Survival of <i>Escherichia coli</i> O157:H7 during Manufacture and Storage of White Brined Cheese
Bibliographic record
Abstract
Escherichia coli O157:H7 is a major foodborne pathogen that causes severe disease in humans. Survival of E. coli O157:H7 during processing and storage of white brined cheese was investigated. Cheeses were prepared using pasteurized milk inoculated with a 4 strain E. coli O157:H7 cocktail (7 log(10) CFU/g) with or without yogurt starter culture (Lactobacillus delbrueckii ssp. bulgaricus and Streptococcus salivarius ssp. thermophilus) and stored in 10% or 15% NaCl brine at 10 and 21 ºC for 28 d. NaCl concentration, water activity (a(w)), pH, and numbers of E. coli O157:H7 and lactic acid bacteria (LAB) were determined in cheese and brine. E. coli O157:H7 was able to survive in cheese stored in both brines at 10 and 21 ºC regardless of the presence of starter LAB, although the latter significantly enhanced E. coli O157:H7 reduction in cheese or its brine at 10 ºC. E. coli O157:H7 numbers were reduced by 2.6 and 3.4 log(10) CFU/g in cheese stored in 10% and 15% NaCl brine, respectively, in the presence of starter LAB and by 1.4 and 2.3 log(10) CFU/g, respectively, in the absence of starter LAB at 10 ºC. The pathogen survived, but at lower numbers in the brines. The salt concentration of cheese stored in 10% brine remained about 5% during ripening, but in 15% brine, the NaCl level increased 1.6% to 8.1% (w/w) by 28 d. Values of pH and a(w) slightly decreased 1 d after exposure to brine and reached 5.5 to 6.6 and 0.88 to 0.94, respectively, in all treatments.
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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) | 0.000 | 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 | 0.000 | 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".