Bacteriophage cocktail significantly reduces Escherichia coli O157
Bibliographic record
Abstract
Foods contaminated with Escherichia coli O157:H7 cause more than 63,000 foodborne illnesses in the United States every year, resulting in a significant economic impact on medical costs and product liabilities. Efforts to reduce contamination with E. coli O157:H7 have largely focused on washing, application of various antibacterial chemicals, and gamma-irradiation, each of which has practical and environmental drawbacks. A relatively recent, environmentally-friendly approach proposed for eliminating or significantly reducing E. coli O157:H7 contamination of foods is the use of lytic bacteriophages as biocontrol agents. We found that EcoShield™, a commercially available preparation composed of three lytic bacteriophages specific for E. coli O157:H7, significantly (p < 0.05) reduced the levels of the bacterium in experimentally contaminated beef by ≥ 94% and in lettuce by 87% after a five minute contact time. The reduced levels of bacteria were maintained for at least one week at refrigerated temperatures. However, the one-time application of EcoShield™ did not protect the foods from recontamination with E. coli O157:H7. Our results demonstrate that EcoShield™ is effective in significantly reducing contamination of beef and lettuce with E. coli O157:H7, but does not protect against potential later contamination due to, for example, unsanitary handling of the foods post processing.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.039 | 0.010 |
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; both teacher heads agree on what is shown here.
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".