Efficient biodegradation of malachite green by a newly isolated <i>Klebsiella pneumoniae</i> strain WA‐1
Bibliographic record
Abstract
Abstract Biodegradation by microorganisms is a potential treatment technique of malachite green (MG) in aquaculture environments. In this study, a bacterium with high MG decolorization and biodegradation ability was isolated through enrichment culture and color‐decoloration circle method, and was identified as Klebsiella pneumoniae WA‐1 after molecular and biochemical identification. The MG biodegradation characteristics and the factors affecting the MG biodegradation ability of this strain were studied using KBH4 reduction‐high performance liquid chromatography with fluorescence detector (HPLC‐FLD) method. K. pneumoniae WA‐1 could efficiently biodegrade MG in aqueous solution without any nutrients that over 94.0% MG was biodegraded by this strain at 1–20 mg/L within 0.5 hr and 100% MG were biodegraded at 1–10 mg/L within 12 hr. Fairly stable MG biodegradation performance was observed in complex environments, including various pH, temperature, salinity, and metal ions, especially at low MG concentration. Furthermore, the presence of NaCl, Mn2+, Mg2+, or Cu2+ could enhance the MG biodegradation ability of this strain. These results indicate that K. pneumoniae WA‐1 could be used as a potential MG degradation agent in complex aquaculture environments.
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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 | 0.001 |
| 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".