Mechanisms of Bactericidal Action of Cinnamaldehyde against <i>Listeria monocytogenes</i> and of Eugenol against <i>L. monocytogenes</i> and <i>Lactobacillus sakei</i>
Bibliographic record
Abstract
The spice oil components eugenol and cinnamaldehyde possess activity against both gram-positive and gram-negative bacteria, but the mechanisms of action remain obscure. In broth media at 20 degrees C, 5 mM eugenol or 30 mM cinnamaldehyde was bactericidal (>1-log reduction in the number of CFU per milliliter in 1 h) to Listeria monocytogenes. At a concentration of 6 mM eugenol was bactericidal to Lactobacillus sakei, but treatment with 0.5 M cinnamaldehyde had no significant effect. To investigate the role of interference with energy generation in the mechanism of action, the cellular and extracellular ATP levels of cells in HEPES buffer at 20 degrees C were measured. Treatment of nonenergized L. monocytogenes with 5 mM eugenol, 40 mM cinnamaldehyde, or 10 microM carbonyl cyanide m-chlorophenylhydrazone (CCCP) for 5 min prevented an increase in the cellular ATP concentration upon addition of glucose. Treatment of energized L. monocytogenes with 40 mM cinnamaldehyde or 10 microM CCCP caused a rapid decline in cellular ATP levels, but 5 mM eugenol had no effect on cellular ATP. Treatment of L. sakei with 10 mM eugenol prevented ATP generation by nonenergized cells and had no effect on the cellular ATP of energized cells. CCCP at a concentration of 100 microM had no significant effect on the cellular ATP of L. sakei. No significant changes in extracellular ATP were observed. Due to their rapidity, effects on energy generation clearly play a major role in the activity of eugenol and cinnamaldehyde at bactericidal concentrations. The possible mechanisms of inhibition of energy generation are inhibition of glucose uptake or utilization of glucose and effects on membrane permeability.
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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 | 0.001 |
| 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 | 0.000 | 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".