Incorporation of Actinobacillus pleuropneumoniae in Preformed Biofilms by Escherichia coli Isolated From Drinking Water of Swine Farms
Bibliographic record
Abstract
Actinobacillus pleuropneumoniae, the etiological agent of porcine pleuropneumonia, represents one of the most important health problems in the swine industry worldwide and it is included in the porcine respiratory disease complex. One of the bacterial survival strategies is biofilm formation, which are bacterial communities embedded in an extracellular matrix that could be attached to a living or an inert surface. Until recently, A. pleuropneumoniae was considered to be an obligate pathogen. However, recent studies have shown that A. pleuropneumoniae is present in farm drinking water. In this study, the drinking water microbial communities of Aguascalientes (Mexico) swine farms were analyzed, where the most frequent isolated bacterium was Escherichia coli. Biofilm formation was tested in vitro; producing E. coli biofilms under optimal growth conditions; subsequently, A. pleuropneumoniae serotype 1 (strains 4074 and 719) was incorporated to these biofilms. Interaction between both bacteria was evidenced, producing an increase in biofilm formation. Extracellular matrix composition of two-species biofilms was also characterized using fluorescent markers and enzyme treatments. In conclusion, results confirm that A. pleuropneumoniae is capable of integrates into biofilms formed by environmental bacteria, indicative of a possible survival strategy in the environment and a mechanism for disease dispersion.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".