Eliminating antibiotics by white-rot-fungi Trametes versicolor from manure solids and synthetic wastewater
Bibliographic record
Abstract
Antibiotics have been abused in livestock as veterinary drug and feed additive. Their incomplete metabolization by animals resulted in heavy accumulation in livestock manure, and therefore they can pose a threat to the environment. In this study, the mechanism of three antibiotics (oxytetracycline (OTC), sulfadiazine (SDZ), enrofloxacin (ENR)) removal/biodegradation by Trametes versicolor pellets in air-pulse fluidized-bed reactor was explored, and the effects of wood immobilized T . versicolor on four antibiotics (OTC, SDZ, ENR and chloramphenicol (CAP)) removal in solid cow manures were evaluated. T . versicolor could remove OTC, SDZ, ENR through adsorption and biodegradation, with the removal efficiency at 92% and 98% in 21 hours and 98% after 68 hours, respectively. The removal kinetics of those three antibiotics fitted well with the first-order kinetic model, with the removal constant k at -0.238 h -1 , -0.102 h -1 and -0.023 h -1 , respectively. T . versicolor could biodegrade those three antibiotics using laccase and cytochrome P450 system with the order SDZ≈OTC>ENR. Furthermore, wood immobilized T. versicolor promoted SDZ, OTC, ENR and chloramphenicol (CAP) antibiotic biodegradation in cow manure, especially in high inoculation ratio (wood immobilized T . versicolor : solid cow manures=1:2). This study revealed the mechanism of simultaneous SDZ, OTC, ENR and CAP antibiotic removal/biodegradation by white-rot fungi T. versicolor even by wood immobilized T. versicolor in solid cow manures, which provide a theoretical basis for future application of biological removal of antibiotics present in wastewater and solid manures.
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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) | 0.001 | 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".