Antimicrobial activity of essential oils and structurally related synthetic food additives towards selected pathogenic and beneficial gut bacteria
Bibliographic record
Abstract
AIMS: To assess the potential of essential oils and structurally related synthetic food additives in reducing bacterial pathogens in swine intestinal tract. METHODS AND RESULTS: The antimicrobial activity of essential oils/compounds was measured by determining the inhibition of bacterial growth. Among 66 essential oils/compounds that exhibited > or =80% inhibition towards Salmonellatyphimurium DT104 and Escherichia coli O157:H7, nine were further studied. Most of the oils/compounds demonstrated high efficacy against S. typhimurium DT104, E. coli O157:H7, and E. coli with K88 pili with little inhibition towards lactobacilli and bifidobacteria. They were also tolerant to the low pH. When mixed with pig cecal digesta, these oils/compounds retained their efficacy against E. coli O157:H7. In addition, they significantly inhibited E. coli and coliform bacteria in the digesta, but had little effect on the total number of lactobacilli and anaerobic bacteria. CONCLUSIONS: Some essential oils/compounds demonstrated good potential, including efficacy, tolerance to low pH, and selectivity towards bacterial pathogens, in reducing human and animal bacterial pathogens in swine intestinal tract. SIGNIFICANCE AND IMPACT OF THE STUDY: This study has identified candidates of essential oils/compounds for in vivo studies to develop antibiotic substitutes for the reduction of human and animal bacterial pathogens in swine intestinal tract.
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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) | 0.001 | 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".