<i>Escherichia coli</i>in postweaning diarrhea in pigs: an update on bacterial types, pathogenesis, and prevention strategies
Bibliographic record
Abstract
Escherichia coli is one of the most important causes of postweaning diarrhea in pigs. This diarrhea is responsible for economic losses due to mortality, morbidity, decreased growth rate, and cost of medication. The E. coli causing postweaning diarrhea mostly carry the F4 (K88) or the F18 adhesin. Recently, an increase in incidence of outbreaks of severe E. coli-associated diarrhea has been observed worldwide. The factors contributing to the increased number of outbreaks of this more severe form of E. coli-associated diarrhea are not yet fully understood. These could include the emergence of more virulent E. coli clones, such as the 0149:LT:STa:STb:EAST1:F4ac, or recent changes in the management of pigs. Development of multiple bacterial resistance to a wide range of commonly used antibiotics and a recent increase in the prevalence and severity of the postweaning syndromes will necessitate the use of alternative measures for their control. New vaccination strategies include the oral immunization of piglets with live avirulent E. coli strains carrying the fimbrial adhesins or oral administration of purified F4 (K88) fimbriae. Other approaches to control this disease include supplementation of the feed with egg yolk antibodies from chickens immunized with F4 or F18 adhesins, breeding of F18- and F4-resistant animals, supplementation with zinc and/ or spray-dried plasma, dietary acidification, phage therapy, or the use of probiotics. To date, not a single strategy has proved to be totally effective and it is probable that the most successful approach on a particular farm will involve a combination of diet modification and other preventive measures.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".