Identification and Characterization of Achromobacter spanius P-9 and Elucidation of its Deoxynivalenol-Degrading Potential
Bibliographic record
Abstract
Abstract Deoxynivalenol (DON) poses significant challenges due to its frequent contamination of grains and associated products. Microbial strategies for mitigating DON toxicity showed application potential. Eight bacterial isolates with DON degradation activity over 5% were obtained from various samples of organic fertilizer in this study. One of the isolates emerged as a standout, demonstrating a substantial degradation capability, achieving a 99.21% reduction in DON levels. This isolate, underwent thorough morphological, biochemical, and molecular characterization to confirm its identity, and was identified as a new strain of Achromobacter spanius P-9. Subsequent evaluations revealed that the strain P-9 retains its degradation activity after a 24-hour incubation, reaching optimal performance at 35°C with a pH of 8.0. Further studies indicated that Ca2+ ions enhance the degradation process, whereas Zn2+ ions exert an inhibitory effect. This is the pioneering report of DON degradation by Achromobacter spanius, illuminating its prospective utility in addressing DON contamination challenges.
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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 | 0.001 |
| 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".