Prevalence of O1/K1- and O2/K3-Reactive <i>Actinobacillus suis</i> in Healthy and Diseased Swine
Bibliographic record
Abstract
A cell surface antigen-typing system was devised for the swine pathogen Actinobacillus suis and used to examine the prevalence of different lipopolysaccharide (O) types in healthy and diseased pigs. The strains examined in this study were isolated from a variety of locations in Canada and from Kansas. Lipopolysaccharide preparations of 151 isolates of A. suis were characterized by immunoblotting using polyclonal antisera generated to strains SO4 (O1/K1), H89-1173 (O2/K3), and VSB 3714, a rough strain. Approximately 54% (62 of 114) of A. suis isolates from diseased pigs, all (11 of 11) isolates from healthy pigs, and all (4 of 4) reference strains reacted with O1/K1 antiserum. More than 80% (18 of 22) of A. suis strains used for bacterin production and approximately 41% (47 of 114) of isolates from diseased pigs bound O2/K3 antiserum. One isolate appeared to be rough, and five were untypeable. O1/K1- and O2/K3-reactive strains were equally prevalent in Kansas, whereas O2/K3-reactive strains were more common in Québec and western Canada and O1/K1 strains were most common in Ontario. The fact that virtually all of the strains submitted for bacterin production were O2/K3-reactive strains is consistent with the notion that these strains may be more virulent than O1/K1 strains; alternatively, this may reflect geographic or other biases. In addition, we observed cross-reactivity between A. suis cell surface antigens and swine antisera to several other important pathogens. This finding may explain why previous attempts to develop a simple serodiagnostic test for A. suis have been unsuccessful.
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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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".