AIMC Topic: Foodborne Diseases
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Machine Learning Methods as a Tool for Predicting Risk of Illness Applying Next-Generation Sequencing Data.
Risk analysis : an official publication of the Society for Risk Analysis
Nov 21, 2018
Next-generation sequencing (NGS) data present an untapped potential to improve microbial risk assessment (MRA) through increased specificity and redefinition of the hazard. Most of the MRA models do not account for differences in survivability and vi...
Rapid screening and multi-toxin profile confirmation of tetrodotoxins and analogues in human body fluids derived from a puffer fish poisoning incident in New Caledonia.
Food and chemical toxicology : an international journal published for the British Industrial Biological Research Association
Dec 30, 2017
In August 2014, a puffer fish poisoning incidence resulting in one fatality was reported in New Caledonia. Although tetrodotoxin (TTX) intoxication was established from the patients' signs and symptoms, the determination of TTX in the patient's urine...
Label-free screening of foodborne Salmonella using surface plasmon resonance imaging.
Analytical and bioanalytical chemistry
Dec 26, 2017
It is estimated that 95% of the foodborne infections are caused by 15 major pathogens. Therefore, rapid and effective multiplex screening techniques for these pathogens with improved efficiencies could benefit public health at lower costs. Surface pl...
Endolysin LysSA97 is synergistic with carvacrol in controlling Staphylococcus aureus in foods.
International journal of food microbiology
Dec 27, 2016
LysSA97 is an endolysin encoded by the bacteriophage SA97, the genome sequence of which has been recently revealed. LysSA97 has lytic activity against a variety of Staphylococcus strains that cause foodborne illness. In order to improve its potential...
Prediction of bacterial associations with plants using a supervised machine-learning approach.
Environmental microbiology
Jun 27, 2016
Recent scenarios of fresh produce contamination by human enteric pathogens have resulted in severe food-borne outbreaks, and a new paradigm has emerged stating that some human-associated bacteria can use plants as secondary hosts. As a consequence, t...
Salmonella infections modelling in Mississippi using neural network and geographical information system (GIS).
BMJ open
Mar 3, 2016
OBJECTIVES: Mississippi (MS) is one of the southern states with high rates of foodborne infections. The objectives of this paper are to determine the extent of Salmonella and Escherichia coli infections in MS, and determine the Salmonella infections ...
Towards a Food Safety Knowledge Base Applicable in Crisis Situations and Beyond.
BioMed research international
Jul 13, 2015
In case of contamination in the food chain, fast action is required in order to reduce the numbers of affected people. In such situations, being able to predict the fate of agents in foods would help risk assessors and decision makers in assessing th...
Application of Bioinformatics and Machine Learning Tools in Food Safety.
Current nutrition reports
May 19, 2025
PURPOSE OF REVIEW: Food safety is a fundamental challenge in public health and sustainable development, facing threats from microbial, chemical, and physical contamination. Innovative technologies improve our capacity to detect contamination early an...
Using GWAS and Machine Learning to Identify and Predict Genetic Variants Associated with Foodborne Bacteria Phenotypic Traits.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2025
One of the main challenges in food microbiology is to prevent the risk of outbreaks by avoiding the distribution of food contaminated by bacteria. This requires constant monitoring of the circulating strains throughout the food production chain. Bact...
Integrating MALDI-TOF Mass Spectrometry with Machine Learning Techniques for Rapid Antimicrobial Resistance Screening of Foodborne Bacterial Pathogens.
Methods in molecular biology (Clifton, N.J.)
Jan 1, 2025
Although MALDI-TOF mass spectrometry (MS) is considered as the gold standard for rapid and cost-effective identification of microorganisms in routine laboratory practices, its capability for antimicrobial resistance (AMR) detection has received limit...
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