Evaluation of the biodegradation feasibility of antibiotics by three bacteria involving glutathione S-transferasesA paper submitted to the Journal of Environmental Engineering and Science.
Bibliographic record
Abstract
Swine wastewater is not easy to dispose of in usual biological wastewater treatment plants. One reason is that some antibiotics are not easily degradable in the normal treatment system and suppress or inhibit microorganisms in the treatment system. Specifically tetracycline, sulfathiazole, and ampicillin have been widely used as antibiotics in pig feed. For treating disposal and spillage of these antibiotics biologically, a special enzyme based method is needed. Detoxifying enzymes caused the antibiotics to be bio-converted in this experiment and degraded them in this biological experiment. The glutathione S-transferases (GSTs) catalyzed the conjugation of glutathione (GSH) to a number of hydrophobic electrophilic substrates. In this study, we hypothesized that the microorganisms with GSTs degraded the representative manure antibiotics. The initial concentrations of tetracycline, sulfathiazole, and ampicillin were 100 mg/L, 100 mg/L, and 50 mg/L, respectively. These concentrations of antibiotics in pig feed are typical levels. Evaluation of the biodegradation feasibility of antibiotics was carried out by three bacteria possessing glutathione S-transferases under the strong concentration of antibiotics (standards for livestock pharmaceuticals in pig feed).
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| 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 | 0.001 | 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".