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Microbial Sensitivity Tests

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Evaluation of parameters affecting performance and reliability of machine learning-based antibiotic susceptibility testing from whole genome sequencing data.

PLoS computational biology
Prediction of antibiotic resistance phenotypes from whole genome sequencing data by machine learning methods has been proposed as a promising platform for the development of sequence-based diagnostics. However, there has been no systematic evaluation...

Emergence of mcr-1 mediated colistin resistant Escherichia coli from a hospitalized patient in Bangladesh.

Journal of infection in developing countries
INTRODUCTION: The emergence of plasmid mediated mcr in bacteria has become global public health threat. Herein, we report a mcr-1 positive E. coli in normal human flora from a patient admitted in Dhaka Medical College Hospital (DMCH).

Biocide susceptibilities and biofilm-forming capacities of Acinetobacter baumannii clinical isolates from Malaysia.

Journal of infection in developing countries
INTRODUCTION: Acinetobacter baumannii is a Gram-negative nosocomial pathogen that has the capacity to develop resistance to all classes of antimicrobial compounds. However, very little is known regarding its susceptibility to biocides (antiseptics an...

Cholecalciferol, Ergosterol, and Cholesterol Enhance the Antibiotic Activity of Drugs.

International journal for vitamin and nutrition research. Internationale Zeitschrift fur Vitamin- und Ernahrungsforschung. Journal international de vitaminologie et de nutrition
UNLABELLED: Background: This is the first report demonstrating the antibiotic-modifying activity of cholecalciferol.

Fast and reliable determination of Escherichia coli susceptibility to antibiotics: Infrared microscopy in tandem with machine learning algorithms.

Journal of biophotonics
Antimicrobial drugs have an important role in controlling bacterial infectious diseases. However, the increasing resistance of bacteria to antibiotics has become a global health care problem. Rapid determination of antimicrobial susceptibility of cli...

Heterologous Machine Learning for the Identification of Antimicrobial Activity in Human-Targeted Drugs.

Molecules (Basel, Switzerland)
The emergence of microbes resistant to common antibiotics represent a current treat to human health. It has been recently recognized that non-antibiotic labeled drugs may promote antibiotic-resistance mechanisms in the human microbiome by presenting ...

Modeling Antibacterial Activity with Machine Learning and Fusion of Chemical Structure Information with Microorganism Metabolic Networks.

Journal of chemical information and modeling
Predicting the activity of new chemical compounds over pathogenic microorganisms with different metabolic reaction networks (MRN ) is an important goal due to the different susceptibility to antibiotics. The ChEMBL database contains >160 000 outcomes...

Argentinian multicenter study on urinary tract infections due to Streptococcus agalactiae in adult patients.

Journal of infection in developing countries
INTRODUCTION: Streptococcus agalactiae (group B streptococcus, GBS) is a recognized urinary pathogen both in males and pregnant or non-pregnant women. Data regarding GBS serotypes recovered from urinary tract infections (UTIs) are scarce. The aim of ...

Using Machine Learning To Predict Antimicrobial MICs and Associated Genomic Features for Nontyphoidal .

Journal of clinical microbiology
Nontyphoidal species are the leading bacterial cause of foodborne disease in the United States. Whole-genome sequences and paired antimicrobial susceptibility data are available for strains because of surveillance efforts from public health agencie...