Prevalence, antimicrobial susceptibility and virulotyping of Listeria species and Listeria monocytogenes isolated from open-air fish markets
Bibliographic record
Abstract
The aim of this study was to investigate the prevalence and characterization of Listeria species and Listeria monocytogenes isolated from raw fish and open-air fish market environments. Eight hundred and sixty two samples including raw fish and fish market environments (samples from workers' hands, workers' knives, containers and work surface) were collected from the open-air fish markets in the Northern region of Iran.Listeria spp. was isolated from 104/488 (21.3%) raw fish and 29/374 (7.8%) of samples from open-air fish market environment. The isolates of Listeria spp. included L. innocua (35.3%), L. monocytogenes (32.3%), L. seeligeri (18%), and L. ivanovii (14.3%). Of the 43 L. monocytogenes isolates, 31 (72.1%), 10 (23.3%) and 2 (4.7%) belonged to serovars 1/2a, 4b, and 1/2b, respectively. The inlA, inlB, inlC, inlJ, actA, hlyA, iap, plcA, and prfA virulence-associated genes were detected in almost all of the L. monocytogenes isolates. The Listeria spp. isolates showed high resistance against tetracycline (23.3%), penicillin G, and cephalothin (each 16.5%). Besides, we observed significant resistance level to tetracycline (27.9%), ampicillin (20.9%), cephalothin, penicillin G, and streptomycin (each 16.3%) in the L. monocytogenes isolates. All of the isolates were susceptible to cefotaxime, gentamicin, kanamycin, and pefloxacin. We found that tetM (25.6%), tetA (23.3%), ampC (14%), and penA (11.6%) were the most prevalent antibiotic resistance genes in the L. monocytogenes isolates.Recovery of potentially pathogenic L. monocytogenes from raw fish and environment of open-air fish market samples in this study is a convincing evidence for the zoonotic potential of listeriosis.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".