A Strain of <i>Enterococcus faecium</i> (18C23) Inhibits Adhesion of Enterotoxigenic <i>Escherichia coli</i> K88 to Porcine Small Intestine Mucus
Bibliographic record
Abstract
Few studies, if any, have addressed the adhesion of enterococci to the intestinal mucosa and their interference with the adhesion of pathogens, although more than 60% of probiotic preparations in the market contain strains of enterococci. The objective of this study was to investigate if Enterococcus faecium 18C23 has the ability to inhibit the adhesion of Escherichia coli K88ac and K88MB to the small intestine mucus of piglets. Approximately 9% of E. faecium 18C23 organisms adhered to the small intestine mucus, and the adhesion was found to be specific. Living E. faecium 18C23 culture efficiently inhibited the adhesion of E. coli K88ac and K88MB to the piglet intestine mucus. Inhibition of the adhesion of E. coli K88ac to the small intestine mucus was found to be dose dependent. Inhibition of >90% was observed when 10(9) CFU or more of living E. faecium 18C23 culture per ml was added simultaneously with E. coli to immobilized mucus. The substances from both the 18C23 cells and the spent culture supernatant contributed to the inhibition of adhesion of E. coli K88 to the small intestine mucus receptors. The inhibiting effect was not solely a pH effect since considerable inhibitory action was demonstrated after neutralizing the mixture or spent culture supernatant to pH 7.0. Part of the inhibition of adhesion of E. coli K88ac by E. faecium 18C23 or its supernatant might occur through steric hindrance.
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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) | 0.001 | 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) | 0.001 | 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".