Binding activity of Natto (a fermented food) and <i>Bacillus natto</i> isolates to mutagenic-carcinogenic heterocyclic amines
Bibliographic record
Abstract
The fermented food, whole meal Natto, viscous polymeric material from Natto, Natto bean, cooked soya bean, and 28 bacterial isolates from Natto were studied for their binding capacity to foodborne mutagenic-carcinogenic heterocyclic amines. The mutagenic heterocyclic amines used were Trp-P-1 (3-amino-1,4-dimethyl-5H-pyrido(4,3-b)indole); Trp-P-2 (3-amino-1-methyl-5H-pyrido(4,3-b)indole); Glu-P-1 (2-amino-6-methyldipyrido(1,2-a:3'2'-d)imidazole); PhIP (2-amino-1-methyl-6-phenylimidazo(4,5-b)pyridine); IQ (2-amino-3-methylimidazo(4,5-f)quinoline); MeIQ (2-amino-3,4-dimethylimidazo(4,5-f)quinoxaline); MeIQx (2-amino-3,8-dimethylimidazo(4,5-f)quinoxaline); and MeAalphaC (2-amino-3-methyl-9H-pyrido(2,3)indole). The lyophilized Natto and other fractions of Natto exhibited high binding activity towards Trp-P-1, Trp-P-2, PhIP, and MeAalphaC, while Glu-P-1, IQ, and MeIQ were not effectively bound. The binding capacity of bacterial isolates (Bacillus natto) were isolate-mutagen dependent. Heat treated lyophilized cells, cell wall, and cytoplasmic contents of the bacterial isolate with the highest binding capacity were analyzed for their ability to bind different heterocyclic amines. The results indicate the importance of the cell wall in binding to heterocyclic amines, whereas the cytoplasmic contents were less effective. Heat-treated cells were not much different from that of viable cells in their binding. The impact of different factors, such as pH, incubation time, metal ions, different concentrations of sodium chloride and alcohol, various enzymes, and acetylation of mutagens on binding of Trp-P-1 and IQ, were discussed. The significance of the present results is also discussed from the viewpoint that Natto, a fermented food, is able to scavenge dietary mutagenic heterocyclic amines through binding.
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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".