Emergence of Antibiotic Resistance in <i>Listeria monocytogenes</i> Isolated from Food Products: A Comprehensive Review
Bibliographic record
Abstract
Listeria monocytogenes is an opportunistic pathogen that has been involved in several deadly illness outbreaks. Future outbreaks may be more difficult to manage because of the emergence of antibiotic resistance among L. monocytogenes strains isolated from food products. The present review summarizes the available evidence on the emergence of antibiotic resistance among L. monocytogenes strains isolated from food products and the possible ways this resistance has developed. Furthermore, the resistance of food L. monocytogenes isolates to antibiotics currently used in the treatment of human listeriosis such as penicillin, ampicillin, tetracycline, and gentamicin, has been documented. Acquisition of movable genetic elements is considered the major mechanism of antibiotic resistance development in L. monocytogenes. Efflux pumps have also been linked with resistance of L. monocytogenes to some antibiotics including fluoroquinolones. Some L. monocytogenes strains isolated from food products are intrinsically resistant to several antibiotics. However, factors in food processing chains and environments (from farm to table) including extensive or sub-inhibitory antibiotics use, horizontal gene transfer, exposure to environmental stresses, biofilm formation, and presence of persister cells play crucial roles in the development of antibiotic resistance by L. monocytogenes.
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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) | 0.004 | 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".