AIMC Topic: Enterococcus faecium

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Explainable deep learning and virtual evolution identifies antimicrobial peptides with activity against multidrug-resistant human pathogens.

Nature microbiology Jan 17, 2025
Artificial intelligence (AI) is a promising approach to identify new antimicrobial compounds in diverse microbial species. Here we developed an AI-based, explainable deep learning model, EvoGradient, that predicts the potency of antimicrobial peptide...
Drug Resistance, Multiple, Bacterial Mice Klebsiella pneumoniae Deep Learning Microbial Sensitivity Tests Acinetobacter baumannii Enterococcus faecium Antimicrobial Peptides Bacteria Escherichia coli Anti-Bacterial Agents Animals Humans
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Identification of Staphylococcus aureus, Enterococcus faecium, Klebsiella pneumoniae, Pseudomonas aeruginosa and Acinetobacter baumannii from Raman spectra by Artificial Intelligent Raman Detection and Identification System (AIRDIS) with machine learning.

Journal of microbiology, immunology, and infection = Wei mian yu gan ran za zhi Nov 29, 2024
BACKGROUND: Rapid and accurate identification of bacteria is required in order to develop effective treatment strategies. Traditional culture-based methods are time-consuming, while MALDI-TOF MS is expensive. The Raman spectroscopy, due to its relati...
Humans Spectrum Analysis, Raman Acinetobacter baumannii Enterococcus faecium Staphylococcus aureus Pseudomonas aeruginosa Machine Learning Klebsiella pneumoniae
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VacSol-ML(ESKAPE) Machine learning empowering vaccine antigen prediction for ESKAPE pathogens.

Vaccine Aug 9, 2024
The ESKAPE family, comprising Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Enterobacter spp., poses a significant global threat due to their heightened virulence and extensiv...
Antigens, Bacterial Enterococcus faecium Vaccinology Enterobacter Bacterial Vaccines Staphylococcus aureus Pseudomonas aeruginosa Acinetobacter baumannii Klebsiella pneumoniae Computational Biology Humans Machine Learning
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Machine Learning Assisted MALDI Mass Spectrometry for Rapid Antimicrobial Resistance Prediction in Clinicals.

Analytical chemistry Aug 3, 2024
Antimicrobial susceptibility testing (AST) plays a critical role in assessing the resistance of individual microbial isolates and determining appropriate antimicrobial therapeutics in a timely manner. However, conventional AST normally takes up to 72...
Anti-Bacterial Agents Drug Resistance, Bacterial Microbial Sensitivity Tests Humans Machine Learning Enterococcus faecium Vancomycin-Resistant Enterococci Support Vector Machine Spectrometry, Mass, Matrix-Assisted Laser Desorption-Ionization
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Identification of key drivers of antimicrobial resistance in using machine learning.

Canadian journal of microbiology Jul 30, 2024
With antimicrobial resistance (AMR) rapidly evolving in pathogens, quick and accurate identification of genetic determinants of phenotypic resistance is essential for improving surveillance, stewardship, and clinical mitigation. Machine learning (ML)...
Machine Learning Anti-Bacterial Agents Humans Gram-Positive Bacterial Infections Drug Resistance, Bacterial Genome, Bacterial Bacterial Proteins Enterococcus faecalis Microbial Sensitivity Tests Enterococcus faecium Plasmids
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Modeling Antibacterial Activity with Machine Learning and Fusion of Chemical Structure Information with Microorganism Metabolic Networks.

Journal of chemical information and modeling Mar 4, 2019
Predicting the activity of new chemical compounds over pathogenic microorganisms with different metabolic reaction networks (MRN ) is an important goal due to the different susceptibility to antibiotics. The ChEMBL database contains >160 000 outcomes...
Acinetobacter baumannii Enterococcus faecium Microbial Sensitivity Tests Metabolic Networks and Pathways Models, Biological Machine Learning Anti-Bacterial Agents
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Characterization of fecal vancomycin-resistant enterococci with acquired and intrinsic resistance mechanisms in wild animals, Spain.

Microbial ecology Jul 21, 2015
The objectives were to evaluate the presence of vancomycin-resistant enterococci with acquired (VRE-a) and intrinsic (VRE-i) resistance mechanisms in fecal samples from different wild animals, and analyze their phenotypes and genotypes of antimicrobi...
Microbial Sensitivity Tests Ampicillin Resistance Tetracycline Drug Resistance, Multiple, Bacterial Multilocus Sequence Typing Tetracycline Resistance Carbon-Oxygen Ligases Feces Spain Vancomycin-Resistant Enterococci Enterococcus faecium Animals Vancomycin Falconiformes Aminoglycosides Animals, Wild Bacterial Proteins Sus scrofa Ampicillin Galliformes
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