PSVII-16 Galactosylated chitosan-oligosaccharides have anti-adhesive effect against enterotoxigenic Escherichia coli in piglets
Bibliographic record
Abstract
Abstract Enterotoxigenic Escherichia coli (ETEC) is a major cause of diarrhea in piglets. In vitro, high molecular weight β-galactosylated chitosan-oligosaccharides (Gal-COS) had strong anti-adhesive activity against ETEC-expressing K88 fimbriae (ETEC K88) binding to porcine erythrocytes. This study assessed the effects of Gal-COS differing in structure on anti-adhesive properties against ETEC in a small intestinal segment perfusion (SISP) model in 8 piglets (BW 10 kg; 5-wk old). With 10 jejunal segments in each pig, 5 segments were infected with ETEC K88, and the other 5 segments were infused with saline (non-ETEC). Every 2 paired segments (ETEC or non-ETEC) from the same pig were treated for 8 h with 64 ml of 10 g L-1 of one of the following test products: 1) α-Gal-COS; 2) β-Gal-COS; 3) exopolysaccharides produced by Lactobacillus reuteri; and 4) raffinose in a double 4 × 4 Latin square with a saline control. Infection by ETEC K88 was verified by quantitative PCR. Net fluid loss was calculated as difference of fluid loss between ETEC segment and its paired non-ETEC segment. Data were analyzed using the mixed model with segment and test product as fixed effects, and pig as random effect. Number of eubacterial rRNA genes was 10-fold greater (P < 0.001) in ETEC segments than non-ETEC segments, indicating that ETEC K88 accounted for > 90% of bacterial gene counts. Test product did not affect (P > 0.10) the number of ETEC bacteria in the outflow fluid. Furthermore, net fluid loss caused by ETEC tended (P = 0.08) to be decreased by β-Gal-COS compared to all other treatments. In conclusion, the in vivo SISP model confirmed that Gal-COS had anti-diarrheal effects, indicating that β-Gal-COS is a potential feed additive to reduce the ETEC-induced diarrhea in piglets.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".