Influence of the chemical structure on the biodegradability of acids yellow 17, violet 7 and orange 52 byPseudomonas putida
Bibliographic record
Abstract
In the present study, the textiles azo dyes acids orange 52 (AO52), yellow 17 (AY17) and violet 7 (AV7) were degraded by Pseudomonas putida mt-2 in mineral medium at concentration up to 100 mg/l. The culture media were completely (case of AO52) or partially (case of AY17 and AV7) decolourised under static incubation, this faster than under continuous shaking incubation. Decolourisation kinetic by intact cells indicated that AO52 disappeared completely and faster than the two other azo dyes. To understand the differentiated action of this bacterium on the three dyes, cell-free extracts activity was assessed and compared for each couple of dyes “inductor-substrate”. Results showed the same halfsaturation constant Km for a given dye as a substrate whatever the dye inductor, from where the assumption of a same protein with nonspecific azoreductase activity. The enzyme showed slightly more affinity for AO52 than for AY17 and AV7, but especially weaker specific activities against these two last dyes independently of the inductor. Finally, AO52 would be the best azoreductase inductor among the three tested dyes. These results indicated that the level as well the induction as the specificity of the azoreductase activity seems to be strongly dependent on the chemical structure of the dyes.
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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) | 0.000 | 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".