Antimicrobial Resistance and Genomic Characterization of Salmonella Serovars Typhimurium and 4,[5],12:i:- in Huzhou, China
Bibliographic record
Abstract
Wei Yan, Lei Ji, Yunfeng Zha, Fenfen Dong, Deshun Xu Huzhou Center for Disease Control and Prevention, Huzhou, 313000, People’s Republic of ChinaCorrespondence: Deshun Xu, Huzhou Center for Disease Control and Prevention, 999 Changxing Road, Huzhou, Zhejiang, 313000, People’s Republic of China, Email xds666092@126.comObjective: Salmonella serovar Typhimurium (S. Typhimurium) and its monophasic variant, Salmonella 4,[5],12:i:-, have become two of the most frequently isolated serovars worldwide, in both humans and animals. This study investigated the antimicrobial resistance and genomic characteristics of these two serovar Salmonella.Methods: Between 2021 and 2023, a total of 90 S. Typhimurium and Salmonella 4,[5],12:i:-were collected from clinical and food samples in Huzhou. Their antimicrobial resistance phenotype and genes, virulence genes, and phylogenetic relationship were analyzed.Results: Salmonella 4,[5],12:i:-, which all belong to ST34, has become the main serotype of Salmonella isolated in Huzhou instead of S. Typhimurium. Notably, we observed a higher incidence of infections among the young population (< 5 years old). The 90 Salmonella isolates were mainly resistant to tetracycline (94.4%), ampicillin (72.2%), and trimethoprim/sulfamethoxazole (70.0%), with multidrug resistance (MDR) rates as high as 93.3%. Genome sequencing indicated that these isolates possessed 39 antimicrobial resistance genes and 184 virulence genes.Conclusion: This research enhances our understanding of S. Typhimurium and Salmonella 4,[5],12:i:- infections, which is helpful to guide clinical responses.Keywords: Salmonella typhimurium, monophasic variant, antimicrobial resistance, multidrug resistance, whole genome sequencing
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".