AIMC Topic: Anti-Bacterial Agents

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Rapid identification of the resistance of urinary tract pathogenic bacteria using deep learning-based spectroscopic analysis.

Analytical and bioanalytical chemistry
The resistance of urinary tract pathogenic bacteria to various antibiotics is increasing, which requires the rapid detection of infectious pathogens for accurate and timely antibiotic treatment. Here, we propose a rapid diagnosis strategy for the ant...

Predicting bloodstream infection outcome using machine learning.

Scientific reports
Bloodstream infections (BSI) are a main cause of infectious disease morbidity and mortality worldwide. Early prediction of BSI patients at high risk of poor outcomes is important for earlier decision making and effective patient stratification. We de...

Accelerating antibiotic discovery through artificial intelligence.

Communications biology
By targeting invasive organisms, antibiotics insert themselves into the ancient struggle of the host-pathogen evolutionary arms race. As pathogens evolve tactics for evading antibiotics, therapies decline in efficacy and must be replaced, distinguish...

Delivery mode and perinatal antibiotics influence the predicted metabolic pathways of the gut microbiome.

Scientific reports
Delivery mode and perinatal antibiotics influence gut microbiome composition in children. Most microbiome studies have used the sequencing of the bacterial 16S marker gene but have not reported the metabolic function of the gut microbiome, which may ...

Machine Learning of Bacterial Transcriptomes Reveals Responses Underlying Differential Antibiotic Susceptibility.

mSphere
antibiotic susceptibility testing often fails to accurately predict drug efficacies, in part due to differences in the molecular composition between standardized bacteriologic media and physiological environments within the body. Here, we investiga...

Fast identification of off-target liabilities in early antibiotic discovery with Fourier-transform infrared spectroscopy.

Biotechnology and bioengineering
Structural modifications of known antibiotic scaffolds have kept the upper hand on resistance, but we are on the verge of not having antibiotics for many common infections. Mechanism-based discovery assays reveal novelty, exclude off-target liabiliti...

Performance of Fully Automated Antimicrobial Disk Diffusion Susceptibility Testing Using Copan WASP Colibri Coupled to the Radian In-Line Carousel and Expert System.

Journal of clinical microbiology
The purpose of the present study was to assess the agreement at the categorical level between the Vitek 2 system and the Colibri coupled to the Radian under real routine laboratory conditions. The 675 nonduplicate clinical strains included in this st...

A hybrid machine learning/pharmacokinetic approach outperforms maximum a posteriori Bayesian estimation by selectively flattening model priors.

CPT: pharmacometrics & systems pharmacology
Model-informed precision dosing (MIPD) approaches typically apply maximum a posteriori (MAP) Bayesian estimation to determine individual pharmacokinetic (PK) parameters with the goal of optimizing future dosing regimens. This process combines knowled...

Broad-Spectrum Bactericidal Activity and Remarkable Selectivity of Main-Chain Sulfonium-Containing Polymers with Alternating Sequences.

ACS macro letters
Incorporation of cationic groups into polymers represents one of the most widely used strategies to prepare antibacterial materials. Sulfonium, as a typical cationic moiety, displays potent antibacterial efficacy in the form of small molecules, howev...

Application of machine learning to large in vitro databases to identify drug-cancer cell interactions: azithromycin and KLK6 mutation status.

Oncogene
Recent advances in machine learning promise to yield novel insights by interrogation of large datasets ranging from gene expression and mutation data to CRISPR knockouts and drug screens. We combined existing and new algorithms with available experim...