AIMC Topic: Klebsiella pneumoniae

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Prediction of antimicrobial resistance from MALDI-TOF mass spectra using machine learning: a validation study.

Journal of clinical microbiology
UNLABELLED: Matrix-assisted laser desorption-ionization-time of flight (MALDI-TOF) mass spectra can be used to predict antimicrobial resistance (AMR) using machine learning (ML). This study aimed to validate the performance of ML models for AMR predi...

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...

Coral-Derived Antimicrobial Peptides Identified In Silico from Acropora digitifera Transcriptomes: Potential Candidates Against Resistant Pathogens.

Marine biotechnology (New York, N.Y.)
Antimicrobial resistance is a serious threat to global public health and requires new therapeutic approaches. Antimicrobial peptides (AMP) are recognized as promising candidates to address antimicrobial resistance. AMP can disrupt cell membranes by i...

Use of IR Biotyper as a feasible methodology to type .

Microbiology spectrum
UNLABELLED: is one of the most frequently reported healthcare-associated pathogens. The current gold standard approach to perform the epidemiological typing of these bacteria is Whole Genome Sequencing (WGS), which is an expensive and challenging pr...

Unravelling mutation patterns in Extended-Spectrum β-Lactamases for precision drug design against AMR in Enterobacteriaceae.

Molecular genetics and genomics : MGG
Antimicrobial resistance (AMR) presents a critical global challenge, causing over 1.27 million deaths annually, with projections reaching 10 million by 2050. Among the most concerning contributors are Enterobacteriaceae, particularly Escherichia coli...

Machine learning-based evaluation of risk factors for carbapenem-resistant dissemination in neonatal units.

mSystems
Healthcare-associated infections (HAIs), particularly in neonatal intensive care units (NICUs), pose significant challenges due to neonates' vulnerability and the rapid infection spread. However, risk factors facilitating pathogen persistence and dis...

LC-MS/MS metabolomics unravels the resistant phenotype of carbapenemase-producing Enterobacterales.

Metabolomics : Official journal of the Metabolomic Society
INTRODUCTION: The degree of antimicrobial resistance demonstrated by carbapenemase-producing Enterobacterales (CPE) represents a growing public health challenge. Conventional methods for detecting CPE involve culture-based techniques with lengthy inc...

Machine Learning and DIA Proteomics Reveal New Insights into Carbapenem Resistance Mechanisms in .

Journal of proteome research
The emergence of Carbapenem-resistant (CRKP) represents a major public health concern, primarily driven by its ability to evade a wide range of antibiotics. Despite extensive genomic studies, proteomic insights into antibiotic resistance mechanisms ...