AIMC Topic: Anti-Bacterial Agents

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Artificial intelligence in protein-based detection and inhibition of AMR pathways.

Journal of computer-aided molecular design
Antimicrobial Resistance (AMR) is a global concern demanding high-throughput and precise AMR surveillance strategies. This review provides a comprehensive list of Artificial Intelligence (AI) driven frameworks widely employed in the early detection, ...

Time-Lapse Deep Learning for Single-Cell Subcellular Structural Phenotypic Antimicrobial Susceptibility Testing.

Analytical chemistry
Antimicrobial resistance (AMR) is a global health concern that complicates the effective treatment of infections, resulting in an increased severity of illness and elevated healthcare costs. Traditional phenotypic antimicrobial susceptibility testing...

Toxicity assessment of doxycycline-aided artificial intelligence-assisted drug design targeting candidate 16S rRNA methyltransferase gene.

BMC pharmacology & toxicology
BACKGROUND: The misfunction of the protein 16SrRNA methyltransferase can result in Urinary tract infections (UTI), Gastrointestinal (GI) infections, sepsis, pneumonia, and wound infections; various tactics are used to lessen the fatal consequences. I...

AI-Enhanced Rapid SERS Screening of Trace Quinolone Antibiotics across the Source-Pathway-Sink Ecosystem.

Analytical chemistry
The overused quinolone antibiotics in animal husbandry and clinical medicine pose a growing threat for global health as they enter ecosystem via agricultural discharge and medical wastewater. Consequently, risk assessment for environmental and human ...

Impact of COVID-19 isolation measures on ICU microbial resistance dynamics: simulation-based statistical modeling analysis.

Antimicrobial resistance and infection control
BACKGROUND: The transmission of antibiotic-resistant bacteria in intensive care units (ICUs) poses a significant challenge to infection control and patient safety. While direct patient-to-patient transmission is well documented, the relative contribu...

Comparative assessment of annotation tools reveals critical antimicrobial resistance knowledge gaps in Klebsiella pneumoniae.

Scientific reports
Bacterial antimicrobial resistance (AMR) poses a significant public health threat. The increase of both global awareness and affordable whole genome sequencing has yielded an ever-growing collection of bacterial genome sequence datasets and correspon...

CarbaDetector: a machine learning model for detecting carbapenemase-producing Enterobacterales from disk diffusion tests.

Nature communications
Carbapenemase-producing Enterobacterales (CPE) are considered among the highest threats to global health by WHO. Their detection is difficult and time-consuming. We developed a random-forest machine learning (ML) model, CarbaDetector, to predict carb...

Label-free phenotypic antimicrobial susceptibility testing on microfluidic platforms: a review of advances and translation.

Mikrochimica acta
The escalating global threat of antimicrobial resistance (AMR) necessitates a paradigm shift towards rapid and scalable diagnostic technologies. Conventional antimicrobial susceptibility testing (AST) methods, while reliable, are hindered by prolonge...

Homogeneous multi-antibiotics residual identification in various actual water via SERS spectra multilayer perceptron algorithm combined with Gaussian kernel density estimation data augmentation.

Analytica chimica acta
BACKGROUND: Antibiotic residues pose varying degrees of potential hazards to the water environment and human health due to their diverse types. Surface-enhanced Raman spectroscopy (SERS) technology can achieve rapid detection of various antibiotic re...

Identifying Structure-Activity Relationships for Cyanine-Derived Antibiotics Using Machine Learning and Commercial Large Language Models.

Journal of chemical information and modeling
Understanding the structure-activity relationship (SAR) of antibiotic scaffolds is crucial for the development of antibiotics to counter the growing crisis of antimicrobial resistant bacteria. However, an overwhelming space of structural features imp...