AIMC Topic: Salmonella enterica

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Global genomic survey of Kentucky: discovery of a chromosomeborne and the emergence of ST314, an MDR clone mediated by the IncR plasmid.

Emerging microbes & infections
Antimicrobial resistance (AMR) in enterica serotype Kentucky ( Kentucky) is a global challenge, with increasing resistance to cephalosporins, ciprofloxacin, and carbapenems significantly limiting treatment strategies, yet its worldwide dissemination...

A machine learning approach to predict strain-specific phage-host interactions.

Scientific reports
The use of bacteriophages for biological control of bacterial infections is a promising approach to combat antimicrobial resistant bacteria. Prediction of phage-bacteria interactions is key to identify sensitive bacterial strains to phage therapy. Si...

Machine learning reveals the dynamic importance of accessory sequences for outbreak clustering.

mBio
UNLABELLED: Bacterial typing at whole-genome scales is now feasible owing to decreasing costs in high-throughput sequencing and the recent advances in computation. The unprecedented resolution of whole-genome typing is achieved by genotyping the vari...

An exploration of descriptive machine learning approaches for antimicrobial resistance: Multidrug resistance patterns in Salmonella enterica.

Preventive veterinary medicine
Salmonellosis is one of the most common foodborne diseases worldwide, with the ability to infect humans and animals. Antimicrobial resistance (AMR) and, particularly, multidrug resistance (MDR) among Salmonella enterica poses a risk to human health. ...

Machine learning-driven electronic identifications of single pathogenic bacteria.

Scientific reports
A rapid method for screening pathogens can revolutionize health care by enabling infection control through medication before symptom. Here we report on label-free single-cell identifications of clinically-important pathogenic bacteria by using a poly...

Sanitation of tomatoes based on a combined approach of washing process and pulsed light in conjunction with selected disinfectants.

Food research international (Ottawa, Ont.)
In this study, we evaluated the performance of a large-scale decontamination system based on a washing process in combination with pulsed light (PL) exposure and HO/chlorine. In order to identify optimum processing condition, we first evaluated the e...

Machine learning identifies signatures of host adaptation in the bacterial pathogen Salmonella enterica.

PLoS genetics
Emerging pathogens are a major threat to public health, however understanding how pathogens adapt to new niches remains a challenge. New methods are urgently required to provide functional insights into pathogens from the massive genomic data sets no...

In vitro activity of Nigella sativa against antibiotic resistant Salmonella enterica.

Environmental toxicology and pharmacology
Salmonellosis is a major food-borne disease worldwide and antimicrobial resistance in Salmonella is a public health problem. Phytochemicals are alternative therapeutics to treat antibiotic resistant Salmonella. Biochemically identified Salmonella ent...

Patchy promiscuity: machine learning applied to predict the host specificity of and .

Microbial genomics
and are bacterial species that colonize different animal hosts with sub-types that can cause life-threatening infections in humans. Source attribution of zoonoses is an important goal for infection control as is identification of isolates in reserv...