Identification of Didecyldimethylammonium Salts and Salicylic Acid as Antimicrobial Compounds in Commercial Fermented Radish Kimchi
Bibliographic record
Abstract
Daikon radish (Raphanus sativus) fermented with lactic acid bacteria, especially Leuconostoc or Lactobacillus spp., can be used to make kimchi, a traditional Korean fermented vegetable. Commercial Leuconostoc/radish root ferment filtrates are claimed to have broad spectrum antimicrobial activity. Leuconostoc kimchii fermentation products are patented as preservatives for cosmetics, and certain strains of this organism are reported to produce antimicrobial peptides (bacteriocins). We examined the antimicrobial agents in commercial Leuconostoc/radish root ferment filtrates. Both activity-guided fractionation with Amberlite XAD-16 and direct extraction with ethyl acetate gave salicylic acid as the primary agent with activity against Gram-negative bacteria. Further analysis of the ethyl acetate extract revealed that a didecyldimethylammonium salt was responsible for the Gram-positive activity. The structures of these compounds were confirmed by a combination of (1)H- and (13)C NMR, high-performance liquid chromatography, high-resolution mass spectrometry, and tandem mass spectrometry analyses. Radiocarbon dating indicates that neither compound is a fermentation product. No antimicrobial peptides were detected.
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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 | 0.001 | 0.001 |
| 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) | 0.000 | 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".