Decolorizing Activity of Malachite Green and Its Mechanisms Involved in Dye Biodegradation by <i>Achromobacter xylosoxidans</i> MG1
Bibliographic record
Abstract
An Achromobacter xylosoxidans MG1 strainisolated from the effluent treatment plant of a textile and dyeing factory from Yunnan Province in China was found capable of decolorizing the malachite green dye at a high efficacy. Strain MG1 reduced 86% malachite green at the concentration of 2,000 mg/l within 1 h, representing a greater ability for decolorizing and a higher tolerance of this compound than all previously reported bacteria. Color removal was optimal at pH 6 and 38°C. Further experimental evidences demonstrated that both cytoplasmic and extracellular biodegradation contributed to the decolorization of malachite green. Nested PCR was employed to identify the candidate genes responsible for malachite green decolorization, and we identified a cytoplasmic triphenylmethane reductase gene with 100% amino acid similarity to the corresponding gene in Citrobacter sp. strain. In contrast to our expectation, the addition of metyrapone had little effect on the cytoplasmic biodegradation, suggesting that cytochrome P450 was not involved in the high-performance reduction. The extracellular biodegradation was likely attributable to the secretion of extracellular proteases and some heat-resistant compounds.
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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) | 0.000 | 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".