Screening of Pig-Derived Zearalenone-Degrading Bacteria through the Zearalenone Challenge Model, and Their Degradation Characteristics
Bibliographic record
Abstract
Zearalenone (ZEN) is widely found in food and feed. Its cytotoxicity, reproductive toxicity, genetic toxicity, immunotoxicity and hepatorenal toxicity have serious impacts on human and animal health. In order to help animals avoid ZEN poisoning in feed, ZEN-degrading bacterial strains were screened from fecal samples through a zearalenone challenge pig model, and their degradation characteristics were researched. Through the optimization of parameters such as the culture time, pH value, temperature, and strain concentration, the optimal conditions for the ZEN-degrading ability of these strains were preliminarily determined, and the active site of the ZEN degradation was explored. In this study, three strains (SY-3, SY-14, SY-20) with high ZEN degradation capacities were obtained. SY-3 was identified as Proteus mirabilis, and its main degrading component was the supernatant. SY-14 and SY-20 were identified as Bacillus subtilis. Their main degrading components were the intracellular fluid of SY-14, and the intracellular fluid and cell wall of SY-20. The above results showed that the ZEN challenge model was an effective way to screen ZEN-degrading bacteria.
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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 | 0.000 | 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".