Postprocessing In Vitro Digestion Challenge To Evaluate Survival of <i>Escherichia coli</i> O157:H7 in Fermented Dry Sausages
Bibliographic record
Abstract
Fermented dry sausages, inoculated with Escherichia coli O157:H7 during batter preparation, were submitted to an in vitro digestion challenge to evaluate the extent to which passage through the human gastrointestinal tract could inactivate the pathogenic cells, previously stressed by the manufacturing process. The numbers of surviving E. coli O157:H7 cells remained constant after a 1-min exposure of the finely chopped sausage to synthetic saliva or during the following 120-min exposure to synthetic gastric juice at an initial pH of 2.0. However, significant (P < or = 0.05) growth of the pathogen (1.03 to 2.16 log10 CFU/g) was observed in a subsequent 250-min exposure to a synthetic pancreatic juice at pH 8.0. In a different set of experiments, fractions from the gastric suspension were transferred into the synthetic pancreatic juice at 30-min intervals to mimic the dynamics of gastric emptying. Concurrently, the pH of the remaining gastric fluid was reduced to 3.0, 2.5, and 2.0 to simulate the gradual reacidification of the stomach contents after the initial buffering effect resulting from meal ingestion. Under these new conditions, pathogen growth during pancreatic challenge was observed for the first few fractions released from the stomach (90 min of exposure [pH 2.5]), but growth was no longer possible in the fractions submitted to the most severe gastric challenge (120 min of exposure [pH < 2.2]).
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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 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".