Rapid identification of Salmonella serovars Enteritidis and Typhimurium using whole cell matrix assisted laser desorption ionization - Time of flight mass spectrometry (MALDI-TOF MS) coupled with multivariate analysis and artificial intelligence.

Salmonella is a common food-borne pathogen with Enteritidis and Typhimurium being among the most important serovars causing numerous outbreaks. A rapid method was investigated to identify these serovars using whole-cell MALDI-TOF MS coupled with multivariate analysis and artificial intelligence and 113 Salmonella strains, including 38 Enteritidis (SE), 38 Typhimurium (ST) and 37 strains from 32 other Salmonella serovars (SG). Datasets of ions (presence/absence) with high discriminative power were created using newly developed criteria and subject to multivariate analyses and eight artificial intelligence (AI) tools.

Interpretation and Implications of Lognormal Linear Regression Used for Bacterial Enumeration.

Background: Bacterial enumeration data are typically log transformed to realize a more normal distribution and stabilize the variance. Unfortunately, statistical results from log transformed data are often misinterpreted as data within the arithmetic domain.

Objective: To explore the implication of slope and intercept from an unweighted linear regression and compare it to the results of the regression of log transformed data.