Survival and predictive modeling of Listeria monocytogenes under simulated human gastric conditions in the presence of bovine milk products
Bibliographic record
Abstract
Listeria monocytogenes is an opportunistic foodborne pathogen which has been implicated in many outbreaks of foodborne diseases. This study evaluated the effects of gastric acidity and gastric digestion time of adults, L. monocytogenes strain and food type on the survival of L. monocytogenes under simulated stomach conditions of adults in in vitro gastric models with dynamic pH changes occurring throughout the exposure. Individual strains as well as a cocktail of L. monocytogenes, inoculated at 8 log CFU/mL in filtered bovine milk products, 0 % milk, 2 % milk, 2 % chocolate milk and 3.25 % milk, were introduced to the gastric models for 2 h. The survival of L. monocytogenes depended on a combination of factors, including gastric acidity and gastric digestion time of adults, L. monocytogenes strain, food type and recovery method (P < 0.05). The survival rates of L. monocytogenes inoculated in 2 % milk after a 2-h exposure to simulated gastric fluids with pH values of 1.5, 2.0 and 3.0 were 0.003 to 0.040 %, 22.7 to 43.4 % and 16.6 to 27.2 %, respectively. Fluid milk containing a higher milk fat content (3.25 % vs 0 % milk) protected L. monocytogenes from being inactivated when they were exposed to the human stomach model with a gastric acidity of pH 2.0. Compared to 0 % and 3.25 % milk, L. monocytogenes survived the best in 2 % chocolate milk, which appears to be due to the presence of milk fat (2 %) and the additional nutrients that are present in chocolate milk. A predictive mathematical model was developed that captured the population of the strains of L. monocytogenes under the in vitro conditions. This study advances our understanding of the behaviour of L. monocytogenes under various human gastric conditions and provides key parameters that can affect the survival of L. monocytogenes in the stomachs of adults. The mathematical models developed in this study can be used as a supplementary tool to help predict the survival of L. monocytogenes under similar scenarios and for relevant risk-assessment studies.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".