AIMC Topic: Staphylococcus aureus

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Machine learning and genetic algorithm-guided directed evolution for the development of antimicrobial peptides.

Journal of advanced research
INTRODUCTION: Antimicrobial peptides (AMPs) are valuable alternatives to traditional antibiotics, possess a variety of potent biological activities and exhibit immunomodulatory effects that alleviate difficult-to-treat infections. Clarifying the stru...

Predicting S. aureus antimicrobial resistance with interpretable genomic space maps.

Molecular informatics
Increasing antimicrobial resistance (AMR) represents a global healthcare threat. To decrease the spread of AMR and associated mortality, methods for rapid selection of optimal antibiotic treatment are urgently needed. Machine learning (ML) models bas...

MAC-ErrorReads: machine learning-assisted classifier for filtering erroneous NGS reads.

BMC bioinformatics
BACKGROUND: The rapid advancement of next-generation sequencing (NGS) machines in terms of speed and affordability has led to the generation of a massive amount of biological data at the expense of data quality as errors become more prevalent. This i...

MI-DenseCFNet: deep learning-based multimodal diagnosis models for Aureus and Aspergillus pneumonia.

European radiology
OBJECTIVE: To build and merge a diagnostic model called multi-input DenseNet fused with clinical features (MI-DenseCFNet) for discriminating between Staphylococcus aureus pneumonia (SAP) and Aspergillus pneumonia (ASP) and to evaluate the significant...

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...

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 enhanced multiplex detection of viable foodborne pathogens in digital microfluidic chip.

Biosensors & bioelectronics
Culture plating is worldwide accepted as the gold standard for quantifying viable foodborne pathogens. However, it is time-consuming (1-2 days) and requires specialized laboratory and personnel. This study reported a deep learning enhanced digital mi...

Methyl cellulose/okra mucilage composite films, functionalized with Hypericum perforatum oil and gentamicin, as a potential wound dressing.

International journal of biological macromolecules
There is a growing demand for the development of functional wound dressings enriched with bioactive natural compounds to improve the quality of life of the population by accelerating the healing process of chronic wounds. In this regard, a functional...

Bacterial metabolism-triggered-chemiluminescence-based point-of-care testing platform for sensitive detection and photothermal inactivation of Staphylococcus aureus.

Analytica chimica acta
Post-operative pathogenic infections in liver transplantation seriously threaten human health. It is essential to develop novel methods for the highly sensitive and rapid detection of Staphylococcus aureus (S. aureus). Interestingly, the combination ...

Identification of inhibitors for Agr quorum sensing system of Staphylococcus aureus by machine learning, pharmacophore modeling, and molecular dynamics approaches.

Journal of molecular modeling
CONTEXT: Staphylococcus aureus is a highly pathogenic organism that is the most common cause of postoperative complications as well as severe infections like bacteremia and infective endocarditis. By mediating the formation of biofilms and the expres...