Bacteriophages Contribute to the Spread of Antibiotic Resistance Genes among Foodborne Pathogens of the Enterobacteriaceae Family – A Review
Bibliographic record
Abstract
Foodborne illnesses continue to have an economic impact on global health care systems. There is a growing concern regarding the increasing frequency of antibiotic resistance in foodborne bacterial pathogens and how such resistance may affect treatment outcomes. In an effort to better understand how to reduce the spread of resistance, many research studies have been conducted regarding the methods by which antibiotic resistance genes are mobilized and spread between bacteria. Transduction by bacteriophages is one of many horizontal gene transfer mechanisms, and recent findings have shown phage-mediated transduction to be a significant contributor to dissemination of antibiotic resistance genes. Here, we review the viability of transduction as a contributing factor to the dissemination of antibiotic resistance genes in foodborne pathogens of the Enterobacteriaceae family, including nontyphoidal Salmonella and Shiga toxin-producing Escherichia coli, as well as environmental factors that increase transduction of antibiotic resistance genes.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".