AIMC Topic: Pseudomonas aeruginosa
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Antimicrobial Peptides Design Using Deep Learning and Rational Modifications: Activity in Bacteria, Candida albicans, and Cancer Cells.
Current microbiology
Jul 11, 2025
Resistance to antimicrobial agents has become a global threat, estimated to cause 10-million deaths annually by 2050. Antimicrobial peptides are emerging as an alternative and offer advantages over traditional antibiotics. Antimicrobial peptides gene...
Combinatorial discovery of microtopographical landscapes that resist biofilm formation through quorum sensing mediated autolubrication.
Nature communications
Jun 18, 2025
Bio-instructive materials that intrinsically inhibit biofilm formation have significant anti-biofouling potential in industrial and healthcare settings. Since bacterial surface attachment is sensitive to surface topography, we experimentally surveyed...
Predicting carbapenem-resistant Pseudomonas aeruginosa infection risk using XGBoost model and explainability.
Scientific reports
Jun 5, 2025
The prevalence and spread of carbapenem-resistant Pseudomonas aeruginosa (CRPA) is a global public health problem. This study aims to identify the risk factors of CRPA infection and construct a machine learning model to provide a prediction tool for ...
Multi-omics profiling of cross-resistance between ceftazidime-avibactam and meropenem identifies common and strain-specific mechanisms in clinical isolates.
mBio
Jun 4, 2025
is a highly versatile and resilient pathogen that can infect different tissues and rapidly develop resistance to multiple drugs. Ceftazidime-avibactam (CZA) is an antibiotic often used to treat multidrug-resistant infections; however, the knowledge ...
Development and evaluation of a direct disk diffusion, rapid antimicrobial susceptibility testing method from blood culture positive for Gram-negative bacilli using rapid molecular testing and microbiology laboratory automation.
Microbiology spectrum
May 15, 2025
Rapid antimicrobial susceptibility testing (RAST) using disk diffusion (DD) from positive blood cultures (BC) can aid initiation of effective antimicrobial therapy. Rapid molecular blood culture identification panels (BCID) and microbiology laborator...
Performance and hypothetical clinical impact of an mNGS-based machine learning model for antimicrobial susceptibility prediction of five ESKAPEE bacteria.
Microbiology spectrum
Apr 17, 2025
UNLABELLED: Antimicrobial resistance is an escalating global health crisis, underscoring the urgent need for timely and targeted therapies to ensure effective clinical treatment. We developed a machine learning model based on metagenomic next-generat...
Measuring water pollution effects on antimicrobial resistance through explainable artificial intelligence.
Environmental pollution (Barking, Essex : 1987)
Jan 7, 2025
Antimicrobial resistance refers to the ability of pathogens to develop resistance to drugs designed to eliminate them, making the infections they cause more difficult to treat and increasing the likelihood of disease diffusion and mortality. As such,...
High-content imaging and deep learning-driven detection of infectious bacteria in wounds.
Bioprocess and biosystems engineering
Dec 2, 2024
Fast and accurate detection of infectious bacteria in wounds is crucial for effective clinical treatment. However, traditional methods take over 24 h to yield results, which is inadequate for urgent clinical needs. Here, we introduce a deep learning-...
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...
Antimicrobial efficacy of an experimental UV-C robot in controlled conditions and in a real hospital scenario.
The Journal of hospital infection
Nov 19, 2024
BACKGROUND: Among no-touch automated disinfection devices, ultraviolet-C (UV-C) radiation has been proven to be one of the most effective against a broad spectrum of micro-organisms causing healthcare-associated infections.
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