Serotype diversity and antimicrobial susceptibility profiles of Actinobacillus pleuropneumoniae isolated in Italian pig farms from 2015 to 2022
Bibliographic record
Abstract
Actinobacillus pleuropneumoniae (APP) is a bacterium frequently associated with porcine pleuropneumonia. The acute form of the disease is highly contagious and often fatal, resulting in significant economic losses for pig farmers. Serotype diversity and antimicrobial resistance (AMR) of APP strains circulating in north Italian farms from 2015 to 2022 were evaluated retrospectively to investigate APP epidemiology in the area. A total of 572 strains isolated from outbreaks occurring in 337 different swine farms were analysed. The majority of isolates belonged to serotypes 9/11 (39.2%) and 2 (28.1%) and serotype diversity increased during the study period, up to nine different serotypes isolated in 2022. The most common resistances were against tetracycline (53% of isolates) and ampicillin (33%), followed by enrofloxacin, florfenicol and trimethoprim/sulfamethoxazole (23% each). Multidrug resistance (MDR) was common, with a third of isolates showing resistance to more than three antimicrobial classes. Resistance to the different classes and MDR varied significantly depending on the serotype. In particular, the widespread serotype 9/11 was strongly associated with florfenicol and enrofloxacin resistance and showed the highest proportion of MDR isolates. Serotype 5, although less common, showed instead a concerning proportion of trimethoprim/sulfamethoxazole resistance. Our results highlight how the typing of circulating serotypes and the analysis of their antimicrobial susceptibility profile are crucial to effectively manage APP infection and improve antimicrobial stewardship.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".