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Record W2132749869 · doi:10.1680/jees.2013.0057

Evaluation of the biodegradation feasibility of antibiotics by three bacteria involving glutathione S-transferases

2013· article· en· W2132749869 on OpenAlexvenueno aff
Hye-Young Park, Youn-Kyoo Choung

Bibliographic record

VenueJournal of Environmental Engineering and Science · 2013
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicGlutathione Transferases and Polymorphisms
Canadian institutionsnot available
Fundersnot available
KeywordsSulfathiazoleAntibioticsTetracyclineBiodegradationChemistryGlutathioneManureTetracycline antibioticsSulfadimethoxineMicroorganismAmpicillinBacteriaSewage treatmentMicrobiologyEnzymeBiochemistryBiologyChromatographyOrganic chemistryWaste management

Abstract

fetched live from OpenAlex

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).

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.232
Threshold uncertainty score0.173

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.012
GPT teacher head0.217
Teacher spread0.205 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations10
Published2013
Admission routes1
Has abstractyes

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