity of antiretroviral drugs on key commensal bacteria from the human microbiota.

Frontiers in cellular and infection microbiology
INTRODUCTION: Antiretroviral therapy has improved life expectancy in HIV-infected patients. However, people living with HIV under antiretroviral therapy are at higher risks of developing chronic complications and acquiring multidrug resistant bacteri...

Investigating the bispecific lead compounds against methicillin-resistant SarA and CrtM using machine learning and molecular dynamics approach.

Journal of biomolecular structure & dynamics
Methicillin-resistant Staphylococcus aureus (MRSA) is a notorious pathogen that has emerged as a serious global health concern over the past few decades. Staphylococcal accessory regulator A (SarA) and 4,4'-diapophytoene synthase (CrtM) play a crucia...

Discovery of a structural class of antibiotics with explainable deep learning.

Nature
The discovery of novel structural classes of antibiotics is urgently needed to address the ongoing antibiotic resistance crisis. Deep learning approaches have aided in exploring chemical spaces; these typically use black box models and do not provide...

Deep Learning-Assisted Surface-Enhanced Raman Scattering for Rapid Bacterial Identification.

ACS applied materials & interfaces
Bloodstream infection (BSI) is characterized by the presence of viable microorganisms in the bloodstream and may induce systemic immune responses. Early and appropriate antibiotic usage is crucial to effectively treating BSI. However, conventional cu...

S. aureus and IgE-mediated diseases: pilot or copilot? A narrative review.

Expert review of clinical immunology
INTRODUCTION: is a major opportunistic pathogen that has been implicated in the pathogenesis of several chronic inflammatory diseases including bronchial asthma, chronic rhinosinusitis with nasal polyps (CRSwNP), chronic spontaneous urticaria (CSU),...