Aflatoxin B1 Degradation by Stenotrophomonas Maltophilia and Other Microbes Selected Using Coumarin Medium
Bibliographic record
Abstract
Aflatoxin B(1) (AFB(1)) is one of the most harmful mycotoxins in animal production and food industry. A safe, effective and environmentally sound detoxification method is needed for controlling this toxin. In this study, 65 samples were screened from various sources with vast microbial populations using a newly developed medium containing coumarin as the sole carbon source. Twenty five single-colony bacterial isolates showing AFB(1) reduction activity in a liquid culture medium were selected from the screen. Isolate 35-3, obtained from tapir feces and identified to be Stenotrophomonas maltophilia, reduced AFB(1) by 82.5% after incubation in the liquid medium at 37 degrees C for 72 h. The culture supernatant of isolate 35-3 was able to degrade AFB(1) effectively, whereas the viable cells and cell extracts were far less effective. Factors influencing AFB(1) degradation by the culture supernatant were investigated. Activity was reduced to 60.8% and 63.5% at 20 degrees C and 30 degrees C, respectively, from 78.7% at 37 degrees C. The highest degradation rate was 84.8% at pH 8 and the lowest was only 14.3% at pH 4.0. Ions Mg(2+) and Cu(2+) were activators for AFB(1) degradation, however ion Zn(2+) was a strong inhibitor. Treatments with proteinase K, proteinase K plus SDS and heating significantly reduced or eradicated the degradation activity of the culture supernatant. The results indicated that the degradation of AFB(1) by S. maltophilia 35-3 was enzymatic and could have a great potential in industrial applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 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".