Biodegradation of plasticizers by <i>Rhodotorula rubra</i>
Bibliographic record
Abstract
Abstract The degradation of plasticizers by the yeast Rhodotorula rubra J-96-1 (American Type Culture Collection 9449) in the presence of glucose was studied. The plasticizers included the commonly used bis-2-ethylhexyl adipate (B(EH)A), dioctyl phthalate (DOP), and dioctyl terephthalate (DOTP), and the less commonly used dipropylene glycol dibenzoate (D(PG)DB) and diethylene glycol dibenzoate (D(EG)DB). The proposal had been made that the latter two plasticizers be used as alternatives to the first three, which have been associated with negative environmental impacts. The degradation of D(PG)DB or D(EG)DB led to a significant increase in solution toxicity, which was associated with the production of metabolites resulting from the incomplete breakdown of the plasticizers. The toxic metabolites in the D(PG)DB system were identified as isomers of dipropylene glycol monobenzoate. A pathway for the formation of this metabolite was proposed. The metabolite observed when D(EG)DB was being degraded was tentatively identified as diethylene glycol monobenzoate by analogy to the D(PG)DB system. In contrast, no metabolites were observable and toxicity did not increase in the media during the degradation of B(EH)A, DOP, or DOTP by R. rubra. Collectively, these results do not support the use of D(PG)DB and D(EG)DB as environmentally safe alternatives to B(EH)A, DOP, or DOTP.
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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) | 0.001 | 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".