AIMC Topic: Enterobacteriaceae

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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...

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...

AI verification for spirulina's antimicrobial power in total coliform and Staphylococcus aureus isolated from tilapia fillet.

Scientific reports
Seafood products, including fresh tilapia fillets, are highly susceptible to rapid quality deterioration due to microbial contamination, posing a significant concern for food safety and public health. This study investigated, both experimentally and ...

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 clinician predictions of antibiotic resistance in Enterobacterales bloodstream infections.

The Journal of infection
BACKGROUND: Patients with Gram-negative bloodstream infections are at risk of serious adverse outcomes without active treatment, but identifying who has antimicrobial resistance (AMR) to target empirical treatment is challenging.

Integrating machine learning and multitargeted drug design to combat antimicrobial resistance: a systematic review.

Journal of drug targeting
Antimicrobial resistance (AMR) is a critical global health challenge, undermining the efficacy of antimicrobial drugs against microorganisms like bacteria, fungi and viruses. Multidrug resistance (MDR) arises when microorganisms become resistant to m...

Improving fecal bacteria estimation using machine learning and explainable AI in four major rivers, South Korea.

The Science of the total environment
This study addresses the critical public health issue of fecal coliform contamination in the four major rivers in South Korea (Han, Nakdong, Geum, and Yeongsan rivers) by applying advanced machine learning (ML) algorithms combined with Explainable Ar...

Determination of minimum inhibitory concentrations using machine-learning-assisted agar dilution.

Microbiology spectrum
UNLABELLED: Effective policy to address the global threat of antimicrobial resistance requires robust antimicrobial susceptibility data. Traditional methods for measuring minimum inhibitory concentration (MIC) are resource intensive, subject to human...

Evaluation of the VITEK 2 Advanced Expert System performance for predicting resistance mechanisms in Enterobacterales acquired from a hospital-based screening program.

Pathology
There is limited literature examining the accuracy of the VITEK 2 Advanced Expert System (AES) in characterisation of β-lactamase resistance patterns. We present a prospective single centre study to better ascertain the performance characteristics of...

Deep learning model for prediction of extended-spectrum beta-lactamase (ESBL) production in community-onset Enterobacteriaceae bacteraemia from a high ESBL prevalence multi-centre cohort.

European journal of clinical microbiology & infectious diseases : official publication of the European Society of Clinical Microbiology
Adequate empirical antimicrobial coverage is instrumental in clinical management of community-onset Enterobacteriaceae bacteraemia in areas with high ESBL prevalence, while balancing the risk of carbapenem overuse and emergence of carbapenem-resistan...